METHODS AND COMPOSITIONS FOR DIAGNOSING AND TREATING VIRALLY-ASSOCIATED DISEASE
20230417747 ยท 2023-12-28
Inventors
Cpc classification
C12Q1/6881
CHEMISTRY; METALLURGY
International classification
Abstract
Methods of treating viral diseases are disclosed herein. Certain methods include diagnostic methods that quantify levels of biological features associated with T.sub.FH or CD4-CTL cells. Certain methods include treatment methods that affect the number, functionality, activity, or expression of T.sub.FH or CD4-CTL cells or T.sub.REG cells.
Claims
1. A method comprising: (a) obtaining a biological sample; (b) quantifying a level of a biological feature associated with the number or activity of cytotoxic follicular helper (TFH) or CD4-CTL cells from the biological sample; and (c) comparing the level of the biological feature associated with the TFH or CD4-CTL cells against a quantifiable reference value, wherein when the level of the biological feature is higher than the quantifiable reference value, the viral infection is associated with SARS-CoV-2.
2. The method of claim 1, wherein the quantifiable reference value comprises a biological feature associated with the activity or number of TFH or CD4-CTL cells isolated from a source infected with a non-SARS-CoV-2 virus.
3. The method of claim 1, wherein the quantifiable reference value comprises a biological feature associated with TFH or CD4-CTL cells isolated from a source infected with an influenza virus.
4. The method of claim 1, wherein the biological feature comprises the expression or activity of one or more genes set forth in Table 2 and/or Table 3, or one or more of the T-cell receptor (TCR) sequences set forth in Table 6, or a homolog, variant, subsequence, or derivative thereof.
5. The method of claim 4, wherein the biological feature comprises expression or activity of one or more of CXCL13, IL21, CD200, BTLA, POU2AF1, PRF1, GZMB, GZMH, GNLY, or NKG7.
6. A method comprising: (a) obtaining a biological; (b) quantifying a level of a biological feature associated with the number or activity of cytotoxic follicular helper (TFH) or cells from the biological sample; and (c) comparing the level of the biological feature against a quantifiable reference value, wherein when the level of the biological feature is above the quantifiable reference value, the virally-induced disease is severe.
7. The method of claim 6, wherein the quantifiable reference value comprises a biological feature associated with the number or activity of TFH cells isolated from a second subject suffering from a non-severe case of the virally-induced disease.
8. The method of claim 6, wherein the biological feature comprises expression or activity of one or more genes set forth in Table 3, or one or more of the TCR sequences set forth in Table 6, or a homolog, variant, subsequence, or derivative thereof.
9. The method of claim 6, wherein the biological feature comprises expression or activity of one or more of ZBED2, ZBTB32, TIGIT, LAG3, TIM3, PD1, DUSP4, CD70, PRF1, or GZMB.
10. The method of claim 6, wherein the virally-induced disease is COVID-19 or is associated with SARS-CoV-2.
11. A method comprising: (a) obtaining a biological sample; (b) quantifying a level of a biological feature associated with the number or activity of CD4-CTL cells from the biological sample; and (c) comparing the level of the biological feature against a quantifiable reference value, wherein when the level of the biological feature is above the quantifiable reference value, the virally-induced disease is severe.
12. The method of claim 11, wherein the quantifiable reference value comprises a biological feature associated with the number or activity of CD4-CTL cells isolated from a second subject suffering from a non-severe case of the virally-induced disease.
13. The method of claim 11, wherein the biological feature comprises expression or activity of one or more genes set forth in Table 2 or Table 4, or one or more of the TCR sequences set forth in Table 6, or a homolog, variant, subsequence, or derivative thereof.
14. The method of claim 11, wherein the biological feature comprises expression or activity of one or more of CD72, GPR18, HOPX, ZEB2, CCL3, CCL4, CCL5, CCR1, CCR3, CCR5, XCL1, or XCL2.
15. The method of claim 11, wherein the virally-induced disease is COVID-19 or is associated with SARS-CoV-2.
16. A method comprising: (a) obtaining a biological sample; (b) quantifying a level of a biological feature associated with the number or activity of TREG cells from the biological sample; and (c) comparing the level of the biological feature associated with T.sub.REG against a quantifiable reference value, wherein when the level of the biological feature is below the quantifiable reference value, the virally-induced disease is severe.
17. The method of claim 16, wherein the quantifiable reference value comprises a biological feature associated with the number or activity of TREG cells isolated from a second subject suffering from a mild form of the virally-induced disease.
18. The method of claim 16, wherein the biological feature comprises expression or activity of FOXP3, or one or more of the TCR sequences set forth in Table 7, or a homolog, variant, subsequence, or derivative thereof.
19. (canceled)
20. The method of claim 16, wherein the biological feature comprises the expression or activity of T-bet, IFN-, IL-2, TNF, IL-3, CSF2, IL-23A, or CCL20.
21. The method of claim 16, wherein the virally-induced disease is COVID-19 or is associated with SARS-CoV-2.
22.-121. (canceled)
Description
BRIEF DESCRIPTION OF THE FIGURES
[0073] In the present Application:
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DETAILED DESCRIPTION
[0093] A detailed description of one or more embodiments of the disclosure is provided below along with any accompanying figures that illustrate the principles of the embodiments described herein. The disclosure is described in connection with such embodiments, but the disclosure is not limited to any embodiment. Numerous specific details are set forth in the following description in order to provide a thorough understanding of the disclosure. These details are provided for the purpose of non-limiting examples and the embodiments may be practiced according to the claims without some or all of these specific details. For the purpose of clarity, technical material that is known in the technical fields related to the disclosure has not been described in detail so that the disclosure is not unnecessarily obscured.
Overview of the Disclosure
[0094] The present disclosure describes methods for the diagnosis and treatment of viral infections including viral infections associated with SARS-CoV-2. The disclosure describes methods of assessing and modulating the levels of TFH, CD4-CTL, and T.sub.REG cells. The disclosure also describes modified T-cells for treating viral infections.
Definitions and Interpretation
[0095] The terms acceptable, effective, or sufficient, if and as used herein, and when used to describe the selection of any components, ranges, dose forms, etc. as disclosed herein intend that said component, range, dose form, etc. is suitable for the disclosed purpose.
[0096] As used herein, the phrase baseline expression, in reference to a gene, refers to the expression of a gene in normal, untreated conditions.
[0097] As used herein, the phrase CD4-CTL cells refers to a subset of CD4.sup.+ T cells that have cytotoxic activity. CD4-CTL cells referenced herein include any type of CD4-CTL cells known in the art. CD4-CTL cells is synonymous with CD4.sup.+-CTL cells.
[0098] As used herein, the term composition typically but not always intends a combination of the active agent, e.g., an cell or an engineered immune cell, and a naturally-occurring or non-naturally-occurring carrier, inert (for example, a detectable agent or label) or active, such as an adjuvant, diluent, binder, stabilizer, buffers, salts, lipophilic solvents, preservative, adjuvant or the like and include pharmaceutically acceptable carriers. Carriers also include pharmaceutical excipients and additives proteins, peptides, amino acids, lipids, and carbohydrates (e.g., sugars, including monosaccharides, di-, tri-, tetra-oligosaccharides, and oligosaccharides; derivatized sugars such as alditols, aldonic acids, esterified sugars and the like; and polysaccharides or sugar polymers), which can be present singly or in combination, comprising alone or in combination 1-99.99% by weight or volume. Exemplary protein excipients include serum albumin such as human serum albumin (HSA), recombinant human albumin (rHA), gelatin, casein, and the like. Representative amino acid/antibody components, which can also function in a buffering capacity, include alanine, arginine, glycine, arginine, betaine, histidine, glutamic acid, aspartic acid, cysteine, lysine, leucine, isoleucine, valine, methionine, phenylalanine, aspartame, and the like. Carbohydrate excipients are also intended within the scope of this technology, examples of which include but are not limited to monosaccharides such as fructose, maltose, galactose, glucose, D-mannose, sorbose, and the like; disaccharides, such as lactose, sucrose, trehalose, cellobiose, and the like; polysaccharides, such as raffinose, melezitose, maltodextrins, dextrans, starches, and the like; and alditols, such as mannitol, xylitol, maltitol, lactitol, xylitol sorbitol (glucitol) and myoinositol.
[0099] As used herein, the term derivative, in reference to an amino acid sequence, refers to an amino acid sequence in which at least one of an amino group or an acyl group has been modified.
[0100] An effective amount is an amount sufficient to effect beneficial or desired results. An effective amount can be administered in one or more administrations, applications or dosages. Such delivery is dependent on a number of variables including the time period for which the individual dosage unit is to be used, the bioavailability of the therapeutic agent, the route of administration, etc. It is understood, however, that specific dose levels of the therapeutic agents disclosed herein for any particular subject depends upon a variety of factors including the activity of the specific compound employed, bioavailability of the compound, the route of administration, the age of the animal and its body weight, general health, sex, the diet of the animal, the time of administration, the rate of excretion, the drug combination, and the severity of the particular disorder being treated and form of administration. In general, one will desire to administer an amount of the compound that is effective to achieve a serum level commensurate with the concentrations found to be effective in vivo. These considerations, as well as effective formulations and administration procedures are well known in the art and are described in standard textbooks.
[0101] In and as used herein, the term expression level refers to protein, RNA, or mRNA level of a particular gene of interest. Any methods known in the art can be utilized to determine the expression level of a particular gene of interest. Examples include, but are not limited to, reverse transcription and amplification assays (such as PCR, ligation RT-PCR or quantitative RT-PCT), hybridization assays, Northern blotting, dot blotting, in situ hybridization, gel electrophoresis, capillary electrophoresis, column chromatography, Western blotting, immunohistochemistry, immunostaining, or mass spectrometry. Assays can be performed directly on biological samples or on protein/nucleic acids isolated from the samples. It is routine practice in the relevant art to carry out these assays. For example, the detecting step in any method described herein includes contacting the nucleic acid sample from the biological sample obtained from the subject with one or more primers that specifically hybridize to the gene of interest presented herein. Alternatively, the detecting step of any method described herein includes contacting the protein sample from the biological sample obtained from the subject with one or more antibodies that bind to the gene product of the interest presented herein. In some embodiment, the level is an absolute amount or concentration of the protein, RNA, or mRNA level of a particular gene of interest in a cell. In some embodiments, the level is normalized to a control, such as a housekeeping gene.
[0102] As used herein, the term homolog, in reference to an amino acid sequence, refers to an amino acid sequence that shares similarity to a reference amino acid sequence due to having a common evolutionary origin.
[0103] The term isolated as used herein refers to molecules, biologicals, cellular materials, cells or biological samples being substantially free from other materials. In one aspect, the term isolated refers to nucleic acid, such as DNA or RNA, or protein or polypeptide (e.g., an antibody or derivative thereof), or cell or cellular organelle, or tissue or organ, separated from other DNAs or RNAs, or proteins or polypeptides, or cells or cellular organelles, or tissues or organs, respectively, that are present in the natural source. In some embodiments, the term isolated is used herein to refer to cells or tissues that are isolated from other cells or tissues and is meant to encompass both cultured and engineered cells or tissues.
[0104] As used herein, the term isolated cell generally refers to a cell that is substantially separated from other cells of a tissue.
[0105] As used herein, the phrase ligand mimetic refers to a composition that contains similar binding properties to ligands, such as the ability to bind receptors.
[0106] As used herein, the phrase normalized mean gene expression refers to the average intensity of expression of a gene measured on a given array.
[0107] As used herein, the term subsequence, in reference to an amino acid sequence, refers to a portion or a fragment of a larger amino acid sequence.
[0108] If and as used herein, substantially or essentially means nearly totally or completely, for instance, 95% or greater of some given quantity. In some embodiments, substantially or essentially means 95%, 96%, 97%, 98%, 99%, 99.5%, or 99.9%.
[0109] As used herein, the phrase T-cell receptor (TCR) refers to any receptor found on the surface of T cells that is capable of recognizing fragments of an antigen bound to major histocompatibility complex.
[0110] If and as used herein, therapeutically effective amount of a drug or an agent refers to an amount of the drug or the agent that is an amount sufficient to obtain a pharmacological response; or alternatively, is an amount of the drug or agent that, when administered to a patient with a specified disorder or disease, is sufficient to have the intended effect, e.g., treatment, alleviation, amelioration, palliation or elimination of one or more manifestations of the specified disorder or disease in the patient. A therapeutic effect does not necessarily occur by administration of one dose, and may occur only after administration of a series of doses. Thus, a therapeutically effective amount may be administered in one or more administrations.
[0111] As used here, the phrase T.sub.FH cells refers to any type of follicular helper T cell known in the art.
[0112] As used herein, the phrase T.sub.REG cells refers to any type of regulatory T cell known in the art.
[0113] As used herein, the term variant refers to an equivalent having a native polypeptide sequence and structure with one or more amino acid additions, substitutions (generally conservative in nature) or deletions, so long as the modifications do not destroy biological activity and which are substantially identical to the reference polypeptide. Variants generally include substitutions that are conservative in nature, i.e., those substitutions that take place within a family of amino acids that are related in their side chains. Specifically, amino acids are generally divided into four families: (1) acidic: aspartate and glutamate; (2) basic: lysine, arginine, histidine; (3) non-polar: alanine, valine, leucine, isoleucine, proline, phenylalanine, methionine, tryptophan; and (4) uncharged polar: glycine, asparagine, glutamine, cysteine, serine threonine, tyrosine. Phenylalanine, tryptophan, and tyrosine are sometimes classified as aromatic amino acids. For example, it is reasonably predictable that an isolated replacement of leucine with isoleucine or valine, an aspartate with a glutamate, a threonine with a serine, or a similar conservative replacement of an amino acid with a structurally related amino acid, will not have a major effect on the biological activity. For example, the polypeptide of interest can include up to about 5-10 conservative or non-conservative amino acid substitutions, or even up to about 15-25 conservative or non-conservative amino acid substitutions, or any integer between 5-25, so long as the desired function of the polypeptide remains intact. One of skill in the art can readily determine regions of the polypeptide of interest that can tolerate change by reference to Hopp/Woods and Kyte-Doolittle plots, well known in the art.
DESCRIPTION OF ASPECTS AND EMBODIMENTS OF THE DISCLOSURE
[0114] As embodied and broadly described herein, an aspect of the present disclosure relates to a method of diagnosing a viral infection in a subject, the method comprising obtaining a biological sample from the subject, quantifying a level of a biological feature associated with TFH or CD4-CTL cells from the biological sample; and comparing the level of the biological feature associated with the TFH or CD4-CTL cells against a quantifiable reference value, wherein when the level of the biological feature is higher than the quantifiable reference value, the viral infection is associated with SARS-CoV-2. In various embodiments, the quantifiable reference value comprises a biological feature associated with the activity or number of TFH or CD4-CTL cells isolated from a source infected with a non-SARS-CoV-2 virus. In various embodiments the quantifiable reference value comprises a biological feature associated with TFH or CD4-CTL cells isolated from a source infected with an influenza virus. In various embodiments, the biological feature comprises the expression or activity of one or more genes set forth in Table 2 and/or Table 3, or one or more of the T-cell receptor (TCR) sequences set forth in Table 6, or a homolog, variant, subsequence, or derivative thereof. In various embodiments, the biological feature comprises expression or activity of one or more of CXCL13, IL21, CD200, BTLA, POU2AF1, PRF1, GZMB, GZMH, GNLY, or NKG7.
[0115] In another aspect, described herein is a method of diagnosing the severity of a virally-induced disease in a subject, the method comprising obtaining a biological sample from the subject; quantifying a level of a biological feature associated with T.sub.FH cells from the biological sample; and comparing the level of the biological feature against a quantifiable reference value, wherein when the level of the biological feature is above the quantifiable reference value, the virally-induced disease is severe. In various embodiments, the quantifiable reference value comprises a biological feature associated with the number or activity of T.sub.FH cells isolated from a second subject suffering from a non-severe case of the virally-induced disease. In various embodiments, the biological feature comprises expression or activity of one or more genes set forth in Table 3, or one or more of the TCR sequences set forth in Table 6, or a homolog, variant, subsequence, or derivative thereof. In various embodiments, the biological feature comprises expression or activity of one or more of ZBED2, ZBTB32, TIGIT, LAG3, TIM3, PD1, DUSP4, CD70, PRF1, or GZMB. In various embodiments, the virally-induced disease is COVID-19 or is associated with SARS-CoV-2.
[0116] In some embodiments, the virally-induced disease is the result of a viral infection. In some embodiments, the viral infection is caused by a virus selected from the group consisting of influenza virus, coronavirus, enterovirus (such as coxsackievirus and echovirus), cytomegalovirus, Zika virus, rabies virus, West Nile virus, rubella virus, polio virus, rotavirus, norovirus, herpes simplex virus, varicella-zoster virus, lymphocytic choriomeningitis virus, human immunodeficiency virus, Chikungunya virus, Crimean-Congo hemorrhagic fever virus, Japanese encephalitis virus, Rift Valley Fever virus, Ross River virus, and louping ill virus. In various embodiments, the virally-induced disease is COVID-19 or is associated with SARS-CoV-2.
[0117] In another aspect, described herein is a method of diagnosing the severity of a virally-induced disease in a subject, the method comprising obtaining a biological sample from the subject; quantifying a level of a biological feature associated with CD4-CTL cells from the biological sample; and comparing the level of the biological feature against a quantifiable reference value, wherein when the level of the biological feature is above the quantifiable reference value, the virally-induced disease is severe. In various embodiments, the quantifiable reference value comprises a biological feature associated with the number or activity of CD4-CTL cells isolated from a second subject suffering from a non-severe case of the virally-induced disease. In various embodiments, the biological feature comprises expression or activity of one or more genes set forth in Table 2 or Table 4, or one or more of the TCR sequences set forth in Table 6, or a homolog, variant, subsequence, or derivative thereof. In various embodiments, the biological feature comprises expression or activity of one or more of CD72, GPR18, HOPX, ZEB2, CCL3, CCL4, CCL5, CCR1, CCR3, CCR5, XCL1, or XCL2. In various embodiments, the virally-induced disease is COVID-19 or is associated with SARS-CoV-2.
[0118] In another aspect, described herein is a method of diagnosing severity of a virally-induced disease in a subject, the method comprising obtaining a biological sample from the subject; quantifying a level of a biological feature associated with T.sub.REG cells from the biological sample; and comparing the level of the biological feature associated with T.sub.REG against a quantifiable reference value, wherein when the level of the biological feature is below the quantifiable reference value, the virally-induced disease is severe. In various embodiments, the quantifiable reference value comprises a biological feature associated with the number or activity of T.sub.REG cells isolated from a second subject suffering from a mild form of the virally-induced disease. In various embodiments, the biological feature comprises expression or activity of FOXP3, or one or more of the TCR sequences set forth in Table 7, or a homolog, variant, subsequence, or derivative thereof. In various embodiments, the virally-induced disease is COVID-19 or is associated with SARS-CoV-2. In various embodiments, the biological feature comprises the expression or activity of T-bet, IFN-, IL-2, TNF, IL-3, CSF2, IL-23A, or CCL20. In various embodiments, the virally-induced disease is COVID-19 or is associated with SARS-CoV-2.
[0119] In another aspect, described herein is a method of treating a coronavirus infection, treating a disease associated with coronavirus infection, or decreasing, reducing, inhibiting, suppressing, limiting or controlling an adverse symptom or disorder resulting from the coronavirus infection in a subject, the method comprising administering to the subject a therapeutically effective amount of T.sub.REG cells.
[0120] In another aspect, described herein is a method of treating a coronavirus infection, treating a disease associated with coronavirus infection, or decreasing, reducing, inhibiting, suppressing, limiting or controlling an adverse symptom or disorder resulting from the coronavirus infection in a subject, the method comprising administering to the subject a therapeutic effective amount of an agent that can selectively increase T.sub.REG cells in the subject.
[0121] In another aspect, described herein is a method of treating a coronavirus infection, treating a disease associated with coronavirus infection, or decreasing, reducing, inhibiting, suppressing, limiting or controlling an adverse symptom or disorder resulting from the coronavirus infection in a subject, the method comprising administering to the subject a therapeutic effective amount of an agent that can selectively reduce T.sub.FH or CD4+ CTL cells in the subject. In various embodiments, the agent comprises an antibody that selectively binds to a protein expressed by T.sub.FH or CD4+ CTL cells.
[0122] In another aspect, described herein is a method of treating a coronavirus infection, treating a disease associated with coronavirus infection, or decreasing, reducing, inhibiting, suppressing, limiting or controlling an adverse symptom or disorder resulting from the coronavirus infection in a subject, the method comprising administering to the subject an effective amount of a population of T-cells that exhibit higher than or lower than baseline expression of one or more genes set forth in Table 1, Table 2, Table 3, Table 4, Table 5, or that express a T-cell receptor (TCR) comprising at least one of the amino acid sequences set forth in Tables 6 and 7, or a homolog, variant, subsequence, or derivative thereof. In various embodiments, the method comprises administering a population of T-cells that exhibit higher than baseline expression of one or more genes set forth in Table 1 and Table 5, or that express a TCR comprising at least one of the amino acid sequences set forth in Table 7, or a homolog, variant, subsequence, or derivative thereof. In various embodiments, the T-cell is a T.sub.REG cell. In various embodiments, the one or more genes are selected from the group of T-bet, IFN-, IL-2, TNF, IL-3, CSF2, IL-23A, CCL20, IL17A, FOXP3, and IL17F. In various embodiments, the at least one amino acid sequence is selected from Table 7. In various embodiments, the method comprises administering a population of T-cells that exhibit lower than baseline expression of one or more genes set forth in Table 2, Table 3, or Table 4, or that express a TCR comprising at least one of the amino acid sequences set forth in Table 6, or a homolog, variant, subsequence, or derivative thereof. In various embodiments, the one or more genes are selected from the group of ZBED2, ZBTB32, TIGIT, LAG3, TIM3, PD1, DUSP4, CD70, PRF1, and GZMB. In various embodiments, the T-cell is a T.sub.FH cell. In various embodiments, the one or more genes are selected from the group of CD72, GPR18, HOPX, ZEB2, CCL3, CCL4, CCL5, CCR1, CCR3, CCR5, XCL1, and XCL2. In various embodiments, the T cell is a CD4-CTL T cell. In various embodiments, the at least one amino acid sequence is selected from Table 6.
[0123] In another aspect, described herein is a method of treating a coronavirus infection, treating a disease associated with coronavirus infection, or decreasing, reducing, inhibiting, suppressing, limiting or controlling an adverse symptom or disorder resulting from the coronavirus in a subject, the method comprising administering to the subject an effective amount of an agent that induces higher than or lower than baseline expression of one or more genes set forth in Table 1, Table 2, Table 3, Table 4, and/or Table 5 in T cells, or of a TCR of at least one of the amino acid sequences set forth in Tables 6 and 7, or a homolog, variant, subsequence, or derivative thereof.
[0124] In another aspect, described herein is a method of treating a coronavirus infection, treating a disease associated with coronavirus infection, or decreasing, reducing, inhibiting, suppressing, limiting or controlling an adverse symptom or disorder resulting from the coronavirus in a subject, the method comprising administering an effective amount of an agent that induces or inhibits T cell activity of one or more proteins encoded by one or more genes set forth in Table 1, Table 2, Table 3, Table 4, and/or Table 5, or that modulates expression of a T-cell receptor (TCR) comprising at least one of the amino acid sequences set forth in Tables 6 and 7, or a homolog, variant, subsequence, or derivative thereof. In various embodiments, the agent is an antibody, a small molecule, a protein, a peptide, a ligand mimetic, or a nucleic acid. In various embodiments, the baseline expression is normalized mean gene expression. In various embodiments, higher than baseline expression is at least about a 2-fold increase in expression relative to baseline expression and/or lower than baseline expression is at least about a 2-fold decrease in expression relative to baseline expression.
[0125] In another aspect, described herein is a modified T-cell modified to exhibit higher than or lower than baseline expression of one or more genes set forth in Table 1, Table 2, Table 3, Table 4, and/or Table 5, or one or more T-cell receptor (TCR) comprising at least one of the amino acid sequences set forth in Tables 6 and 7, or a homolog, variant, subsequence, or derivative thereof. In various embodiments, the modified T cell exhibits higher than baseline expression of one or more genes set forth in Table 1 or Table 5, or expresses a TCR comprising at least one of the amino acid sequences set forth in Table 7, or a homolog, variant, subsequence, or derivative thereof. In various embodiments, the one or more genes are selected from the group of T-bet, IFN-, IL-2, TNF, IL-3, CSF2, IL-23A, CCL20, IL17A, FOXP3, and IL17F. In various embodiments, the at least one amino acid sequence is selected from Table 7. In various embodiments, the modified T cell is a T.sub.REG cell. In various embodiments, the baseline expression is normalized mean gene expression. In various embodiments, higher than baseline expression is at least about a 2-fold increase in expression relative to baseline expression and/or lower than baseline expression is at least about a 2-fold decrease in expression relative to baseline expression. In various embodiments, the modified T-cell is genetically modified, optionally using one or more of gene editing, recombinant methods and/or a CRISPR/Cas system.
[0126] In various embodiments, the modified T-cell is further modified to express a protein that binds to a cytokine, chemokine, lymphokine, or a receptor each thereof. In various embodiments, the protein comprises an antibody or an antigen binding fragment thereof. In various embodiments, the antibody is an IgG, IgA, IgM, IgE or IgD, or a subclass thereof. In various embodiments, the antibody is an IgG selected from the group of IgG1, IgG2, IgG3 or IgG4. In various embodiments, the antigen binding fragment is selected from the group of a Fab, Fab, F(ab)2, Fv, Fd, single-chain Fvs (scFv), disulfide-linked Fvs (sdFv) or VL or VH In various embodiments, the modified T-cell comprises a chimeric antigen receptor (CAR). In various embodiments, the chimeric antigen receptor (CAR) comprises: (a) an antigen binding domain; (b) a hinge domain; (c) a transmembrane domain; (d) and an intracellular domain.
[0127] In various embodiments, the CAR further comprises one or more costimulatory signaling regions. In various embodiments, the antigen binding domain comprises an anti-CD19 antigen binding domain, the transmembrane domain comprises a CD28 or a CD8 transmembrane domain, the one or more costimulatory regions selected from a CD28 costimulatory signaling region, a 4-1BB costimulatory signaling region, an ICOS costimulatory signaling region, and an OX40 costimulatory region or a CD3 zeta signaling domain. In various embodiments, the anti-CD19 binding domain comprises a single-chain variable fragment (scFv) that specifically recognizes a humanized anti-CD19 binding domain. In various embodiments, the anti-CD19 binding domain scFv of the CAR comprises a heavy chain variable region and a light chain variable region. In various embodiments, the anti-CD19 binding domain of the CAR further comprises a linker polypeptide located between the anti-CD19 binding domain scFv heavy chain variable region and the anti-CD19 binding domain scFv light chain variable region. In various embodiments, the linker polypeptide of the CAR comprises a polypeptide of the sequence (GGGGS)n wherein n is an integer from 1 to 6. In various embodiments, the CAR further comprises a detectable marker attached to the CAR. In various embodiments, the CAR further comprises a purification marker attached to the CAR. In various embodiments, the modified T-cell comprises a polynucleotide encoding the CAR, and optionally, wherein the polynucleotide encodes and anti-CD19 binding domain.
[0128] In various embodiments, the polynucleotide further comprises a promoter operatively linked to the polynucleotide to express the polynucleotide in the modified T-cell. In various embodiments, the polynucleotide further comprises a 2A self-cleaving peptide (T2A) encoding polynucleotide sequence located upstream of a polynucleotide encoding the anti-CD19 binding domain. In various embodiments, the polynucleotide further comprises a polynucleotide encoding a signal peptide located upstream of a polynucleotide encoding the anti-CD19 binding domain. In various embodiments, the polynucleotide further comprises a vector. In various embodiments, the vector is a plasmid. In various embodiments, the vector is a viral vector selected from the group of a retroviral vector, a lentiviral vector, an adenoviral vector, and an adeno-associated viral vector.
[0129] In another aspect, described herein is a composition comprising a population of modified T-cells as detailed herein.
[0130] In an aspect, a method of treating a viral infection, disease associated with viral infection, or decreasing, reducing, inhibiting, suppressing, limiting or controlling an adverse symptom or disorder resulting from the virus in a subject is provided, the method comprising administering to the subject an effective amount of the modified T-cells and/or the compositions described herein.
[0131] In certain embodiments, the viral infection may result from any of the following viral families: Arenaviridae, Arterivirus, Astroviridae, Baculoviridae, Badnavirus, Barnaviridae, Birnaviridae, Bromoviridae, Bunyaviridae, Caliciviridae, Capillovirus, Carlavirus, Caulimovirus, Circoviridae, Closterovirus, Comoviridae, Coronaviridae (e.g., Coronavirus, such as severe acute respiratory syndrome (SARS) virus), Corticoviridae, Cystoviridae, Deltavirus, Dianthovirus, Enamovirus, Filoviridae (e.g., Marburg vims and Ebola virus (e.g., Zaire, Reston, Ivory Coast, or Sudan strain)), Flaviviridae, (e.g., Hepatitis C vims, Dengue vims 1, Dengue vims 2, Dengue virus 3, and Dengue virus 4), Hepadnaviridae, Herpesviridae (e.g., Human herpesvirus 1, 3, 4, 5, and 6, and Cytomegalovirus), Hypoviridae, Iridoviridae, Leviviridae, Lipothrixviridae, Microviridae, Orthomyxoviridae (e.g., Influenzavirus A and B and C), Papovaviridae, Paramyxoviridae (e.g., measles, mumps, and human respiratory syncytial virus), Parvoviridae, Picomaviridae (e.g., poliovirus, rhinovirus, hepatovims, and aphthovirus), Poxviridae (e.g., vaccinia and smallpox vims), Reoviridae (e.g., rotavims), Retroviridae (e.g., lentivirus, such as human immunodeficiency vims (HIV) 1 and HIV 2), Rhabdoviridae (for example, rabies vims, measles virus, respiratory syncytial virus, etc.), Togaviridae (for example, mbella virus, dengue virus, etc.), and Totiviridae. Suitable viral antigens also include all or part of Dengue protein M, Dengue protein E, Dengue DiNS1, Dengue D1NS2, and Dengue DINS3.
[0132] The viral infection or virus may be derived from a particular strain such as a papilloma vims, a herpes vims, e.g., herpes simplex 1 and 2; a hepatitis vims, for example, hepatitis A vims (HAV), hepatitis B vims (HBV), hepatitis C virus (HCV), the delta hepatitis D vims (HDV), hepatitis E virus (HEV) and hepatitis G vims (HGV), the tick-borne encephalitis viruses; parainfluenza, varicella-zoster, cytomeglavirus, Epstein-Barr, rotavirus, rhinovims, adenovims, coxsackieviruses, equine encephalitis, Japanese encephalitis, yellow fever, Rift Valley fever, and lymphocytic choriomeningitis.
[0133] In another aspect, described herein is a method of treating a coronavirus infection, treating a disease associated with coronavirus infection, or decreasing, reducing, inhibiting, suppressing, limiting or controlling an adverse symptom or disorder resulting from the coronavirus in a subject, the method comprising administering to the subject an effective amount of modified T-cells as detailed herein and/or a composition as detailed herein. In various embodiments, the coronavirus infection is SARS-CoV-2. In various embodiments, the disease associated with coronavirus infection is COVID-19. In various embodiments, the method comprises agonizing a population of or increasing the level, expression, or activity of T.sub.REG cells in the subject. In various embodiments, the method comprises antagonizing a population of or decreasing or depleting the level, expression, or activity of T.sub.FH or CD4-CTL cells in the subject.
[0134] In another aspect, described herein is a method of diagnosing a viral infection ex vivo, the method comprising quantifying, ex vivo, a level of a biological feature associated with T.sub.FH or CD4-CTL cells from a biological sample; and comparing the level of the biological feature associated with the T.sub.FH or CD4-CTL cells against a quantifiable reference value, wherein when the level of the biological feature is higher than the quantifiable reference value, the viral infection is associated with SARS-CoV-2. In various embodiments, the quantifiable reference value comprises a biological feature associated with the activity or number of T.sub.FH or CD4-CTL cells isolated from a biological sample infected with a non-SARS-CoV-2 virus. In various embodiments, the quantifiable reference value comprises a biological feature associated with T.sub.FH or CD4-CTL cells isolated from a biological sample infected with an influenza virus. In various embodiments, the biological feature comprises the expression or activity of one or more genes set forth in Table 2 and/or Table 3, or one or more of the T-cell receptor (TCR) sequences set forth in Table 6, or a homolog, variant, subsequence, or derivative thereof. In various embodiments, the biological feature comprises expression or activity of one or more of CXCL13, IL21, CD200, BTLA, POU2AF1, PRF1, GZMB, GZMH, GNLY, or NKG7.
