METHOD AND KIT FOR HBV-HOST JUNCTION SEQUENCE IDENTIFICATION, AND USE THEREOF IN HEPATOCELLULAR CARCINOMA CHARACTERIZATION
20210017611 ยท 2021-01-21
Assignee
Inventors
Cpc classification
C12Q2537/143
CHEMISTRY; METALLURGY
C12Q2537/143
CHEMISTRY; METALLURGY
International classification
Abstract
A method and a kit for identifying HBV-host junction sequences (HBV-JSs) from a biological sample are provided. The method includes: preparing a DNA sample (e.g. DNA library) and performing at least one round of enrichment. Each round of enrichment includes a sub-step of capturing HBV DNA sequence-containing DNA molecules from the DNA sample by means of an HBV probe set, which includes a plurality of elaborately designed HBV primers configured to selectively and respectively target different regions of an HBV genome, and each HBV primer is labelled with an immobilization portion such as biotin moiety so as to allow immobilization onto a solid support such as magnetic beads. The method and kit can be used for non-invasively detecting HBV-JSs using a urine sample and other body fluids. The information of the HBV-JSs can be further utilized in the screening, diagnosis, prognosis and management of HBV-associated HCC.
Claims
1. A method for identifying at least one HBV-host junction sequence (HBV-JS) from a biological sample of a subject, comprising: preparing a DNA sample from the biological sample; performing at least one round of enrichment over the DNA sample, each round comprising: capturing, by means of an HBV probe set, HBV DNA sequence-containing DNA molecules from the DNA sample, wherein the HBV probe set comprises a plurality of HBV primers having sequences thereof selectively and respectively corresponding to different regions of an HBV genome, and each labelled with an immobilization portion configured to allow immobilization onto a solid support.
2. The method of claim 1, wherein the capturing, by means of an HBV probe set, HBV DNA sequence-containing DNA molecules from the DNA sample is through a primer extension capture assay, comprising: denaturing the DNA sample to thereby obtain a denatured DNA sample; contacting the plurality of HBV primers with the denatured DNA sample for annealing; performing a primer extension reaction; immobilizing the DNA molecules captured by the plurality of HBV primers; and eluting the DNA molecules.
3. The method of claim 1, wherein each of the at least one round of enrichment further comprises: amplifying the DNA molecules.
4. The method of claim 1, wherein each of the plurality of HBV primers comprises a sequence selected from a group consisting of SEQ ID NOS: 49-175.
5. The method of claim 1, wherein the preparing a DNA sample from the biological sample comprises: constructing a DNA library from the biological sample.
6. The method of claim 5, wherein the DNA library is an ssDNA library.
7. The method of claim 1, wherein a number of the at least one round of enrichment is more than one.
8. The method of claim 1, wherein the biological sample is a body fluid sample.
9. The method of claim 8, wherein the biological sample is a urine sample.
10. The method of claim 1, wherein in the preparing a DNA sample from the biological sample, each DNA molecule obtained thereby comprises a pair of adaptors flanking a DNA fragment from the subject, wherein in the capturing, by means of an HBV probe set, HBV DNA sequence-containing DNA molecules from the DNA sample, the DNA molecules are captured in presence of at least one adaptor blocker configured to hybridize with sequences corresponding to the pair of adaptors in the each DNA molecule so as to minimize off-target capture.
11. A kit for identifying at least one HBV-host junction sequence (HBV-JS) from a biological sample of a subject, comprising: an HBV probe set, comprising a plurality of HBV primers having sequences thereof selectively and respectively corresponding to different regions of an HBV genome, each labelled with an immobilization portion; and a solid support, conjugated with a coupling partner on a surface thereof, wherein the coupling partner is configured to form a secure coupling to the immobilization portion of each HBV primer to thereby allow immobilization of HBV DNA sequence-containing DNA molecules to the solid support.
12. The kit according to claim 11, wherein each of the plurality of HBV primers comprises a sequence selected from a group consisting of SEQ ID NOS: 49-175.
13. The kit according to claim 11, further comprising a pair of adaptors, configured to be ligated to two ends of each DNA molecule in the biological sample to thereby obtain a DNA library from the biological sample.
14. The kit according to claim 13, further comprising at least one adaptor blocker configured to hybridize with sequences corresponding to the pair of adaptors in the each DNA molecule in the DNA library so as to minimize off-target capture.
15. The kit according to claim 13, wherein the DNA library is a single-stranded DNA library.
16. The kit according to claim 11, further comprising at least one pair of amplifying primers, configured to amplify the HBV DNA sequence-containing DNA molecules.
17. The kit according to claim 11, wherein: the immobilization portion comprises a biotin moiety; and the coupling partner comprises at least one of streptavidin, avidin, or an anti-biotin antibody.
18. The kit according to claim 17, wherein the solid support comprises streptavidin magnetic beads.
19. The kit according to claim 11, further comprising a software for identifying the at least one HBV-JS from data obtained from a sequencing assay over the HBV DNA sequence-containing DNA molecules.
20. The method of claim 19, wherein the software is ChimericSeq.
Description
BRIEF DESCRIPTION OF THE DRAWINGS
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DETAILED DESCRIPTION OF THE INVENTION
[0082] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art pertinent to the methods and compositions described. As used herein, the following terms and phrases have the meanings ascribed to them unless specified otherwise.
[0083] Various embodiments will be described in detail through the displayed figures. Reference to these embodiments does not limit the scope of the claims attached hereto. Provided examples are not meant to limit the scope of methods and claims herein, but rather describe example uses of the embodiments of the claims.
[0084] The terms a, an, and the as used herein include plural referents, unless the context clearly indicates otherwise.
[0085] The term genome and genomic refer to any nucleic acid sequences (coding and non-coding) originating from any living or non-living organism or single-cell. These terms also apply to any naturally occurring variations that may arise through mutation or recombination through means of biological or artificial influence. An example is the human genome, which is composed of approximately 3109 base pairs of DNA packaged into chromosomes, of which there are 22 pairs of autosomes and 1 allosome pair.
[0086] The term nucleotide sequence as used herein indicates a polymer of repeating nucleic acids (Adenine, Guanine, Thymine, and Cytosine, and Uracil) that is capable of base-pairing with complement sequences through Watson-Crick interactions. This polymer may be produced synthetically or originate from a biological source.
[0087] The term nucleic acid refers to a deoxyribonucleotide (DNA) or ribonucleotide (RNA) and complements thereof. The size of nucleotides is expressed in base pairs bp. Polynucleotides are single- or double-stranded polymers of nucleic acids and complements thereof.
[0088] The term deoxyribonucleic acid and DNA refer to a polymer of repeating deoxyribonucleic acids.
[0089] The term ribonucleic acid and RNA refer to a polymer of repeating ribonucleic acids.
[0090] The term disease or disorder is used interchangeably herein, and refers to any alteration in state of the body or of some of the organs, interrupting or disturbing the performance of the functions and/or causing symptoms such as discomfort, dysfunction, distress, or even death to the person afflicted or those in contact with a person. A disease or disorder can also relate to a distemper, ailing, ailment, malady, disorder, sickness, illness, complaint, or affectation.
[0091] As used herein, cancer refers to any stage of abnormal growth or migration of cells or tissue, including precancerous and all stages of cancerous cells, including but not limited to adenomas, metaplasias, heteroplasias, dysplasias, neoplasias, hyperplasias, and anaplasias.
[0092] As used herein, cancer progression refers to any measure of cancer growth, development, and/or maturation including metastasis. Cancer progression includes increase in cell number, cell size, tumor size, and number of tumors, as well as morphological and other cellular and molecular changes and other characteristics. As an example, one measure of cancer progression is the use of staging characteristics. As an additional example, one measure of cancer progression is the use of detecting expression, whether at the protein or mRNA level, of certain genes
[0093] The term diagnosing means any method, determination, or indication that an abnormal or disease condition or phenotype is present. Diagnosing includes detecting the presence or absence of an abnormal or disease condition, and can be qualitative or quantitative.
[0094] The term gene is well known in the art, and herein includes non-coding region such as promoter or other regulatory sequences or proximal non-coding region.
[0095] The terms express and produce are used synonymously herein, and refer to the biosynthesis of a gene product. These terms encompass the transcription of a gene into RNA. These terms also encompass translation of RNA into one or more polypeptides, and further encompass all naturally occurring post-transcriptional and post-translational modifications. The expression/production of an antibody or antigen-binding fragment can be within the cytoplasm of the cell, and/or into the extracellular milieu such as the growth medium of a cell culture.
[0096] The term biomarker is an agent used as an indicator of a biological state. It can be a characteristic that is objectively measured and evaluated as an indicator of normal biological processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention. A biomarker can be a fragment of genomic DNA sequence that causes disease or is associated with susceptibility to disease, and may or may not comprise a gene.
[0097] The term low molecular weight or LMW nucleic acid refers a nucleic acid, such as DNA, of less than 1000 base pairs, usually less than 300 base pairs.
[0098] The term nucleotide amplification reaction refers to any suitable procedure that amplifies a specific region of polynucleotides (target) using primers.
[0099] A protein is a macromolecule comprising one or more polypeptide chains. A protein may also comprise non-peptidic components, such as carbohydrate groups. Carbohydrates and other non-peptidic substituents may be added to a protein by the cell in which the protein is produced, and will vary with the type of cell. Proteins are defined herein in terms of their amino acid backbone structures; substituents such as carbohydrate groups are generally not specified, but may be present nonetheless.
[0100] The terms amino-terminal and carboxyl-terminal are used herein to denote positions within polypeptides. Where the context allows, these terms are used with reference to a particular sequence or portion of a polypeptide to denote proximity or relative position. For example, a certain sequence positioned carboxyl-terminal to a reference sequence within a polypeptide is located proximal to the carboxyl terminus of the reference sequence, but is not necessarily at the carboxyl terminus of the complete polypeptide.
[0101] The term chimeric reads herein refers to a nucleotide sequence obtained from next generation sequencing, whereby the length of the read contains genomic material from two separate biological entities or chromosomes joined covalently through integration. For example, viruses can integrate viral nucleotide sequences into the genomic nucleotide sequence of a human host.
[0102] Throughout the disclosure, the terms probe set, probe panel, or alike, are considered to be exchangeable, and the term HBV primer mentioned in the HBV probe set is also considered to be exchangeable to HBV probe.
[0103] Due to the imprecision of standard analytical methods, molecular weights and lengths of polymers are understood to be approximate values. When such a value is expressed as about X or approximately X, the stated value of X will be understood to be accurate to 10%.
[0104] Provided herein include methods and kits that can provide a sensitive, specific, and noninvasive platform for detecting HBV-JS in circulating nucleic acid sequences from a biological sample including body fluid or HBV-infected liver tissue DNA. Any HBV-JS DNA found in cell-free DNA isolated from a patient's body fluid can be used because it is representative of liver-derived DNA. The methods use a biotinylated HBV primer extension to enrich for HBV sequences of library DNA. The enriched libraries were analyzed for HBV-JS by NGS. As shown in the following examples, the methods are useful for HCC screening and monitoring of HBV-infected individuals. This method is particularly useful for high-risk HCC individuals and individuals with occult HBV infection to undergo frequent noninvasive screening to monitor disease progression, as they are often asymptomatic.
[0105] The present disclosure features at least the following three components used in developing an integrative HBV-JS analysis platform. First, a biotinylated HBV primer extension enrichment was used to enrich DNA samples for HBV DNA sequences that may contain HBV-JSs. Second, the enriched libraries are amplified by primers targeting all DNA template and sequenced by Illumina next generation sequencing platform. Lastly, the NGS data can be analyzed by ChimericSeq for identifying HBV-JSs, where the analysis results were successfully confirmed for an 87% validation rate (13/15).