[0135] In another aspect, described herein is a method of diagnosing the severity of a virally-induced disease ex vivo, the method comprising quantifying, ex vivo, a level of a biological feature associated with T.sub.FH cells from the biological sample; and comparing the level of the biological feature against a quantifiable reference value, wherein when the level of the biological feature is above the quantifiable reference value, the virally-induced disease is severe. In various embodiments, the quantifiable reference value comprises a biological feature associated with the number or activity of T.sub.FH cells isolated from a biological sample of a subject suffering from a non-severe case of the virally-induced disease. In various embodiments, the biological feature comprises expression or activity of one or more genes set forth in Table 3, or one or more of the TCR sequences set forth in Table 6, or a homolog, variant, subsequence, or derivative thereof. In various embodiments, the biological feature comprises expression or activity of one or more of ZBED2, ZBTB32, TIGIT, LAG3, TIM3, PD1, DUSP4, CD70, PRF1, or GZMB. In various embodiments, the virally-induced disease is COVID-19 or is associated with SARS-CoV-2.
[0136] In another aspect, described herein is a method of diagnosing the severity of a virally-induced disease ex vivo, the method comprising quantifying, ex vivo, a level of a biological feature associated with CD4-CTL cells from the biological sample; and comparing the level of the biological feature against a quantifiable reference value, wherein when the level of the biological feature is above the quantifiable reference value, the virally-induced disease is severe. In various embodiments, the quantifiable reference value comprises a biological feature associated with the number or activity of CD4-CTL cells isolated from a biological sample of a subject suffering from a non-severe case of the virally-induced disease. In various embodiments, the biological feature comprises expression or activity of one or more genes set forth in Table 2 or Table 4, or one or more of the TCR sequences set forth in Table 6, or a homolog, variant, subsequence, or derivative thereof. In various embodiments, the biological feature comprises expression or activity of one or more of CD72, GPR18, HOPX, ZEB2, CCL3, CCL4, CCL5, CCR1, CCR3, CCR5, XCL1, or XCL2. In various embodiments, the virally-induced disease is COVID-19 or is associated with SARS-CoV-2.
[0137] In another aspect, described herein is a method of diagnosing severity of a virally-induced disease ex vivo, the method comprising quantifying, ex vivo, a level of a biological feature associated with T.sub.REG cells from the biological sample; and comparing the level of the biological feature associated with T.sub.REG against a quantifiable reference value, wherein when the level of the biological feature is below the quantifiable reference value, the virally-induced disease is severe. In various embodiments, the quantifiable reference value comprises a biological feature associated with the number or activity of T.sub.REG cells isolated from a biological sample of a subject suffering from the virally-induced disease. In various embodiments, the biological sample is isolated from a subject suffering from a mild form of the virally-induced disease. In various embodiments, the biological sample is isolated from a subject suffering from a severe form of the virally-induced disease. In various embodiments, the biological feature comprises expression or activity of FOXP3, or one or more of the TCR sequences set forth in Table 7, or a homolog, variant, subsequence, or derivative thereof. In various embodiments, the virally-induced disease is COVID-19 or is associated with SARS-CoV-2. In various embodiments, the biological feature comprises the expression or activity of T-bet, IFN-, IL-2, TNF, IL-3, CSF2, IL-23A, or CCL20. In various embodiments, the virally-induced disease is COVID-19 or is associated with SARS-CoV-2.
[0138] In another aspect, described herein is a method of treating a viral infection, treating a disease associated with the viral infection, or decreasing, reducing, inhibiting, suppressing, limiting or controlling an adverse symptom or disorder resulting from the viral infection in a subject, the method comprising administering to the subject a therapeutically effective amount of T.sub.REG cells.
[0139] In another aspect, described herein is a method of treating a viral infection, treating a disease associated with viral infection, or decreasing, reducing, inhibiting, suppressing, limiting or controlling an adverse symptom or disorder resulting from the viral infection in a subject, the method comprising administering to the subject a therapeutic effective amount of an agent that can selectively increase T.sub.REG cells in the subject.
[0140] In another aspect, described herein is a method of treating a viral infection, treating a disease associated with the viral infection, or decreasing, reducing, inhibiting, suppressing, limiting or controlling an adverse symptom or disorder resulting from the viral infection in a subject, the method comprising administering to the subject a therapeutic effective amount of an agent that can selectively reduce T.sub.FH or CD4+ CTL cells in the subject. In various embodiments, the agent comprises an antibody that selectively binds to a protein expressed by T.sub.FH or CD4+ CTL cells.
[0141] In another aspect, described herein is a method of treating a viral infection, treating a disease associated with the viral infection, or decreasing, reducing, inhibiting, suppressing, limiting or controlling an adverse symptom or disorder resulting from the viral infection in a subject, the method comprising administering to the subject an effective amount of a population of T-cells that exhibit higher than or lower than baseline expression of one or more genes set forth in Table 1, Table 2, Table 3, Table 4, and/or Table 5, or that express a T-cell receptor (TCR) comprising at least one of the amino acid sequences set forth in Tables 6 and 7, or a homolog, variant, subsequence, or derivative thereof. In various embodiments, the method comprises administering a population of T-cells that exhibit higher than baseline expression of one or more genes set forth in Table 1 or Table 5, or that express a TCR comprising at least one of the amino acid sequences set forth in Table 7, or a homolog, variant, subsequence, or derivative thereof. In various embodiments, the T-cell is a T.sub.REG cellIn various embodiments, the one or more genes are selected from the group of T-bet, IFN-, IL-2, TNF, IL-3, CSF2, IL-23A, CCL20, IL17A, FOXP3, and IL17F. In various embodiments, the at least one amino acid sequence is selected from Table 7. In various embodiments, the method comprises administering a population of T-cells that exhibit lower than baseline expression of one or more genes set forth in Table 2, Table 3, or Table 4, or that express a TCR comprising at least one of the amino acid sequences set forth in Table 6, or a homolog, variant, subsequence, or derivative thereof. In various embodiments, the one or more genes are selected from the group of ZBED2, ZBTB32, TIGIT, LAG3, TIM3, PD1, DUSP4, CD70, PRF1, and GZMB. In various embodiments, the T-cell is a T.sub.FH cell. In various embodiments, the one or more genes are selected from the group of CD72, GPR18, HOPX, ZEB2, CCL3, CCL4, CCL5, CCR1, CCR3, CCR5, XCL1, and XCL2. In various embodiments, the T cell is a CD4-CTL T cell. In various embodiments, the at least one amino acid sequence is selected from Table 6.
[0142] In another aspect, described herein is a method of treating a viral infection, treating a disease associated with the viral infection, or decreasing, reducing, inhibiting, suppressing, limiting or controlling an adverse symptom or disorder resulting from the viral infection in a subject, the method comprising administering to the subject an effective amount of an agent that induces higher than or lower than baseline expression of one or more genes set forth in Table 1, Table 2, Table 3, Table 4, and/or Table 5 in T cells, or of a TCR of at least one of the amino acid sequences set forth in Tables 6 and 7, or a homolog, variant, subsequence, or derivative thereof.
[0143] In another aspect, described herein is a method of treating a viral infection, treating a disease associated with the viral infection, or decreasing, reducing, inhibiting, suppressing, limiting or controlling an adverse symptom or disorder resulting from the viral infection in a subject, the method comprising administering an effective amount of an agent that induces or inhibits T cell activity of one or more proteins encoded by one or more genes set forth in Table 1, Table 2, Table 3, Table 4, and/or Table 5, or that modulates expression of a T-cell receptor (TCR) comprising at least one of the amino acid sequences set forth in Tables 6 and 7, or a homolog, variant, subsequence, or derivative thereof. In various embodiments, the agent is an antibody, a small molecule, a protein, a peptide, a ligand mimetic or a nucleic acid. In various embodiments, baseline expression is normalized mean gene expression. In various embodiments, higher than baseline expression is at least about a 2-fold increase in expression relative to baseline expression and/or lower than baseline expression is at least about a 2-fold decrease in expression relative to baseline expression.
[0144] In another aspect, described herein is a method of treating a viral infection, treating a disease associated with viral infection, or decreasing, reducing, inhibiting, suppressing, limiting or controlling an adverse symptom or disorder resulting from the viral infection in a subject, the method comprising administering to the subject an effective amount of modified T-cells as detailed herein and/or a composition as detailed herein. In various embodiments, the method further comprises agonizing a population of or increasing the level, expression, or activity of T.sub.REG cells in the subject. In various embodiments, the method comprises antagonizing a population of or decreasing or depleting the level, expression, or activity of T.sub.FH or CD4-CTL cells in the subject.
Methods of Isolating and Detecting CD4-CTLs
[0145] Numerous methods can be used to isolate CD4-CTL cells. In an aspect, CD4-CTL cells are detected using an Interferon-Gamma Release Assay. In embodiments, peripheral blood mononuclear cells (PBMCs) are isolated from a patient and the level of Interferon-Gamma in the PBMCs are detected. In embodiments, high levels of Interferon-Gamma would be indicative of the patient having high levels of CD4-CTL cells. In embodiments, the high levels of CD4-CTL cells would indicate that the patient is suffering from a viral disease described herein.
[0146] In an aspect, CD4-CTL cells are detected using flow cytometry. In embodiments a sample is derived from a patient. In embodiments, the sample is PBMCs. In embodiments, the sample is assayed for gene expression of a specific gene subset. In embodiments, the specific gene subset is correlated to CD4-CTL cell expression or activity.
Viral Infections
[0147] In an aspect, the methods and compositions described herein can be used to diagnose and treat SARS-CoV-2.
[0148] Coronaviruses is a family of single-stranded, positive-strand RNA viruses characterized with crown-like spikes on their surface. The coronaviruses belong to the Coronaviridae family, Nidovirales order. There are four sub-groupings or categories of CoVs, alpha, beta, gamma, and delta. The CoVs are the largest known RNA viruses, comprising 16 non-structural proteins and 4 structural proteins which include spike (S) protein, envelope (E) protein, membrane (M) protein, and nucleocapsid (N) protein.
[0149] There are seven species of coronaviruses that are known to cause respiratory and intestinal infections in humans. The seven species are 229E (or -type HCoV-229E), NL63 (or -type HCoV-NL63), OC43 (or -type HCoV-OC43), HKU1 (or 3-type HCoV-HKU1), MERS-CoV (the -type HCoV that causes Middle East Respiratory Syndrome or MERS), SARS-CoV (the -type HCoV that causes severe acute respiratory syndrome or SARS), and SARS-CoV2 (the -type HCoV that causes the coronavirus disease of 2019, COVID-19, or 2019-nCoV).
[0150] In some embodiments, the CoVs are also classified based on their pathogenicity. In some instances, the mild pathogenic CoVs include HCoV-229E, HCoV-OC43, HCoV-NL63, and HCoV-HKU1. In some instances, the highly pathogenic CoVs include SARS-CoV, MERS-CoV, and SARS-CoV2. In some cases, the mild pathogens infect the upper respiratory tract and causes seasonal, mild to moderate cold-like respiratory diseases in the subject. In some cases, the highly pathogenic CoVs infect the lower respiratory tract and cause severe pneumonia, leading, in some cases, to fatal acute lung injury (ALI) and/or acute respiratory distress syndrome (ARDS).
[0151] In an aspect, the methods and compositions described herein can be used to diagnose and treat viral infections that result from viruses other than SARS-CoV-2. In embodiments, the methods and compositions described herein can be used to treat viral infections that result from any of the following viral families: Arenaviridae, Arterivirus, Astroviridae, Baculoviridae, Badnavirus, Bamaviridae, Birnaviridae, Bromoviridae, Bunyaviridae, Caliciviridae, Capillovirus, Carlavirus, Caulimovirus, Circoviridae, Closterovirus, Comoviridae, Coronaviridae (e.g., Coronavirus, such as severe acute respiratory syndrome (SARS) virus), Corticoviridae, Cystoviridae, Deltavirus, Dianthovirus, Enamovirus, Filoviridae (e.g., Marburg vims and Ebola virus (e.g., Zaire, Reston, Ivory Coast, or Sudan strain)), Flaviviridae, (e.g., Hepatitis C vims, Dengue vims 1, Dengue vims 2, Dengue virus 3, and Dengue virus 4), Hepadnaviridae, Herpesviridae (e.g., Human herpesvirus 1, 3, 4, 5, and 6, and Cytomegalovirus), Hypoviridae, Iridoviridae, Leviviridae, Lipothrixviridae, Microviridae, Orthomyxoviridae (e.g., Influenzavirus A and B and C), Papovaviridae, Paramyxoviridae (e.g., measles, mumps, and human respiratory syncytial virus), Parvoviridae, Picornaviridae (e.g., poliovirus, rhinovirus, hepatovims, and aphthovirus), Poxviridae (e.g., vaccinia and smallpox vims), Reoviridae (e.g., rotavims), Retroviridae (e.g., lentivirus, such as human immunodeficiency vims (HIV) 1 and HIV 2), Rhabdoviridae (for example, rabies vims, measles virus, respiratory syncytial virus, etc.), Togaviridae (for example, mbella virus, dengue virus, etc.), and Totiviridae. Suitable viral antigens also include all or part of Dengue protein M, Dengue protein E, Dengue DiNS1, Dengue D1NS2, and Dengue D1NS3.
[0152] In an aspect, the technology described herein may be used to diagnose and treat viral infections that preferentially upregulate the levels, expression, or activity of TFH or CD4-CTL cells and/or downregulate the levels, expression, or activity of T.sub.REG cells.
Compositions
[0153] In compositions used in accordance with the disclosure, including cells, treatments, therapies, agents, drugs and pharmaceutical formulations can be packaged in dosage unit form for ease of administration and uniformity of dosage. The term unit dose or dosage refers to physically discrete units suitable for use in a subject, each unit containing a predetermined quantity of the composition calculated to produce the desired responses in association with its administration, i.e., the appropriate route and regimen. The quantity to be administered, both according to number of treatments and unit dose, depends on the result and/or protection desired. Precise amounts of the composition also depend on the judgment of the practitioner and are peculiar to each individual. Factors affecting dose include physical and clinical state of the subject, route of administration, intended goal of treatment (alleviation of symptoms versus cure), and potency, stability, and toxicity of the particular composition. Upon formulation, solutions will be administered in a manner compatible with the dosage formulation and in such amount as is therapeutically or prophylactically effective. The formulations are easily administered in a variety of dosage forms, such as the type of injectable solutions described herein.
[0154] In some embodiments, the compositions disclosed herein are administered to a subject by multiple administration routes, including but not limited to, parenteral, oral, buccal, rectal, sublingual, or transdermal administration routes. In some cases, parenteral administration comprises intravenous, subcutaneous, intramuscular, intracerebral, intranasal, intra-arterial, intra-articular, intradermal, intravitreal, intraosseous infusion, intraperitoneal, or intratechal administration. In some instances, the composition (e.g., pharmaceutical composition) is formulated for local administration. In other instances, the composition (e.g., pharmaceutical composition) is formulated for systemic administration.
[0155] In some embodiments, the compositions (e.g., pharmaceutical composition or formulations) include, but are not limited to, aqueous liquid dispersions, self-emulsifying dispersions, solid solutions, liposomal dispersions, aerosols, solid dosage forms, powders, immediate release formulations, controlled release formulations, fast melt formulations, tablets, capsules, pills, delayed release formulations, extended release formulations, pulsatile release formulations, multiparticulate formulations (e.g., nanoparticle formulations), and mixed immediate and controlled release formulations.
[0156] In some embodiments, the compositions (e.g., pharmaceutical composition or formulations) include a carrier or carrier materials selected on the basis of compatibility with the composition disclosed herein, and the release profile properties of the desired dosage form. Exemplary carrier materials include, e.g., binders, suspending agents, disintegration agents, filling agents, surfactants, solubilizers, stabilizers, lubricants, wetting agents, diluents, and the like.
[0157] In some instances, the compositions (e.g., pharmaceutical composition or formulations) further include pH adjusting agents or buffering agents. In some instances, the compositions (e.g., pharmaceutical composition or formulations) includes one or more salts in an amount required to bring osmolality of the composition into an acceptable range.
[0158] In some embodiments, the compositions (e.g., pharmaceutical composition or formulations) include, but are not limited to, sugars or salts and/or other agents such as heparin to increase the solubility and in vivo stability of polypeptides.
[0159] In some instances, the compositions (e.g., pharmaceutical composition or formulations) further include diluent which are used to stabilize compounds because they can provide a more stable environment. In some cases, the compositions (e.g., pharmaceutical composition or formulations) include disintegration agents or disintegrants to facilitate the breakup or disintegration of a substance.
[0160] As it would be understood by one of skill in the art, any embodiments, instances, aspects, examples, or cases can be combined or substituted with any other embodiments, instances, aspects, examples, or cases as disclosed herein, no matter where the embodiments, instances, aspects, examples or cases are provided in this disclosure.