[0106] Throughout the disclosure, the term biological sample can be deemed to comprise a tissue sample, such as a biopsy sample or a tissue culture sample. A biological sample may as well comprises biological fluids (i.e. liquid sample) including, but not limited to, saliva, nasopharyngeal, blood, plasma, serum, gastrointestinal fluid, bile, cerebrospinal fluid, pericardial, vaginal fluid, seminal fluid, prostatic fluid, peritoneal fluid, pleural fluid, urine, synovial fluid, interstitial fluid, intracellular fluid or cytoplasm and lymph, bronchial secretions, mucus, or vitreous or aqueous humor. Biological samples can also include cultured medium. In certain embodiments, the preferred biological fluid is urine, and in such cases, the method disclosed in this present application can be used to non-invasively detect HBV-JSs for HCC screening, cancer progression, and for HBV-HCC disease monitoring.
[0107] In certain embodiments, the platform uses biological samples containing fragmented circulation derived DNA known as low molecular weight (LMW) DNA. The DNA is low molecule weight because it is generally less than 300 base pairs in size. This LMW DNA is released into circulation through necrosis or apoptosis by both normal and cancer cells. It has been shown that LWM DNA is excreted into the urine and can be used to detect tumor-derived DNA, provided a suitable assay, such as a short template assay for which detection is available (Su Y H et al. 2008).
[0108] The inventions disclosed herein have the advantage that the procedures provided are capable of screening for HBV-related hepatocellular carcinoma, where unique major HBV-JSs serve as a marker of uncontrolled clonal expansion.
[0109] The methods described herein can be used to determine the status of an existing disease identified in a subject. For example, 19 HCC, 21 hepatitis and 19 cirrhosis urine samples were evaluated for HBV-JSs, and all HCC urine samples with HBV-JSs contained only integrated HBV sequences in the DR1-2 region, a higher load of HBV-JS, and a reduced HBV-JS complexity compared to non-HCC patients. Thus, the HBV-JS load and HBV-JS species detected in urine can be used to screen for HBV-HCC and monitor HBV related disease.
[0110] The methods described herein can be used to identify subject patients for treatment and to determine risk factors associated with HBV-JSs. Such methods can include, for example, determining whether an individual has relatives who have been diagnosed with a particular disease. Screening methods can also include, for example, conventional work-ups to determine familial status for a particular disease known to have a heritable component. Screening may be implemented as indicated by known patient symptomology, age factors, related risk factors, etc. These methods allow the clinician to routinely select patients in need of the methods described herein for treatment. In accordance with these methods, screening may be implemented as an independent program or as a follow-up, adjunct, or to coordinate with other treatments. Thus, the methods of the present inventions can be used for cancer screening, particularly for early detection, monitoring of recurrence, disease management, and to develop a personalized medicine regime for a cancer patient.
[0111] It is to be understood that the above described embodiments are merely illustrative of numerous and varied other embodiments which may constitute applications of the principles of the inventions disclosed herein. Other embodiments may be readily devised by those skilled in the art without departing from the spirit or scope of this invention and they shall be deemed within the scope of the disclosure.
[0112] The inventions provided in the disclosure is further illustrated by the following non-limiting examples.
Example 1: Development of a Method for Detecting HBV-JSs and the Use of Major HBV-JSs in Urine as a Marker for HBV-HCC Screening and Uncontrolled Clonal Expansion
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[0114] In order to be able to reliably detect major HBV-JSs in urine samples, a biotinylated HBV primer extension enriched NGS assay was first developed. The following protocol was used: approximately 50-200 ng of tissue DNA was fragmented by sonication and subjected to NGS library DNA preparation as described by Ding et al. 2012 with minor modifications including 10 cycles of library DNA amplification (SEQ ID NO: 1, 2, 3) using Herculase II Fusion polymerase (Agilent Technologies, Santa Clara, Calif.). All the oligo sequences and reaction conditions for library preparation are listed in Table 1. To enrich for DNA that contains HBV DR1-2 DNA sequences, a multiplex biotin HBV primer extension reaction was performed using amplified library DNA in a reaction containing 1 Herculase II Buffer, 250 M dNTP, and 20 pmol of biotinylated HBV primers as listed in Table 2. The reaction was held at the condition of 95 C. 2 mins, then 55 C. for 5 hrs with rotation. After a 5 hr incubation, 0.2 l of heat inactivated Herculase II Fusion polymerase was added to each reaction and incubated at 55 C. for another 30 mins, followed by 72 C. for 90 s. The primer extended DNA was collected by using hydrophilic streptavidin magnetic beads (New England Biolabs, Ipswich, Mass.) as described by Gnirke et al. 2009 and used as the template in an indexing PCR (SEQ ID NO: 4 and 5) to add a unique barcode to each patient sample. Each indexed library was quantified and pooled accordingly for one NGS. NGS was performed to generate 150 bp paired-end reads on the Illumina MiSeq platform (Penn State Hershey Genomics Sciences Facility at Penn State College of Medicine, Hershey, Pa.). Sequences were analyzed using the ChimericSeq software to identify HBV-JSs.
TABLE-US-00001 TABLE1 OligosandreactionconditionsforthepreparationofHBVDR1-2enrichedlibraryDNA. Primer Primer Tm Name Length (C.) Sequence5-3 PCRconditions ModP_4F 22 65 CAAGCAGAAGACGGCA 95C.2mins,then95C. TAC*G*A(SEQIDNO:1) 20s,65C.20s,58C.30s, ModP_3R 20 66 AATGATACGGCGACCA 72C.20sfor10cycles, CC*G*A(SEQIDNO:2) and72C.3mins Ad-Ad 10 78 +g-A+T+C+T+g+A+T+C+ LNAclamp g-PH(SEQIDNO:3) Primer Primer Tm Name Barcode Length (C.) Sequence5-3 PCRconditions Indexed TATAGCCT 71 79 AATGATACGGCGACCA 95C.2mins,then95C. ATAGAGG 80 CCGAGATCTACACTANN 20s,60C.60s,72C.20s C NNNNNNacactctaccctacacg for8cycles,and72C.3 CCTATCCT 80 acgctcttccgatc(SEQIDNO: mins. GGCTCTGA 81 4) AGGCGAA 81 G GTACTGAC 80 Mod 24 67 CAAGCAGAAGACGGCA P_R TACGAG*A*T(SEQID NO:5) +denotes a modified locked nucleic acid nucleotide. -PH denotes a 3phosphorylation of the oligo. *denotes a phosphorothioate bond to prevent excision from the 3-5exonuclease activity. Lower case sequences denote a 32 bp overlapping sequence between the HBV DR1-2 enrichment and indexing primers. Rbase denotes degenerate nucleotides containing A and G nucleotides. Ndenotes the designated sequence of the i5 barcode.
TABLE-US-00002 TABLE2 5BiotinylatedHBVprimersinanHBVprobepanel. Primer Primer Tm Name Region Length (C.) Sequence5-3* 1 3-34 30 68-71 ACAACATTCCACCAARCTCTKCTAGATCCC(SEQIDNO:6) 2 95-126 39 70 AAGATTGACGATATGGWTGAGGCAGTAGTCGGAACAGGG (SEQIDNO:7) 3 201-240 40 73 GGTATTGTGAGGATTTTTGTCAACAAGAAAAACCCCGCCT (SEQIDNO:8) 4 270-299 29 70-72 GACACACGGGTGYTCCCCCTAGAAAATTG(SEQIDNO:9) 5 382-356 30 69-74 ACACATCCAGCGATARCCAGGACAAYTRGG(SEQID NO:10) 6 456-486 30 69-70 AGGTATGTTGCCCGTTTGTCCTCTAMTTCC(SEQIDNO:11) 7 570-597 27 67-69 TACAAAACCTWCGGACGGAAAYTGCAC(SEQIDNO:12) 8 605-635 30 72-74 CCCATCCCATCATCYTGGGCTTTCGCAARA(SEQIDNO:13) 9 693-725 31 74 AAACAGTGGGGGAAAGCCCTACGAACCACTG(SEQID NO:14) 10 749-780 31 72 GGTACTGGGGGCCAAGTCTGTACAACATCTT(SEQID NO:15) 11 781-810 40 71 GAGTCCCTTTATRCCGCTRTTACCAATTTTCTTTTGTCTT (SEQIDNO:16) 12 871-900 35 69 CCCTTAACTTCATGGGATATGTAATTGGRAGTTGG(SEQID NO:17) 13 951-980 40 69-72 TTCCAATCAATAGGYCTGTTTACAGGCAGTTTCCKAAAAC (SEQIDNO:18) 14 1033-1077 45 69 CAATGTGGMTATCCTGCTTTRATGCCTTTATATGCATGTAT ACAA(SEQIDNO:19) 15 1101-1130 30 69 TGTTTACACAGAAAGGCCTTGTAAGTTGGC(SEQIDNO:20) 16 1183-1212 30 80 GCCCCAACCCGTGGGGGTTGCGTCAGCAAA(SEQID NO:21) 17 1261-1290 30 73-75 AGCKGCTAGGAGTTCCGCAGTATGGATCGG(SEQID NO:22) 18 1342-1371 30 71 GTTGTCCTCTCTCGGAAATACACCGCCTTT(SEQIDNO:23) 19 1395-1424 30 76 CAACTGGATCCTGCGCGGGACGTCCTTTGT(SEQIDNO:24) 20 1513-1542 30 79 CCGACCACGGGGCGCACCTCTCTTTACGCG(SEQIDNO:25) 21 1575-1604 30 76 ACGTGCAGAGGTGAAGCGAAGTGCACACGG(SEQID NO:26) 22 1613-1629 17 67 GACCACCGTGAACGCCC(SEQIDNO:27) 23 1633-1653 21 64 AGGTCTTGCCCAAGGTCTTAC(SEQIDNO:28) 24 1650-1671 22 65 TTGCACAACAGGACTCTTGGAC(SEQIDNO:29) 25 1685-1719 25 68 AACGACCGACCTTGAGGCATACTTC(SEQIDNO:30) 26 1691-1720 31 69 CCGACCTTGAGGCATACTTCAAAGACTGTTT(SEQID NO:31) 27 1737-1754 17 56-60 GAGTTRGGGGAGGAGAT(SEQIDNO:32) 28 1741-167 26 64-67 TRGGGGAGGAGATAAGGTTAAAGGTC(SEQIDNO:33) 29 1828-1862 35 70 CCTCTGCCTAATCATCTCATGTTCATGTCCTACTG(SEQID NO:34) 30 1896-1930 35 71-72 GGGGCATGGACATTGACCCSTATAAAGAATTTGGA(SEQ IDNO:35) 31 1997-2026 30 75 ACCGCCTCTGCTCTGTATCGGGAGGCCTTA(SEQIDNO:36) 32 2081-2110 30 71-73 TGTTGGGGTGAGTTGATGAATCTRGCCACC(SEQIDNO:37) 33 2146-2190 45 70 ATTTTTAGGCCCATATTAACRTTGACATAGCTGACTACTAA TTCC(SEQIDNO:38) 34 2221-2260 40 67-70 CACCAAATAYTCAAGRACAGTTTCTCTTCCAAAAGTAAGR (SEQIDNO:39) 35 2305-2340 36 70 GTAGTTTCCGGAAGTGTTGATAAGATAGGGGCATTT(SEQ IDNO:40) 36 2380-2409 30 75 TCCCTCGCCTCGCAGACGAAGGTCTCAATC(SEQIDNO:41) 37 2466-2502 37 69 TAGAAGAATAAAGCCCAGTAAAGTTTCCCACCTTATG (SEQIDNO:42) 38 2541-2580 40 66-69 TTTCCTSACATTCATCTACAGGAGGACATTRTTRATAGAT (SEQIDNO:43) 39 2697-2740 44 70-72 CCGTATTATCCWGARCATGCAGTTAATCATTACTTCAAAA CTAG(SEQIDNO:44) 40 2783-2812 30 68-72 CAAAATGAGGCGCTRCGTGTAGTYTCTCTY(SEQIDNO:45) 41 2851-2880 30 73 GGAGGTTGGTCTTCCAAACCTCGACAAGGC(SEQIDNO:46) 42 2931-2960 30 72-76 CCAGTTGGACCCTGCRTTCRRAGCCAACTC(SEQIDNO:47) 43 3181-3215 24 70 TCATCCTCAGGCCATGCAGTGGAA(SEQIDNO:48) *All primers are labelled with a 5biotin modification. Rbase denotes redundant A +G base. Ybase denotes redundant C +T base. Wbase denotes redundant A +T base. Sbase denotes C +G base.