Tables
[0161] As referred to herein, Tables 1 and 5 generally depict transcriptome analysis of various genes in T.sub.REG cells. As referred to herein, Tables 2 and 4 generally depict transcriptome analysis of various genes in CD4-CTLs. As referred to herein, Table 3 generally depicts transcriptome analysis of various genes in Tfh cells. As referred to herein, Table 6 generally depicts CD4-CTL-related TCR sequences. As referred to herein, Table 7 generally depicts T.sub.REG-related TCR sequences.
[0162] As referred herein, Table 1 depicts as follows:
TABLE-US-00001 TABLE 1 Test statistics Fraction of Average expressing cells logged Cluster- Other Fold Adjusted Gene ID Cluster specific cells Change P-value P-value CXCL10 2 0.28 0.02 2.08 0 0 LTB 2 0.99 0.63 1.92 0 0 S100A4 2 0.93 0.49 1.53 0 0 LGALS3 2 0.88 0.22 1.53 0 0 S100A6 2 0.99 0.68 1.41 0 0 IFIT3 2 0.70 0.16 1.36 0 0 CORO1A 2 0.97 0.56 1.29 0 0 GBP5 2 0.85 0.41 1.27 0 0 IL32 2 1.00 0.87 1.25 0 0 CISH 2 0.81 0.15 1.23 0 0 GBP1 2 0.91 0.42 1.22 0 0 IL4I1 2 0.76 0.14 1.20 0 0 LY6E 2 0.94 0.66 1.20 0 0 CYTIP 2 0.94 0.49 1.18 0 0 TYMP 2 0.88 0.37 1.18 0 0 GBP4 2 0.80 0.25 1.16 0 0 PTPRCAP 2 0.89 0.37 1.15 0 0 IFI6 2 0.83 0.48 1.15 0 0 RGS1 2 0.55 0.15 1.14 0 0 TMSB10 2 1.00 0.95 1.13 0 0 STAT1 2 0.96 0.62 1.13 0 0 MYL12A 2 0.99 0.85 1.13 0 0 SAMHD1 2 0.82 0.17 1.12 0 0 S100A11 2 0.97 0.68 1.11 0 0 ALOX5AP 2 0.79 0.29 1.07 0 0 FLT3LG 2 0.85 0.18 1.07 0 0 OSM 2 0.47 0.05 1.06 0 0 ISG15 2 0.87 0.48 1.05 0 0 MT2A 2 0.58 0.29 1.05 0 0 LGALS1 2 0.74 0.38 1.05 0 0 TMSB4X 2 1.00 0.96 1.03 0 0 BST2 2 0.92 0.57 1.03 0 0 IL22 2 0.15 0.02 1.02 0 0 CMTM6 2 0.90 0.50 1.00 0 0 SAMD9L 2 0.73 0.15 0.99 0 0 VIM 2 0.99 0.82 0.99 0 0 OAS1 2 0.64 0.18 0.99 0 0 GIMAP7 2 0.71 0.24 0.99 0 0 RSAD2 2 0.47 0.06 0.98 0 0 IFI35 2 0.83 0.36 0.96 0 0 RNF213 2 0.86 0.34 0.96 0 0 CTSH 2 0.62 0.11 0.94 0 0 MX1 2 0.76 0.35 0.91 0 0 PSME1 2 0.99 0.83 0.91 0 0 IFITM1 2 0.97 0.78 0.90 0 0 TRADD 2 0.71 0.12 0.86 0 0 IFIT1 2 0.43 0.10 0.86 0 0 OAS3 2 0.63 0.12 0.86 0 0 PLP2 2 0.88 0.48 0.86 0 0 OSTF1 2 0.80 0.26 0.85 0 0 ISG20 2 0.89 0.64 0.85 0 0 FAS 2 0.71 0.17 0.85 0 0 ARHGDIB 2 0.94 0.52 0.84 0 0 PSMB9 2 0.98 0.73 0.84 0 0 ANXA2 2 0.92 0.55 0.84 0 0 PIM2 2 0.64 0.32 0.84 0 0 IRF1 2 0.93 0.60 0.83 0 0 TNFSF13B 2 0.43 0.06 0.83 0 0 KLF6 2 0.99 0.76 0.83 0 0 DPP4 2 0.63 0.08 0.83 0 0 CASP1 2 0.67 0.15 0.82 0 0 PSMB10 2 0.94 0.60 0.82 0 0 CLDND1 2 0.82 0.51 0.82 0 0 SOCS1 2 0.66 0.27 0.81 0 0 XAF1 2 0.77 0.27 0.81 0 0 DUSP1 2 0.61 0.30 0.80 0 0 HSPA1A 2 0.59 0.26 0.78 0 0 SAT1 2 0.87 0.64 0.77 0 0 GIMAP4 2 0.59 0.19 0.76 0 0 OPTN 2 0.75 0.24 0.76 0 0 IFI44L 2 0.74 0.30 0.75 0 0 PIM1 2 0.78 0.33 0.74 0 0 GPSM3 2 0.88 0.42 0.73 0 0 ARHGAP15 2 0.76 0.31 0.72 0 0 HAPLN3 2 0.64 0.20 0.72 0 0 PSME2 2 0.99 0.90 0.72 0 0 IRF7 2 0.71 0.31 0.72 0 0 CARD16 2 0.67 0.16 0.72 0 0 GSDMD 2 0.67 0.19 0.72 0 0 TPM4 2 0.78 0.35 0.71 0 0 MVP 2 0.78 0.35 0.71 0 0 TUBA1A 2 0.60 0.17 0.70 0 0 EMP3 2 1.00 0.89 0.70 0 0 CDKN1A 2 0.52 0.20 0.69 0 0 SQSTM1 2 0.82 0.50 0.69 0 0 CD47 2 0.86 0.45 0.69 0 0 ANKRD12 2 0.89 0.52 0.68 0 0 ARPC1B 2 0.97 0.71 0.68 0 0 DDX58 2 0.49 0.10 0.68 0 0 CAST 2 0.79 0.35 0.67 0 0 TUBB 2 0.95 0.76 0.67 0 0 PPM1K 2 0.55 0.16 0.67 0 0 CAPN2 2 0.67 0.24 0.67 0 0 PARP9 2 0.71 0.24 0.67 0 0 GSTK1 2 0.88 0.55 0.67 0 0 MAL 2 0.50 0.11 0.66 0 0 FOXP3 2 0.18 0.03 0.65 0 0 OASL 2 0.49 0.18 0.65 0 0 LIMDZ 2 0.88 0.54 0.65 0 0 CCR6 2 0.48 0.07 0.65 0 0 IFIT2 2 0.31 0.05 0.64 0 0 CXCR4 2 0.51 0.16 0.64 0 0 IFI44 2 0.57 0.16 0.64 0 0 UBE2L6 2 0.90 0.59 0.63 0 0 EIF2AK2 2 0.69 0.33 0.63 0 0 SAMD9 2 0.59 0.19 0.62 0 0 IL10RA 2 0.56 0.11 0.62 0 0 ETV7 2 0.47 0.07 0.62 0 0 VAMP8 2 0.80 0.40 0.62 0 0 ACAT2 2 0.58 0.18 0.62 0 0 GIMAP5 2 0.70 0.38 0.62 0 0 PLSCR1 2 0.58 0.26 0.61 0 0 IFITM2 2 0.90 0.70 0.61 0 0 TAPBP 2 0.92 0.65 0.61 0 0 ARL6IP5 2 0.92 0.60 0.61 0 0 MYL6 2 1.00 0.94 0.61 0 0 PSMB8 2 0.96 0.78 0.61 0 0 SOS1 2 0.45 0.06 0.60 0 0 APOL2 2 0.54 0.13 0.60 0 0 APOL3 2 0.49 0.07 0.60 0 0 ANXA1 2 0.89 0.58 0.60 0 0 APOL6 2 0.73 0.33 0.59 0 0 DRAP1 2 0.89 0.62 0.59 0 0 SQRDL 2 0.65 0.21 0.58 0 0 CMPK2 2 0.41 0.06 0.58 0 0 ILK 2 0.64 0.22 0.58 0 0 IFITM3 2 0.25 0.11 0.58 0 0 MX2 2 0.50 0.17 0.57 0 0 AHNAK 2 0.63 0.25 0.57 0 0 LCP2 2 0.78 0.45 0.57 0 0 HSPB1 2 0.71 0.38 0.57 0 0 GLRX 2 0.46 0.08 0.57 0 0 CD74 2 0.97 0.74 0.57 0 0 TNFSF10 2 0.79 0.58 0.57 0 0 TNFRSF14 2 0.67 0.25 0.56 0 0 CAPG 2 0.41 0.07 0.56 0 0 ACAP1 2 0.56 0.15 0.56 0 0 HERC5 2 0.39 0.09 0.56 0 0 CDK2AP2 2 0.74 0.43 0.56 0 0 TAP1 2 0.97 0.77 0.55 0 0 EPSTI1 2 0.72 0.37 0.55 0 0 TXN 2 0.96 0.84 0.55 0 0 RTN4 2 0.67 0.35 0.55 0 0 LAPTM5 2 0.87 0.51 0.55 0 0 C10orf128 2 0.44 0.10 0.55 0 0 RAC2 2 0.97 0.79 0.55 0 0 SP100 2 0.84 0.57 0.55 0 0 PFN1 2 1.00 0.98 0.54 0 0 STK17B 2 0.82 0.52 0.54 0 0 LGALS9 2 0.39 0.08 0.54 0 0 RARRES3 2 0.56 0.23 0.54 0 0 KLRB1 2 0.58 0.24 0.54 0 0 FLNA 2 0.74 0.41 0.54 0 0 ZFP36 2 0.49 0.22 0.54 0 0 DTX3L 2 0.58 0.19 0.54 0 0 ACTB 2 1.00 0.99 0.53 0 0 SNX10 2 0.50 0.12 0.53 0 0 CLEC2B 2 0.53 0.20 0.53 0 0 EML4 2 0.74 0.39 0.53 0 0 CYB5A 2 0.51 0.13 0.53 0 0 TBCB 2 0.75 0.42 0.52 0 0 ERAP2 2 0.45 0.11 0.52 0 0 ACTG1 2 0.99 0.96 0.52 0 0 IFIH1 2 0.48 0.12 0.51 0 0 GNB2 2 0.73 0.43 0.51 0 0 SELPLG 2 0.44 0.09 0.51 0 0 CFL1 2 1.00 0.96 0.51 0 0 ITM2B 2 0.97 0.79 0.51 0 0 AHR 2 0.63 0.29 0.51 0 0 HERC6 2 0.42 0.08 0.50 0 0 SERPINB1 2 0.59 0.22 0.50 0 0 OAS2 2 0.57 0.23 0.50 0 0 NFKB2 2 0.71 0.42 0.50 0 0 DYNLT1 2 0.64 0.33 0.50 0 0 PARP14 2 0.64 0.30 0.50 0 0 IL2RA 2 0.73 0.48 0.50 0 0 PDE4B 2 0.52 0.18 0.49 0 0 PAG1 2 0.56 0.20 0.49 0 0 PARP12 2 0.48 0.12 0.49 0 0 UNC119 2 0.44 0.10 0.49 0 0 IL15RA 2 0.52 0.19 0.49 0 0 DBI 2 0.88 0.68 0.49 0 0 CASP4 2 0.60 0.26 0.49 0 0 CALM1 2 0.99 0.92 0.49 0 0 TANK 2 0.72 0.39 0.49 0 0 LMO4 2 0.46 0.11 0.49 0 0 XRN1 2 0.59 0.27 0.49 0 0 MGST3 2 0.61 0.23 0.48 0 0 KIAA1551 2 0.62 0.32 0.48 0 0 BHLHE40 2 0.77 0.46 0.48 0 0 DDX60 2 0.48 0.13 0.48 0 0 LPXN 2 0.72 0.43 0.48 0 0 CNN2 2 0.46 0.16 0.48 0 0 CD63 2 0.74 0.47 0.48 0 0 TIFA 2 0.47 0.18 0.48 0 0 FAM6SB 2 0.41 0.08 0.47 0 0 ARID5A 2 0.56 0.26 0.47 0 0 ICAM1 2 0.42 0.12 0.47 0 0 IL2RB 2 0.63 0.32 0.47 0 0 GABARAP 2 0.94 0.71 0.47 0 0 SNX6 2 0.75 0.47 0.47 0 0 CCSER2 2 0.49 0.14 0.47 0 0 TSPO 2 0.73 0.45 0.46 0 0 IRF2 2 0.50 0.15 0.46 0 0 BIN2 2 0.49 0.16 0.46 0 0 NFKBIA 2 0.96 0.86 0.46 0 0 EBP 2 0.50 0.16 0.46 0 0 IFIT5 2 0.51 0.19 0.46 0 0 JAK1 2 0.85 0.56 0.46 0 0 PARP10 2 0.40 0.07 0.46 0 0 SH3BP5 2 0.46 0.13 0.46 0 0 RSU1 2 0.51 0.16 0.46 0 0 ACTR3 2 0.96 0.83 0.46 0 0 HUWE1 2 0.61 0.34 0.46 0 0 ARL4C 2 0.51 0.20 0.46 0 0 PRMT2 2 0.54 0.18 0.46 0 0 NDUFV2 2 0.96 0.82 0.46 0 0 JUNB 2 0.83 0.65 0.46 0 0 DDIT4 2 0.50 0.28 0.45 0 0 WIPF1 2 0.72 0.41 0.45 0 0 CALCOCO2 2 0.66 0.33 0.45 0 0 UPP1 2 0.47 0.14 0.45 0 0 SP110 2 0.57 0.26 0.45 0 0 CSTB 2 0.88 0.66 0.45 0 0 PDE4D 2 0.48 0.16 0.45 0 0 SLFN5 2 0.43 0.11 0.45 0 0 DHRS7 2 0.66 0.31 0.45 0 0 KDSR 2 0.64 0.38 0.45 0 0 NECAP2 2 0.61 0.29 0.44 0 0 KCNA3 2 0.42 0.09 0.44 0 0 PHF11 2 0.74 0.48 0.44 0 0 ARHGDIA 2 0.93 0.77 0.44 0 0 SOCS2 2 0.37 0.08 0.44 0 0 USP18 2 0.36 0.10 0.44 0 0 CTSS 2 0.53 0.21 0.44 0 0 NUB1 2 0.51 0.22 0.43 0 0 SMCHD1 2 0.74 0.48 0.43 0 0 C19orf66 2 0.75 0.49 0.43 0 0 CDC42SE2 2 0.73 0.44 0.43 0 0 TAGLN2 2 0.91 0.76 0.43 0 0 DDX60L 2 0.41 0.12 0.43 0 0 ARHGAP30 2 0.53 0.21 0.43 0 0 STAT2 2 0.43 0.13 0.42 0 0 LCP1 2 0.94 0.75 0.42 0 0 CD53 2 0.94 0.77 0.42 0 0 MYO1G 2 0.43 0.12 0.42 0 0 NAPA 2 0.75 0.50 0.42 0 0 KIFZA 2 0.67 0.40 0.42 0 0 PML 2 0.45 0.17 0.42 0 0 GLTSCR2 2 0.89 0.74 0.42 0 0 MAGED2 2 0.50 0.19 0.41 0 0 RABAC1 2 0.86 0.62 0.41 0 0 ITGB7 2 0.44 0.15 0.41 0 0 CYBA 2 0.87 0.73 0.41 0 0 CYTH1 2 0.47 0.16 0.41 0 0 TREX1 2 0.42 0.15 0.41 0 0 ARL6IP6 2 0.46 0.15 0.41 0 0 RBMS1 2 0.51 0.20 0.40 0 0 CCND3 2 0.75 0.49 0.40 0 0 NMI 2 0.61 0.35 0.40 0 0 BIN1 2 0.41 0.10 0.40 0 0 AES 2 0.64 0.33 0.40 0 0 NMRK1 2 0.41 0.11 0.40 0 0 EVL 2 0.71 0.38 0.40 0 0 ETS1 2 0.43 0.13 0.40 0 0 RAB11FIP1 2 0.56 0.27 0.40 0 0 ODF2L 2 0.39 0.09 0.40 0 0 AC017002.1 2 0.37 0.21 0.40 0 0 ZC3HAV1 2 0.56 0.27 0.40 0 0 ICAM3 2 0.63 0.34 0.40 0 0 PPP1CA 2 0.89 0.69 0.40 0 0 ARPC5 2 0.83 0.59 0.40 0 0 LAP3 2 0.67 0.50 0.39 0 0 RPS27L 2 0.67 0.50 0.39 0 0 GIMAP1 2 0.40 0.13 0.39 0 0 S100A10 2 0.97 0.79 0.39 0 0 YWHAH 2 0.49 0.23 0.39 0 0 MAT2B 2 0.67 0.41 0.39 0 0 VAMP5 2 0.40 0.14 0.39 0 0 SOCS3 2 0.32 0.09 0.39 0 0 TRAT1 2 0.59 0.28 0.39 0 0 ITGA4 2 0.52 0.30 0.39 0 0 MYL12B 2 0.99 0.93 0.39 0 0 NAGK 2 0.47 0.18 0.38 0 0 SHISA5 2 0.64 0.39 0.38 0 0 TMEM123 2 0.81 0.60 0.38 0 0 FDPS 2 0.66 0.45 0.38 0 0 AQP3 2 0.35 0.13 0.38 0 0 HLA-C 2 1.00 1.00 0.38 0 0 HSP90AA1 2 1.00 0.96 0.38 0 0 LSP1 2 0.66 0.35 0.38 0 0 MYD88 2 0.48 0.21 0.38 0 0 UGP2 2 0.48 0.20 0.38 0 0 ADAM8 2 0.36 0.09 0.38 0 0 TRIM21 2 0.48 0.20 0.38 0 0 TALDO1 2 0.77 0.54 0.38 0 0 FTH1 2 1.00 0.96 0.38 0 0 PIGER2 2 0.45 0.20 0.38 0 0 NUCB1 2 0.54 0.25 0.38 0 0 TMEM50A 2 0.91 0.74 0.38 0 0 PPDPF 2 0.92 0.77 0.37 0 0 RPS6KAS 2 0.36 0.08 0.37 0 0 MYH9 2 0.77 0.56 0.37 0 0 CLIP1 2 0.42 0.16 0.37 0 0 RPL10 2 1.00 1.00 0.37 0 0 CLIC1 2 0.98 0.93 0.37 0 0 LDLR 2 0.41 0.14 0.37 0 0 SGK1 2 0.46 0.22 0.37 0 0 GNA15 2 0.48 0.20 0.37 0 0 SPOCK2 2 0.67 0.34 0.37 0 0 KIAA0040 2 0.34 0.07 0.37 0 0 TPM3 2 0.98 0.89 0.37 0 0 FAM177A1 2 0.56 0.29 0.37 0 0 GRAP2 2 0.41 0.14 0.37 0 0 ADAR 2 0.76 0.56 0.37 0 0 ACAP2 2 0.50 0.21 0.37 0 0 RALB 2 0.34 0.06 0.36 0 0 HELZ2 2 0.35 0.09 0.36 0 0 TBC1D10C 2 0.37 0.10 0.36 0 0 C5orf56 2 0.40 0.12 0.36 0 0 TRPV2 2 0.35 0.07 0.36 0 0 PRDX5 2 0.79 0.57 0.36 0 0 TXNIP 2 0.32 0.10 0.36 0 0 ANXA2R 2 0.31 0.06 0.36 0 0 TRAFD1 2 0.43 0.17 0.36 0 0 SYNE2 2 0.80 0.56 0.36 0 0 MB21D1 2 0.44 0.19 0.36 0 0 COX17 2 0.72 0.50 0.35 0 0 ZNF267 2 0.56 0.28 0.35 0 0 RPL41 2 0.99 0.97 0.35 0 0 TRAPPC1 2 0.73 0.49 0.35 0 0 PPP1R15A 2 0.74 0.59 0.35 0 0 TMEM219 2 0.48 0.20 0.35 0 0 CCR2 2 0.21 0.01 0.35 0 0 TUBB4B 2 0.81 0.67 0.35 0 0 RNASEK 2 0.89 0.72 0.35 0 0 ANXA6 2 0.71 0.44 0.34 0 0 CSF1 2 0.29 0.08 0.34 0 0 TMEM50B 2 0.40 0.13 0.34 0 0 GUK1 2 0.93 0.78 0.34 0 0 TUBA1B 2 0.92 0.83 0.34 0 0 MGAT4A 2 0.42 0.14 0.34 0 0 HMHA1 2 0.33 0.07 0.34 0 0 LIF 2 0.24 0.08 0.34 0 0 RP11- 2 0.26 0.09 0.34 0 0 124N14.3 TMEM230 2 0.59 0.33 0.34 0 0 CYLD 2 0.65 0.38 0.34 0 0 PHTF2 2 0.40 0.14 0.34 0 0 MAP4 2 0.53 0.28 0.33 0 0 SEPW1 2 0.82 0.62 0.33 0 0 FDFT1 2 0.78 0.61 0.33 0 0 PMVK 2 0.53 0.30 0.33 0 0 ANXA11 2 0.71 0.46 0.33 0 0 IDH2 2 0.35 0.11 0.33 0 0 P2RY8 2 0.28 0.04 0.33 0 0 CYB5R3 2 0.51 0.25 0.33 0 0 SATB1 2 0.50 0.28 0.33 0 0 GLIPRZ 2 0.39 0.14 0.33 0 0 C9orf142 2 0.69 0.47 0.33 0 0 LYSMD2 2 0.57 0.33 0.33 0 0 LAMP3 2 0.32 0.11 0.32 0 0 GNAI2 2 0.39 0.14 0.32 0 0 RPL28 2 1.00 0.99 0.32 0 0 DCTN2 2 0.55 0.30 0.32 0 0 VPS28 2 0.74 0.53 0.32 0 0 CAPN1 2 0.38 0.13 0.32 0 0 IKBKE 2 0.29 0.06 0.32 0 0 DCK 2 0.37 0.13 0.32 0 0 FYB 2 0.59 0.37 0.32 0 0 CD37 2 0.82 0.61 0.32 0 0 RPS12 2 1.00 1.00 0.32 0 0 HLA-F 2 0.87 0.67 0.32 0 0 FBXW5 2 0.44 0.19 0.32 0 0 RGS19 2 0.45 0.24 0.32 0 0 FURIN 2 0.37 0.18 0.32 0 0 EMB 2 0.46 0.21 0.32 0 0 PRKX 2 0.35 0.15 0.31 0 0 CHST12 2 0.34 0.13 0.31 0 0 FXYD5 2 0.97 0.89 0.31 0 0 SELK 2 0.84 0.66 0.31 0 0 MB21D2 2 0.28 0.04 0.31 0 0 WAS 2 0.49 0.24 0.31 0 0 RCSD1 2 0.44 0.20 0.31 0 0 VPS29 2 0.62 0.40 0.31 0 0 S1PR1 2 0.33 0.13 0.31 0 0 CRYZ 2 0.31 0.08 0.31 0 0 SLC4A10 2 0.20 0.02 0.31 0 0 LGALS3BP 2 0.28 0.12 0.31 0 0 RORA 2 0.63 0.33 0.31 0 0 ATP5H 2 0.77 0.57 0.31 0 0 CD247 2 0.76 0.51 0.31 0 0 CAP1 2 0.88 0.73 0.31 0 0 PGLS 2 0.57 0.34 0.31 0 0 PARP8 2 0.39 0.15 0.31 0 0 ETHE1 2 0.40 0.17 0.31 0 0 C19orf60 2 0.59 0.36 0.30 0 0 ACAA2 2 0.45 0.20 0.30 0 0 EHD4 2 0.57 0.35 0.30 0 0 OST4 2 0.93 0.81 0.30 0 0 COMMD6 2 0.84 0.66 0.30 0 0 CPNE3 2 0.40 0.17 0.30 0 0 C4orf3 2 0.83 0.64 0.30 0 0 DCTN3 2 0.46 0.21 0.30 0 0 MSC 2 0.23 0.07 0.30 0 0 TMEM59 2 0.77 0.56 0.30 0 0 RGS14 2 0.26 0.05 0.30 0 0 RPL13 2 1.00 1.00 0.30 0 0 FKBP2 2 0.80 0.64 0.29 0 0 RCAN3 2 0.33 0.11 0.29 0 0 RBX1 2 0.84 0.69 0.29 0 0 ELOVL1 2 0.54 0.31 0.29 0 0 C6orf1 2 0.32 0.09 0.29 0 0 DYNLRB1 2 0.73 0.53 0.29 0 0 RASAL3 2 0.54 0.30 0.29 0 0 VPS13C 2 0.44 0.21 0.29 0 0 PRDM1 2 0.41 0.17 0.29 0 0 APOL1 2 0.27 0.05 0.29 0 0 YWHAZ 2 0.99 0.94 0.29 0 0 IQGAP1 2 0.59 0.34 0.29 0 0 PSIP1 2 0.44 0.21 0.29 0 0 HLA-B 2 1.00 1.00 0.29 0 0 FLOT1 2 0.45 0.27 0.29 0 0 GMFG 2 0.83 0.62 0.29 0 0 C14orf1 2 0.56 0.35 0.29 0 0 IKZF1 2 0.64 0.39 0.29 0 0 COMMD7 2 0.37 0.14 0.29 0 0 IFI16 2 0.69 0.51 0.29 0 0 TMEM173 2 0.35 0.16 0.29 0 0 LMF2 2 0.39 0.15 0.29 0 0 GNG2 2 0.77 0.53 0.29 0 0 RAB11A 2 0.70 0.55 0.29 0 0 LST1 2 0.22 0.03 0.28 0 0 NFKBIZ 2 0.46 0.23 0.28 0 0 RPS4X 2 1.00 0.99 0.28 0 0 TNIP1 2 0.71 0.48 0.28 0 0 ECH1 2 0.51 0.28 0.28 0 0 SMAP 2 0.55 0.33 0.28 0 0 SUMO3 2 0.57 0.36 0.28 0 0 DOCK8 2 0.51 0.28 0.28 0 0 SPINT2 2 0.24 0.07 0.28 0 0 SLC25A24 2 0.26 0.05 0.28 0 0 RAB1B 2 0.72 0.53 0.28 0 0 LRP10 2 0.49 0.25 0.28 0 0 GLO1 2 0.50 0.29 0.28 0 0 STK17A 2 0.49 0.28 0.28 0 0 SPG20 2 0.33 0.11 0.28 0 0 CAMK4 2 0.48 0.24 0.27 0 0 B2M 2 1.00 1.00 0.27 0 0 RAB7L1 2 0.37 0.16 0.27 0 0 NME3 2 0.38 0.20 0.27 0 0 GPR65 2 0.44 0.23 0.27 0 0 CRELD2 2 0.46 0.25 0.27 0 0 MANF 2 0.76 0.60 0.27 0 0 GPR137 2 0.34 0.13 0.27 0 0 ARL2BP 2 0.42 0.21 0.27 0 0 MITD1 2 0.43 0.23 0.27 0 0 ANXA5 2 0.62 0.35 0.27 0 0 C19orf70 2 0.75 0.58 0.27 0 0 GDI1 2 0.55 0.36 0.27 0 0 ITSN2 2 0.51 0.29 0.27 0 0 ATOX1 2 0.58 0.41 0.27 0 0 BCL3 2 0.23 0.04 0.27 0 0 PNRC1 2 0.66 0.44 0.27 0 0 HBEGF 2 0.14 0.03 0.27 0 0 MAPKAPK3 2 0.48 0.31 0.27 0 0 RTP4 2 0.24 0.05 0.26 0 0 CHMP4A 2 0.52 0.33 0.26 0 0 STK10 2 0.33 0.12 0.26 0 0 BLVRA 2 0.39 0.19 0.26 0 0 PSENEN 2 0.54 0.33 0.26 0 0 HMGN3 2 0.39 0.18 0.26 0 0 PYCARD 2 0.24 0.06 0.26 0 0 KMT2A 2 0.35 0.16 0.26 0 0 GCH1 2 0.31 0.12 0.26 0 0 REEP5 2 0.76 0.57 0.26 0 0 HINT1 2 0.99 0.96 0.26 0 0 CIGALT1 2 0.52 0.32 0.26 0 0 RASA2 2 0.33 0.13 0.26 0 0 FAM46C 2 0.28 0.08 0.26 0 0 SNX3 2 0.60 0.42 0.26 0 0 TMEM256- 2 0.35 0.16 0.26 0 0 PLSCR3 STOM 2 0.42 0.21 0.26 0 0 JAK3 2 0.42 0.22 0.26 0 0 SPATS2L 2 0.24 0.05 0.26 0 0 NDUFB7 2 0.71 0.55 0.25 0 0 LAMTOR4 2 0.68 0.50 0.25 0 0 LNPEP 2 0.37 0.15 0.25 0 0 UQCRB 2 0.89 0.76 0.25 0 0 SLC39A8 2 0.32 0.13 0.25 0 0 C1orf86 2 0.40 0.21 0.25 0 0 FBXO6 2 0.27 0.09 0.25 0 0 PHF1 2 0.42 0.20 0.25 0 0 SEPT1 2 0.66 0.47 0.26 4.41813263137076e319 6.12220638729047e315 GSTP1 2 0.85 0.73 0.27 3.67359914106818e314 5.09050632977817e310 CKLF 2 0.55 0.40 0.30 8.6472877116679e311 1.20E306 GPX1 2 0.60 0.40 0.29 8.37E298 1.16E293 CTSC 2 0.68 0.50 0.30 3.58E294 4.97E290 SOD2 2 0.52 0.36 0.26 2.16E257 2.99E253 CCR7 2 0.34 0.20 0.34 2.13E222 2.95E218 FOS 2 0.43 0.41 0.35 3.30E192 4.58E188 JUN 2 0.49 0.38 0.37 8.10E191 1.12E186 GZMA 2 0.15 0.08 0.28 2.03E142 2.82E138 FTL 2 0.99 0.96 0.25 1.07E123 1.48E119
[0163] As referred to herein, Table 2 depicts as follows:
TABLE-US-00002 TABLE 2 Test statistics Fraction of Average expressing cells logged Cluster- Other fold Adjusted Gene ID Cluster specific cells Change P-value P-value CCL4 4 0.97 0.30 2.99 0 0 XCL1 4 0.81 0.13 2.99 0 0 XCL2 4 0.78 0.10 2.95 0 0 GZMB 4 0.96 0.19 2.44 0 0 CCL3 4 0.77 0.11 2.43 0 0 PRF1 4 0.94 0.20 1.99 0 0 CCL4L2 4 0.57 0.04 1.84 0 0 CCL5 4 0.93 0.23 1.71 0 0 PLEK 4 0.86 0.12 1.68 0 0 NKG7 4 0.89 0.18 1.61 0 0 CCL4L1 4 0.47 0.06 1.60 0 0 GZMH 4 0.69 0.06 1.54 0 0 GNLY 4 0.64 0.10 1.51 0 0 CRTAM 4 0.40 0.05 1.46 0 0 SLAMF7 4 0.67 0.08 1.14 0 0 HOPX 4 0.78 0.20 1.14 0 0 CD72 4 0.53 0.08 1.03 0 0 CST7 4 0.91 0.52 0.92 0 0 FASLG 4 0.80 0.41 0.91 0 0 EGR2 4 0.76 0.40 0.86 0 0 ZEB2 4 0.70 0.30 0.83 0 0 PCID2 4 0.55 0.41 0.75 0 0 IQCG 4 0.29 0.07 0.75 0 0 PPP1R2 4 0.92 0.77 0.73 0 0 ZFP36L1 4 0.93 0.83 0.69 0 0 TNFRSF9 4 0.83 0.53 0.69 0 0 BTG1 4 0.99 0.95 0.67 0 0 TRIM22 4 0.86 0.66 0.66 0 0 CD160 4 0.20 0.02 0.66 0 0 LITAF 4 0.70 0.47 0.65 0 0 APOBEC3G 4 0.83 0.58 0.65 0 0 TAGAP 4 0.92 0.76 0.62 0 0 CFLAR 4 0.89 0.79 0.59 0 0 GPR18 4 0.40 0.13 0.59 0 0 TGIF1 4 0.69 0.52 0.59 0 0 CBLB 4 0.79 0.59 0.58 0 0 EVI2A 4 0.72 0.53 0.58 0 0 TMBIM1 4 0.63 0.47 0.53 0 0 IL18RAP 4 0.39 0.15 0.53 0 0 LTBP4 4 0.73 0.55 0.53 0 0 TNFSF9 4 0.48 0.19 0.53 0 0 CX3CR1 4 0.25 0.03 0.52 0 0 APOBEC3C 4 0.55 0.37 0.51 0 0 CD84 4 0.50 0.29 0.51 0 0 CD97 4 0.74 0.59 0.50 0 0 LYST 4 0.61 0.46 0.50 0 0 CD58 4 0.67 0.51 0.50 0 0 NUCB2 4 0.38 0.27 0.50 0 0 TNFAIP8 4 0.90 0.83 0.49 0 0 PAM 4 0.69 0.50 0.48 0 0 VCL 4 0.32 0.11 0.47 0 0 THEMIS 4 0.34 0.18 0.47 0 0 CCDC107 4 0.53 0.38 0.46 0 0 SRGN 4 1.00 0.99 0.45 0 0 HMGB1 4 0.89 0.86 0.45 0 0 DUSP18 4 0.39 0.23 0.45 0 0 RHOG 4 0.94 0.86 0.45 0 0 SLAMF6 4 0.48 0.31 0.44 0 0 STAT5A 4 0.58 0.47 0.44 0 0 CD6 4 0.74 0.62 0.43 0 0 DNAJB9 4 0.47 0.32 0.43 0 0 ARL6IP1 4 0.77 0.74 0.42 0 0 CCL3L1 4 0.11 0.01 0.42 0 0 UCP2 4 0.62 0.49 0.42 0 0 UBB 4 0.96 0.93 0.41 0 0 PRKCH 4 0.82 0.70 0.41 0 0 XIRP1 4 0.19 0.08 0.41 0 0 PDHA1 4 0.60 0.51 0.41 0 0 CD82 4 0.98 0.91 0.40 0 0 BCL2A1 4 0.86 0.68 0.40 0 0 TUBA1B 4 0.90 0.84 0.40 0 0 PGAM1 4 1.00 0.97 0.39 0 0 PRSS23 4 0.17 0.04 0.39 0 0 SSR2 4 0.84 0.84 0.39 0 0 RINS 4 0.26 0.09 0.39 0 0 CHMP4B 4 0.62 0.51 0.39 0 0 YWHAQ 4 0.88 0.85 0.38 0 0 SEC61B 4 0.97 0.94 0.38 0 0 H3F3B 4 1.00 0.99 0.38 0 0 MIR4435-1HG 4 0.64 0.42 0.38 0 0 ARF4 4 0.82 0.78 0.38 0 0 RP11- 4 0.49 0.41 0.38 0 0 773D16.1 GLUD1 4 0.71 0.62 0.38 0 0 PPM1B 4 0.36 0.23 0.36 0 0 HLA-DPB1 4 0.34 0.16 0.36 0 0 ETS2 4 0.32 0.22 0.36 0 0 HECTD2 4 0.32 0.18 0.36 0 0 TPS12 4 0.40 0.30 0.36 0 0 PIGT 4 0.51 0.42 0.35 0 0 IL12RB2 4 0.27 0.16 0.35 0 0 RAP1B 4 0.85 0.80 0.35 0 0 SSR3 4 0.68 0.65 0.35 0 0 SEC61A1 4 0.61 0.55 0.35 0 0 BCL2L1 4 0.69 0.62 0.35 0 0 MAST3 4 0.23 0.10 0.35 0 0 OSTC 4 0.83 0.81 0.34 0 0 BCL2L11 4 0.31 0.21 0.34 0 0 SERP1 4 0.89 0.89 0.34 0 0 ATP1B3 4 0.82 0.76 0.34 0 0 MIR155HG 4 0.99 0.94 0.34 0 0 PKM 4 1.00 0.98 0.33 0 0 PTTG1 4 0.35 0.26 0.33 0 0 SPCS2 4 0.85 0.84 0.33 0 0 KDELR2 4 0.73 0.71 0.33 0 0 UBE2B 4 0.68 0.64 0.32 0 0 ATP1B1 4 0.19 0.07 0.32 0 0 AGO2 4 0.47 0.37 0.32 0 0 TROVE2 4 0.44 0.38 0.32 0 0 RHOB 4 0.24 0.12 0.31 0 0 LRRFIP2 4 0.36 0.29 0.31 0 0 GORASP2 4 0.56 0.53 0.31 0 0 C10orf54 4 0.91 0.75 0.31 0 0 SEC61G 4 0.84 0.84 0.31 0 0 GSTO1 4 0.53 0.51 0.29 0 0 IFNG 4 0.95 0.62 0.29 0 0 CCND3 4 0.59 0.51 0.28 0 0 TMEM167A 4 0.57 0.56 0.28 0 0 C19orf10 4 0.80 0.80 0.28 0 0 MAP2K3 4 0.87 0.75 0.27 0 0 INPP1 4 0.20 0.11 0.27 0 0 RAB27A 4 0.68 0.58 0.27 0 0 RGCC 4 0.90 0.74 0.27 0 0 ARF1 4 0.92 0.92 0.27 0 0 HMGN2 4 0.72 0.74 0.26 0 0 TMED2 4 0.77 0.79 0.25 0 0 ZNF706 4 0.80 0.78 0.25 0 0 CREB3L2 4 0.19 0.10 0.25 0 0 SLAMF1 4 0.87 0.76 0.40 1.88733076711356e321 2.61527424398926e317 PPP1R18 4 0.63 0.57 0.34 3.08626504790714e318 4.27663747688492e314 EXOC2 4 0.36 0.27 0.35 2.40955222598001e317 3.3389165195405e313 HLA-DPA1 4 0.35 0.22 0.26 3.41094275739994e317 4.7265433789291e313 HLA-B 4 1.00 1.00 0.31 1.45823270332801e315 2.02067305700162e311 HCST 4 0.77 0.71 0.40 2.13866733213076e312 2.96E308 PAIP2 4 0.61 0.59 0.27 4.82158305607204e310 6.68E306 TESK1 4 0.21 0.08 0.27 1.29E305 1.78E301 CINNA1 4 0.44 0.32 0.38 2.14E305 2.96E301 CLCF1 4 0.17 0.08 0.25 3.74E302 5.18E298 STARD4 4 0.43 0.34 0.31 6.32E302 8.76E298 HLA-E 4 1.00 1.00 0.27 1.79E301 2.48E297 QPCT 4 0.20 0.09 0.30 3.38E301 4.68E297 CTSC 4 0.60 0.52 0.33 5.06E299 7.01E295 TMED10 4 0.76 0.75 0.31 3.14E297 4.35E293 BIRC3 4 0.80 0.69 0.59 1.52E295 2.11E291 SSR1 4 0.57 0.56 0.25 5.61E293 7.78E289 GPR137B 4 0.24 0.15 0.29 1.87E289 2.60E285 IGF2R 4 0.31 0.18 0.33 2.16E285 2.99E281 ARMCX3 4 0.39 0.32 0.31 9.66E280 1.34E275 PRR13 4 0.67 0.67 0.27 1.66E274 2.30E270 ATP2B4 4 0.33 0.21 0.34 3.27E273 4.53E269 SERPINE2 4 0.26 0.18 0.34 1.56E272 2.17E268 ANKRD28 4 0.34 0.18 0.37 1.84E269 2.55E265 TUBA1C 4 0.78 0.78 0.25 5.71E268 7.91E264 NR3C1 4 0.63 0.54 0.40 9.96E267 1.38E262 ZYX 4 0.58 0.52 0.32 2.41E264 3.34E260 VASP 4 0.72 0.70 0.27 6.99E260 9.68E256 TNFRSF1B 4 0.76 0.72 0.28 1.69E252 2.34E248 SDCBP 4 0.70 0.65 0.40 6.48E246 8.98E242 MDFIC 4 0.51 0.43 0.32 1.69E243 2.35E239 CHSY1 4 0.24 0.14 0.27 3.49E242 4.84E238 TNFRSF1A 4 0.31 0.20 0.31 2.44E239 3.38E235 GLUL 4 0.33 0.22 0.31 5.30E239 7.35E235 TIGIT 4 0.34 0.26 0.35 1.23E237 1.70E233 HBP1 4 0.30 0.19 0.33 1.67E232 2.31E228 IQGAP2 4 0.32 0.24 0.28 1.68E232 2.32E228 KIF21A 4 0.33 0.26 0.29 1.36E231 1.89E227 MAP3K8 4 0.47 0.35 0.33 3.45E227 4.78E223 DYNLT3 4 0.50 0.41 0.37 1.93E225 2.67E221 NFATC3 4 0.29 0.22 0.26 1.60E224 2.21E220 STX5 4 0.35 0.30 0.25 1.96E221 2.71E217 TNFAIP3 4 0.74 0.66 0.40 5.43E220 7.53E216 CDC42EP3 4 0.59 0.45 0.42 6.46E219 8.96E215 SLC29A1 4 0.36 0.36 0.27 1.12E213 1.56E209 NR4A2 4 0.58 0.43 0.38 1.83E213 2.54E209 MAP1LC3A 4 0.34 0.24 0.32 9.57E213 1.33E208 TMC6 4 0.35 0.26 0.32 2.14E212 2.96E208 CREB3 4 0.36 0.31 0.26 5.57E209 7.72E205 JARID2 4 0.49 0.41 0.33 3.89E205 5.38E201 EIF1B 4 0.69 0.69 0.25 6.51E204 9.02E200 CD83 4 0.50 0.41 0.51 7.44E203 1.03E198 TNFSF10 4 0.73 0.59 0.28 4.11E202 5.70E198 N4BP2L1 4 0.25 0.17 0.27 9.24E199 1.28E194 HERPUD2 4 0.24 0.18 0.26 6.84E196 9.48E192 HOXB2 4 0.26 0.17 0.26 1.22E193 1.69E189 GNAS 4 0.55 0.54 0.26 3.34E192 4.63E188 EPS15 4 0.34 0.28 0.25 8.72E191 1.21E186 TLN1 4 0.42 0.36 0.28 1.15E181 1.60E177 PIM1 4 0.48 0.38 0.31 2.52E181 3.49E177 FYN 4 0.74 0.66 0.31 3.41E180 4.73E176 PRNP 4 0.82 0.74 0.46 4.41E180 6.11E176 RLF 4 0.41 0.32 0.30 5.49E179 7.61E175 BATF3 4 0.17 0.12 0.26 1.05E174 1.45E170 LBH 4 0.57 0.53 0.28 1.24E164 1.72E160 SLA 4 0.69 0.60 0.35 1.73E160 2.40E156 SLC4A7 4 0.34 0.24 0.30 7.47E160 1.04E155 TRAF1 4 0.72 0.66 0.32 5.74E153 7.95E149 N4BP2L2 4 0.59 0.60 0.25 2.93E151 4.06E147 RASSF5 4 0.70 0.66 0.29 1.09E148 1.52E144 SIT1 4 0.31 0.24 0.27 6.04E145 8.37E141 CD48 4 0.89 0.88 0.26 3.64E135 5.04E131 SLC20A1 4 0.40 0.34 0.29 9.68E134 1.34E129 IRF4 4 0.59 0.51 0.29 1.62E130 2.24E126 TM2D3 4 0.65 0.60 0.25 8.24E129 1.14E124 PIGER2 4 0.36 0.22 0.31 2.95E121 4.08E117 BCL2 4 0.43 0.36 0.28 1.60E118 2.21E114 IL7R 4 0.91 0.79 0.41 1.91E116 2.65E112 AC006369.2 4 0.26 0.15 0.31 1.02E111 1.41E107 KLF10 4 0.50 0.43 0.30 4.43E110 6.14E106 MAML2 4 0.42 0.33 0.26 8.95E108 1.24E103 KMT2E 4 0.70 0.68 0.28 2.92E107 4.05E103 CTLA4 4 0.42 0.41 0.25 1.06E105 1.46E101 XBP1 4 0.74 0.70 0.29 1.65E103 2.28E99 KDM6B 4 0.62 0.53 0.30 5.01E103 6.95E99 ITK 4 0.65 0.62 0.26 2.88E102 3.99E98 LGALS1 4 0.50 0.42 0.27 6.13E97 8.49E93 PHLDA1 4 0.61 0.57 0.27 8.32E81 1.15E76 PIGER4 4 0.56 0.47 0.32 1.52E71 2.11E67 BIG2 4 0.55 0.47 0.38 1.04E68 1.45E64 NR4A3 4 0.42 0.35 0.32 1.03E56 1.42E52