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[0116] Using the above developed approach, detection of major HBV-JSs derived from HBV-HCC tissue in matched tissue and urine samples was carried out.
[0117] Furthermore, the urine samples of HBV-infected patients are tested for the detection of HBV-JSs.
[0118] In order to be able to efficiently detect chimeric reads in the nucleotide sequence data, a software package ChimericSeq is developed.
[0119] In order to evaluate the detection efficiency of integration events with defined lengths of HBV insert, random HBV fragments of specified lengths (0-100 bp) were joined to random human genomic DNA of 100 bp. As shown in
[0120] A primer extension capture (PEC) approach for the HBV enrichment has been developed, whose schematic for only one target HBV-host junction sequence (HBV-JS, i.e. a chimeric DNA sequence containing a human genomic DNA and an integrated HBV DNA fragment) is illustrated in
[0121] It is noted that
[0122] With a purpose to provide a broader coverage, an optimized probe panel is further developed, which includes a total of 127 probes (Table 3) covering the most frequent four genotypes (A-D) of HBV and covering the entire HBV genome, is further developed. Briefly, to design an HBV probe panel with high specificity and sensitivity for application in an HBV primer-extension capture (PEC) approach, a human micro-homology analysis was first performed to identify regions within the HBV genome that are highly homologous to the human genome. The analysis was done by performing an NCBI BLAST query to the human genome for every 50 bp increments of HBV DNA along the entire 3.2 kb genome. The analysis uncovered 142 human micro-homologous stretches of HBV DNA ranging from 10-30 bp (average size of 19.6 bp) with melting temperatures (Tm) as high as 65 C. A total of 127 HBV probes were next designed to target the antisense strand along the entire HBV genome for genotypes A-D that avoided these human micro-homologous stretches. When it was not possible to avoid human micro-homologous stretches containing a Tm of 55 C. or less, the HBV primer was designed to target the HBV sense strand to ensure full HBV genome coverage during the enrichment.
TABLE-US-00003 TABLE3 PrimerlistsintheoptimizedHBVprobepanel. Primer Primer Name Region Sequence SEQIDNOS 1 3-34F ACAACATTCCACCAARCTCTKCTAGATCCC SEQIDNO:49 2 95-126R AAGATTGACGATATGGWTGAGGCAGTAGTCGGAACAG SEQIDNO:50 GG 3 201-240R GGTATTGTGAGGATTTTTGTCAACAAGAAAAACCCCGC SEQIDNO:51 CT 4 270-299R GACACACGGGTGYTCCCCCTAGAAAATTG SEQIDNO:52 5 382-356R ACACATCCAGCGATARCCAGGACAAYTRGG SEQIDNO:53 6 456-486F AGGTATGTTGCCCGTTTGTCCTCTAMTTCC SEQIDNO:54 7 570-597F TACAAAACCTWCGGACGGAAAYTGCAC SEQIDNO:55 8 605-635F CCCATCCCATCATCYTGGGCTTTCGCAARA SEQIDNO:56 9 693-725R AAACAGTGGGGGAAAGCCCTACGAACCACTG SEQIDNO:57 10 749-780F GGTACTGGGGGCCAAGTCTGTACAACATCTT SEQIDNO:58 11 781-810F GAGTCCCTTTATRCCGCTRTTACCAATTTTCTTTTGTCTT SEQIDNO:59 12 871-900F CCCTTAACTTCATGGGATATGTAATTGGRAGTTGG SEQIDNO:60 13 951-980R TTCCAATCAATAGGYCTGTTTACAGGCAGTTTCCKAAA SEQIDNO:61 AC 14 1033-1077F CAATGTGGMTATCCTGCTTTRATGCCTTTATATGCATGT SEQIDNO:62 ATACAA 15 1101-1130R TGTTTACACAGAAAGGCCTTGTAAGTTGGC SEQIDNO:63 16 1183-1212R GCCCCAACCCGTGGGGGTTGCGTCAGCAAA SEQIDNO:64 17 1261-1290R AGCKGCTAGGAGTTCCGCAGTATGGATCGG SEQIDNO:65 18 1342-1371F GTTGTCCTCTCTCGGAAATACACCGCCTTT SEQIDNO:66 19 1395-1424F CAACTGGATCCTGCGCGGGACGTCCTTTGT SEQIDNO:67 20 1513-1542F CCGACCACGGGGCGCACCTCTCTTTACGCG SEQIDNO:68 21 1575-1604R ACGTGCAGAGGTGAAGCGAAGTGCACACGG SEQIDNO:69 22 1613-1629F