[0164] As referred to herein, Table 3 depicts as follows:
TABLE-US-00003 TABLE 3 Test statistics Fraction of Average expressing cells logged Cluster- Other Fold Adjusted Gene ID Cluster specific cells Change P-value P-value AC006129.4 6 0.72 0.10 1.25 0 0 DOK5 6 0.41 0.04 1.23 0 0 NMB 6 0.58 0.18 1.07 0 0 FABPS 6 1.00 0.67 1.06 0 0 ZBED2 6 0.59 0.15 0.99 0 0 HLA-DRA 6 0.58 0.08 0.91 0 0 POUZAF1 6 0.89 0.28 0.90 0 0 FKBP1A 6 0.99 0.84 0.87 0 0 CD70 6 0.51 0.16 0.86 0 0 SLC27A2 6 0.91 0.28 0.84 0 0 DYNLL1 6 0.95 0.61 0.82 0 0 DUSP4 6 0.93 0.44 0.79 0 0 EID1 6 0.96 0.72 0.78 0 0 MIR4435-1HG 6 0.94 0.40 0.76 0 0 ITM2A 6 0.90 0.55 0.75 0 0 GNG4 6 0.77 0.22 0.70 0 0 C16orf45 6 0.59 0.13 0.68 0 0 RAB27A 6 0.94 0.56 0.65 0 0 REXO2 6 0.95 0.62 0.64 0 0 ANXA5 6 0.75 0.35 0.64 0 0 LAT 6 0.90 0.58 0.64 0 0 CCND3 6 0.80 0.50 0.63 0 0 PGAM1 6 1.00 0.97 0.62 0 0 ZBTB32 6 0.68 0.18 0.61 0 0 HLA-DRB1 6 0.58 0.17 0.60 0 0 GALM 6 0.75 0.29 0.60 0 0 LAG3 6 0.68 0.27 0.59 0 0 AHI1 6 0.85 0.40 0.59 0 0 AGK 6 0.81 0.34 0.58 0 0 TRAF3IP3 6 0.66 0.24 0.57 0 0 CD200 6 0.93 0.50 0.57 0 0 ANKH 6 0.62 0.26 0.57 0 0 ATP5G3 6 0.99 0.89 0.56 0 0 SOD1 6 1.00 0.91 0.56 0 0 RPS6KA1 6 0.75 0.27 0.56 0 0 TBC1D4 6 0.84 0.35 0.55 0 0 PPP1CC 6 0.95 0.65 0.54 0 0 TIMMDC1 6 0.75 0.28 0.53 0 0 ARMC9 6 0.46 0.07 0.52 0 0 RGCC 6 0.98 0.73 0.52 0 0 COTL1 6 0.99 0.78 0.51 0 0 CNIH1 6 0.95 0.68 0.50 0 0 C7orf73 6 0.85 0.42 0.50 0 0 C1QBP 6 0.99 0.88 0.49 0 0 DSTN 6 0.75 0.40 0.49 0 0 IFNG 6 0.93 0.62 0.49 0 0 TIMM13 6 0.94 0.62 0.48 0 0 PDCD1 6 0.81 0.40 0.48 0 0 PRDX3 6 0.93 0.62 0.48 0 0 LINC00152 6 0.96 0.62 0.48 0 0 PFDN4 6 0.80 0.42 0.48 0 0 ADSS 6 0.89 0.53 0.47 0 0 PARVB 6 0.66 0.18 0.47 0 0 SMS 6 0.89 0.56 0.47 0 0 LDHA 6 1.00 0.96 0.47 0 0 FERMT3 6 0.90 0.54 0.47 0 0 TIGIT 6 0.54 0.24 0.47 0 0 SEC11A 6 0.94 0.64 0.46 0 0 UBASH3B 6 0.62 0.16 0.46 0 0 GEM 6 0.61 0.17 0.46 0 0 SDC4 6 0.75 0.37 0.46 0 0 COA6 6 0.86 0.47 0.46 0 0 PARK7 6 1.00 0.94 0.46 0 0 GLRX3 6 0.94 0.62 0.45 0 0 TMED3 6 0.75 0.32 0.45 0 0 MRPS34 6 0.89 0.55 0.45 0 0 MDH2 6 0.95 0.68 0.45 0 0 PLEKHF1 6 0.42 0.08 0.44 0 0 HLA-DRB5 6 0.47 0.13 0.44 0 0 GALNT2 6 0.59 0.16 0.42 0 0 INPP5F 6 0.47 0.10 0.42 0 0 C12orf10 6 0.73 0.31 0.42 0 0 TMEM173 6 0.51 0.16 0.42 0 0 XIRP1 6 0.31 0.07 0.42 0 0 CCDC50 6 0.35 0.10 0.42 0 0 MYO1E 6 0.36 0.02 0.42 0 0 C16orf87 6 0.63 0.20 0.42 0 0 GRAMD1A 6 0.54 0.19 0.42 0 0 ANAPC1 6 0.43 0.21 0.41 0 0 SMOX 6 0.48 0.13 0.41 0 0 PPP1R2 6 0.98 0.77 0.41 0 0 NUCB2 6 0.58 0.25 0.41 0 0 CXCR3 6 0.81 0.38 0.41 0 0 CD109 6 0.56 0.13 0.40 0 0 GTF3C6 6 0.93 0.67 0.40 0 0 GPI 6 0.94 0.67 0.40 0 0 FAM3C 6 0.48 0.17 0.40 0 0 POU2F2 6 0.91 0.58 0.40 0 0 TSHZ2 6 0.70 0.25 0.39 0 0 YWHAE 6 0.92 0.62 0.39 0 0 MYL6B 6 0.49 0.08 0.39 0 0 APOBEC3C 6 0.75 0.36 0.38 0 0 PSMA1 6 0.98 0.82 0.38 0 0 CD74 6 0.94 0.75 0.38 0 0 TIMM17A 6 0.89 0.58 0.38 0 0 ATP1B3 6 0.98 0.74 0.38 0 0 RDH10 6 0.42 0.08 0.38 0 0 SNX8 6 0.56 0.17 0.38 0 0 ENOPH1 6 0.79 0.43 0.38 0 0 C12orf75 6 0.42 0.12 0.38 0 0 LEPROTL1 6 0.87 0.51 0.38 0 0 CTPS1 6 0.88 0.50 0.38 0 0 APOBEC3G 6 0.87 0.58 0.38 0 0 PHB2 6 0.97 0.79 0.37 0 0 CLTA 6 0.94 0.69 0.37 0 0 RCC1 6 0.92 0.61 0.37 0 0 POMP 6 0.99 0.87 0.37 0 0 NDUFS8 6 0.86 0.53 0.37 0 0 PRKCDBP 6 0.21 0.01 0.37 0 0 SFT2D1 6 0.72 0.31 0.37 0 0 UBE2N 6 0.96 0.80 0.37 0 0 CRTAM 6 0.23 0.07 0.37 0 0 PDCD6 6 0.91 0.62 0.37 0 0 PFKP 6 0.93 0.63 0.37 0 0 ATP5J 6 0.95 0.75 0.36 0 0 AC006129.2 6 0.52 0.17 0.36 0 0 C1orf43 6 0.92 0.64 0.36 0 0 PSMBS 6 0.83 0.50 0.36 0 0 PSMA4 6 0.93 0.66 0.36 0 0 STAMBP 6 0.53 0.17 0.36 0 0 MDH1 6 0.92 0.67 0.36 0 0 HSBP1 6 0.82 0.46 0.36 0 0 CD58 6 0.86 0.49 0.36 0 0 MICAL2 6 0.43 0.10 0.36 0 0 ATP5C1 6 0.96 0.76 0.35 0 0 TXNDC17 6 0.90 0.58 0.35 0 0 IFNAR2 6 0.79 0.37 0.35 0 0 HMGB1 6 0.98 0.85 0.35 0 0 HDDC2 6 0.77 0.39 0.35 0 0 DESI1 6 0.80 0.45 0.35 0 0 VDAC2 6 0.95 0.75 0.35 0 0 ITPA 6 0.79 0.41 0.35 0 0 SHFM1 6 0.96 0.74 0.35 0 0 ELMO1 6 0.87 0.47 0.35 0 0 UBE2V1 6 0.85 0.54 0.35 0 0 ATP5A1 6 0.93 0.69 0.35 0 0 MPG 6 0.68 0.28 0.35 0 0 ATP5G2 6 0.99 0.90 0.34 0 0 EXOSC7 6 0.76 0.39 0.34 0 0 ARL5A 6 0.90 0.61 0.34 0 0 MMADHC 6 0.90 0.61 0.34 0 0 ASF1A 6 0.63 0.28 0.34 0 0 MRPL51 6 0.89 0.60 0.34 0 0 UBE2V2 6 0.79 0.42 0.33 0 0 PTPN11 6 0.76 0.41 0.33 0 0 WDR1 6 0.96 0.77 0.33 0 0 HTATIP2 6 0.68 0.30 0.33 0 0 SNX9 6 0.75 0.45 0.33 0 0 NTSC 6 0.77 0.38 0.33 0 0 ETFA 6 0.79 0.45 0.33 0 0 ZNF706 6 0.97 0.77 0.33 0 0 NUDT21 6 0.85 0.52 0.33 0 0 MRPS23 6 0.84 0.51 0.33 0 0 PSTPIP1 6 0.52 0.16 0.33 0 0 CD99 6 0.98 0.85 0.33 0 0 NDUFS3 6 0.80 0.45 0.32 0 0 ETFB 6 0.58 0.24 0.32 0 0 PSMB2 6 0.95 0.74 0.32 0 0 PSMD8 6 0.98 0.85 0.32 0 0 PSMD11 6 0.95 0.74 0.32 0 0 PSMB1 6 0.99 0.88 0.32 0 0 LAMTOR5 6 0.95 0.73 0.31 0 0 MRPL42 6 0.73 0.37 0.31 0 0 LBH 6 0.81 0.51 0.31 0 0 HAVCR2 6 0.26 0.04 0.31 0 0 CMC2 6 0.90 0.62 0.31 0 0 TMEM167A 6 0.86 0.54 0.31 0 0 PAM 6 0.89 0.49 0.31 0 0 SH2D2A 6 0.97 0.83 0.31 0 0 UBE2L3 6 0.92 0.68 0.31 0 0 NUDT5 6 0.82 0.49 0.31 0 0 PCED1B 6 0.76 0.42 0.30 0 0 MRPL34 6 0.77 0.44 0.30 0 0 HLA-DPA1 6 0.53 0.20 0.30 0 0 ATP6V1B2 6 0.66 0.31 0.30 0 0 UQCRFS1 6 0.96 0.77 0.30 0 0 SRGN 6 1.00 0.99 0.29 0 0 C11orf31 6 0.97 0.81 0.29 0 0 MBOAT7 6 0.55 0.23 0.29 0 0 SNRNP35 6 0.61 0.27 0.29 0 0 SLC6A6 6 0.49 0.15 0.29 0 0 C11orf58 6 0.95 0.76 0.29 0 0 LAMTOR1 6 0.83 0.50 0.29 0 0 EIF4E 6 0.92 0.67 0.29 0 0 ARL1 6 0.70 0.34 0.28 0 0 RAC1 6 0.89 0.62 0.28 0 0 MAP2K3 6 0.98 0.74 0.27 0 0 H3F3A 6 1.00 0.96 0.27 0 0 GSTO1 6 0.79 0.49 0.27 0 0 AIP 6 0.83 0.53 0.27 0 0 CAPZB 6 0.96 0.81 0.27 0 0 TNFRSF9 6 0.87 0.53 0.27 0 0 TERF2IP 6 0.88 0.60 0.27 0 0 MEAF6 6 0.85 0.54 0.26 0 0 CSNK2B 6 0.96 0.78 0.26 0 0 GBP2 6 0.98 0.84 0.26 0 0 GCNT1 6 0.44 0.14 0.26 0 0 SLA2 6 0.40 0.10 0.26 0 0 STX10 6 0.59 0.25 0.25 0 0 PRSS23 6 0.22 0.04 0.25 0 0 EWSR1 6 0.96 0.77 0.28 1.23516411460312e322 1.71156691360554e318 SERPINE2 6 0.46 0.17 0.26 5.51031414806742e320 7.63564231497703e316 TXNL1 6 0.90 0.64 0.27 6.18421968899488e320 8.56947322304021e316 CDC123 6 0.90 0.61 0.30 3.68330879631108e319 5.10396099904826e315 CLNS1A 6 0.87 0.54 0.34 8.30761502169139e319 1.15118621355578e314 MRPL36 6 0.88 0.57 0.32 1.71572694634352e318 2.37748282954822e314 LYPLA1 6 0.84 0.50 0.34 2.70025007661444e316 3.74173653116462e312 GAPDH 6 1.00 0.99 0.43 3.93110653166459e316 5.44733432092762e312 NTRK1 6 0.34 0.09 0.33 7.56614835544762e315 1.04844117761438e310 COX5A 6 0.98 0.86 0.37 2.87544253875645e314 3.98450072595482e310 FAM96A 6 0.70 0.35 0.29 1.44787776470577e313 0.00E+00 SNRPD3 6 0.97 0.78 0.32 2.50204094853181e313 0.00E+00 COMT 6 0.65 0.29 0.30 3.03144507962767e312 4.20E308 PSMB7 6 0.92 0.64 0.35 4.08084880701111e311 5.65E307 UBA5 6 0.66 0.30 0.29 0.00E+00 1.41E305 BTLA 6 0.76 0.34 0.38 6.86E307 9.50E303 PRDX4 6 0.83 0.56 0.35 2.00E305 2.77E301 SNX5 6 0.77 0.43 0.27 1.00E301 1.39E297 ABHD2 6 0.43 0.13 0.31 5.74E301 7.95E297 MINOS1 6 0.82 0.51 0.26 2.31E299 3.20E295 C5orf15 6 0.59 0.27 0.27 1.08E298 1.50E294 UCHL3 6 0.81 0.45 0.42 2.95E295 4.09E291 NDUFA11 6 0.88 0.59 0.28 3.28E294 4.54E290 MRPL17 6 0.87 0.59 0.29 3.67E294 5.08E290 TCEB1 6 0.96 0.78 0.26 1.27E293 1.76E289 MTCH2 6 0.81 0.47 0.30 5.79E292 8.02E288 VDAC1 6 0.96 0.76 0.42 2.59E291 3.59E287 HLA-DQB1 6 0.39 0.14 0.31 8.05E291 1.12E286 SH3BGRL3 6 1.00 0.96 0.28 2.81E288 3.90E284 NDUFB9 6 0.94 0.75 0.27 2.45E286 3.40E282 POLR2K 6 0.94 0.72 0.26 1.64E285 2.27E281 LYRM4 6 0.69 0.32 0.34 3.03E284 4.19E280 RBBP8 6 0.64 0.27 0.32 3.58E284 4.97E280 MRPS7 6 0.91 0.68 0.28 3.96E283 5.49E279 UCP2 6 0.80 0.48 0.42 5.45E283 7.55E279 AIMP2 6 0.79 0.43 0.33 1.10E282 1.53E278 PARL 6 0.78 0.45 0.26 3.03E281 4.20E277 LIMA1 6 0.43 0.12 0.31 1.73E280 2.39E276 SUPT4H1 6 0.87 0.59 0.26 3.20E277 4.44E273 EIF1AY 6 0.56 0.24 0.33 7.96E277 1.10E272 CTLA4 6 0.69 0.39 0.25 6.12E276 8.49E272 DNPH1 6 0.80 0.45 0.34 8.80E276 1.22E271 NPM3 6 0.80 0.38 0.42 1.39E275 1.93E271 MRPL27 6 0.71 0.37 0.26 8.54E275 1.18E270 ERH 6 0.98 0.83 0.33 2.75E274 3.81E270 GRSF1 6 0.86 0.58 0.26 7.54E272 1.05E267 MFF 6 0.77 0.44 0.28 4.62E269 6.41E265 MRPL3 6 0.92 0.66 0.33 7.17E268 9.94E264 RUVBL1 6 0.70 0.31 0.36 1.89E267 2.61E263 WDR18 6 0.74 0.37 0.33 1.01E266 1.39E262 FAM207A 6 0.72 0.38 0.29 1.02E266 1.42E262 FADD 6 0.49 0.16 0.25 5.01E266 6.95E262 TMEM70 6 0.84 0.49 0.30 5.63E266 7.80E262 MRPS25 6 0.72 0.37 0.27 2.60E264 3.60E260 STRAP 6 0.96 0.76 0.27 4.81E264 6.66E260 EIF4E2 6 0.72 0.37 0.28 1.79E263 2.48E259 GPX1 6 0.78 0.39 0.44 2.61E263 3.61E259 LSM2 6 0.86 0.56 0.29 4.65E263 6.44E259 HN1 6 0.88 0.57 0.42 8.45E263 1.17E258 GTPBP4 6 0.92 0.66 0.30 1.16E261 1.61E257 PSMD13 6 0.95 0.75 0.30 1.25E260 1.74E256 NUDCD2 6 0.76 0.43 0.27 2.11E260 2.92E256 OLA1 6 0.88 0.57 0.30 4.50E260 6.24E256 URM1 6 0.79 0.45 0.27 5.70E260 7.89E256 PDHB 6 0.66 0.30 0.28 1.10E258 1.52E254 FHL3 6 0.43 0.11 0.28 1.35E258 1.87E254 RBPJ 6 0.93 0.68 0.29 6.56E256 9.09E252 BZW2 6 0.91 0.62 0.33 7.42E256 1.03E251 CINP 6 0.55 0.22 0.26 2.46E253 3.41E249 SMIM11 6 0.59 0.28 0.25 8.82E253 1.22E248 PPA2 6 0.62 0.28 0.27 2.25E252 3.12E248 NME1 6 0.88 0.52 0.36 1.65E251 2.29E247 NAA10 6 0.88 0.59 0.29 7.14E247 9.89E243 HPCAL1 6 0.65 0.32 0.30 3.25E245 4.51E241 TOMM34 6 0.69 0.35 0.26 1.54E243 2.13E239 CISD1 6 0.67 0.29 0.34 1.82E243 2.52E239 EXOSC5 6 0.72 0.34 0.31 4.67E241 6.48E237 ARMCX6 6 0.50 0.20 0.26 9.10E239 1.26E234 NDFIP2 6 0.88 0.60 0.26 5.91E238 8.19E234 C19orf24 6 0.86 0.54 0.32 7.25E238 1.00E233 PPM1G 6 0.93 0.72 0.25 9.91E238 1.37E233 EEF1E1 6 0.89 0.61 0.28 2.57E237 3.56E233 TXN2 6 0.68 0.35 0.25 3.64E235 5.04E231 TIMP1 6 0.60 0.39 0.63 9.82E234 1.36E229 C14orf166 6 0.96 0.79 0.26 3.39E233 4.70E229 MRPL15 6 0.77 0.40 0.35 5.83E232 8.09E228 PHF6 6 0.73 0.37 0.26 2.27E231 3.14E227 GNG5 6 0.98 0.85 0.30 6.92E230 9.58E226 NDUFB10 6 0.78 0.47 0.26 8.97E229 1.24E224 ATP5G1 6 0.89 0.61 0.27 9.77E229 1.35E224 BNIP3 6 0.41 0.23 0.31 2.63E228 3.64E224 EED 6 0.65 0.33 0.33 1.89E226 2.63E222 ATIC 6 0.89 0.56 0.35 1.87E225 2.59E221 RANBP1 6 0.97 0.80 0.36 1.27E223 1.76E219 CXCL13 6 0.16 0.02 1.54 1.75E223 2.42E219 SSNA1 6 0.84 0.51 0.29 3.00E223 4.15E219 FAM216A 6 0.53 0.18 0.31 5.88E223 8.15E219 BAG2 6 0.45 0.12 0.28 1.17E222 1.63E218 TRAP1 6 0.82 0.47 0.36 2.47E216 3.42E212 LDHB 6 0.99 0.92 0.45 3.57E215 4.95E211 MRPS26 6 0.74 0.41 0.28 6.39E213 8.85E209 SNRPC 6 0.93 0.67 0.29 1.10E211 1.52E207 EXOSC4 6 0.69 0.34 0.28 1.84E210 2.55E206 VDAC3 6 0.75 0.43 0.27 1.36E208 1.89E204 NDUFAB1 6 0.97 0.81 0.31 5.70E208 7.89E204 COA4 6 0.84 0.56 0.26 1.04E205 1.44E201 GGCT 6 0.69 0.33 0.30 1.06E204 1.47E200 PRDX1 6 1.00 0.97 0.34 2.75E204 3.81E200 LTV1 6 0.81 0.48 0.30 3.61E203 5.00E199 CYC1 6 0.87 0.60 0.26 8.73E201 1.21E196 TMEM121 6 0.38 0.10 0.25 1.22E197 1.68E193 STOML2 6 0.89 0.61 0.31 2.20E197 3.05E193 PFDN2 6 0.95 0.76 0.27 3.70E197 5.13E193 ANXA2 6 0.87 0.57 0.42 5.17E197 7.16E193 GK 6 0.54 0.20 0.43 9.44E197 1.31E192 CRIP1 6 0.84 0.52 0.38 7.91E196 1.10E191 DCUN1D5 6 0.90 0.60 0.32 5.51E195 7.64E191 UQCRC2 6 0.88 0.62 0.29 1.61E187 2.23E183 AKZ 6 0.91 0.59 0.36 1.33E184 1.84E180 MRPL4 6 0.92 0.67 0.30 3.16E178 4.38E174 OCIAD2 6 0.70 0.40 0.27 2.65E177 3.67E173 SNRPD1 6 0.98 0.82 0.29 5.53E177 7.66E173 FARSA 6 0.88 0.58 0.30 5.93E177 8.21E173 TOMM22 6 0.96 0.79 0.25 2.95E171 4.09E167 ANP32A 6 0.90 0.67 0.26 1.49E170 2.07E166 IFI27 6 0.29 0.09 0.82 3.17E170 4.39E166 UCK2 6 0.66 0.32 0.29 9.87E170 1.37E165 PAICS 6 0.94 0.68 0.29 3.50E167 4.85E163 KIAA1217 6 0.29 0.07 0.26 1.08E166 1.50E162 SLC25A3 6 0.99 0.92 0.28 3.26E166 4.51E162 PLS3 6 0.12 0.01 0.33 3.83E163 5.31E159 SRSF2 6 0.98 0.87 0.30 7.16E161 9.93E157 SLC38A5 6 0.74 0.40 0.29 1.61E158 2.23E154 EJF6 6 0.95 0.76 0.25 3.32E157 4.61E153 APEX1 6 0.89 0.62 0.26 8.58E157 1.19E152 PEBP1 6 0.91 0.69 0.29 6.73E156 9.33E152 AGFG1 6 0.54 0.21 0.25 1.32E154 1.83E150 CRADD 6 0.34 0.11 0.28 5.01E152 6.94E148 F5 6 0.66 0.28 0.27 3.46E150 4.79E146 TIMM8B 6 0.80 0.49 0.27 1.11E145 1.53E141 RRP1 6 0.78 0.45 0.26 3.81E145 5.28E141 IGFBP4 6 0.37 0.11 0.36 4.79E145 6.63E141 TPI1 6 1.00 0.97 0.27 5.16E141 7.15E137 TPM4 6 0.70 0.38 0.27 1.27E140 1.76E136 HMGA1 6 0.81 0.50 0.36 1.03E138 1.42E134 IRF8 6 0.66 0.33 0.30 1.66E137 2.31E133 ATP5B 6 0.99 0.92 0.32 1.00E135 1.39E131 CPM 6 0.46 0.12 0.41 2.34E132 3.24E128 G0S2 6 0.20 0.03 0.83 2.85E125 3.95E121 HSPD1 6 0.99 0.89 0.33 5.13E124 7.12E120 PPIF 6 0.71 0.41 0.31 6.88E123 9.53E119 CD27 6 0.69 0.40 0.37 7.42E121 1.03E116 POLR3K 6 0.57 0.25 0.26 1.98E118 2.75E114 ANKRD10 6 0.52 0.24 0.30 3.45E110 4.78E106 CCT8 6 0.97 0.82 0.25 8.72E108 1.21E103 RAN 6 1.00 0.98 0.33 5.95E107 8.24E103 CCDC86 6 0.78 0.45 0.28 5.59E105 7.75E101 IER3 6 0.66 0.47 0.30 1.22E104 1.69E100 PSMA2.1 6 0.90 0.65 0.28 2.32E101 3.22E97 TXN 6 0.99 0.85 0.29 1.36E99 1.88E95 SORD 6 0.46 0.15 0.26 3.97E98 5.51E94 THAP4 6 0.49 0.23 0.25 8.64E97 1.20E92 BOP1 6 0.71 0.38 0.26 3.35E96 4.64E92 AHCY 6 0.77 0.42 0.30 1.87E95 2.60E91 TNFSF11 6 0.41 0.16 0.31 9.84E95 1.36E90 TALDO1 6 0.84 0.55 0.26 4.41E94 6.11E90 TKT 6 0.91 0.66 0.30 8.79E90 1.22E85 GYPC 6 0.79 0.48 0.30 4.96E78 6.87E74 SRSF3 6 0.97 0.84 0.28 2.72E76 3.77E72 CCT3 6 0.98 0.86 0.27 1.96E70 2.71E66 EBNA1BP2 6 0.92 0.65 0.27 6.28E60 8.71E56 PPA1 6 0.98 0.84 0.29 3.16E58 4.38E54 BCAT1 6 0.42 0.14 0.25 4.73E42 6.56E38 CACYBP 6 0.90 0.64 0.26 4.08E39 5.66E35 NPM1 6 1.00 0.99 0.27 1.64E13 2.28E09
[0165] As referred to herein, Table 4 depicts as follows:
TABLE-US-00004 TABLE 4 Test statistics Fraction of Average expressing cells logged Cluster- Other Fold Adjusted Gene ID Cluster specific cells Change P-value P-value CCL4L1 8 0.72 0.06 2.62 0 0 NKG7 8 0.99 0.21 2.58 0 0 GNLY 8 0.85 0.11 2.47 0 0 CCLS 8 0.96 0.26 1.93 0 0 GZMB 8 0.98 0.22 1.75 0 0 HOPX 8 0.91 0.22 1.74 0 0 CCL3 8 0.75 0.14 1.72 0 0 CCL4 8 0.98 0.33 1.71 0 0 PLEK 8 0.91 0.15 1.67 0 0 GZMH 8 0.81 0.08 1.57 0 0 CST7 8 0.98 0.53 1.36 0 0 HLA-DRB5 8 0.67 0.13 1.28 0 0 PRF1 8 0.88 0.23 1.20 0 0 CCL4L2 8 0.42 0.07 1.13 0 0 KLRG1 8 0.58 0.10 1.04 0 0 ARIDZ 8 0.65 0.17 1.04 0 0 HLA-DPB1 8 0.65 0.15 1.03 0 0 SIT1 8 0.63 0.22 1.02 0 0 CD74 8 0.94 0.76 0.97 0 0 KLRB1 8 0.72 0.26 0.96 0 0 CCDC107 8 0.76 0.37 0.95 0 0 LAIR2 8 0.41 0.04 0.94 0 0 LAG3 8 0.66 0.28 0.93 0 0 CX3CR1 8 0.46 0.02 0.92 0 0 CD72 8 0.52 0.10 0.91 0 0 TAGAP 8 0.94 0.76 0.88 0 0 HLA-DPA1 8 0.66 0.21 0.88 0 0 GADD45B 8 0.72 0.55 0.86 0 0 ITGB2 8 0.69 0.43 0.86 0 0 ZEB2 8 0.73 0.31 0.85 0 0 CD52 8 0.95 0.76 0.85 0 0 HCST 8 0.89 0.70 0.78 0 0 HLA-DRB1 8 0.58 0.19 0.77 0 0 LITAF 8 0.80 0.47 0.77 0 0 SLAMF7 8 0.53 0.11 0.75 0 0 CD97 8 0.82 0.60 0.73 0 0 HLA-F 8 0.90 0.69 0.73 0 0 SLA 8 0.82 0.59 0.72 0 0 EGR2 8 0.71 0.41 0.70 0 0 FGFBP2 8 0.30 0.01 0.70 0 0 GZMA 8 0.38 0.08 0.69 0 0 APOBEC3C 8 0.65 0.37 0.69 0 0 FEZ1 8 0.32 0.05 0.68 0 0 GNG2 8 0.77 0.55 0.68 0 0 HLA-B 8 1.00 1.00 0.66 0 0 APOBEC3G 8 0.85 0.59 0.66 0 0 PNRC1 8 0.74 0.45 0.66 0 0 UCP2 8 0.60 0.50 0.65 0 0 KMT2E 8 0.86 0.67 0.65 0 0 ABI3 8 0.39 0.07 0.64 0 0 HLA-C 8 1.00 1.00 0.64 0 0 TNFRSF9 8 0.72 0.55 0.63 0 0 ITGA4 8 0.58 0.32 0.62 0 0 IL2RG 8 0.99 0.98 0.61 0 0 PTGER4 8 0.71 0.46 0.61 0 0 AKAP13 8 0.68 0.43 0.60 0 0 SAMD3 8 0.35 0.04 0.59 0 0 UTS2 8 0.31 0.01 0.59 0 0 GLIPR1 8 0.52 0.23 0.59 0 0 ARL6IP5 8 0.83 0.63 0.59 0 0 LINC00152 8 0.87 0.63 0.58 0 0 LCP1 8 0.91 0.77 0.58 0 0 HLA-E 8 1.00 1.00 0.58 0 0 PTPRC 8 0.98 0.93 0.58 0 0 CISD3 8 0.69 0.48 0.58 0 0 NR3C1 8 0.73 0.54 0.57 0 0 ANXA1 8 0.84 0.61 0.57 0 0 RORA 8 0.63 0.36 0.56 0 0 CTSC 8 0.74 0.51 0.56 0 0 RAP1B 8 0.90 0.80 0.55 0 0 GPSM3 8 0.75 0.46 0.55 0 0 TRIM22 8 0.84 0.67 0.55 0 0 ID2 8 0.73 0.52 0.55 0 0 ARHGDIB 8 0.85 0.55 0.55 0 0 LYST 8 0.68 0.47 0.55 0 0 RAMP1 8 0.23 0.01 0.55 0 0 FLNA 8 0.67 0.44 0.54 0 0 AC017002.1 8 0.46 0.21 0.54 0 0 ATP284 8 0.47 0.21 0.54 0 0 BTG1 8 0.98 0.95 0.54 0 0 SH3BGRL3 8 1.00 0.96 0.53 0 0 PYHIN1 8 0.36 0.11 0.53 0 0 SRGN 8 1.00 0.99 0.53 0 0 TNFRSF1A 8 0.45 0.20 0.52 0 0 CD3G 8 0.71 0.51 0.52 0 0 THEMIS 8 0.45 0.18 0.52 0 0 HLA-DQA1 8 0.25 0.03 0.52 0 0 IKZF3 8 0.44 0.20 0.52 0 0 NEAT1 8 0.66 0.42 0.52 0 0 HOXB2 8 0.42 0.16 0.52 0 0 TUBA4A 8 0.62 0.40 0.51 0 0 TGFBR3 8 0.38 0.13 0.51 0 0 ITM2C 8 0.32 0.12 0.50 0 0 IGF2R 8 0.43 0.18 0.50 0 0 ALOX5AP 8 0.63 0.34 0.49 0 0 MT-ND4 8 0.96 0.93 0.49 0 0 CD53 8 0.90 0.78 0.49 0 0 ANP32E 8 0.76 0.63 0.49 0 0 IL18RAP 8 0.41 0.16 0.49 0 0 CLIC1 8 0.99 0.93 0.49 0 0 HLA-A 8 1.00 1.00 0.49 0 0 RASSF5 8 0.79 0.66 0.48 0 0 TNFRSF1B 8 0.84 0.72 0.48 0 0 IER2 8 0.61 0.47 0.48 0 0 TLN1 8 0.54 0.36 0.48 0 0 RASAL3 8 0.54 0.32 0.47 0 0 CTSW 8 0.29 0.05 0.47 0 0 SEPT7 8 0.89 0.81 0.46 0 0 BCL2L11 8 0.40 0.21 0.46 0 0 CD99 8 0.95 0.86 0.46 0 0 GZMM 8 0.53 0.32 0.46 0 0 HLA-DRA 8 0.26 0.11 0.46 0 0 MSN 8 0.90 0.83 0.45 0 0 PTMS 8 0.34 0.15 0.45 0 0 HLA-DMA 8 0.29 0.08 0.45 0 0 GPR137B 8 0.33 0.15 0.45 0 0 MALAT1 8 1.00 1.00 0.45 0 0 ARHGAP25 8 0.42 0.19 0.44 0 0 BTN3A2 8 0.41 0.19 0.44 0 0 NFAT5 8 0.65 0.49 0.43 0 0 PTPN7 8 0.79 0.67 0.42 0 0 AC092580.4 8 0.24 0.05 0.42 0 0 RHOC 8 0.32 0.12 0.42 0 0 JAK1 8 0.75 0.59 0.41 0 0 B2M 8 1.00 1.00 0.41 0 0 MYL6 8 0.99 0.94 0.41 0 0 ACTB 8 1.00 0.99 0.41 0 0 CCNI 8 0.94 0.89 0.40 0 0 CD3D 8 0.99 0.96 0.40 0 0 RAC2 8 0.91 0.81 0.40 0 0 GABARAP 8 0.86 0.73 0.40 0 0 SH2D2A 8 0.91 0.83 0.40 0 0 RP11-94L15.2 8 0.33 0.13 0.39 0 0 MT-ATP8 8 0.93 0.91 0.38 0 0 CAP1 8 0.82 0.75 0.38 0 0 ARPC2 8 0.99 0.96 0.38 0 0 ARPC5L 8 0.75 0.68 0.37 0 0 PKM 8 0.99 0.99 0.37 0 0 C9orf16 8 0.84 0.82 0.37 0 0 RP11-81H14.2 8 0.20 0.02 0.37 0 0 SRSF5 8 0.88 0.84 0.36 0 0 ARPC1B 8 0.85 0.74 0.36 0 0 UBB 8 0.96 0.93 0.34 0 0 HLA-DQA2 8 0.16 0.01 0.34 0 0 RP11 8 0.21 0.05 0.34 0 0 325F22.2 C1orf21 8 0.16 0.01 0.33 0 0 DAZAP2 8 0.93 0.90 0.33 0 0 WDR1 8 0.85 0.78 0.32 0 0 MT-CO1 8 1.00 1.00 0.31 0 0 LINC00938 8 0.20 0.05 0.30 0 0 FCRL3 8 0.15 0.01 0.30 0 0 MT-CO2 8 1.00 1.00 0.30 0 0 HAVCR2 8 0.19 0.05 0.30 0 0 GPR56 8 0.12 0.00 0.26 0 0 H3F3A 8 0.99 0.96 0.26 0 0 EVL 8 0.65 0.41 0.49 1.16599492418534e321 1.61571916644363e317 CDC42EP3 8 0.65 0.45 0.50 7.94704591335645e320 1.1012221522138e315 YWHAQ 8 0.89 0.85 0.35 9.15996719258379e318 1.26929665387634e313 MATK 8 0.31 0.15 0.40 4.78308060498768e314 6.62791479433142e310 RGS3 8 0.24 0.09 0.32 1.08782628591787e311 1.51E307 TSC22D4 8 0.50 0.35 0.36 9.25382851542122e311 1.28E306 SYTL2 8 0.18 0.04 0.29 2.31980791762278e310 3.21E306 ZFP36L1 8 0.93 0.83 0.46 0.00E+00 2.48E305 GMFG 8 0.78 0.64 0.36 6.57E308 9.10E304 VCL 8 0.31 0.11 0.37 4.08E305 5.66E301 IL12RB1 8 0.32 0.15 0.35 1.21E303 1.67E299 RPA3 8 0.54 0.44 0.34 7.08E303 9.81E299 ARHGAP9 8 0.39 0.21 0.39 4.97E300 6.89E296 RNF19A 8 0.92 0.81 0.42 2.02E299 2.80E295 PCED1B 8 0.62 0.43 0.41 2.45E298 3.39E294 CREB3 8 0.44 0.30 0.36 6.05E298 8.39E294 ZYX 8 0.65 0.52 0.41 8.41E298 1.17E293 ZBTB38 8 0.26 0.10 0.34 7.03E297 9.74E293 RAP1A 8 0.83 0.76 0.35 3.77E296 5.23E292 SPN 8 0.51 0.32 0.43 7.41E296 1.03E291 CALM1 8 0.96 0.93 0.31 4.05E294 5.62E290 RHBDD2 8 0.50 0.35 0.40 1.31E293 1.81E289 TAX1BP1 8 0.75 0.68 0.33 6.44E293 8.93E289 SP140 8 0.58 0.43 0.41 7.71E292 1.07E287 CD4 8 0.41 0.24 0.39 8.24E292 1.14E287 FGL2 8 0.16 0.03 0.31 9.91E288 1.37E283 ADRB2 8 0.14 0.02 0.26 3.39E287 4.70E283 MACF1 8 0.52 0.30 0.45 9.67E285 1.34E280 CTDSP1 8 0.34 0.17 0.37 7.30E284 1.01E279 FTH1 8 0.99 0.97 0.36 1.48E283 2.06E279 TNFAIP3 8 0.77 0.66 0.47 6.83E283 9.47E279 ADO 8 0.33 0.18 0.34 6.92E279 9.58E275 C4orf3 8 0.74 0.66 0.34 7.55E276 1.05E271 KMT2EAS1 8 0.24 0.10 0.31 5.82E275 8.06E271 GOLGA7 8 0.52 0.44 0.31 1.06E273 1.47E269 PSMVB9 8 0.85 0.75 0.35 1.74E272 2.41E268 ARID4B 8 0.67 0.57 0.36 1.72E271 2.39E267 SYNE1 8 0.21 0.07 0.31 6.50E270 9.01E266 NFATC3 8 0.36 0.22 0.33 7.47E268 1.04E263 CD247 8 0.66 0.53 0.36 3.54E265 4.90E261 PRR5L 8 0.20 0.05 0.30 2.74E262 3.80E258 DHRS7 8 0.54 0.34 0.38 3.25E262 4.50E258 MAST3 8 0.25 0.10 0.31 7.92E261 1.10E256 TPP1 8 0.37 0.21 0.35 5.38E259 7.46E255 MIR142 8 0.38 0.25 0.37 2.49E258 3.45E254 CD84 8 0.50 0.30 0.44 4.95E258 6.86E254 GNPTAB 8 0.24 0.09 0.31 2.79E256 3.86E252 RIN3 8 0.25 0.10 0.34 2.19E255 3.04E251 ANXA6 8 0.60 0.47 0.36 1.33E252 1.84E248 PTGER2 8 0.45 0.22 0.53 2.87E252 3.98E248 CTB-58E17.1 8 0.28 0.15 0.30 2.75E251 3.81E247 BNIP3L 8 0.38 0.20 0.38 7.71E250 1.07E245 CD3E 8 0.98 0.97 0.28 1.82E245 2.53E241 C10orf128 8 0.32 0.13 0.33 2.63E245 3.64E241 TACC1 8 0.30 0.17 0.29 4.15E238 5.75E234 PTPN6 8 0.57 0.45 0.35 9.73E238 1.35E233 ARHGEF2 8 0.51 0.39 0.36 4.53E237 6.27E233 IL12RB2 8 0.32 0.17 0.34 1.91E236 2.64E232 LCP2 8 0.66 0.49 0.40 8.87E236 1.23E231 TESK1 8 0.23 0.09 0.29 1.12E235 1.56E231 GPX4 8 0.79 0.67 0.36 4.15E235 5.75E231 TMEM66 8 0.98 0.95 0.30 5.58E233 7.73E229 ST8SIA4 8 0.42 0.25 0.37 1.34E232 1.86E228 IGFLR1 8 0.44 0.28 0.36 5.52E231 7.65E227 SDCBP 8 0.75 0.65 0.44 9.44E231 1.31E226 ITGB1 8 0.60 0.43 0.36 1.66E230 2.30E226 EDARADD 8 0.22 0.08 0.36 1.78E227 2.47E223 EFHD2 8 0.33 0.22 0.27 1.25E225 1.74E221 MBNL1 8 0.85 0.79 0.35 1.53E225 2.13E221 NFKBIA 8 0.91 0.87 0.43 6.34E219 8.79E215 TSC22D3 8 0.42 0.26 0.54 1.29E218 1.79E214 C19orf66 8 0.64 0.52 0.34 4.62E215 6.40E211 TAPBPL 8 0.30 0.16 0.28 1.05E213 1.46E209 VASP 8 0.75 0.70 0.31 1.38E211 1.91E207 FMNL1 8 0.32 0.18 0.29 7.78E211 1.08E206 SH3BP1 8 0.26 0.15 0.27 4.47E210 6.19E206 TRIM5 8 0.32 0.19 0.33 1.23E209 1.71E205 S100A10 8 0.91 0.81 0.26 6.98E209 9.68E205 GSTP1 8 0.80 0.74 0.25 1.13E208 1.57E204 NUCB2 8 0.42 0.27 0.38 2.36E207 3.27E203 LINC00861 8 0.40 0.23 0.40 8.81E207 1.22E202 LGALS1 8 0.61 0.41 0.45 7.93E206 1.10E201 LASP1 8 0.33 0.21 0.28 1.26E205 1.75E201 CBLB 8 0.75 0.60 0.39 3.09E205 4.28E201 TOMM7 8 0.86 0.80 0.30 1.15E204 1.60E200 UBE2E3 8 0.40 0.29 0.29 7.97E204 1.10E199 TOB1 8 0.25 0.14 0.27 2.09E203 2.89E199 PPP1R18 8 0.67 0.57 0.33 2.01E201 2.79E197 LY9 8 0.25 0.10 0.29 5.12E201 7.10E197 UPP1 8 0.34 0.18 0.34 1.37E200 1.90E196 AHNAK 8 0.47 0.29 0.36 2.77E199 3.84E195 JUND 8 0.41 0.28 0.33 2.78E197 3.85E193 DECR1 8 0.38 0.28 0.27 1.53E196 2.12E192 LBH 8 0.66 0.53 0.38 2.22E196 3.08E192 MAP3K8 8 0.50 0.36 0.43 2.92E195 4.05E191 MAP1LC3A 8 0.40 0.24 0.38 7.97E195 1.10E190 TRIM69 8 0.52 0.41 0.31 1.13E194 1.57E190 IQGAP1 8 0.50 0.37 0.31 1.48E194 2.05E190 TAPSAR1 8 0.37 0.26 0.29 6.20E194 8.59E190 OASL 8 0.36 0.21 0.31 1.52E193 2.10E189 WIPF1 8 0.58 0.44 0.30 2.98E193 4.13E189 SH3KBP1 8 0.53 0.42 0.31 6.34E193 8.79E189 STAT4 8 0.56 0.42 0.33 4.32E192 5.98E188 GPR108 8 0.55 0.47 0.30 4.15E191 5.75E187 PHLDA1 8 0.70 0.56 0.40 1.39E190 1.92E186 BZW1 8 0.92 0.91 0.27 3.38E189 4.68E185 ANKRD28 8 0.36 0.19 0.35 1.84E188 2.55E184 TNIP1 8 0.60 0.50 0.28 3.77E188 5.22E184 SYTL3 8 0.26 0.13 0.31 1.80E186 2.50E182 LSP1 8 0.52 0.38 0.33 2.05E186 2.84E182 ISCU 8 0.77 0.73 0.26 3.51E186 4.86E182 ITM2B 8 0.91 0.81 0.30 6.11E186 8.46E182 CHD4 8 0.60 0.52 0.31 3.24E184 4.50E180 HMGN2 8 0.76 0.73 0.25 4.95E184 6.86E180 GLIPR2 8 0.29 0.16 0.28 1.54E182 2.13E178 PRKCH 8 0.80 0.70 0.33 7.19E181 9.96E177 NAB2 8 0.45 0.33 0.34 1.20E180 1.66E176 GMIP 8 0.29 0.18 0.25 6.68E180 9.25E176 ARID5B 8 0.76 0.65 0.41 2.52E179 3.49E175 UQCRB 8 0.81 0.78 0.26 2.99E179 4.14E175 AFTPH 8 0.44 0.34 0.30 1.62E178 2.25E174 LRRFIP1 8 0.81 0.80 0.26 7.07E178 9.80E174 TGIF1 8 0.61 0.53 0.42 1.65E177 2.29E173 MYO1G 8 0.29 0.15 0.29 3.55E177 4.92E173 RILPL2 8 0.76 0.75 0.38 5.50E177 7.62E173 BHLHE40 8 0.63 0.49 0.37 2.27E176 3.14E172 TMC6 8 0.40 0.26 0.33 6.02E175 8.34E171 PTPN22 8 0.61 0.49 0.31 5.78E173 8.01E169 GIMAP7 8 0.45 0.29 0.27 3.42E170 4.73E166 PAIP2 8 0.64 0.59 0.25 1.23E169 1.70E165 ZNFX1 8 0.57 0.51 0.28 2.43E169 3.37E165 ZBTB1 8 0.31 0.21 0.26 5.09E169 7.05E165 SYNE2 8 0.73 0.58 0.31 1.74E168 2.42E164 WSB2 8 0.27 0.17 0.26 1.23E167 1.70E163 SH3BGRL 8 0.44 0.33 0.26 1.53E167 2.12E163 RARRES3 8 0.41 0.27 0.33 1.54E167 2.14E163 CLEC2B 8 0.38 0.23 0.30 8.47E167 1.17E162 KLF10 8 0.55 0.43 0.41 1.85E164 2.56E160 LAPTM5 8 0.67 0.55 0.31 9.45E164 1.31E159 BCL2 8 0.47 0.36 0.32 6.97E162 9.66E158 ZFP36L2 8 0.48 0.37 0.32 4.17E159 5.78E155 CD6 8 0.73 0.62 0.28 2.04E156 2.83E152 RARG 8 0.30 0.17 0.26 3.78E156 5.23E152 UTRN 8 0.29 0.15 0.28 1.10E154 1.53E150 CTSB 8 0.54 0.43 0.31 2.03E154 2.81E150 EPS15 8 0.38 0.28 0.27 2.93E154 4.07E150 CD96 8 0.65 0.50 0.32 2.14E152 2.96E148 ACADVL 8 0.47 0.39 0.26 2.79E152 3.87E148 YPEL5 8 0.39 0.28 0.27 3.04E152 4.21E148 SAMSN1 8 0.61 0.51 0.28 3.43E152 4.76E148 CD58 8 0.62 0.52 0.25 1.40E151 1.94E147 CREM 8 0.67 0.59 0.40 3.58E151 4.97E147 GPR18 8 0.28 0.14 0.31 7.93E151 1.10E146 MYH9 8 0.65 0.59 0.29 2.57E150 3.56E146 FASLG 8 0.63 0.44 0.37 5.87E150 8.13E146 SQRDL 8 0.38 0.26 0.25 1.49E149 2.07E145 AD000671.6 8 0.35 0.23 0.28 2.04E146 2.83E142 EVI2A 8 0.68 0.54 0.48 6.02E145 8.34E141 IDS 8 0.57 0.47 0.29 5.66E142 7.84E138 EIF1B 8 0.70 0.69 0.26 2.49E141 3.46E137 ITK 8 0.69 0.62 0.29 4.57E139 6.33E135 HSPB1 8 0.46 0.42 0.27 1.99E138 2.76E134 IVNS1ABP 8 0.42 0.39 0.27 5.28E136 7.32E132 PBX4 8 0.39 0.26 0.27 3.60E135 4.99E131 PRNP 8 0.76 0.75 0.43 1.70E133 2.36E129 DDX3Y 8 0.41 0.30 0.28 2.13E133 2.95E129 ARAP2 8 0.46 0.35 0.30 6.00E132 8.32E128 MBP 8 0.41 0.29 0.29 1.16E131 1.60E127 BTG2 8 0.60 0.47 0.39 3.44E131 4.76E127 SPPL2A 8 0.54 0.44 0.26 4.39E131 6.08E127 DOCK8 8 0.41 0.30 0.26 1.22E130 1.69E126 RHOF 8 0.54 0.48 0.25 1.57E130 2.18E126 SLC44A2 8 0.29 0.18 0.25 4.14E125 5.74E121 LINC00944 8 0.23 0.10 0.26 7.19E125 9.96E121 FBXO34 8 0.29 0.20 0.26 3.52E123 4.88E119 CRY1 8 0.49 0.41 0.30 5.70E123 7.90E119 TRAF1 8 0.74 0.66 0.30 1.99E119 2.76E115 HBP1 8 0.30 0.19 0.25 3.77E119 5.22E115 SAMD9 8 0.36 0.24 0.27 7.17E117 9.94E113 GIMAPS 8 0.52 0.41 0.29 2.85E116 3.95E112 TBX21 8 0.39 0.28 0.31 7.76E114 1.08E109 IFITM2 8 0.75 0.73 0.36 6.07E113 8.42E109 PHF1 8 0.35 0.22 0.26 2.02E112 2.80E108 ANKRD44 8 0.45 0.35 0.28 2.74E110 3.80E106 RGS16 8 0.59 0.51 0.34 8.74E109 1.21E104 CRTAM 8 0.16 0.07 0.57 5.09E107 7.05E103 PBXIP1 8 0.25 0.14 0.27 8.89E107 1.23E102 XAF1 8 0.44 0.33 0.26 1.03E102 1.43E98 LTBP4 8 0.63 0.56 0.26 1.50E102 2.07E98 SLC20A1 8 0.42 0.34 0.29 9.44E101 1.31E96 RAB8B 8 0.66 0.60 0.26 5.69E97 7.89E93 TMBIM1 8 0.56 0.48 0.25 3.74E81 5.18E77 SLC2A3 8 0.58 0.48 0.26 9.69E76 1.34E71 KLF6 8 0.83 0.78 0.27 5.50E70 7.62E66 CD83 8 0.48 0.41 0.26 5.77E55 8.00E51 NR4A3 8 0.40 0.35 0.30 2.60E28 3.61E24
[0166] As referred to herein, Table 5 depicts as follows:
TABLE-US-00005 TABLE 5 Test statistics Fraction of Average expressing cells logged Cluster- Other Fold Adjusted Gene ID Cluster specific cells Change P-value P-value IL17F 9 0.36 0.02 3.91 0 0 IL17A 9 0.39 0.02 3.45 0 0 CTSH 9 0.73 0.15 1.24 0 0 LGALS3 9 0.87 0.28 1.24 0 0 S100A4 9 0.88 0.53 1.16 0 0 CCR6 9 0.68 0.10 1.14 0 0 MSC 9 0.58 0.06 1.12 0 0 CCL20 9 0.67 0.33 1.10 0 0 LTB 9 0.94 0.67 0.99 0 0 IL4I1 9 0.73 0.19 0.96 0 0 IL32 9 0.99 0.88 0.93 0 0 CORO1A 9 0.93 0.60 0.91 0 0 S100A6 9 0.96 0.71 0.89 0 0 OSTF1 9 0.76 0.30 0.89 0 0 IL2RA 9 0.84 0.50 0.88 0 0 CD74 9 0.97 0.76 0.88 0 0 LGALS1 9 0.72 0.41 0.84 0 0 NTRK2 9 0.43 0.04 0.81 0 0 PTP4A3 9 0.37 0.14 0.80 0 0 TMSB4X 9 0.99 0.96 0.79 0 0 CXCR6 9 0.36 0.07 0.78 0 0 KLRBP 9 0.62 0.27 0.77 0 0 TYMP 9 0.83 0.41 0.77 0 0 ARHGDIB 9 0.86 0.55 0.77 0 0 TMSB10 9 1.00 0.95 0.76 0 0 PTPRCAP 9 0.76 0.42 0.74 0 0 TNFRSF4 9 0.96 0.85 0.73 0 0 GNA15 9 0.66 0.21 0.70 0 0 CCR4 9 0.57 0.21 0.70 0 0 TXN 9 0.98 0.85 0.70 0 0 ARPC1B 9 0.94 0.74 0.69 0 0 TNFRSF18 9 0.96 0.81 0.69 0 0 VIM 9 0.97 0.83 0.69 0 0 TPM4 9 0.78 0.39 0.69 0 0 ANXA2 9 0.90 0.58 0.64 0 0 RGS1 9 0.45 0.19 0.64 0 0 LAPTM5 9 0.82 0.54 0.63 0 0 PIM2 9 0.68 0.34 0.63 0 0 SPOCK2 9 0.72 0.36 0.62 0 0 NFKBIA 9 0.97 0.87 0.61 0 0 CYTIP 9 0.88 0.53 0.60 0 0 ANKRD12 9 0.87 0.56 0.60 0 0 LSP1 9 0.67 0.38 0.60 0 0 FLT3LG 9 0.72 0.25 0.60 0 0 ACTG1 9 0.99 0.96 0.58 0 0 FTH1 9 1.00 0.97 0.58 0 0 BATF 9 0.84 0.60 0.57 0 0 CMTM6 9 0.84 0.54 0.57 0 0 ARL6IPS 9 0.89 0.63 0.57 0 0 MYO1G 9 0.54 0.14 0.56 0 0 RORA 9 0.76 0.35 0.55 0 0 KLF6 9 0.96 0.78 0.55 0 0 MYL6 9 0.99 0.94 0.55 0 0 SQSTM1 9 0.82 0.53 0.55 0 0 GBP5 9 0.75 0.45 0.54 0 0 ACTB 9 1.00 0.99 0.54 0 0 FLNA 9 0.75 0.44 0.54 0 0 RNF213 9 0.74 0.39 0.54 0 0 CTSC 9 0.77 0.51 0.54 0 0 GPX1 9 0.69 0.41 0.53 0 0 SAMHD1 9 0.61 0.23 0.53 0 0 KIF2A 9 0.72 0.42 0.53 0 0 TNFRSF25 9 0.82 0.56 0.53 0 0 LCP1 9 0.96 0.77 0.53 0 0 OPTN 9 0.66 0.29 0.53 0 0 LMO4 9 0.45 0.14 0.52 0 0 EML4 9 0.76 0.42 0.52 0 0 GPSM3 9 0.77 0.46 0.51 0 0 EMP3 9 0.99 0.90 0.51 0 0 CAMK4 9 0.63 0.25 0.51 0 0 IL2RB 9 0.68 0.35 0.50 0 0 PTPN13 9 0.35 0.05 0.50 0 0 CAPG 9 0.37 0.10 0.50 0 0 RORC 9 0.41 0.11 0.49 0 0 FAS 9 0.60 0.22 0.49 0 0 ENTPD1 9 0.25 0.03 0.49 0 0 STK17B 9 0.83 0.55 0.49 0 0 PLP2 9 0.79 0.52 0.49 0 0 ANXAS 9 0.69 0.37 0.49 0 0 LPXN 9 0.77 0.45 0.48 0 0 NFKB2 9 0.74 0.44 0.47 0 0 GPR183 9 0.63 0.30 0.47 0 0 PSME1 9 0.98 0.84 0.47 0 0 TNFRSF14 9 0.64 0.29 0.47 0 0 PHTF2 9 0.48 0.15 0.46 0 0 PFN1 9 1.00 0.98 0.46 0 0 TSPO 9 0.75 0.48 0.45 0 0 SH3BP5 9 0.47 0.16 0.45 0 0 FURIN 9 0.48 0.19 0.44 0 0 NMRK1 9 0.42 0.13 0.44 0 0 TNIP1 9 0.78 0.49 0.44 0 0 RAC2 9 0.96 0.81 0.43 0 0 PIM1 9 0.67 0.37 0.43 0 0 JAK1 9 0.86 0.58 0.43 0 0 TANK 9 0.74 0.42 0.42 0 0 NDUFV2 9 0.96 0.84 0.42 0 0 GNG2 9 0.80 0.54 0.42 0 0 TRADD 9 0.52 0.17 0.42 0 0 GSDMD 9 0.55 0.23 0.42 0 0 AHR 9 0.61 0.32 0.41 0 0 CISH 9 0.54 0.21 0.41 0 0 SQRDL 9 0.58 0.25 0.41 0 0 RAP1B 9 0.92 0.80 0.41 0 0 ACTR3 9 0.96 0.84 0.40 0 0 SYTL3 9 0.39 0.12 0.40 0 0 CUTA 9 0.74 0.49 0.40 0 0 UNC119 9 0.38 0.13 0.39 0 0 DPP4 9 0.41 0.14 0.39 0 0 CD80 9 0.25 0.03 0.38 0 0 GPR65 9 0.53 0.24 0.38 0 0 TAPBP 9 0.90 0.67 0.38 0 0 SOCS2 9 0.37 0.10 0.38 0 0 PRDM1 9 0.48 0.19 0.37 0 0 CFL1 9 1.00 0.97 0.37 0 0 MGAT4A 9 0.46 0.16 0.37 0 0 IL12RB1 9 0.43 0.15 0.37 0 0 RSU1 9 0.48 0.19 0.35 0 0 PBX4 9 0.53 0.25 0.34 0 0 KCNA3 9 0.39 0.12 0.33 0 0 CCNG2 9 0.18 0.02 0.31 0 0 IL26 9 0.20 0.03 0.30 0 0 IL2RG 9 1.00 0.98 0.28 0 0 RP11- 9 0.19 0.02 0.27 0 0 316P17.2 MAL 9 0.36 0.15 0.55 3.45845952088873e323 4.79238735809551e319 ACAT2 9 0.51 0.21 0.42 1.43279037293961e322 1.98541761978242e318 PSMB10 9 0.87 0.63 0.42 2.42092166462211e322 3.35467115066686e318 PPARG 9 0.20 0.03 0.29 2.69142260572019e319 3.72950430474647e315 PBXIP1 9 0.37 0.13 0.34 1.12350527864299e318 1.5568412646156e314 ADAM8 9 0.35 0.12 0.33 1.7049069086996e318 2.36248950338503e314 AC017002.1 9 0.46 0.21 0.51 5.31755596794596e316 7.36853730478272e312 CD47 9 0.79 0.49 0.35 6.56168624755142e315 9.09252863323201e311 ALOX5AP 9 0.63 0.34 0.47 1.84421290228056e314 2.55552581869017e310 DSE 9 0.28 0.07 0.27 2.12807192584966e312 2.95E308 PLIN2 9 0.46 0.23 0.44 2.68658046365998e310 3.72E306 SELPLG 9 0.37 0.13 0.39 1.28E307 1.77E303 CAST 9 0.68 0.40 0.35 4.77E305 6.61E301 CD247 9 0.79 0.53 0.40 8.61E305 1.19E300 BHLHE40 9 0.74 0.48 0.40 2.18E304 3.03E300 BLM 9 0.25 0.06 0.28 3.95E304 5.47E300 S1PR1 9 0.38 0.14 0.32 1.81E303 2.51E299 PDE4D 9 0.45 0.19 0.40 4.10E301 5.68E297 FTL 9 0.99 0.96 0.65 1.94E299 2.68E295 MVP 9 0.68 0.39 0.41 1.18E295 1.63E291 PSME2 9 0.99 0.91 0.35 3.77E295 5.22E291 C10orf128 9 0.36 0.13 0.36 7.38E294 1.02E289 EVL 9 0.66 0.41 0.42 6.62E293 9.18E289 CNN2 9 0.42 0.18 0.44 9.63E293 1.33E288 MYL12A 9 0.94 0.86 0.45 3.32E287 4.60E283 CARD16 9 0.49 0.21 0.33 1.71E285 2.37E281 TNFRSF1B 9 0.86 0.72 0.43 9.33E283 1.29E278 PTPN4 9 0.33 0.11 0.27 2.60E282 3.60E278 LCP2 9 0.73 0.48 0.40 1.70E281 2.36E277 AHNAK 9 0.55 0.28 0.40 1.56E280 2.17E276 GPR25 9 0.16 0.03 0.35 2.84E279 3.94E275 TBC1D10C 9 0.35 0.13 0.33 3.12E279 4.33E275 GBP1 9 0.75 0.47 0.47 2.35E275 3.25E271 CALM1 9 0.98 0.93 0.30 1.36E273 1.89E269 STAT1 9 0.86 0.66 0.47 2.94E272 4.08E268 CYTH1 9 0.44 0.19 0.32 8.39E271 1.16E266 ACAP1 9 0.43 0.19 0.35 6.68E270 9.26E266 HUWE1 9 0.61 0.37 0.37 1.75E268 2.42E264 DNPH1 9 0.73 0.47 0.41 1.76E268 2.44E264 DBI 9 0.88 0.70 0.39 1.85E268 2.56E264 IL22 9 0.17 0.03 2.17 1.09E266 1.51E262 TUBA1A 9 0.48 0.21 0.35 1.13E266 1.57E262 CCNI 9 0.97 0.89 0.28 1.53E266 2.12E262 ICAM1 9 0.38 0.15 0.38 1.59E265 2.21E261 ITGAL 9 0.32 0.10 0.28 5.69E265 7.88E261 CALCOCO2 9 0.64 0.36 0.33 4.60E262 6.37E258 LY6E 9 0.91 0.69 0.42 4.66E262 6.46E258 JUNB 9 0.85 0.66 0.40 1.07E259 1.48E255 FAM129A 9 0.51 0.25 0.36 1.53E257 2.12E253 ARHGAP15 9 0.62 0.35 0.32 7.29E257 1.01E252 APOL3 9 0.34 0.11 0.28 5.18E256 7.17E252 MAF 9 0.48 0.22 0.39 3.32E255 4.59E251 RAB11FIP1 9 0.55 0.30 0.41 9.09E255 1.26E250 EED 9 0.58 0.35 0.43 3.88E252 5.38E248 VPS13C 9 0.48 0.22 0.30 2.08E251 2.89E247 FAM46C 9 0.30 0.10 0.26 2.91E247 4.03E243 CLDND1 9 0.76 0.54 0.41 5.16E246 7.15E242 EBP 9 0.44 0.19 0.31 1.85E245 2.56E241 RAB9A 9 0.43 0.24 0.35 2.52E245 3.49E241 MAN2B1 9 0.39 0.16 0.28 6.35E245 8.79E241 MVD 9 0.37 0.14 0.28 1.98E244 2.74E240 MAST4 9 0.31 0.11 0.27 1.25E243 1.73E239 HLA-DQB1 9 0.36 0.15 0.47 6.72E243 9.31E239 LIMD2 9 0.79 0.57 0.44 6.98E243 9.67E239 XAF1 9 0.59 0.32 0.29 1.47E238 2.03E234 PMVK 9 0.58 0.32 0.34 1.65E237 2.29E233 SEPT9 9 0.48 0.23 0.32 2.57E235 3.56E231 CYB5A 9 0.41 0.17 0.30 1.59E234 2.20E230 FDPS 9 0.67 0.47 0.37 4.79E234 6.64E230 TPM3 9 0.97 0.90 0.30 5.25E234 7.28E230 IL1R2 9 0.12 0.02 0.33 3.46E233 4.80E229 CAPN2 9 0.55 0.28 0.36 9.55E231 1.32E226 CD4 9 0.46 0.23 0.36 5.60E228 7.77E224 GBP4 9 0.58 0.31 0.38 7.23E228 1.00E223 ILK 9 0.52 0.26 0.31 2.92E227 4.04E223 MT2A 9 0.57 0.31 0.55 8.78E224 1.22E219 OSM 9 0.29 0.10 0.45 8.66E223 1.20E218 SASH3 9 0.38 0.16 0.30 9.58E223 1.33E218 ARHGDIA 9 0.92 0.78 0.32 1.85E222 2.57E218 CDC42 9 0.95 0.86 0.27 4.88E222 6.77E218 WIPF1 9 0.66 0.44 0.36 2.68E221 3.71E217 AC092580.4 9 0.20 0.05 0.28 4.53E221 6.27E217 TBCB 9 0.69 0.46 0.33 1.60E219 2.21E215 PLEC 9 0.26 0.08 0.27 1.17E218 1.62E214 PRMT2 9 0.46 0.21 0.26 1.18E218 1.64E214 GABARAP 9 0.88 0.73 0.27 1.91E218 2.65E214 ISG15 9 0.80 0.51 0.40 3.42E218 4.74E214 NFKBIZ 9 0.50 0.25 0.34 1.03E217 1.43E213 DUSP1 9 0.56 0.33 0.40 1.83E216 2.53E212 SYTL1 9 0.31 0.12 0.26 1.84E216 2.55E212 ACTN4 9 0.64 0.41 0.30 8.08E216 1.12E211 IFI35 9 0.68 0.40 0.32 3.25E214 4.50E210 BIN1 9 0.33 0.13 0.26 1.52E213 2.10E209 CAP1 9 0.88 0.74 0.30 2.07E213 2.86E209 PSMB9 9 0.92 0.75 0.32 4.82E212 6.68E208 IRF1 9 0.84 0.63 0.34 3.19E210 4.42E206 FNBP1 9 0.72 0.51 0.29 8.74E209 1.21E204 GRINA 9 0.40 0.19 0.29 1.84E206 2.56E202 ICAM3 9 0.60 0.36 0.32 7.29E206 1.01E201 SYNGR2 9 0.89 0.76 0.27 2.02E205 2.80E201 HSPB1 9 0.64 0.41 0.37 1.52E201 2.10E197 DDIT4 9 0.53 0.30 0.41 1.74E201 2.41E197 ELOVL5 9 0.74 0.52 0.29 2.19E201 3.04E197 NECAP2 9 0.54 0.32 0.28 1.95E200 2.70E196 ANXA6 9 0.70 0.47 0.35 1.05E197 1.46E193 FOXP3 9 0.17 0.04 0.47 6.98E196 9.68E192 PPDPF 9 0.91 0.78 0.28 1.07E195 1.49E191 CDKZAP2 9 0.67 0.46 0.37 1.76E195 2.44E191 PPP1CA 9 0.87 0.71 0.31 2.40E195 3.32E191 RDX 9 0.34 0.14 0.29 9.71E193 1.35E188 ARHGAP30 9 0.47 0.24 0.29 2.03E192 2.81E188 DHCR7 9 0.33 0.13 0.25 2.26E190 3.13E186 TUBB 9 0.90 0.78 0.39 5.41E190 7.50E186 HLA-DQA1 9 0.16 0.04 0.38 1.38E183 1.92E179 AD000671.6 9 0.43 0.23 0.28 1.29E182 1.79E178 IGFLR1 9 0.49 0.28 0.29 6.50E182 9.01E178 SNX10 9 0.35 0.16 0.28 8.31E182 1.15E177 GMFG 9 0.81 0.64 0.33 1.49E181 2.07E177 MIIP 9 0.37 0.17 0.26 1.23E180 1.71E176 INSIG1 9 0.60 0.38 0.57 4.10E180 5.68E176 ID2 9 0.71 0.53 0.38 4.95E180 6.86E176 ZFP36L1 9 0.91 0.83 0.35 8.91E177 1.23E172 IFI6 9 0.76 0.51 0.25 2.45E176 3.40E172 ARPC2 9 0.99 0.96 0.25 1.68E173 2.32E169 TOX 9 0.30 0.11 0.32 4.63E172 6.41E168 ECH1 9 0.52 0.30 0.27 1.44E171 2.00E167 ITGB1 9 0.59 0.43 0.26 2.67E169 3.70E165 APOL2 9 0.37 0.17 0.25 2.77E166 3.84E162 RPS4Y1 9 0.78 0.55 0.28 7.66E163 1.06E158 MAP4 9 0.53 0.30 0.26 1.71E162 2.36E158 CTSL 9 0.12 0.09 0.51 4.13E161 5.72E157 DBNL 9 0.63 0.42 0.27 2.57E159 3.57E155 S100A11 9 0.84 0.71 0.36 6.52E153 9.03E149 RCSD1 9 0.43 0.22 0.26 1.06E152 1.47E148 GSTK1 9 0.77 0.58 0.31 2.02E152 2.80E148 MYH9 9 0.77 0.58 0.29 3.25E151 4.51E147 HLA-DRB1 9 0.35 0.20 0.56 1.71E148 2.38E144 VAMP8 9 0.65 0.44 0.25 4.34E147 6.02E143 RTN4 9 0.58 0.38 0.27 2.86E146 3.97E142 BST2 9 0.82 0.61 0.30 3.07E146 4.25E142 CYP51A1 9 0.59 0.38 0.27 1.08E145 1.49E141 ELOVL1 9 0.55 0.32 0.26 2.94E144 4.08E140 ATFS 9 0.29 0.14 0.28 3.46E143 4.79E139 TIFA 9 0.39 0.20 0.27 2.88E142 3.99E138 TMEM173 9 0.36 0.18 0.35 4.98E140 6.90E136 WDR1 9 0.91 0.78 0.26 2.21E139 3.06E135 AQP3 9 0.31 0.15 0.27 1.54E137 2.13E133 IL1R1 9 0.25 0.10 0.27 2.50E129 3.46E125 TRAPPC1 9 0.71 0.51 0.27 4.77E127 6.60E123 ITGA4 9 0.50 0.32 0.30 1.01E126 1.40E122 LTA 9 0.80 0.64 0.39 8.43E126 1.17E121 CHCHD10 9 0.49 0.30 0.27 2.93E124 4.06E120 ZBTB32 9 0.36 0.21 0.40 7.14E121 9.90E117 CSTB 9 0.82 0.68 0.27 1.81E120 2.51E116 HLA-DRB5 9 0.30 0.15 0.42 1.47E118 2.04E114 TAGLN2 9 0.90 0.77 0.30 2.08E117 2.88E113 EPSTI1 9 0.61 0.41 0.29 2.59E115 3.59E111 HLA-DPA1 9 0.38 0.22 0.31 5.73E113 7.94E109 TALDO1 9 0.75 0.56 0.28 8.52E105 1.18E100 ARPCS 9 0.76 0.62 0.26 1.12E104 1.55E100 GZMA 9 0.15 0.09 0.41 2.37E99 3.28E95 CTLA4 9 0.56 0.41 0.39 8.31E96 1.15E91 LCK 9 0.75 0.60 0.25 2.15E74 2.98E70 LMNA 9 0.56 0.44 0.29 1.25E51 1.74E47 HLA-DRA 9 0.21 0.12 0.37 1.51E47 2.09E43 CD70 9 0.31 0.18 0.28 5.66E45 7.84E41