GACCACCGTGAACGCCC SEQIDNO:70 23 1633-1653F AGGTCTTGCCCAAGGTCTTAC SEQIDNO:71 24 1650-1671F TTGCACAACAGGACTCTTGGAC SEQIDNO:72 25 1686-1709F AACGACCCGACCTTGAGGCATACTTC SEQIDNO:73 26 1741-1767F TRGGGGAGGAGATAAGGTTAAAGGTC SEQIDNO:74 27 HBV_F_1650_ TTACATAAGAGGACTCTTGGAC SEQIDNO:75 1672_1 28 HBV_F_1741_ TRGGGGAGGAGATTAGGTTAAAGGTC SEQIDNO:76 1767_1 29 HBV_F_1741_ TGGGGGAGGAGATTAGGTTAATGATC SEQIDNO:77 1767_DM 30 1828-1862F CCTCTGCCTAATCATCTCATGTTCATGTCCTACTG SEQIDNO:78 31 1896-1930F GGGGCATGGACATTGACCCSTATAAAGAATTTGGA SEQIDNO:79 32 1997-2026F ACCGCCTCTGCTCTGTATCGGGAGGCCTTA SEQIDNO:80 33 2081-2110F TGTTGGGGTGAGTTGATGAATCTRGCCACC SEQIDNO:81 34 2146-2190R ATTTTTAGGCCCATATTAACRTTGACATAGCTGACTACT SEQIDNO:82 AATTCC 35 2221-2260R CACCAAATAYTCAAGRACAGTTTCTCTTCCAAAAGTAA SEQIDNO:83 GR 36 2305-2340R GTAGTTTCCGGAAGTGTTGATAAGATAGGGGCATTT SEQIDNO:84 37 2380-2409F TCCCTCGCCTCGCAGACGAAGGTCTCAATC SEQIDNO:85 38 2466-2502R TAGAAGAATAAAGCCCAGTAAAGTTTCCCACCTTATG SEQIDNO:86 39 2541-2580F TTTCCTSACATTCATCTACAGGAGGACATTRTTRATAGA SEQIDNO:87 T 40 2697-2740F CCGTATTATCCWGARCATGCAGTTAATCATTACTTCAA SEQIDNO:88 AACTAG 41 2783-2812R CAAAATGAGGCGCTRCGTGTAGTYTCTCTY SEQIDNO:89 42 2851-2880F GGAGGTTGGTCTTCCAAACCTCGACAAGGC SEQIDNO:90 43 2931-2960F CCAGTTGGACCCTGCRTTCRRAGCCAACTC SEQIDNO:91 44 3181-3215F TCATCCTCAGGCCATGCAGTGGAA SEQIDNO:92 45 HBV_2146_ AACTTTAGGCCCATATTAGTRTTGACATAGCTGACTACT SEQIDNO:93 2190_D_RC AGGTCY 46 HBV_95_126_ AAGATTGACGATATGGGAGAGGCAGTAGTCGGAACAG SEQIDNO:94 RC_C GG 47 HBV_95_126_ AAGATTGACGATATGGMAGAGGCAGTATTCTGARCAG SEQIDNO:95 RC_B GG 48 HBV_95_126_ AAGATTGACGATAWGGGAGAGGCAGTAGTCRGAACAG SEQIDNO:96 RC_A GG 49 HBV_3_34_A ACARCCTTCCACCAARCTCTKCAAGATCCC SEQIDNO:97 B_D 50 HBV_50_80_ TATTTYCCTGCTGGTGGCTCCAGTTCMGGAA SEQIDNO:98 All 51 HBV_340_ ACATCCAGCGATAACCAGGACAAGTTGGAGGACARGA SEQIDNO:99 380_RC_A_D GGTT 52 HBV_340_ ACATCCAGCGATARCCAGGACAARTTGGAGGACAASAG SEQIDNO:100 380_RC_B_C GTT 53 HBV_1997_ ACCGCCTCAGCTCTGTATCGGGAGGCCTTA SEQIDNO:101 2026_A_D 54 HBV_520_ AGAGGTTCCTTGAGCAGGAATCGTGCAGGTT SEQIDNO:102 550_All_RC 55 HBV_390_ AGCAGCAGGATGAAGAGGAAKATGATAAAAC SEQIDNO:103 420_RC_All 56 HBV_1220_ AGGAGCCACAAAGGTTCCACGCATGCGCYGATGGCCY SEQIDNO:104 1260_B_C_RC A 57 HBV_1220_ AGGAGCCASAAAGGTTCCACGCATGCGCCGATGGCCYA SEQIDNO:105 1260_A_D_RC 58 HBV_305_ AGTGACTGGAGATTTGGGACTGCGAATTTTG SEQIDNO:106 335_RC_B 59 HBV_305_ AGTGATTGGAGGTTGGGGACTGCGAATTTTG SEQIDNO:107 335_RC_A_D_ C 60 HBV_2146_ ATCTTTAGGCCCATATTAGTRTTGACATAGTTGACTACT SEQIDNO:108 2190_A_RC AGATCC 61 HBV_640_ ATGGGAGTGGGCCTCAGYCCGTTTCTCCTGGCTCAGTTT SEQIDNO:109 680_All AC 62 HBV_1033_ CAATGTGGMTATCCTGCYTTRATGCCTTTRTATGCATGT SEQIDNO:110 1077_B_C ATACAA 63 HBV_1033_ CAATGTGGWTATCCTGCTTTRATGCCYTTGTATGCATG SEQIDNO:111 1077_A_D TATTCAA 64 HBV_170_ CAGGAYTCCTAGGACCCCTGCTCGTGTTA SEQIDNO:112 200_All 65 HBV_2931_ CCAGTTGGATCCAGCCTTCAGAGCAAACAC SEQIDNO:113 2960_D 66 HBV_605_ CCCATCCCATCATCYTGGGCTTTCGGAAAA SEQIDNO:114 635_D 67 HBV_871_ CCCTAAAYTTCATGGGYTATGTAATTGGRAGTTGG SEQIDNO:115 900_A_D-1 68 HBV_910_ CCGCAAGATCAYATYRTACAAAAAATCAAGG SEQIDNO:116 940_A_D 69 HBV_910_ CCRCARGAACATATTGTACAAAAAATCAARC SEQIDNO:117 940_B_C 70 HBV_1828_ CCTCTGCCTAATCATCTCWTGTTCATGTCCTACTG SEQIDNO:118 1862_B_C_D 71 HBV_2697_ CCTTATTATCCAGAGCATGTAGTTAATCATTACTTCCA SEQIDNO:119 2740_B GACRAG 72 HBV_2697_ CCTTATTATCCWGARCATSTAGTTAATCATTACTTCCAA SEQIDNO:120 2740_A_D ACYAG 73 HBV_1300_ CGCAGCCGGTCTGGAGCGAAACTCATCGGAACTGAC SEQIDNO:121 1334_A 74 HBV_1300_ CGCAGCCGGTCTGGAGCGAAACTTATCGGAACCGAC SEQIDNO:122 1334_C 75 HBV_1300_ CGCAGCMGGTCTGGAGCGAAAATTATCGGAACTGAY SEQIDNO:123 1334_B_D 76 HBV_1135_ CTAAACCTTTACCCCGTTGCCCGGCAACGGTCAGGT SEQIDNO:124 1170_A_D 77 HBV_1135- CTAAACCTTTACCCCGTTGCTCGGCAACGGCCAGGT SEQIDNO:125 1170_B 78 HBV_1135_ CTAAACCTTTACCCCGTTGCTCGGCAACGGTCAGGT SEQIDNO:126 1170_C 79 HBV_1828_ CTCTGCCTAATCATCTCTTGTACATGTCCTACTK SEQIDNO:127 1862_A 80 HBV_2110_ CTGGGTGGGWARTAATTTGGAAGAYCCAGCR SEQIDNO:128 2140_All 81 HBV_871_ CTYTAAATTTCATGGGYTATGTCATTGGRAGTTAT SEQIDNO:129 900_A_D-2 82 HBV_270_ GACACRCGGKWGYTCCCCCTAGAAAATTG SEQIDNO:130 299_RC_All 83 HBV_130_ GAGGACTGGGGACCCTGCRCCGAACATGGAG SEQIDNO:131 160_A_B_C 84 HBV_130_ GAGGATTGGGGACCCTGCGCTGAACATGGAG SEQIDNO:132 160_D 85 HBV_781_ GAGTCCCTTTWTRCCGCTRTTACCAATTTTCTTTTGTCT SEQIDNO:133 810_All T 86 HBV_1183_ GCCCCARCCAGTGGGGGTTGCGTCAGCAAA SEQIDNO:134 1212_All_RC 87 HBV_2410_ GCCGCGTCGCAGAAGATCTCAATCTCGGGAA SEQIDNO:135 2440_All 88 HBV_1780_ GCTGTAGGCATAAATTGGTCTGCGCACCAGCACCAT SEQIDNO:136 1810_A_D 89 HBV_1780_ GCTGTAGGCATAAATTGGTCTGTTCACCAGCACCAT SEQIDNO:137 1810_B_C 90 HBV_990_ GGGGCAGCAAAGCCCAAAAGACCCACAATTCKTTGA SEQIDNO:138 1025_RC_All 91 HBV_1896_ GGGGCATGGACATTGACCCKTATAAAGAATTTGGA SEQIDNO:139 1930_All 92 HBV_749_ GGTATTGGGGGCCAAGTCTGTACARCATCTT SEQIDNO:140 780_All 93 HBV_201_ GGTATTGTGAGGATTYTTGTCAACAAGAAAAACCCCGC SEQIDNO:141 240_RC_All CT 94 HBV_1342_ GTYGTCCTCTCCCGSAAATATACAGCGTTT SEQIDNO:142 1371_A_B_D 95 HBV-570_ TACCAAACCTTCGGACGGAAAYTGCAC SEQIDNO:143 597_D 96 HBV_2466_ TAGAAGAATAAAGCCCMGTAAAGTTTCCCACCTTATG SEQIDNO:144 2502_All_RC 97 HBV_3181_ TCATCCTCAGGCCATGCAGTGG SEQIDNO:145 3215_D 98 HBV_2081_ TGCTGGGGGGARTTGATGACTCTRGCTACC SEQIDNO:146 2110_A_B_D 99 HBV_1101_ TGTTTACAYAGAAAGGCCTTGTAAGTTGGC SEQIDNO:147 1130_All_RC 100 HBV_951_ TTCCAATCAATAGGTCTATTTACAGGAAGTTTTCKAAA SEQIDNO:148 980_C_RC AC 101 HBV_951_ TTCCAATCAATAGGYCTGTTAACAGGAAGTTTTCKAAA SEQIDNO:149 980_A_D_RC AC 102 HBV_820_ TTGGGTATACATTTGAACCCTAACAAAACCAAACGA SEQIDNO:150 855_A_D 103 HBV_820_ TTGGGTATACATTTGAACCCTAATAAAACAAAAACGT SEQIDNO:151 855_B 104 HBV_820_ TTGGGTATACATTTGAACCCTAATAAAACCAAACGT SEQIDNO:152 855_C 105 HBV_1650_ TTRCACAAGAGGACTCTTGGAC SEQIDNO:153 1671_All 106 HBV_2541_ TTTCCTAARATTCATTTACAWGAGGACATTRTTAATAG SEQIDNO:154 2580_A AT 107 HBV_2541_ TTTCCTAATATACATTTACAGCAGGACATTATCAAAAA SEQIDNO:155 2580_D AT 108 HBV_1480_ CTCTATCGTCCCCTTCTTCATCTGCCGTTCC SEQIDNO:156 1510_A_D 109 HBV_1480_ CTCTACCGYCCSCTTCTTCATCTGCCGTWCC SEQIDNO:157 1510_B_C 110 HBV_1940_ GGAAAGAAGTCAGAAGGCAAAAACGAGAGTAACTC SEQIDNO:158 1970_RC_A_D 111 HBV_1940_ GGAAAGAAGTCAGAAGGCAAAAAAGAGAGTAACTC SEQIDNO:159 1970_RC_B_C 112 HBV_2030_ TCTCCTGARCATTGYTCACCTCACCATACRG SEQIDNO:160 2060_A_B 113 HBV_2030_ TCTCCTGAGCATTGTTCACCTCACCATACTG SEQIDNO:161 2060_D 114 HBV_2030_ TCTCCGGAACATTGTTCACCTCACCATACAG SEQIDNO:162 2060_C 115 HBV_2510_ TATCTTTAATCCTGAATGGCAAACTC SEQIDNO:163 2535_A 116 HBV_2510_ TGTCTTTAATCCTCATTGGAAAACAC SEQIDNO:164 2535_D 117 HBV_2510_ TGTCTTTAATCCTGARTGGCAAACTC SEQIDNO:165 2535_B_C 118 2620_2650_ AACCTAGCAGGCATAATCAATTKCARTCTTC SEQIDNO:166 RC_A_D 119 HBV_2620_ AACCTAGCAGGCATAATTAATTTTAGTCTCC SEQIDNO:167 2650_RC_B 120 HBV_2620_ AACCTAGCAGGCATAATTAATTTTAATCTCC SEQIDNO:168 2650_RC_C 121 HBV_2822_ CATGCTGTAGCTCTTGTTCCCAAGAATAT SEQIDNO:169 2850_RC_All 122 HBV_2890_ AATCTTTCTGTYCCCAATCCTCTGGGATTCTTTCCCGAT SEQIDNO:170 2930_A_B_C CA 123 HBV_2890_ AATCTTTCCACCAGCAATCCTCTGGGATTCTTTCCCGAC SEQIDNO:171 2930_D CA 124 HBV_3010_ CCAACAAGGTAGGAGYKGGAGCATTCGGGC SEQIDNO:172 3040_All 125 HBV_3060_ ATATGCCCTGAGCCTGAGGGCTCCACCCCAAAACACCT SEQIDNO:173 3100_RC_A CCG 126 HBV_3060_ GTATGCCCTGAGCCTGAGGGCTCCACCCCAAAAGKCCY SEQIDNO:174 3100_RC_D_B CCR 127 HBV_3060_ ATATGCCCTGAGCCTGAGGGCTCCACCCCAAAAGACCG SEQIDNO:175 3100_RC_C CCG *All primers are labelled with a 5biotin modification. Rbase denotes redundant A +G base. Ybase denotes redundant C +T base. Wbase denotes redundant A +T base. Sbase denotes G +C base. Kbase denotes redundant G +T base. Mbase denotes redundant A +C base.