[0167] As referred to herein, Table 6 depicts as follows:
TABLE-US-00006 TABLE6 Virus- ClonotypeID CDR3AminoAcidSequences reactivity CloneSize clonotype32211 TRA:CAVDPILTGGGNKLTF(SEQIDNO:1); CV 1871 TRB:CASSLSRDTYNEQFF(SEQIDNO:2) clonotype20067 TRA:CAMREVNTGNQFYF;(SEQIDNO:3) CV 1714 TRB:CASSPRDSAQSWYGYTF(SEQIDNO: 4) clonotype20068 TRA:CAVSDGIQGAQKLVF;(SEQIDNO:5) CV 1175 TRB:CSVDQGLNYGYTF(SEQIDNO:6) clonotype20069 TRA:CAPLGAGGFKTIF;(SEQIDNO:7) CV 670 TRB:CASSEALSGGAFGGELFF(SEQIDNO: 8) clonotype20070 TRA:CAESWAGGGADGLTF;(SEQIDNO:9) CV 622 TRB:CASNRPGQGINEQFF(SEQIDNO:10) clonotype50222 TRA:CAVDPILTGGGNKLTF;(SEQIDNO: CV 155 11) TRB:CSLSGTAATNYGYTF(SEQIDNO:12) clonotype50223 TRA:CALSSPNFGNEKLTF;(SEQIDNO:13) CV 118 TRA:CAVDSRGGATNKLIF;(SEQIDNO:14) TRB:CASSGGAATTNEKLFF(SEQIDNO:15) clonotype20071 TRB:CASSPRDSAQSWYGYTF(SEQIDNO: CV 107 16) clonotype50224 TRA:CALSSPNFGNEKLTF;(SEQIDNO:17) CV 95 TRB:CASSGGAATTNEKLFF(SEQIDNO:18) clonotype50225 TRA:CAARGTGTASKLTF;(SEQIDNO:19) CV 85 TRA:CAPDNYGGSQGNLIF;(SEQIDNO:20) TRB:CASTGAEAATNEKLFF(SEQIDNO:21) clonotype20073 TRA:CAPLGAGGFKTIF(SEQIDNO:22) CV 83 clonotype25395 TRA:CAMSDILTGGGNKLTF;(SEQIDNO: CV 125 23) TRB:CASSQVDRTEAFF(SEQIDNO:24) clonotype32218 TRA:CAFYASGGSYIPTF;(SEQIDNO:25) CV 68 TRB:CASSLAEGAYEQYF(SEQIDNO:26) clonotype32213 TRA:CAVEDRDGGATNKLIF;(SEQIDNO: CV 99 27) TRB:CASSLAQGAAGELFF(SEQIDNO:28) clonotype20074 TRB:CSVDQGLNYGYTF(SEQIDNO:29) CV 63 clonotype50227 TRA:CAARGTGTASKLTF;(SEQIDNO:30) CV 58 TRA:CAPDNYGGSQGNLIF(SEQIDNO:31) clonotype32219 TRA:CAVDPILTGGGNKLTF(SEQIDNO:32) CV 51 clonotype32215 TRA:CAENRLNYQLIW;(SEQIDNO:33) CV 75 TRB:CASSRAGMGRTEAFF(SEQIDNO:34) clonotype50228 TRA:CALSLSGYALNF;(SEQIDNO:35) CV 49 TRB:CASSEGIGQNQETQYF(SEQIDNO:36) clonotype25398 TRA:CAASNYGQNFVF;(SEQIDNO:37) CV 169 TRB:CASSPIAAYNEQFF(SEQIDNO:38) clonotype38510 TRA:CAMRGFNTNAGKSTF;(SEQIDNO:39) CV 41 TRB:CASTTGAAPYNEQFF(SEQIDNO:40) clonotype32216 TRA:CAVVAPQTGANNLFF;(SEQIDNO:41) CV 81 TRB:CASSTGAGSSYNEQFF(SEQIDNO:42) clonotype20081 TRA:CAVSDGIQGAQKLVF(SEQIDNO:43) CV 64 clonotype38513 TRA:CAMRPWNTGNQFYF;(SEQIDNO:44) CV 35 TRB:CASSQEEAGGIDTQYF(SEQIDNO:45) clonotype50229 TRA:CALSLSGYALNF(SEQIDNO:46) CV 34 clonotype32221 TRB:CASSLSRDTYNEQFF(SEQIDNO:47) CV 34 clonotype25402 TRA:CATPAGGYNKLIF;(SEQIDNO:48) CV 399 TRB:CASRGLSTDTQYF(SEQIDNO:49) clonotype20132 TRA:CAMREVNTGNQFYF;(SEQIDNO:50) CV 23 TRA:CAPLGAGGFKTIF;(SEQIDNO:51) TRB:CASSEALSGGAFGGELFF;(SEQIDNO: 52) TRB:CASSPRDSAQSWYGYTF(SEQIDNO: 53) clonotype32225 TRA:CAENRLNYQLIW;(SEQIDNO:54) CV 43 TRA:CAVYLNRDDKIIF;(SEQIDNO:55) TRB:CASSRAGMGRTEAFF(SEQIDNO:56) clonotype25399 TRA:CAMSPYSSASKIIF;(SEQIDNO:57) CV 85 TRB:CASSPSGLVQETQYF(SEQIDNO:58) clonotype20105 TRA:CAESWAGGGADGLTF(SEQIDNO:59) CV 22 clonotype20072 TRA:CAVRVAGGSYIPTF;(SEQIDNO:60) CV 159 TRB:CASSLRVETQYF(SEQIDNO:61) clonotype25400 TRA:CAYFPQGGSEKLVF;(SEQIDNO:62) CV 159 TRB:CASSPWGGSNQPQHF(SEQIDNO:63) clonotype32217 TRA:CALLNTNAGKSTF;(SEQIDNO:64) CV 50 TRB:CSARVAGGVYNEQFF(SEQIDNO:65) clonotype32227 TRB:CASSLAQGAAGELFF(SEQIDNO:66) CV 20 clonotype20198 TRA:CAMREVNTGNQFYF(SEQIDNO:67) CV 16 clonotype32248 TRA:CAMRETNQGGKLIF;(SEQIDNO:68) CV 18 TRB:CASSYGDRGFPDEKLFF(SEQIDNO: 69) clonotype50237 TRA:CAASIVSDYKLSF;(SEQIDNO:70) CV 15 TRB:CASSPGATGGSTNYGYTF(SEQIDNO: 71) clonotype20171 TRA:CAMREVNTGNQFYF;(SEQIDNO:72) CV 14 TRA:CAPLGAGGFKTIF;(SEQIDNO:73) TRB:CASSPRDSAQSWYGYTF(SEQIDNO: 74) clonotype50248 TRA:CILRVDMRF;(SEQIDNO:75) CV 12 TRB:CASSEALVVASQPNQPQHF(SEQID NO:76) clonotype20186 TRB:CASNRPGQGINEQFF(SEQIDNO:77) CV 11 clonotype32251 TRB:CASSLAEGAYEQYF(SEQIDNO:78) CV 11 clonotype25406 TRA:CVVSAASNKLIF;(SEQIDNO:79) CV 101 TRB:CASSLGYGLSTPDTQYF(SEQIDNO: 80) clonotype50256 TRA:CAVSAPLQGGSEKLVF;(SEQIDNO: CV 12 81) TRB:CASSEFGTGFTEAFF(SEQIDNO:82) clonotype50261 TRA:CAVDSRGGATNKLIF;(SEQIDNO:83) CV 11 TRB:CASSGGAATTNEKLFF(SEQIDNO:84) clonotype50253 TRA:CAVTKGFGNVLHC;(SEQIDNO:85) CV 9 TRB:CARTSGFYNEQFF(SEQIDNO:86) clonotype50292 TRA:CAAILTGGGNKLTF;(SEQIDNO:87) CV 9 TRB:CASSPGQASGANVLTF(SEQIDNO:88) clonotype32253 TRA:CAASARAQGGSEKLVF;(SEQIDNO: CV 23 89) TRB:CASSHRTGVNEKLFF(SEQIDNO:90) clonotype38533 TRA:CAAIFQGGSEKLVF;(SEQIDNO:91) CV 17 TRB:CASSIVEAVAHNEQFF(SEQIDNO:92) clonotype36501 TRA:CAVQALNNDMRF;(SEQIDNO:93) CV 13 TRB:CASSYNHEQYF(SEQIDNO:94) clonotype20203 TRB:CASSEALSGGAFGGELFF(SEQIDNO: CV 8 95) elonotype50274 TRA:CAVSLWNTGNQFYF(SEQIDNO:96) CV 8 clonotype50309 TRA:CAVSAYSSASKIIF;(SEQIDNO:97) CV 8 TRB:CASSQGSAPATGELFF(SEQIDNO:98) clonotype32223 TRA:CAATQWNTGNQFYF;(SEQIDNO:99) CV 35 TRB:CASSRPGQGSTEAFF(SEQIDNO:100) clonotype32518 TRA:CAAAGVYTGNQFYF;(SEQIDNO:101) CV 13 TRA:CAAVRNNNNDMRF;(SEQIDNO:102) TRB:CASSQGGDTQYF(SEQIDNO:103) clonotype38860 TRA:CAVNPFTSGTYKYIF;(SEQIDNO:104) CV 8 TRB:CASSQNSLGYTYEQYF(SEQIDNO: 105) clonotype20225 TRA:CAPLGAGGFKTIF;(SEQIDNO:106) CV 7 TRB:CASSEALSGGAFGGELFF;(SEQIDNO: 107) TRB:CASSPRDSAQSWYGYTF(SEQIDNO: 108) clonotype20249 TRA:CAMSAFGQGGSEKLVF;(SEQIDNO: CV 7 109) TRB:CASSSNSGNTIYF(SEQIDNO:110) clonotype50252 TRB:CSLSGTAATNYGYTF(SEQIDNO:111) CV 7 clonotype50555 TRA:CAVSLWNTGNQFYF;(SEQIDNO:112) CV 7 TRB:CASSFPGQGYTEAFF(SEQIDNO:113) clonotype32220 TRA:CAVDSILTGGGNKLTF;(SEQIDNO: CV 71 114) TRB:CASSLGGSVWSPLHF(SEQIDNO:115) clonotype25474 TRA:CAMRVLGGYQKVTF;(SEQIDNO: CV 45 116) TRB:CSATRLNADTQYF(SEQIDNO:117) clonotype32237 TRA:CAVSDSGGGADGLTF;(SEQIDNO: CV 19 118) TRB:CASSRAGFANYGYTF(SEQIDNO:119) clonotype50287 TRA:CAVDPILTGGGNKLTF;(SEQIDNO: CV 7 120) TRB:CASSFNRDTYNEQFF(SEQIDNO:121) clonotype50270 TRA:CAPDNYGGSQGNLIF;(SEQIDNO: CV 6 122) TRB:CASTGAEAATNEKLFF(SEQIDNO: 123) clonotype50442 TRA:CAPDNYGGSQGNLIF(SEQIDNO:124) CV 6 clonotype20383 TRA:CAGPHASGGSYIPTF;(SEQIDNO:125) CV 9 TRB:CASSQRDPYNEQFF(SEQIDNO:126) clonotype20072 TRA:CAVRVAGGSYIPTF;(SEQIDNO:127) CV 159 TRB:CASSLRVETQYF(SEQIDNO:128) clonotype25398 TRA:CAASNYGQNFVF;(SEQIDNO:129) CV 169 TRB:CASSPIAAYNEQFF(SEQIDNO:130) clonotype25402 TRA:CATPAGGYNKLIF;(SEQIDNO:131) CV 399 TRB:CASRGLSTDTQYF(SEQIDNO:132) clonotype25400 TRA:CAYFPQGGSEKLVF;(SEQIDNO:133) CV 159 TRB:CASSPWGGSNQPQHF(SEQIDNO:134) clonotype32211 TRA:CAVDPILTGGGNKLTF;(SEQIDNO: CV 1871 135) TRB:CASSLSRDTYNEQFF(SEQIDNO:136) clonotype25399 TRA:CAMSPYSSASKIIF;(SEQIDNO:137) CV 85 TRB:CASSPSGLVQETQYF(SEQIDNO:138) clonotype20067 TRA:CAMREVNTGNQFYF;(SEQIDNO:139) CV 1714 TRB:CASSPRDSAQSWYGYTF(SEQIDNO: 140) clonotype20069 TRA:CAPLGAGGFKTIF;(SEQIDNO:141) CV 670 TRB:CASSEALSGGAFGGELFF(SEQIDNO: 142) clonotype32213 TRA:CAVEDRDGGATNKLIF;(SEQIDNO: CV 99 143) TRB:CASSLAQGAAGELFF(SEQIDNO:144) clonotype32217 TRA:CALLNTNAGKSTF;(SEQIDNO:145) CV 50 TRB:CSARVAGGVYNEQFF(SEQIDNO:146) clonotype20070 TRA:CAESWAGGGADGLTF;(SEQIDNO: CV 622 147) TRB:CASNRPGQGINEQFF(SEQIDNO:148) clonotype25406 TRA:CVVSAASNKLIF;(SEQIDNO:149) CV 101 TRB:CASSLGYGLSTPDTQYF(SEQIDNO: 150) clonotype20068 TRA:CAVSDGIQGAQKLVF;(SEQIDNO: CV 1175 151) TRB:CSVDQGLNYGYTF(SEQIDNO:152) clonotype25395 TRA:CAMSDILTGGGNKLTF;(SEQIDNO: CV 125 153) TRB:CASSQVDRTEAFF(SEQIDNO:154) clonotype32237 TRA:CAVSDSGGGADGLTF;(SEQIDNO:155) CV 19 TRB:CASSRAGFANYGYTF(SEQIDNO:156) clonotype20182 TRA:CAVTSGAGSYQLTF;(SEQIDNO:157) CV 19 TRB:CASSYSLSSYNSPLHF(SEQIDNO:158) clonotype25474 TRA:CAMRVLGGYQKVTF;(SEQIDNO:159) CV 45 TRB:CSATRLNADTQYF(SEQIDNO:160) clonotype39213 TRA:CAVNPQGGSEKLVF;(SEQIDNO:161) CV 240 TRB:CSATSQGFSNQPQHF(SEQIDNO:162) clonotype50222 TRA:CAVDPILTGGGNKLTF;(SEQIDNO: CV 155 163) TRB:CSLSGTAATNYGYTF(SEQIDNO:164) clonotype38529 TRA:CVVSEPNYGQNFVF;(SEQIDNO:165) CV 14 TRB:CASSLRTGGTDTQYF(SEQIDNO:166) clonotype38690 TRA:CAFIRAGNMLTF;(SEQIDNO:167) CV 382 TRB:CASSADRDLEAFF(SEQIDNO:168) clonotype48823 TRA:CAVPGSQGGSEKLVF;(SEQIDNO: CV 158 169) TRB:CASNQAEAGELFF(SEQIDNO:170) clonotype36501 TRA:CAVQALNNDMRF;(SEQIDNO:171) CV 13 TRB:CASSYNHEQYF(SEQIDNO:172) clonotype20433 TRA:CAVRVAGGSYIPTF;(SEQIDNO:173) CV 6 TRB:CASSLRVETQYF(SEQIDNO:174) clonotype50223 TRA:CALSSPNFGNEKLTF;(SEQIDNO:175) CV 118 TRA:CAVDSRGGATNKLIF;(SEQIDNO: 176) TRB:CASSGGAATTNEKLFF(SEQIDNO: 177) clonotype32215 TRA:CAENRLNYQLIW;(SEQIDNO:178) CV 75 TRB:CASSRAGMGRTEAFF(SEQIDNO:179) clonotype32227 TRB:CASSLAQGAAGELFF(SEQIDNO:180) CV 20 clonotype32518 TRA:CAAAGVYTGNQFYF;(SEQIDNO:181) CV 13 TRA:CAAVRNNNNDMRF;(SEQIDNO:182) TRB:CASSQGGDTQYF(SEQIDNO:183) clonotype26177 TRB:CASSPWGGSNQPQHF(SEQIDNO:184) CV 7 clonotype20074 TRB:CSVDQGLNYGYTF(SEQIDNO:185) CV 63 clonotype38634 TRA:CAVEDGYGGATNKLIF;(SEQIDNO: CV 25 186) TRB:CASSLALGMGGETQYF(SEQIDNO: 187) clonotype38848 TRA:CALSRNSGGSNYKLTF;(SEQIDNO: CV 19 188) TRB:CASRTGLRSGTEAFF(SEQIDNO:189) clonotype36505 TRA:CAVQALNNDMRF;(SEQIDNO:190) CV 8 TRB:CASSRPRVEQGKYEQYF;(SEQIDNO: 191) TRB:CASSYNHEQYF(SEQIDNO:192) clonotype25702 TRA:CAMSTYSSASKIIF;(SEQIDNO:193) CV 7 TRB:CASSPSGLAYEQYF(SEQIDNO:194) clonotype20275 TRB:CASSLRVETQYF(SEQIDNO:195) CV 5 clonotype38987 TRA:CAVSAPNYGQNFVF;(SEQIDNO:196) CV 5 TRB:CASRPGTGGNQPQHF(SEQIDNO:197) clonotype20684 TRA:CAVREAGGSYIPTF;(SEQIDNO:198) CV 4 TRB:CASSLRVETQYF(SEQIDNO:199) clonotype32511 TRB:CSARVAGGVYNEQFF(SEQIDNO:200) CV 3 clonotype39198 TRA:CAASSHSGAGSYQLTF;(SEQIDNO: CV 369 201) TRB:CASSLVTDTQYF(SEQIDNO:202) clonotype30274 TRA:CAFTQEAGNTPLVF;(SEQIDNO:203) CV 77 TRB:CASRRGSPTDTQYF(SEQIDNO:204) clonotype50228 TRA:CALSLSGYALNF;(SEQIDNO:205) CV 49 TRB:CASSEGIGQNQETQYF(SEQIDNO:206) clonotype32225 TRA:CAENRLNYQLIW;(SEQIDNO:207) CV 43 TRA:CAVYLNRDDKIIF;(SEQIDNO:208) TRB:CASSRAGMGRTEAFF(SEQIDNO:209) clonotype38510 TRA:CAMRGENTNAGKSTF;(SEQIDNO: CV 41 210) TRB:CASTTGAAPYNEQFF(SEQIDNO:211) clonotype40376 TRA:CAVSDLYGGATNKLIF;(SEQIDNO: CV 22 212) TRB:CASSDGLAGYNEQFF(SEQIDNO:213) clonotype38781 TRA:CVVNMGTSYDKVIF;(SEQIDNO:214) CV 18 TRB:CASSLASYDNEQFF(SEQIDNO:215) clonotype20462 TRA:CVVSDQGNAGKSTF;(SEQIDNO:216) CV 15 TRB:CSASHLKETQYF(SEQIDNO:217) clonotype50261 TRA:CAVDSRGGATNKLIF;(SEQIDNO: CV 11 218) TRB:CASSGGAATTNEKLFF(SEQIDNO: 219) clonotype48858 TRB:CSATSQGFSNQPQHF(SEQIDNO:220) CV 8 clonotype20706 TRA:CALSDPGGTYKYIF;(SEQIDNO:221) CV 7 TRB:CASSPGGGNTEAFF(SEQIDNO:222) clonotype32913 TRA:CAVGRGSTLGRLYF;(SEQIDNO:223) CV 6 TRB:CASSGDSRGGYNNEQFF(SEQIDNO: 224) clonotype25918 TRA:CAARSLYNFNKFYF;(SEQIDNO:225) CV 6 TRB:CASSQDGGSGWETQYF(SEQIDNO: 226) clonotype26248 TRA:CAVGVNNNDMRF;(SEQIDNO:227) CV 6 TRB:CSVPGPYYNEQFF(SEQIDNO:228) clonotype25647 TRA:CAASEVKVTSGSRLTF;(SEQIDNO: CV 4 229) TRB:CASSFGGLATQPQHF(SEQIDNO:230) clonotype50406 TRA:CAYKTSYDKVIF;(SEQIDNO:231) CV 3 TRB:CASSIEGTVSFYEQYF(SEQIDNO:232) clonotype29234 TRA:CAMTSYSSASKIIF;(SEQIDNO:233) CV 2 TRB:CASSPNGAYNEQFF(SEQIDNO:234) clonotype36123 TRA:CASLVEYGNKLVF;(SEQIDNO:235) CV 2 TRA:CATNTDKLIF;(SEQIDNO:236) TRB:CASRQGLDDTQYF(SEQIDNO:237) clonotype41193 TRA:CVVTYSGGYQKVTF;(SEQIDNO:238) CV 2 TRB:CASSPTGDDGYTF(SEQIDNO:239)
[0168] As referred to herein, Table 7 depicts as follows:
TABLE-US-00007 TABLE7 Virus- Clone ClonotypeID CDR3AminoAcidSequences reactivity Size clonotype57836 TRA:CAMKDSGYSTLTF;(SEQIDNO:240) CV 30 TRB:CASSFEGGDTEAFF(SEQIDNO:241) clonotype57835 TRA:CALSDLIGTASKLTF;(SEQIDNO: CV 26 242) TRB:CSARAGARNTGELFF(SEQIDNO: 243) clonotype57833 TRA:CAASRVEAGTYKYIF;(SEQIDNO: CV 21 244) TRB:CSVEDGQWDTGELFF(SEQIDNO: 245) clonotype57837 TRA:CAMSQNRDDKIIF;(SEQIDNO: CV 21 246) TRB:CASRYRGRENTEAFF(SEQIDNO: 247) clonotype57839 TRA:CILRDRTGANNLFF;(SEQIDNO: CV 18 248) TRB:CSARGTGGRNTEAFF(SEQIDNO: 249) clonotype57840 TRA:CALSVFVDDMRF;(SEQIDNO:250) CV 18 TRB:CASSYGGNQPQHF(SEQIDNO:251) clonotype57842 TRA:CAMSAYASNYQLIW;(SEQIDNO:252) CV 17 TRB:CASSGGLALALQETQYF(SEQIDNO: 253) clonotype57857 TRA:CGTVRSNDYKLSF;(SEQIDNO:254) CV 15 TRB:CASSEAGGTGDTHSNQPQHF(SEQID NO:255) clonotype57859 TRA:CAVISGYSTLTF;(SEQIDNO:256) CV 15 TRB:CASSFVSGGGTGELFF(SEQIDNO: 257) clonotype57887 TRA:CAASRDRLMF;(SEQIDNO:258) CV 15 TRB:CASSLEGAEQYF(SEQIDNO:259) clonotypes7846 TRA:CAVSTILSGGYNKLIF;(SEQIDNO:260) CV 14 TRB:CASSPPSGGAYEQYF(SEQIDNO: 261) clonotype58345 TRA:CAMSGNGNAGNMLTF;(SEQIDNO:262) CV 14 TRB:CATSRDPGGTDTQYF(SEQIDNO: 263) clonotype73522 TRA:CASLGAGNMLTF;(SEQIDNO:264) CV 14 TRB:CASSLPLGAGGRDEQFF(SEQIDNO: 265) clonotype57841 TRA:CAVQGAQKLVF;(SEQIDNO:266) CV 13 TRB:CASSTGTYYEQYF(SEQIDNO:267) clonotype57855 TRA:CALSDYGGSQGNLIF;(SEQIDNO:268) CV 13 TRB:CASSSGQGQTQYF(SEQIDNO:269) clonotype57843 TRA:CALIIQGAQKLVF;(SEQIDNO:270) CV 12 TRB:CASSSRTSGIFDTQYF(SEQIDNO: 271) clonotype57856 TRA:CAVQGGSQGNLIF;(SEQIDNO:272) CV 12 TRB:CASSFIKNTEAFF(SEQIDNO:273) clonotype73524 TRA:CAVTGYAGNMLTF;(SEQIDNO:274) CV 12 TRB:CAWSPGLGSYEQYF(SEQIDNO:275) clonotype57853 TRA:CALTASRGSNYKLTF;(SEQIDNO:276) CV 12 TRB:CASSQVGTRDTEAFF(SEQIDNO: 277) clonotype73523 TRA:CAMRRGGAQKLVF;(SEQIDNO:278) CV 12 TRB:CASSLEGQAGELFF(SEQIDNO:279) clonotype57854 TRA:CAMRGNTGKLIF;(SEQIDNO:280) CV 11 TRB:CASSGRTGANEKLFF(SEQIDNO: 281) clonotype57861 TRA:CAVPTGNQFYF;(SEQIDNO:282) CV 11 TRB:CASSAPGLPGNEQFF(SEQIDNO: 283) clonotype57866 TRA:CAFWGQGAQKLVF;(SEQIDNO: CV 11 284) TRB:CAISESPGQGNEQYF(SEQIDNO:285) clonotype57867 TRA:CIATNSGGYQKVTF;(SEQIDNO:286) CV 11 TRB:CATSRLTGATEQFF(SEQIDNO:287) clonotype57882 TRA:CAASISNAGGTSYGKLTF;(SEQIDNO:288) CV 11 TRB:CASRAQGRETQYF(SEQIDNO:289) clonotype57885 TRA:CAASGFGNVLHC;(SEQIDNO:290) CV 11 TRB:CASSLGRGVSAGELFF(SEQIDNO: 291) clonotype57888 TRA:CAVRDSTGGFKTIF;(SEQIDNO:292) CV 11 TRB:CASIFSSGGQYEQYF(SEQIDNO:293) clonotype57939 TRA:CALTSGSRLTF;(SEQIDNO:294) CV 11 TRB:CATSDLGTGSRTGELFF(SEQIDNO: 295) clonotype57868 TRA:CALSGNTPLVF;(SEQIDNO:296) CV 10 TRB:CASSQDSQRGNIQYF(SEQIDNO: 297) clonotype57895 TRA:CIVRSITSGTYKYIF(SEQIDNO:298) CV 10 clonotype57919 TRA:CAAFSGTYKYIF;(SEQIDNO:299) CV 10 TRB:CATLFKAPYEQYF(SEQIDNO:300) clonotype73526 TRA:CAVERDDKIIF;(SEQIDNO:301) CV 10 TRB:CASSLDRGRDEQYF(SEQIDNO:302) clonotype57844 TRA:CAVNGYSSASKIIF;(SEQIDNO:303) CV 9 TRB:CSARERDDSPLHF(SEQIDNO:304) clonotype57870 TRA:CAVLMNTGFQKLVF;(SEQIDNO:305) CV 9 TRB:CASSGPGATNEKLFF(SEQIDNO: 306) clonotype57871 TRA:CAMKDSGYSTLTF(SEQIDNO:307) CV 9 clonotype57880 TRA:CAARAPGRRALTF;(SEQIDNO:308) CV 9 TRA:CAVGKLIF;(SEQIDNO:309) TRB:CASSQEGPSNEQFF(SEQIDNO:310) clonotype57894 TRA:CAVRTGGSYIPTF;(SEQIDNO:311) CV 9 TRB:CAWSSGHTGELFF(SEQIDNO:312) clonotype57924 TRA:CATVPTTSGTYKYIF;(SEQIDNO:313) CV 9 TRB:CASSLLTGWAFF(SEQIDNO:314) clonotype57947 TRA:CAEKGGNNRLAF;(SEQIDNO:315) CV 9 TRB:CASSVDRDYEQYF(SEQIDNO:316) clonotype57998 TRA:CALLNTGGFKTIF;(SEQIDNO:317) CV 9 TRB:CAWSELGQGRGANVLTF(SEQID NO:318) clonotype58510 TRA:CAMREYSSASKIIF;(SEQIDNO:319) CV 9 TRB:CASNDRREEAKNIQYF(SEQIDNO: 320) clonotype73525 TRA:CALSDRAGGTSYGKLTF;(SEQIDNO:321) CV 9 TRB:CASSHGTDNSPLHF(SEQIDNO:322) clonotype57848 TRA:CAQRGFGNEKLTF;(SEQIDNO:323) CV 8 TRB:CASSSGIGGTSYEQYF(SEQIDNO: 324) clonotype57852 TRA:CILSPVYSGTYKYIF;(SEQIDNO:325) CV 8 TRB:CSARKLAASSYNEQFF(SEQIDNO: 326) clonotypes7862 TRA:CALQEAGGFKTIF;(SEQIDNO:327) CV 8 TRB:CATSRGDLLVNEQFF(SEQIDNO: 328) clonotype57879 TRA:CAVRDTGFQKLVF;(SEQIDNO:329) CV 8 TRB:CASSVTRYEQYF(SEQIDNO:330) clonotype57891 TRA:CVVTDLGTYKYIF;(SEQIDNO:331) CV 8 TRB:CAISEGVWTGDTEAFF(SEQIDNO: 332) clonotype57892 TRA:CAVFSGNTGKLIF;(SEQIDNO:333) CV 8 TRB:CASSFVENTEAFF(SEQIDNO:334) clonotype57912 TRA:CAAPFSSGSARQLTF;(SEQIDNO:335) CV 8 TRB:CASGGGTSNFRTYEQYF(SEQIDNO: 336) clonotype57918 TRA:CASLTSGTYKYIF;(SEQIDNO:337) CV 8 TRA:CAVDILTGGGNKLTF;(SEQIDNO: 338) TRB:CASSETDSVNEQFF(SEQIDNO:339) clonotype57936 TRA:CAPLRMGRLYF;(SEQIDNO:340) CV 8 TRB:CASSLMTLGNTEAFF(SEQIDNO: 341) clonotype57948 TRA:CATDARNYQLIW;(SEQIDNO:342) CV 8 TRB:CASSDTGLAGELFF(SEQIDNO:343) clonotype58058 TRA:CALTDRGTNAGKSTF;(SEQIDNO:344) CV 8 TRB:CASSQDPQRGGGADTQYF(SEQID NO:345) clonotype58340 TRA:CAEPSTGGFKTIF;(SEQIDNO:346) CV 8 TRA:CAESKTVTGGGNKLTF;(SEQIDNO: 347) TRB:CASSSSGGERRAFF(SEQIDNO:348) clonotype58428 TRA:CALSDLGNEKLTF;(SEQIDNO:349) CV 8 TRA:CSYQKLVF;(SEQIDNO:350) TRB:CASSLGGLAGGEQFF(SEQIDNO: 351) clonotype62044 TRA:CAMREGRDDKIIF;(SEQIDNO:352) CV 8 TRB:CASSLTLARTDTQYF(SEQIDNO: 353) clonotype73527 TRA:CAENGPRVNTGFQKLVF;(SEQID CV 8 NO:354) TRB:CASMKQTMNTEAFF(SEQIDNO: 355) clonotype73528 TRA:CALRAPNARLMF;(SEQIDNO:356) CV 8 TRB:CASSFGQGSSEAFF(SEQIDNO:357) clonotype57849 TRA:CAPVGGTYKYIF;(SEQIDNO:358) CV 7 TRB:CASSPTGRGEQYF(SEQIDNO:359) clonotype57864 TRA:CACFGAGSYQLTF;(SEQIDNO:360) CV 7 TRB:CASSYTRTSNSPLHF(SEQIDNO:361) clonotype57872 TRA:CALRDNYGQNFVF;(SEQIDNO:362) CV 7 TRA:CAVRSYGGSQGNLIF;(SEQIDNO: 363) TRB:CASSALGGGTDTQYF(SEQIDNO: 364) clonotype57876 TRA:CALSSRAGGTSYGKLTF;(SEQIDNO:365) CV 7 TRA:CAVRINTGNQFYF;(SEQIDNO:366) TRB:CATSDSQVAGSSYNEQFF(SEQID NO:367) clonotype57881 TRA:CAVPNQAGTALIF;(SEQIDNO:368) CV 7 TRB:CASSFRTGDQPQHF(SEQIDNO:369) clonotype57883 TRA:CAVQTSGTYKYIF;(SEQIDNO:370) CV 7 TRB:CASSLVGGAAEAFF(SEQIDNO:371) clonotype57897 TRA:CAVNFLSNNAGNMLTF;(SEQIDNO:372) CV 7 TRB:CASARYEETQYF(SEQIDNO:373) clonotype57931 TRA:CAVESSGGSNYKLTF;(SEQIDNO: CV 7 374) TRB:CSARDLSYTQYF(SEQIDNO:375) clonotype57940 TRA:CAFMKPVGTYKYIF;(SEQIDNO: CV 7 376) TRB:CSASGGDVDTQYF(SEQIDNO:377) clonotype57966 TRA:CVVSAGTGGFKTIF;(SEQIDNO:378) CV 7 TRB:CASSLGPEMGGHNEQFF(SEQIDNO: 379) clonotype57978 TRA:CAVRGLSGTYKYIF;(SEQIDNO:380) CV 7 TRB:CASSLGTGHHEQFF(SEQIDNO:381) clonotype58037 TRA:CAFMTAFNNDMRF;(SEQIDNO:382) CV 7 TRB:CASSSGQGTSGGHNEQFF(SEQID NO:383) clonotype58052 TRA:CGTEAAGNKLTF;(SEQIDNO:384) CV 7 TRB:CASSLLQGSSYNEQFF(SEQIDNO: 385) clonotype58065 TRA:CAVNAPSSASKIIF;(SEQIDNO:386) CV 7 TRB:CASSPGHRGVNVAKNIQYF(SEQIDNO:387) clonotype58147 TRA:CATVETQGGSEKLVF;(SEQIDNO: CV 7 388) TRB:CASSLTPGYGEAFF(SEQIDNO:389) clonotype58331 TRA:CAGGFKTIF;(SEQIDNO:390) CV 7 TRA:CALSDENSGGSNYKLTF;(SEQID NO:391) TRB:CSARGDSNEKLFF(SEQIDNO:392) clonotype58367 TRA:CARWSSARQLTF;(SEQIDNO:393) CV 7 TRA:CAVYSSASKIIF;(SEQIDNO:394) TRB:CASSLGLAGTYEQYF(SEQIDNO: 395) clonotype64911 TRA:CALSGGYGQNFVF;(SEQIDNO:396) CV 7 TRB:CASSLAGTSTDTQYF(SEQIDNO: 397) clonotype57903 TRA:CAVEAIQGAQKLVF;(SEQIDNO: CV 7 398) TRB:CASSEWGEQYF(SEQIDNO:399) clonotype57858 TRA:CAERDTGRRALTF(SEQIDNO:400) CV 6 clonotype57860 TRA:CVVSARNSGYALNF;(SEQIDNO:401) CV 6 TRB:CASSFGQGPYNEQFF(SEQIDNO: 402) clonotype57869 TRA:CAKPRGRGTMEYGNKLVF;(SEQIDNO:403) CV 6 TRA:CAVNLRKTGNQFYF;(SEQIDNO: 404) TRB:CASSLGETQYF(SEQIDNO:405) clonotype57886 TRA:CAVSDQGGSEKLVF;(SEQIDNO:406) CV 6 TRB:CASSEAPRFGNTIYF(SEQIDNO:407) clonotype57889 TRA:CAVRRYSGGGADGLTF;(SEQIDNO:408) CV 6 TRB:CSAGALQGATNEKLFF(SEQIDNO: 409) clonotype57890 TRA:CAGGYQKVTF;(SEQIDNO:410) CV 6 TRB:CASSTLAGVSYNEQFF(SEQIDNO: 411) clonotype57898 TRA:CAARISSGSARQLTF;(SEQIDNO:412) CV 6 TRB:CASSATYNEQFF(SEQIDNO:413) clonotype57909 TRA:CVVNQGGKLIF;(SEQIDNO:414) CV 6 TRB:CSGAAGGYEQYF(SEQIDNO:415) clonotype57913 TRA:CAMRARSNAGGTSYGKLTF;(SEQID CV 6 NO:416) TRA:CIVRGRDQTGANNLFF;(SEQIDNO: 417) TRB:CASSELGRDDEAFF(SEQIDNO:418) clonotype57916 TRA:CALRGNRDDKIIF;(SEQIDNO:419) CV 6 TRA:CAMKKDSNYQLIW;(SEQIDNO: 420) TRB:CAISGAETQYF(SEQIDNO:421) clonotype57925 TRA:CAVRALTSGTYKYIF;(SEQIDNO: CV 6 422) TRB:CASSGGGGVSEQYF(SEQIDNO:423) clonotype57944 TRA:CAGATSGTYKYIF;(SEQIDNO:424) CV 6 TRB:CASSLSPGTFYEQYF(SEQIDNO:425) clonotype57945 TRA:CAVSPSGNTPLVF;(SEQIDNO:426) CV 6 TRB:CASSLTQGDGYTF(SEQIDNO:427) clonotype57996 TRA:CAVRHGDDKIIF;(SEQIDNO:428) CV 6 TRB:CASWTGTQETQYF(SEQIDNO:429) clonotype58012 TRA:CAASKGSDGQKLLF;(SEQIDNO:430) CV 6 TRB:CSARITLGELFF(SEQIDNO:431) clonotype58051 TRA:CAASISNAGGTSYGKLTF(SEQID CV 6 NO:432) clonotype58214 TRA:CAVRGSGGSNYKLTF;(SEQIDNO:433) CV 6 TRB:CASSLVQSGELFF(SEQIDNO:434) clonotype58253 TRA:CAETGGGNKLTF;(SEQIDNO:435) CV 6 TRB:CASSSGTANEKLFF(SEQIDNO:436) clonotype58374 TRA:CAASSQAGTALIF;(SEQIDNO:437) CV 6 TRB:CASSIRSAGAGDTQYF(SEQIDNO: 438) clonotype58533 TRA:CALSYLNQAGTALIF;(SEQIDNO:439) CV 6 TRB:CASSQDLVDREQYF(SEQIDNO:440) clonotype58535 TRA:CAAARDTGNQFYF;(SEQIDNO:441) CV 6 TRB:CASGGSWSKNIQYF(SEQIDNO:442) clonotype58689 TRA:CAANTGNQFYF;(SEQIDNO:443) CV 6 TRB:CASRWGLHQETQYF(SEQIDNO: 444) clonotype59145 TRA:CAPRGLGGGKLIF;(SEQIDNO:445) CV 6 TRB:CASSTPHRGDGVNTEAFF(SEQID NO:446) clonotype60461 TRA:CAAFLYF;(SEQIDNO:447) CV 6 TRB:CASSASTGGIGYTF(SEQIDNO:448) clonotype61158 TRA:CAVGVSGGGADGLTF;(SEQIDNO:449) CV 6 TRB:CASSLDRNEQFF(SEQIDNO:450) clonotype62111 TRA:CAVSNAGNNRKLIW;(SEQIDNO:451) CV 6 TRB:CASSYWGGGNQPQHF(SEQIDNO: 452) clonotype62791 TRA:CAVGGRSGGYNKLIF;(SEQIDNO:453) CV 6 TRB:CASSLAQTGSGNTIYF(SEQIDNO: 454) clonotype72074 TRA:CLVGDHSGNTPLVF;(SEQIDNO:455) CV 6 TRB:CSARAEGEGRYNEQFF(SEQIDNO: 456) clonotype73529 TRA:CVVSSGSGSARQLTF;(SEQIDNO:457) CV 6 TRB:CASSLIGQGLRETQYF(SEQIDNO: 458) clonotype73530 TRA:CAASRGNNRLAF;(SEQIDNO:459) CV 6 TRA:CAVSDGPGGYNKLIF;(SEQIDNO:460) TRB:CASSGGHNTEAFF(SEQIDNO:461) clonotype73531 TRA:CAVPGFGNEKLTF;(SEQIDNO:462) CV 6 TRB:CAISGGERGSYEQYF(SEQIDNO: 463) clonotype73533 TRA:CAVGPGGYQKVTF;(SEQIDNO:464) CV 6 TRB:CASSLARRDREQFF(SEQIDNO:465) clonotype73534 TRA:CVVALLSGGFKTIF;(SEQIDNO:466) CV 6 TRB:CASSLWDSSYGYTF(SEQIDNO:467) clonotype73535 TRA:CAVDKVGSEKLVF;(SEQIDNO:468) CV 6 TRB:CSAGGGINEKLFF(SEQIDNO:469) clonotype23651 TRA:CAGPGNDMRF;(SEQIDNO:470) CV 310 TRB:CASSYSRSSGTNTEAFF(SEQIDNO: 471) clonotype57865 TRA:CAVGRDKLIF;(SEQIDNO:472) CV 8 TRB:CAISENGGGGQGTEAFF(SEQIDNO: 473) clonotype58062 TRA:CAVSDRGSTLGRLYF;(SEQIDNO:474) CV 6 TRB:CATSREEVLLRNQPQHF(SEQIDNO: 475) clonotype62630 TRA:CALSGGVSNFGNEKLTF;(SEQIDNO:476) CV 6 TRA:CAVLEGRDKIIF;(SEQIDNO:477) TRB:CATAPGAGVGGYTF(SEQIDNO:478) clonotype55171 TRA:CAVPSISSGSARQLTF;(SEQIDNO:479) CV 3 TRB:CASRPSDRYNEQFF(SEQIDNO:480) clonotype57875 TRA:CAGDGSSNTGKLIF;(SEQIDNO:481) CV 3 TRB:CASSGTSRRQFF(SEQIDNO:482) clonotype57878 TRA:CAFREYGNKLVF;(SEQIDNO:483) CV 5 TRB:CASSTGTLFTGELFF(SEQIDNO:484) clonotype57884 TRA:CAVFNTDKLIF;(SEQIDNO:485) CV 5 TRB:CAWTGAGTYNEQFF(SEQIDNO: 486) clonotype57893 TRA:CAARGFGAGNKLTF;(SEQIDNO:487) CV 5 TRA:CAGTSGTYKYIF;(SEQIDNO:488) TRB:CASSSGQSYEQYF(SEQIDNO:489) clonotype57900 TRA:CAVSVSGGGADGLTF;(SEQIDNO:490) CV 5 TRB:CASSLDRVGTEAFF(SEQIDNO:491) clonotype57905 TRA:CAMSGGYNKLIF;(SEQIDNO:492) CV 5 TRA:CVVSRSGGYQKVTF;(SEQIDNO: 493) TRB:CSVAGLSGTDTQYF(SEQIDNO:494) clonotype57906 TRA:CALKALGSYIPTF;(SEQIDNO:495) CV 5 TRB:CASSPDSGANVLTF(SEQIDNO:496) clonotype57907 TRA:CALSAIGSGGSNYKLTF;(SEQIDNO:497) CV 5 TRB:CASSQGPVGTGGTDTQYF(SEQID NO:498) clonotype57917 TRA:CALEVGSNTGKLIF;(SEQIDNO:499) CV 5 TRB:CASSYSATGVVYTGELFF(SEQID NO:500) clonotype57920 TRA:CLVGGPDSGAGSYQLTF;(SEQIDNO:501) CV 5 TRB:CASSGRRVDTEAFF(SEQIDNO:502) clonotype57923 TRA:CAASIFGNEKLTF(SEQIDNO:503) CV 3 clonotype57926 TRA:CAVEVVSGGSYIPTF;(SEQIDNO:504) CV 5 TRB:CASSFGSGRVHEQFF(SEQIDNO: 505) clonotype57929 TRA:CAVSSYLTDKLIF;(SEQIDNO:506) CV in TRB:CATSDQTGVRTF(SEQIDNO:507) clonotype57935 TRA:CAASIFGNEKLTF;(SEQIDNO:508) CV 5 TRB:CASSRQVRYEQYF(SEQIDNO:509) clonotype57942 TRA:CAMREGYQGAQKLVF;(SEQIDNO:510) CV 5 TRB:CASSFSSRQALMDEQFF(SEQIDNO: 511) clonotype57954 TRA:CAYRSDNQGGKLIF(SEQIDNO:512); CV 5 TRB:CAISDRDRGRGFF(SEQIDNO:513) clonotype57962 TRA:CAPWGESSYKLIF;(SEQIDNO:514) CV 5 TRB:CAWSASWETQYF(SEQIDNO:515) clonotype57973 TRA:CAASGAGSYQLTF;(SEQIDNO:516) CV 5 TRB:CSARDRNSNEQFF(SEQIDNO:517) clonotype57994 TRA:CAVEQGGSEKLVF;(SEQIDNO:518) CV 5 TRB:CASSRDLFYSGANVLTF(SEQIDNO: 519) clonotype57999 TRA:CAMREGLDNQGGKLIF;(SEQIDNO: CV 5 520) TRB:CSARESNRAAVGYTF(SEQIDNO: 521) clonotype58020 TRA:CATVPYGNNRLAF;(SEQIDNO:522) CV 5 TRB:CASRSSNQPQHF(SEQIDNO:523) clonotype58024 TRA:CAASTGGGSNYKLTF;(SEQIDNO:524) CV 5 TRB:CASSLGSPLHF(SEQIDNO:525) clonotype58027 TRA:CAAAYSGGGADGLTF;(SEQIDNO:526) CV 5 TRB:CASSLDSTDTQYF(SEQIDNO:527) clonotype58039 TRA:CAVDTGNQFYF;(SEQIDNO:528) CV 3 TRB:CSARPAGRDEQYF(SEQIDNO:529) clonotype58053 TRA:CAFGLYAGGTSYGKLTF;(SEQID CV 5 NO:530) TRB:CASSSRPGDEQYF(SEQIDNO:531) clonotype58054 TRA:CIVRFGSSNTGKLIF;(SEQIDNO:532) CV 3 TRB:CASSPGAPSGGETQYF(SEQIDNO: 533) clonotype58057 TRA:CAGNSRDDKIIF;(SEQIDNO:534) CV 5 TRB:CSARKAGGYQPQHF(SEQIDNO:535) clonotype58060 TRA:CILISNFGNEKLTF;(SEQIDNO:536) CV 5 TRB:CASSQVMTHNTGELFF(SEQIDNO: 537) clonotype58071 TRA:CATDGNNDMRF;(SEQIDNO:538) CV 5 TRB:CASSLGGVSLAQYF(SEQIDNO:539) clonotype58115 TRA:CAASPWGNARLMF;(SEQIDNO: CV 5 540) TRA:CAASREGNNARLMF;(SEQIDNO: 541) TRB:CASSPFGENIQYF(SEQIDNO:542) clonotype58169 TRA:CAAAYARLMF;(SEQIDNO:543) CV 5 TRB:CASSPDGSSYNEQFF(SEQIDNO: 544) clonotype58218 TRA:CVVRGGGYNKLIF;(SEQIDNO:545) CV 5 TRB:CASSPMAGSYNEQFF(SEQIDNO: 546) clonotype58251 TRA:CALSGGDSSYKLIF;(SEQIDNO:547) CV 5 TRB:CASSFWFHEQYF(SEQIDNO:548) clonotype58280 TRB:CASSLPGGRSTDTQYF(SEQIDNO: CV 3 549) clonotype58303 TRA:CILNSGGGADGLTF;(SEQIDNO:550) CV 5 TRB:CASSKGQVLADTQYF(SEQIDNO: 551) clonotype58323 TRA:CVVSDRSGGSYIPTF;(SEQIDNO: CV 3 552) TRB:CASSLGLAGAGELFF(SEQIDNO: 553) clonotype58349 TRA:CTENRGSGGYQKVTF;(SEQIDNO:554) CV 5 TRB:CASSASQGLREKLFF(SEQIDNO: 555) clonotype58355 TRA:CAFLERNTGKLIF;(SEQIDNO:556) CV 3 TRB:CASSLVTGAEQYF(SEQIDNO:557) clonotype58377 TRA:CVVNGGGTSYGKLTF;(SEQIDNO:558) CV 5 TRB:CATSRGQGRGTYEQYF(SEQIDNO: 559) clonotype58400 TRA:CAATPNSGGSNYKLTF;(SEQIDNO: CV 3 560) TRA:CAFGGQGNLIF;(SEQIDNO:561) TRB:CASSLASTIAYEQYF(SEQIDNO:562) clonotype58478 TRA:CAVQELFSGGYNKLIF;(SEQIDNO:563) CV 5 TRB:CASSGPSGGAQETQYF(SEQIDNO: 564) clonotype58485 TRA:CAGEPLGNTGKLIF;(SEQIDNO:565) CV 5 TRA:CVGGGTSYGKLTF;(SEQIDNO:566) TRB:CASSSPGKTSGDEQFF(SEQIDNO: 567) clonotype58487 TRA:CGASAGGTSYGKLTF;(SEQIDNO:568) CV 5 TRB:CSARGKSGAFF(SEQIDNO:569) clonotype58498 TRA:CLYSGGYNKLIF;(SEQIDNO:570) CV 3 TRB:CASNWGRINSPLHF(SEQIDNO:571) clonotype58847 TRA:CAVPPYTGTASKLTF;(SEQIDNO:572) CV 5 TRB:CASSLGTGVGGSPLHF(SEQIDNO: 573) clonotype59208 TRA:CVVNTGFQKLVF;(SEQIDNO:574) CV 3 TRB:CAISELQENTEAFF(SEQIDNO:575) clonotype59374 TRA:CAVQAGRNTDKLIF;(SEQIDNO: CV 5 576) TRB:CASSVGTYGGYTF(SEQIDNO:577) clonotype60777 TRA:CAGKGNQGGKLIF;(SEQIDNO:578) CV 3 TRB:CASSPQGHGYTF(SEQIDNO:579) clonotype61418 TRA:CAVISGYSTLTF(SEQIDNO:580) CV 3 clonotype61484 TRA:CAMRENTGGFKTIF;(SEQIDNO:581) CV 5 TRB:CSARDLHRGAGNQPQHF(SEQIDNO: 582) clonotype63292 TRA:CVVSLNSGYSTLTF;(SEQIDNO:583) CV 3 TRB:CASSLPKNIQYF;(SEQIDNO:584) TRB:CASSSGGEQFF(SEQIDNO:585) clonotype64366 TRA:CAVEEGSNYQLIW;(SEQIDNO:586) CV 5 TRB:CASSEKGNYGYTF(SEQIDNO:587) clonotype64660 TRA:CAMSPKLGYALNF;(SEQIDNO:588) CV 3 TRB:CASSLGQGPSANEKLFF(SEQIDNO: 589) clonotype65111 TRA:CARGVDTGNQFYF;(SEQIDNO:590) CV 3 TRA:CIVRAGSSNTGKLIF;(SEQIDNO: 591) TRB:CASSYSRGRSPLHF(SEQIDNO:592) clonotype65268 TRA:CATDGWEGQNFVF;(SEQIDNO: CV 3 593) TRB:CASSLQGGTDTQYF(SEQIDNO:594) clonotype65740 TRA:CIVRPTGNQFYF;(SEQIDNO:595) CV 3 TRB:CASSNGGQDGYTF(SEQIDNO:596) clonotype66085 TRA:CAVSRRGFQKLVF;(SEQIDNO:597) CV 5 TRB:CAWVSDNTEAFF(SEQIDNO:598) clonotype73532 TRA:CAFMRNYGGATNKLIF;(SEQIDNO:599) CV 5 TRB:CAIRGGGTGSPLHF(SEQIDNO:600) clonotype73536 TRA:CATGPQGGSEKLVF;(SEQIDNO:601) CV 5 TRB:CSAAPGTGYQPQHF(SEQIDNO:602) clonotype73538 TRA:CALSEALTGGGNKLTF;(SEQIDNO:603) CV 3 TRB:CASSFGQASYEQYF(SEQIDNO:604) clonotype73539 TRA:CALPPRGSTLGRLYF;(SEQIDNO:605) CV 5 TRB:CASSMRRQPQHF(SEQIDNO:606) clonotype73540 TRA:CALSEGYSSASKIIF;(SEQIDNO:607) CV 5 TRB:CASRGVVGEQFF(SEQIDNO:608) clonotype73541 TRA:CAATGGSQGNLIF;(SEQIDNO:609) CV 5 TRB:CASSLAWGQSSYNEQFF(SEQIDNO: 610) clonotype73542 TRA:CAVEDLGSGYSTLTF;(SEQIDNO:611) CV 3 TRB:CASSNTLGPGGYGYTF(SEQIDNO:612) clonotype73544 TRA:CAVMPGTSYGKLTF;(SEQIDNO:613) CV 5 TRB:CASGRTSGGAVTIEQFF(SEQIDNO: 614) clonotype73545 TRA:CAGRRTGGGADGETF;(SEQIDNO: CV 5 615) TRB:CAITSGGSYNEQFF(SEQIDNO:616)
[0169] The following Examples depict certain aspects and embodiments of the present disclosure.
Example 1: CD4.SUP.+ T Cell Responses in COVID-19 Illness
[0170] To capture CD4.sup.+ T cells responding to SARS-CoV-2 in patients with COVID-19 illness, the inventors employed the antigen-reactive T cell enrichment (ARTE) assay (Bacher et al., 2016; Bacher et al., 2019; Bacher et al., 2013) that relies on in vitro stimulation of peripheral blood mononuclear cells (PBMCs) for 6 hours with overlapping peptide pools targeting the immunogenic domains of the spike and membrane protein of SARS-CoV-2 (see Star Methods (Braun et al., 2020; Thieme et al., 2020)). Following in vitro stimulation, SARS-CoV-2-reactive CD4.sup.+ memory T cells were isolated based on the expression of cell surface markers (CD154 and CD69) that reflect recent engagement of the T cell receptor (TCR) by cognate MHC-peptide complexes (
[0171] Recent evidence from studies in non-exposed individuals (blood sample obtained pre-COVID-19 pandemic) indicates that pre-existing human coronavirus (HCoV)-reactive CD4.sup.+ T cells can cross-react with SARS-CoV-2 antigens, and such cross-reactive cells are observed in up to 50% of the subjects studied (Braun et al., 2020; Grifoni et al., 2020). To capture such cross-reactive CD4.sup.+ T cells, likely to be human coronavirus (HCoV)-reactive, the inventors screened healthy non-exposed subjects and isolated CD4.sup.+ T cells responding to SARS-CoV-2 peptide pools from 4 subjects with highest responder frequency (
Example 2: SARS-CoV-2-Reactive CD4.SUP.+ T Cells are Enriched for T.SUB.FH .Cells and CD4-CTLs
[0172] Analysis of the single-cell transcriptomes of all viral-reactive CD4.sup.+ T cells from all subjects revealed 13 CD4.sup.+ T cell subsets that clustered distinctly (each corresponding to the respective Tables 0-7), reflecting their unique transcriptional profiles (
[0173] The clusters enriched for FLU-reactive CD4.sup.+ T cells (clusters 1 and 10) displayed features suggestive of polyfunctional T.sub.H1 cells which have been associated with protective anti-viral immune responses (Seder et al., 2008). Such features include the expression of transcripts encoding for the canonical T.sub.H1 transcription factor T-bet, cytokines linked to polyfunctionality, IFN-IL-2 and TNF, and several other cytokines and chemokines like IL-3, CSF2, IL-23A and CCL20 (
[0174] Other clusters that were relatively depleted of SARS-CoV-2-reactive CD4.sup.+ T cells included clusters 9 and 2, which were both enriched for T.sub.H17 signature genes, with cluster 9 highly enriched for cells expressing IL17A and IL17F transcripts, thus representing bonafide T.sub.H17 cells (
[0175] Clusters that were evenly distributed across all viral-specific CD4.sup.+ T cells include cluster 5 and 3. Cluster 5 displayed a transcriptional profile consistent with enrichment of interferon-response genes (IFIT3, IFI44L, ISG15, MX2, OAS1), and cluster 3 was enriched for CCR7, IL7R and TCF7 transcripts, likely representing central memory CD4.sup.+ T cell subset (
[0176] Clusters 0, 6 and 7, which were colocalized in UMAP plots were dominated by SARS-CoV-2-reactive CD4.sup.+ T cells (
[0177] Cluster 12, which expressed high levels of transcripts linked to cell cycle genes MKI67 and CDK1, also contained a large proportion of SARS-CoV-2 reactive CD4.sup.+ T cells (
Example 3: SARS-CoV-2-Reactive CD4.SUP.+ T Cell Subsets Associated with Disease Severity
[0178] The inventors next assessed if the proportions of SARS-CoV-2 reactive CD4.sup.+ T cells in ay cluster were greater or lower in patients with severe COVID-19 (n=21, requiring hospitalization) when compared to those with milder disease (n=9, not needing hospitalization). Among the three T.sub.FH clusters (clusters 0,6 and 7), which consisted almost exclusively of CD4.sup.+ T cells reactive to SARS-CoV-2, the relative proportion of cells in T.sub.FH cluster 6 was greater in patients with severe disease compared to mild disease (
[0179] While T cells with cytotoxic function predominantly consist of conventional MHC class I-restricted CD8.sup.+ T cells, MHC class II-restricted CD4.sup.+ T cells with cytotoxic potential (CD4-CTLs) have been reported in several viral infections in humans and are associated with better clinical outcomes (Cheroutre and Husain, 2013; Weiskopf et al., 2015a). Paradoxically, in SARS-CoV-2 infection, the inventors find that cells in the CD4-CTL clusters (cluster 4 and 8) were present at higher frequencies in hospitalized patients with severe disease compared to those with milder disease, potentially contributing to disease severity, although the inventors observed substantial heterogeneity in responses among patients (
Example 4: Massive Clonal Expansion of CD4-CTLs
[0180] The recovery of paired T cell receptor (TCR) sequences from individual single cells enabled us to link transcriptome data to clonotype information and evaluate the clonal relationship between different CD4.sup.+ T cell subsets as well as determine the nature of subsets that display greatest clonal expansion. In SARS-CoV-2 infection, hospitalized patients were characterized by large clonal expansion of the virus-reactive CD4.sup.+ T cells; in contrast, in non-hospitalized patients, less than 45% of TCRs recovered were clonally expanded (
Example 5: SARS-CoV2-Reactive T.SUB.REG .are Reduced in Severe COVID-19 Illness
[0181] In order to capture SARS-CoV-2-reactive CD4.sup.+ T cells that may not upregulate the activation markers (CD154 and CD69) after 6 hours of in vitro stimulation with SARS-CoV-2 peptide pools, the inventors stimulated PMBCs from the same cultures for a total of 24 hours (see STAR Methods) and captured cells based on co-expression of activation markers CD137 (4-1BB) and CD69, a strategy that allowed us to additionally capture antigen-specific regulatory T cells (T.sub.REG) (Bacher et al., 2016)(
[0182] CD4.sup.+ T cell subsets that are reactive to SARS-CoV-2 and other respiratory viruses show remarkable heterogeneity, and across patients with differing severity of COVID-19. Polyfunctional T.sub.H1 cells, which are abundant among FLU-reactive CD4.sup.+ T cells and are considered to be protective (Seder et al., 2008), were present in lower frequencies among SARS-CoV-2-reactive CD4.sup.+ T cells from patients with severe COVID-19. Lower frequencies of T.sub.H17 cells were also observed among SARS-CoV-2-reactive CD4.sup.+ T cells. In contrast, the inventors find increased proportions of SARS-CoV-2-reactive T.sub.FH cells with dysfunctional and cytotoxicity features in hospitalized patients with severe COVID-19 illness. These findings raise the possibility that certain aspects of antigen-specific CD4.sup.+ T cell responses required for immune-protection are not optimally generated in COVID-19. Another striking observation is the abundance of CD4-CTLs that express high levels of transcripts encoding for multiple chemokines (XCL1, XCL2, CCL3, CCL4, CCL5) in SARS-CoV-2-reactive CD4.sup.+ T cells, particularly, from patients with severe COVID-19 illness. The magnitude of CD4-CTL response has been associated with better clinical outcomes in viral infections and following vaccination (Juno et al., 2017), providing that the CD4-CTL responses in COVID-19 illness may also be linked to protection.
Example 6: Experimental Model and Subject Details (Used in Examples 1-5; and Also Referred to Herein as STAR Methods)
COVID-19 Patients and Samples.
[0183] Ethical approval for this study from the Berkshire Research Ethics Committee 20/SC/0155 and the Ethics Committee of La Jolla Institute was in place. Written consent was obtained from all subjects. 21 hospitalized patients in a large teaching hospital in the south of England with SARS-CoV-2 infection, confirmed by reverse transcriptase polymerase chain reaction (RT-PCR) assay for detecting SARS-CoV2, between April-May 2020 were recruited to the study. A further cohort of 9 participants consisting of healthcare workers who were not hospitalized with COVID-19 illness, confirmed based on RT-PCR assay or serological evidence of SARS-CoV-2 antibodies, were also recruited over the same period. All subjects provided up to 80 mls of blood for research studies. Clinical and demographic data were collected from patient records for hospitalized patients including comorbidities, blood results, drug intervention, radiological involvement, thrombotic events, microbiology and virology results. The median age of patients with COVID-19 illness was 53 (26-82) and 67% were male. This cohort consisted of 24 (81%) White British/White Other, 4 (13%) Indian and 2 (7%) Black British participants. Of the 30 participants, 9 (30%) had mild disease and were not hospitalized, 21 (70%) had moderate/severe disease and were hospitalized. The median age of the non-hospitalized group was 40 (26-50) and 44% were male. The median age of the hospitalized patients was 60 (33-82) and 76% were male. All hospitalized patients survived to discharge from hospital.
Healthy Controls
[0184] To study HPIV, HMPV and SARS-CoV-2 reactive CD4.sup.+ T cells, the inventors utilized de-identified buffy coat samples from healthy adult donors who donated blood at the San Diego Blood Bank before 2019, prior to the Covid-19 pandemic. Donors were considered to be in good health, free of cold or flu-like symptoms and with no history of Hepatitis B or Hepatitis C infection. To study FLU-reactive cells, the inventors obtained de-identified blood samples from 8 donors enrolled in the La LJI's Normal Blood Donor Program before and/or after (12-14 days) receiving the FLUCELVAX vaccine. Approval for the use of this material was obtained from the Ethics Committee of La Jolla Institute.
Method Details
PBMC Processing
[0185] Peripheral blood mononuclear cells (PBMCs) were isolated from up to 80 ml of anti-coagulated blood by density centrifugation over Lymphoprep (Axis-Shield PoC AS, Oslo, Norway) and cryopreserved in 50% decomplemented human antibody serum, 40% complete RMPI 1640 medium and 10% DMSO.
SARS-CoV-2 Peptide Pools
[0186] Pools of lyophilized peptides covering the immunodominant sequence of the spike glycoprotein ad the complete sequence of the membrane glycoprotein of SARS-CoV-2 (15-mer sequences with 11 amino acids overlap) were obtained from Miltenyi Biotec (Constantin J Thieme, 2020), resuspended and stored according to the manufacturer's instructions.
Epitope MegaPool (MP) Design
[0187] The Human Parainfluenza (HPIV), Metapneumovirus (HMPV) CD4.sup.+ T cell megapools (MPs) were produced by sequential lyophilization of viral-specific epitopes as previously described (Carrasco Pro et al., 2015; Weiskopf et al., 2015b). T cell prediction was performed using TepiTool tool, available in IEDB analysis resources (IEDB-AR), applying the 7-allele prediction method and a median cutoff20 (Dhanda et al., 2019; Paul et al., 2015; Paul et al., 2016). For the HA-influenza MP, the inventors selected 177 experimentally defined epitopes, retrieved by querying the IEDB database on 07/12/19 with search parameters positive assay only, No B cell assays, No MHC ligand assay, Host: Homo Sapiens and MHC restriction class II. The list of epitopes was enriched with predicted peptides derived from the HA sequences of the vaccine strains available in 2017-2018 and 2018-2019 (A/Michigan/45/2015(H1N1), B/Brisbane/60/2008,A/Hong_Kong/4801/2014_H3N2, A/Michigan/45/2015(H1N1), A/Alaska/06/2016(H3N2), B/Iowa/06/2017, B/Phuket/3073/2013). The resulting peptides were then clustered using the IEDB cluster 2.0 tool and the IEDB recommended method (cluster-break method) with a 70% cut off for sequence identity applied (Dhanda et al., 2019; Dhanda et al., 2018). Peptides were synthesized as crude material (A&A, San Diego, CA), resuspended in DMSO, pooled according to each MP composition and finally sequentially lyophilized (Carrasco Pro et al., 2015). For screening healthy non-exposed subjects (samples provided before the current pandemic) who cross-react to SARS-CoV-2, the inventors screened 20 healthy non-exposed subjects using SARS-CoV-2 peptide CD4-R and CD4-S pools, as described (Grifoni et al., 2020).
Antigen-Reactive T Cell Enrichment (ARTE) Assay
[0188] Enrichment and FACS sorting of virus-reactive CD154.sup.+ or CD137.sup.+ CD4.sup.+ memory T cells following peptide pool stimulation was adapted from Bacher et al. 2016 (Bacher et al., 2016). Briefly, PBMCs from each donor, were thawed, washed, plated in 6-well culture plates at a concentration of 510.sup.6 cells/ml in 1 ml of serum-free TexMACS medium (Miltenyi Biotec) and left overnight (5% CO.sub.2, 37 C.). Cells were stimulated by the addition of individual virus-specific peptide pools (1 g/ml) for 6 h in the presence of a blocking CD40 antibody (1 g/ml; Miltenyi Biotec). For subsequent MACS-based enrichment of CD154.sup.+, cells were sequentially stained with fluorescence-labeled surface antibodies, Cell-hashtag TotalSeq-C antibody (0.5 g/condition), and a biotin-conjugated CD154 antibody (clone 5C8; Miltenyi Biotec) followed by anti-biotin microbeads (Miltenyi Biotec). Labelled cells were added to MS columns (Miltenyi Biotec) and positively selected cells (CD154.sup.+) were eluted and used for FACS sorting of CD154.sup.+ memory CD4.sup.+ T cells. The flow-through from the column was collected and re-plated to harvest cells responding 24 h after peptide stimulation. Analogous to enrichment for CD154.sup.+, CD137-expressing CD4.sup.+ memory T cells were positively selected by staining with biotin-conjugated CD137 antibody (clone REA765; Miltenyi Biotec) followed by anti-biotin MicroBeads and applied to a new MS column. Following elution, enriched populations were immediately sorted using a FACSAria Fusion Cell Sorter (Becton Dickinson) based on dual expression of CD154 and CD69 for 6-hour stimulation condition, and CD137 and CD69 for 24-hour stimulation condition. The gating strategy used for sorting is shown in
Cell Isolation and Single-Cell RNA-Seq Assay (10 Platform).
[0189] For combined single-cell RNA-seq and TCR-seq assays (10 Genomics), a maximum of 60,000 virus-reactive memory CD4.sup.+ T cells from up to 8 donors were pooled by sorting into low retention 1.5 mL collection tubes, containing 500 L of a 1:1 solution of PBS:FBS supplemented with RNAse inhibitor (1:100). Following sorting, ice-cold PBS was added to make up to a volume of 1400 l. Cells were then centrifuged for 5 minutes (600 g at 4 C.) and the supernatant was carefully removed leaving 5 to 10 l. 25 l of resuspension buffer (0.22 m filtered ice-cold PBS supplemented with ultra-pure bovine serum albumin; 0.04%, Sigma-Aldrich) was added to the tube and the pellet was gently but thoroughly resuspended. Following careful mixing, 33 l of the cell suspension was transferred to a PCR-tube for processing as per the manufacturer's instructions (10 Genomics).
[0190] Briefly, single-cell RNA-sequencing library preparation was performed as per the manufacturer's recommendations for the 10 Genomics 5TAG v1.0 chemistry with immune profiling and cell surface protein technology. Both initial amplification of cDNA and library preparation were carried out with 13 cycles of amplification; V(D)J and cell surface protein libraries were generated corresponding to each 5TAG gene expression library using 9 cycles and 8 cycles of amplification, respectively. Libraries were quantified and pooled according to equivalent molar concentrations and sequenced on Illumina's NovaSeq6000 sequencing platform with the following read lengths: read 1101 cycles; read 2101 cycles; and i7 index8 cycles.
Single-Cell Transcriptome Analysis
[0191] Reads from single-cell RNA-seq were aligned and collapsed into Unique Molecular Identifiers (UMI) counts using 10 genomics' Cell Ranger software (v3.1.0) and mapping to GRCh37 reference (v3.0.0) genome. Hashtag UMI counts for each TotalSeq-C antibody capture library were generated with the Feature Barcoding Analysis pipeline from Cell Ranger. To demultiplex donors, UMI counts of cell barcodes were first obtained from the raw data output, and only cells with at least 100 UMI were considered for donor assignment. Donor identities were inferred by MULTIseqDemux (autoThresh=TRUE and maxiter=10) from Seurat (v3.1.5) using the UMI counts. Each cell barcode was assigned a donor ID, marked as a Doublet, or having a Negative enrichment. Cells with multiple barcodes were re-classified as doublets if the ratio of UMI counts between the top 2 barcodes was less than 3. Cells labeled as Doublet or Negative were removed from downstream analyses. Raw 10 data, from four libraries, was aggregated using Cell Ranger's aggr function (v3.1.0). The merged data was transferred to the R statistical environment for analysis using the package Seurat (v3.1.5) (Stuart et al., 2019). To further minimize doublets and to eliminate cells with low quality transcriptomes, cells expressing <800 and >4400 unique genes, <1500 and >20,000 total UMI content, and >10% of mitochondrial reads were excluded. The summary statistics for all the single-cell transcriptome libraries indicate good quality data with no major differences in quality control metrices across multiple batches (
[0192] For single-cell transcriptome analysis only genes expressed in at least 0.1% of the cells were included. The transcriptome data was then log-transformed and normalized (by a factor of 10,000) per cell, using default settings in Seurat software. Variable genes with a mean expression greater than 0.01 and explaining 25% of the total variance were selected using the Variance Stabilizing Transformation method, as described (Stuart et al., 2019). Transcriptomic data from each cell was then further scaled by regressing the number of UMI-detected and percentage of mitochondrial counts. For data from CD4+ T cells stimulated for 6 hours, principal component analysis was performed using the variable genes, and based on the standard deviation of PCs in the elbow plot, the first 38 principal components (PCs) were selected for further analyses. Cells were clustered using the FindNeighbors and FindClusters functions in Seurat with a resolution of 0.6. The robustness of clustering was independently verified by other clustering methods and by modifying the number of PCs and variable genes utilized for clustering. Analysis of clustering patterns across multiple batches revealed no evidence of strong batch effects (
Single-Cell Differential Gene Expression Analysis
[0193] Pair-wise single-cell differential gene expression analysis was performed using the MAST package in R (v1.8.2) (Finak et al., 2015) after conversion of data to counts per million (CPM+1). A gene was considered differentially expressed when Benjamini-Hochberg-adjusted P-value was <0.05 and a log 2 fold change was more than 0.25. For finding cluster markers (transcripts enriched in a given cluster) the function FindAllMarkers from Seurat was used.
Gene Set Enrichment Analysis and Signature Module Scores
[0194] GSEA scores were calculated with the package fgsea in R using the signal-to-noise ratio as a metric. Gene sets were limited by minSize=3 and maxSize=500. Normalized enrichment scores were presented as * plots. Signature module scores were calculated with AddModuleScore function, using default settings in Seurat. Briefly, for each cell, the score is defined by the mean of the signature gene list after the mean expression of an aggregate of control gene lists is subtracted. Control gene lists were sampled (same size as the signature list) from bins created based on the level of expression of the signature gene list.
Single-Cell Trajectory Analysis
[0195] The branched trajectory was constructed using Monocle 3 (v0.2.1, default settings) with the number of UMI and percentage of mitochondrial UMI as the model formula, and including the highly variable genes from Seurat for consistency. After setting a single partition for all cells, the cell-trajectory was projected on the PCA and UMAP generated from Seurat analysis. The root was selected by the get_earliest_principal_node function provided in the package.
T Cell Receptor (TCR) Sequence Analysis
[0196] Reads from single-cell V(D)J TCR sequence enriched libraries were 5 processed with the vdj pipeline from Cell Ranger (v3.1.0 and human annotations reference GRCh38, v3.1.0, as recommended). In brief, the V(D)J transcripts were assembled and their annotations were obtained for each independent library. In order to perform combined analysis of single-cell transcriptome and TCR sequence from the same cells V(D)J libraries were first aggregated using a custom script. Then cell barcode suffixes from these libraries were revised according to the order of their gene expression libraries. Unique clonotypes, as defined by 10 Genomics as a set of productive Complementarity-Determining Region 3 (CDR3) sequences, were identified across all library files and their frequency and proportion (clone statistics) were calculated based on the aggregation result. This procedure was independently applied for data from CD4.sup.+ T cells stimulated for 6 hours and 24 hours. Based on the vdj aggregation files, barcodes captured by the gene expression data and previously filtered to keep only good quality cells, were annotated with a specific clonotype ID alongside their clone size (number of cells with the same clonotypes in both the TCR alpha and beta chains) statistics. Cells that share clonotype with more than 1 cell were called as clonally expanded (clone size 2). Clone size for each cell was visualized on UMAP. Sharing of clonotype between cells in different clusters was depicted using the tool UpSetR.
Quantification and Statistical Analysis
[0197] Processing of data, applied methods and codes are described in the respective section in the STAR Methods. The number of subjects, samples and replicates analyzed, and the statistical test performed are indicated in the figure legends. Statistical analysis for comparison between two groups was assessed with Student's unpaired two-tailed t-test using GraphPad Prism 7.0d.
Example 7: CD4+ T Cell Responses in COVID-19 Illness
[0198] To capture CD4+.sup.T cells responding to SARS-CoV-2 in patients with COVID-19 illness, we employed the antigen-reactive T cell enrichment (ARTE) assay (Bacher et al., 2013, 2016, 2019; Schmiedel et al., 2018) that relies on in vitro stimulation of peripheral blood mononuclear cells (PBMCs) for 6 h with overlapping peptide pools targeting the immunogenic domains of the spike and membrane proteins of SARS-CoV-2 (see STAR Methods; Thieme et al., 2020). Following in vitro stimulation, SARS-CoV-2-reactive CD4+ memory T cells were isolated based on the expression of cell surface markers (CD154 and CD69) that reflect recent engagement of the T cell receptor (TCR) by cognate major histocompatibility complex (MHC)-peptide complexes (
[0199] Recent evidence from studies in non-exposed individuals (blood sample obtained pre-COVID-19 pandemic) indicates pre-existing SARS-CoV-2-reactive CD4+ T cells, possibly indicative of human coronavirus (HCoV) cross-reactivity. Such cells are observed in up to 50% of the subjects studied (Braun et al., 2020; Grifoni et al., 2020; Le Bert et al., 2020). To capture such SARS-CoV-2-reactive CD4+ T cells, likely to be coronavirus (CoV)-reactive, we screened healthy non-exposed subjects and isolated CD4+ T cells responding to SARS-CoV-2 peptide pools from 4 subjects with highest responder frequency (
Example 8: SARS-CoV-2-Reactive CD4+ T Cells are Enriched for TFH Cells and CD4-CTLs
[0200] Analysis of the single-cell transcriptomes of all viral-reactive CD4+ T cells from all subjects revealed 13 CD4+ T cell subsets that clustered distinctly, reflecting their unique transcriptional profiles (
[0201] The clusters enriched for FLU-reactive CD4+ T cells (clusters 1 and 10) displayed features suggestive of polyfunctional T helper (TH)1 cells which have been associated with protective anti-viral immune responses (Seder et al., 2008). Such features include the expression of transcripts encoding for the cytokines linked to polyfunctionality such as IFN-g, IL-2, and TNFa, and several other cytokines and chemokines like IL-3, CSF2, IL-23A, and CCL20 (
[0202] Other clusters that were relatively underrepresented for SARS-CoV-2-reactive CD4+ T cells included clusters 2 and 8, which were both enriched for TH17 signature genes, with cluster 2 highly enriched for cells expressing IL17A and IL17F transcripts, thus representing bona fide TH17 cells (
[0203] Clusters that were evenly distributed across all viral-specific CD4+ T cells include clusters 3 and 4. Cluster 3 displayed a transcriptional profile consistent with enrichment of interferon (IFN)-response genes (IFIT3, IFI44L, ISG15, MX2, OAS1), and cluster 4 was enriched for CCR7, IL7R, and TCF7 transcripts, likely representing central memory CD4+ T cell subset (
[0204] Clusters 0, 5, and 7, which were colocalized in the uniform manifold approximation and projection (UMAP) plot, were dominated by SARS-CoV-2-reactive CD4+ T cells (
Example 9: SARS-CoV-2-Reactive CD4+ T Cell Subsets Associated with Disease Severity
[0205] We next assessed if the proportions of SARS-CoV-2-reactive CD4+ T cells in any cluster were greater or lower in hospitalized COVID-19 patients when compared to non-hospitalized patients. Unsupervised clustering of patients, based on the proportions of SARS-CoV-2-reactive CD4+ T cells in different clusters, showed that patients with an increased proportion of TFH cells in cluster 0 clustered distinctly from those with increased proportions of TFH cells in cluster 5 or CD4-CTL cells (cluster 6) (
[0206] To determine the transcriptional features that differentiated SARS-CoV-2-reactive TFH cells present in cluster 5 from those in cluster 0, we performed single-cell differential gene expression analysis (
[0207] Most strikingly, TFH cells in cluster 5 expressed high levels of cytotoxicity-associated transcripts (PRF1, GZMB) (
[0208] Next, to characterize upstream regulators that may induce the differentiation and maintenance of the cytotoxic TFH cells, we performed Ingenuity Pathway analysis (IPA) of the transcripts increased in SARS-CoV-2-reactive TFH cells in cluster 5 (cytotoxic) when compared to those in cluster 0 (Tables S3D and S3E). Surprisingly, we found that type 1 and 2 IFNs emerged as the top upstream activators of genes enriched in the cytotoxic TFH cluster (
Example 10: Massive Clonal Expansion of CD4-CTLs
[0209] While T cells with cytotoxic function are thought to predominantly consist of conventional MHC class I-restricted CD8+ T cells, MHC class II-restricted CD4+ T cells with cytotoxic potential (CD4-CTLs) have also been reported in several viral infections in humans and are associated with better clinical outcomes (Cheroutre and Husain, 2013; Juno et al., 2017; Meckiff et al., 2019; Weiskopf et al., 2015a). Paradoxically, in SARSCoV-2 infection, we find that cells in the CD4-CTL clusters (
[0210] Interrogation of the transcripts enriched in the CD4-CTL subsets pointed to several interesting molecules and transcription factors that are likely to play an important role in their maintenance and effector function. These include molecules like CD72 and GPR18 that are known to enhance T cell proliferation and maintenance of mucosal T cell subsets, respectively (Jiang et al., 2017; Wang et al., 2014) (
[0211] The recovery of paired TCR sequences from individual single cells enabled us to link transcriptome data to clonotype information and evaluate the clonal relationship between different CD4+ T cell subsets as well as determine the nature of subsets that display greatest clonal expansion. In SARS-CoV-2 infection, hospitalized patients were characterized by large clonal expansion of the virus-reactive CD4+ T cells (mean of 55.8%); in contrast, in non-hospitalized patients, recovered TCRs were less clonally expanded (mean of 38.0%) (
[0212] Initial reports in patients with acute COVID-19 have suggested that circulating T cells that express activation markers such as CD38, HLA-DR, and PD-1 ex vivo (without in vitro peptide stimulation) are enriched for SARS-CoV-2-reactive T cells (Braun et al., 2020; Thevarajan et al., 2020). However, a recent study indicated that bystander T cells reactive to other antigens (e.g., CMV and EBV) can also express these activation markers, likely to be non-specifically activated without TCR engagement (Sekine et al., 2020). Thus, studies in active SARS-CoV-2 infection that just examine T cells expressing activation markers are not likely to reveal the full potential effector function of SARS-CoV-2-reactive T cells. To determine the specificity and molecular features of such T cells expressing activation markers ex vivo, we isolated CD38high HLA-DRhigh PD-1+ memory CD4+ T cells from hospitalized COVID-19 patients and performed single-cell transcriptome and TCR sequence analysis of >20,000 cells. CD4+ T cells expressing activation markers ex vivo clustered distinctly from the SARS-CoV-2-reactive CD4+ T cells, which were isolated following in vitro stimulation with SARS-CoV-2 peptides for 6 h (
Example 11: SARS-CoV-2-Reactive T.SUB.REG .Cells are Reduced in Hospitalized COVID-19 Patients
[0213] In order to capture SARS-CoV-2-reactive CD4+ T cells that may not upregulate the activation markers (CD154 and CD69) after 6 h of in vitro stimulation with SARS-CoV-2 peptide pools, we stimulated PMBCs from the same cultures for a total of 24 h (see STAR Methods) and captured cells based on co-expression of activation markers CD137 (4-1BB) and CD69, a strategy that allowed us to additionally capture antigen-specific regulatory T cells (T.sub.REG) (Bacher et al., 2016) (
[0214] The largest cluster (cluster A) was characterized by high expression of FOXP3 transcripts, which encodes for the T.sub.REG master transcription factor forkhead box P3 (FOXP3) (Rudensky, 2011) (
[0215] Correlation analysis of the proportion of CD4-CTLs and T.sub.REG in our 24 h dataset revealed a significant negative correlation, which indicated that patients with an impaired T.sub.REG response to SARS-CoV-2 mounted a stronger CD4-CTL response (
Example 12: Experimental Model and Subject Details (Used in Examples 7-11) COVID-19 Patients and Samples
[0216] Ethical approval for this study from the Berkshire Research Ethics Committee 20/SC/0155 and the Ethics Committee of La Jolla Institute for Immunology (LJI) was in place. Written consent was obtained from all subjects. 22 hospitalized patients in a large teaching hospital in the south of England with SARS-CoV-2 infection, confirmed by reverse transcriptase polymerase chain reaction (RT-PCR) assay for detecting SARS-CoV-2, between April-May 2020 were recruited to the study. A further cohort of 18 participants consisting of healthcare workers who were not hospitalized with COVID-19 illness, confirmed based on RT-PCR assay or serological evidence of SARS-CoV-2 antibodies, were also recruited over the same period. All subjects provided up to 80 mL of blood for research studies. Clinical and demographic data were collected from patient records for hospitalized patients including comorbidities, blood results, drug intervention, radiological involvement, thrombotic events, microbiology, and virology results. The 22 hospitalized patients had a median age of 60 (33-82), 17 of these patients (77%) were men and this cohort consisted of 16 (73%) White British/White Other, 4 (18%) Indian, and 2 (9%) Black British patients. All hospitalized patients survived to discharge from hospital. All hospitalized patients were still symptomatic at time of blood collection, whereas some of the non-hospitalized patients (4/18) were symptom free. The 18 non-hospitalized participants had a median age of 39 (22-50), 8 (44%) of these participants were men and this cohort consisted of 15 (83%) White British/White Other, 2 (11%) Arab, and 1 (6%) Chinese participant. We noted that the median age of the non-hospitalized patients was lower than the hospitalized COVID-19 patients.
Healthy Controls
[0217] To study HPIV, HMPV, and SARS-CoV-2-reactive CD4+ T cells from healthy non-exposed subjects (pre-COVID-19 pandemic), we utilized de-identified buffy coat samples from 5 healthy adult donors who donated blood at the San Diego Blood Bank before 2019, prior to the Covid-19 pandemic. Donors were considered to be in good health, free of cold or flu-like symptoms and with no history of Hepatitis B or Hepatitis C infection. The median age was 50 (32-71) and 4 of these patients (80%) were men. To study FLU-reactive cells, we obtained de-identified blood samples from 8 donors enrolled in the LJI Normal Blood Donor Program before and/or after (12-14 days) receiving the FLUCELVAX vaccine (September and October 2019). The median age was 37 (26-57) and 5 of these patients (63%) were women. Approval for the use of this material was obtained from the LJI Ethics Committee.
Method Details
PBMC Processing
[0218] Peripheral blood mononuclear cells (PBMCs) were isolated from up to 80 ml of anti-coagulated blood by density centrifugation over Lymphoprep (Axis-Shield PoC AS, Oslo, Norway) and cryopreserved in 50% decomplemented human antibody serum, 40% complete RMPI 1640 medium and 10% DMSO.
SARS-CoV-2 Peptide Pools
[0219] Pools of lyophilized peptides covering the immunodominant sequence of the spike glycoprotein and the complete sequence of the membrane glycoprotein of SARS-CoV-2 (15-mer sequences with 11 amino acids overlap) were obtained from Miltenyi Biotec (Thieme et al., 2020) resuspended and stored according to the manufacturer's instructions.
SARS-CoV-2 Antibody Testing
[0220] The LIAISON SARS-CoV-2 S1/S2 IgG (DiaSorin S.p.A., Saluggia, Italy) was utilized as per the manufacturer's instructions to obtain quantitative antibody results from plasma samples via an indirect chemiluminescence immunoassay (CLIA) in a United Kingdom Accreditation Service (UKAS) diagnostic laboratory at University Hospital Southampton. Sample results were interpreted as positive (R 15 AU/mL), Equivocal (R 12.0 and <15.0 AU/mL) and negative (<12 AU/mL).
SARS-CoV-2 Spike Protein-Specific B Cell Responses
[0221] To assess the level of SARS-CoV-2 S1/S2-specific B cells, cells were prepared in staining buffer (PBS with 2% FBS and 2 mMEDTA), FcgR blocked (clone 2.4G2, BD Biosciences), stained with indicated primary antibodies and biotinylated S1/S2 proteins (Sino Biological) for 30 min at 4_C; washed, and subsequently stained with streptavidin-BV421. Patients 10, 24 and 49 were analyzed on a different day with a lower intensity violet laser and required different gating.
Epitope Megapool to Peptide (MP) Design
[0222] The Human Parainfluenza (HPIV) and Metapneumovirus (HMPV) CD4+ T cell peptide megapools (MPs) were produced by sequential lyophilization of viral-specific epitopes as previously described (Carrasco Pro et al., 2015, Weiskopf et al., 2015b). T cell prediction was performed using TepiTool tool, available in identification epitope database analysis resources (IEDB-AR, LI), applying the 7-allele prediction method and a median cutoff %20 (Dhanda et al., 2019, Paul et al., 2015, Paul et al., 2016). For the HA-influenza MP, we selected 177 experimentally defined epitopes, retrieved by querying the IEDB database (www.IEDB.org) on 07/12/19 with search parameters positive assay only, No B cell assays, No MHC ligand assay, Host: Homo sapiens and MHC restriction class II. The list of epitopes was enriched with predicted peptides derived from the HA sequences of the vaccine strains available in 2017-2018 and 2018-2019 (A/Michigan/45/2015(H1N1), B/Brisbane/60/2008, A/Hong_Kong/4801/2014(H3N2), A/Michigan/45/2015(H1N1), A/Alaska/06/2016(H3N2), B/Iowa/06/2017, and B/Phuket/3073/2013). The resulting peptides were then clustered using the IEDB cluster 2.0 tool and the IEDB recommended method (cluster-break method) with a 70% cut off for sequence identity applied (Dhanda et al., 2019, Dhanda et al., 2018) (Table SlE). Peptides were synthesized as crude material (A&A, San Diego, CA), resuspended in DMSO, pooled according to each MP composition and finally sequentially lyophilized (Carrasco Pro et al., 2015). For screening healthy non-exposed subjects (samples provided before the current pandemic) who cross-react to SARS-CoV-2, we screened 20 healthy non-exposed subjects using SARS-CoV-2 peptide CD4-R and CD4-S pools, as described (Grifoni et al., 2020).
Antigen-Reactive T Cell Enrichment (ARTE) Assay
[0223] Enrichment and FACS sorting of virus-reactive CD154+ CD4+ memory T cells following peptide pool stimulation was adapted from Bacher et al. 2016 (Bacher et al., 2016). Briefly, PBMCs from each donor, were thawed, washed, plated in 24-well culture plates at a concentration of 5 3 106 cells/mL in 1 mL of serum-free TexMACS medium (Miltenyi Biotec) and left overnight (5% CO2, 37_C). Cells were stimulated by the addition of individual virus-specific peptide pools (1 mg/mL) for 6 h in the presence of a blocking CD40 antibody (1 mg/mL; Miltenyi Biotec). For subsequent MACS-based enrichment of CD154+, cells were sequentially stained with fluorescence-labeled surface antibodies (antibody list in Table SIG), Cell-hashtag TotalSeq-C antibody (0.5 mg/condition), and a biotin conjugated CD154 antibody (clone 5C8; Miltenyi Biotec) followed by anti-biotin microbeads (Miltenyi Biotec). Labeled cells were added to MS columns (Miltenyi Biotec) and positively selected cells (CD154+) were eluted and used for FACS sorting of CD154+ memory CD4+ T cells. The flow-through from the column was collected and re-plated to harvest cells responding 24 h after peptide stimulation. Analogous to enrichment for CD154+, CD137-expressing CD4+ memory T cells were positively selected by staining with biotin-conjugated CD137 antibody (clone REA765; Miltenyi Biotec) followed by anti-biotin MicroBeads and applied to a new MS column. Following elution, enriched populations were immediately sorted using a FACSAria Fusion Cell Sorter (Becton Dickinson) based on dual expression of CD154 and CD69 for the 6 h stimulation condition, and CD137 and CD69 for the 24 h stimulation condition. The gating strategy used for sorting is shown in
Cell Isolation and Single-Cell RNA-Seq Assay (10 Platform)
[0224] For combined single-cell RNA-seq and TCR-seq assays (10 Genomics), a maximum of 60,000 virus-reactive memory CD4+ T cells from up to 8 donors were pooled by sorting into low retention 1.5 mL collection tubes, containing 500 ml of a 1:1 solution of PBS:FBS supplemented with recombinant RNase inhibitor (1:100, Takara). For healthy donors, when possible, equal numbers of cells were isolated from each donor and pooled before 10 Genomics single-cell RNA-seq experiments. For analysis of FLU-reactive CD4+ T cell responses, we sequenced paired pre- and post-vaccination samples from 4 donors and supplemented this with 2 non-paired samples for both pre- and post-vaccination. Samples from both pre- and post-vaccination were pooled for analysis of FLU-reactive CD4+ T cells. Following sorting, ice-cold PBS was added to make up to a volume of 1400 ml. Cells were then centrifuged for 5 min (600 g at 4_C) and the supernatant was carefully removed leaving 5 to 10 ml. 25 ml of resuspension buffer (0.22 mm filtered ice-cold PBS supplemented with ultra-pure bovine serum albumin; 0.04%, Sigma-Aldrich) was added to the tube and the pellet was gently but thoroughly resuspended. Following careful mixing, 33 ml of the cell suspension was transferred to a PCR-tube for processing as per the manufacturer's instructions (10 Genomics). Briefly, single-cell RNA-sequencing library preparation was performed as per the manufacturer's recommendations for the 10 Genomics 5 TAG v1.0 chemistry with immune profiling and cell surface protein technology. Both initial amplification of cDNA and library preparation were carried out with 13 cycles of amplification; V(D)J and cell surface protein libraries were generated corresponding to each 5 TAG gene expression library using 9 cycles and 8 cycles of amplification, respectively. Libraries were quantified and pooled according to equivalent molar concentrations and sequenced on Illumina NovaSeq6000 sequencing platform with the following read lengths: read 1-101 cycles; read 2-101 cycles; and i7 index8 cycles.
Single-Cell Transcriptome Analysis
[0225] Reads from single-cell RNA-seq were aligned and collapsed into Unique Molecular Identifiers (UMI) counts using 10 Genomics' Cell Ranger software (v3.1.0) and mapped to GRCh37 reference (v3.0.0) genome. Hashtag UMI counts for each TotalSeq-C antibody capture library were generated with the Feature Barcoding Analysis pipeline from Cell Ranger. To demultiplex donors, UMI counts of cell barcodes were first obtained from the raw data output, and only cells with at least 100 UMI for the hashtag with the highest UMI counts were considered for donor assignment. Donor identities were inferred by MULTIseqDemux (autoThresh=TRUE and maxiter=10) from Seurat (v3.1.5) using the UMI counts. Each cell barcode was assigned a donor ID, marked as a Doublet or having a Negative enrichment. Cells were re-classified as doublets if the ratio of UMI counts between the top 2 barcodes was less than 3. Cells labeled as Doublet or Negative were removed from downstream analyses. Raw 10 data were independently aggregated using Cell Ranger's aggr function (v3.1.0). Donors P28 and P48 were not stained with hashtag antibodies and therefore did not contribute to any donor specific data. The merged data was transferred to the R statistical environment for analysis using the package Seurat (v3.1.5) (Stuart et al., 2019). To further minimize doublets and to eliminate cells with low quality transcriptomes, cells expressing <800 and >4400 unique genes, <1500 and >20,000 total UMI content, and >10% of mitochondrial UMIs were excluded. The summary statistics for all the single-cell transcriptome libraries are provided in Table S2C-E and indicate good quality data with no major differences in quality control metrics across multiple batches, where batches are groups of donors whose libraries were sequenced together (
[0226] For single-cell transcriptome analysis only genes expressed in at least 0.1% of the cells were included. The transcriptome data was then log-transformed and normalized (by a factor of 10,000) per cell, using default settings in Seurat software (Stuart et al., 2019). Variable genes with a mean UMI expression greater than 0.01 and explaining 25% of the total variance were selected using the Variance Stabilizing Transformation method, as described (Stuart et al., 2019). Transcriptomic data from each cell was then further scaled by regressing the number of UMI-detected and percentage of mitochondrial counts. For data from CD4+ T cells stimulated for 6 h, principal component analysis was performed using the variable genes, and based on the standard deviation of PCs in the elbow plot, the first 38 principal components (PCs) were selected for further analyses. Cells were clustered using the Find Neighbors and Find Clusters functions in Seurat with a resolution of 0.6. The robustness of clustering was independently verified by other clustering methods and by modifying the number of PCs and variable genes utilized for clustering. Analysis of clustering patterns across multiple batches revealed no evidence of strong batch effects (
Single-Cell Differential Gene Expression Analysis
[0227] Pairwise single-cell differential gene expression analysis was performed using the MAST package in R (v1.8.2) (Finak et al., 2015) after conversion of data to log 2 counts per million (log 2(CPM+1)). A gene was considered differentially expressed when Benjamini-Hochberg adjusted P-value was <0.05 and a log 2 fold change was more than 0.25. For finding cluster markers (transcripts enriched in a given cluster) the function FindAllMarkers from Seurat was used.
Gene Set Enrichment Analysis and Signature Module Scores
[0228] GSEA scores were calculated with the package fgsea in R using the signal-to-noise ratio (or the log 2 fold change for cluster 5 versus cluster 0 comparison) as a metric. Gene sets were limited by minSize=3 and maxSize=500. Normalized enrichment scores were presented as GSEA plots. Signature module scores were calculated with AddModuleScore function, using default settings in Seurat. Briefly, for each cell, the score is defined by the mean of the signature gene list after the mean expression of an aggregate of control gene lists is subtracted. Control gene lists were sampled (same size as the signature list) from bins created based on the level of expression of the signature gene list. Gene lists used for analysis are provided in Table S2H
Single-Cell Trajectory Analysis
[0229] The branched trajectory was constructed using Monocle 3 (v0.2.1, default settings) (Trapnell et al., 2014) with the number of UMI, percentage of mitochondrial UMI as the model formula and including the highly variable genes from Seurat for consistency. After setting a single partition for all cells, the cell-trajectory was projected on the PCA and UMAP generated from Seurat analysis. The root was selected by the get_earliest_principal_node function provided in the package. Monocle 3 alpha was used to analyze cluster 0 and 5 using the DDRTree algorithm for dimensional reduction after selecting the top 500 highly variable genes with Seurat.
T Cell Receptor (TCR) Sequence Analysis
[0230] Reads from single-cell V(D)J TCR sequence enriched libraries (Table S2D) were processed with the vdj pipeline from Cell Ranger (v3.1.0 and human annotations reference GRCh38, v3.1.0, as recommended). In brief, the V(D)J transcripts were assembled and their annotations were obtained for each independent library. In order to perform combined analysis of single-cell transcriptome and TCR sequence from the same cells, V(D)J libraries were first aggregated using a custom script. Then cell barcode suffixes from these libraries were revised according to the order of their gene expression libraries. Unique clonotypes, as defined by 10 Genomics as a set of productive Complementarity-Determining Region 3 (CDR3) sequences, were identified across all library files and their frequency and proportion (clone statistics) were calculated based on the aggregation result considering only the cells present in the gene expression libraries. This procedure was independently applied for data from CD4+ T cells stimulated for 6 and 24 h. Based on the vdj aggregation files, barcodes captured by our gene expression data and previously filtered to keep only good-quality cells, were annotated with a specific clonotype ID alongside their clone size (number of cells with the same clonotypes in either one or both the TCR alpha and beta chains) and other statistics (Table S4A,B,E and F). Cells that share clonotype with more than 1 cell were called as clonally expanded (clone size >2). Clone size for each cell was visualized on UMAP, depicting only SARS-CoV-2-reactive CD4+ T cells. Sharing of clonotype between cells in different clusters was depicted using the tool UpSetR (Conway et al., 2017). Finally, in order to assess the sharing between the 0- and 6 h datasets, the same aggregation process was applied for all of the vdj libraries from these data and only SARS-CoV-2-reactive CD4+ T cells specifically isolated from matched patients between sets were considered.
Quantification and Statistical Analysis
[0231] Processing of data, applied methods and codes are described in the respective section in the STAR Methods. The number of subjects, samples, replicates analyzed, and the statistical test performed are indicated in the figure legends or STAR methods. Statistical analysis for comparison between two groups were assessed with Mann Whitney U test and correlation assessed with spearman test with using GraphPad Prism.