[0123] In Examples 1-3, all the HBV enrichment experiments, if any, were performed based on the double-stranded DNA (dsDNA) library construction. Out of curiosity, a similar enrichment experiment based on the single-stranded DNA (ssDNA) library construction, was also carried out, and compared with a parallel enrichment experiment based on dsDNA library construction from the same biological sample. Briefly, cell-free DNA (cfDNA) samples isolated form liquid biopsy specimens (urine) from different patient samples, was utilized for both ssDNA and dsDNA library construction, which then underwent HBV enrichment, and NGS sequencing analysis. For ssDNA library construction, the ClaretBio SRSLY PicoPlus DNA NGS Library Preparation Dual UMI Index kit was utilized where a critical DNA denaturing step is performed as the initial step. All other subsequent steps were performed in accordance with the manufacturer's protocol. For library construction of double-stranded DNA, the Takara SMARTer ThruPLEX Tag-seq kit was utilized and performed according to the manufacturer's protocol.
[0124] Unexpectedly, a significantly improved HBV (on-target) enrichment was observed in urine samples utilizing single-strand DNA library construction compared with the same urine samples utilizing double-strand DNA library construction (Table 4). While both methods have obtained a similar level of total NGS reads (
TABLE-US-00004 TABLE 4 Comparison of HBV-targeted enriched NGS results between ssDNA and dsDNA library construction methods over the same urine samples. Single Strand Method Double Strand Method Total HBV # Total HBV # Disease- Patient NGS HBV Reads HBV-JS NGS HBV Reads HBV-JS Type Urine Reads Reads % Reads Reads Reads % Reads HCC U235-2nd 3.20E+07 1.95E+06 7.781 2955 4.14E+07 4.09E+03 0.010 50 HCC U238 3.33E+07 1.44E+06 4.340 1153 4.58E+07 3.20E+05 0.699 77 HCC U247 8.00E+06 1.56E+06 19.485 5718 5.05E+07 2.48E+05 0.491 207 Post-HCC U187 3.55E+07 1.08E+07 30.272 2295 6.70E+07 1.79E+06 2.678 352 Post-HCC U219 4.55E+07 1.09E+07 23.892 9833 5.81E+07 8.46E+05 1.46 101 Cirrhosis U114 1.30E+07 1.18E+06 9.083 1695 3.75E+07 1.39E+06 3.721 145 Cirrhosis U126 3.48E+07 7.84E+06 22.492 2780 7.48E+07 5.10E+06 6.817 307 Cirrhosis U157 1.78E+07 1.13E+06 6.349 513 252816308 6809276 2.693 117 Cirrhosis U233 3.24E+07 6.61E+06 20.411 1657 2.95E+07 3.46E+03 0.012 62 Hepatitis U80 2.36E+07 6.98E+05 2.959 2128 5.69E+07 2.63E+04 0.0462 134 Hepatitis U135 3.12E+06 5.22E+05 16.704 2828 3.37E+07 1.24E+04 0.037 33
[0125] In order to evaluate the performance of the optimized HBV probe panel (n=127, shown in Table 10) relative to the initial HBV probe panel (n=43, shown in Table 1), enrichment analysis was carried out using reconstituted PLC HCC cell-line DNA containing known integrated HBV sequences, where normal DNA samples containing 1%, 0.5%, and 0.1% PLC genomic DNAs were compared for sensitivity and specificity evaluation, and the results are shown in Table 5. After two sequential primer-extension capture (PEC), both panels demonstrate 10.sup.5-fold enrichment compared to whole genome sequence of 100% PLC (no enrichment).
TABLE-US-00005 TABLE 5 Assay assessment of initial vs optimized probe panel. Sample Description Total NGS Reads HBV Reads % PLC 1% Optimized panel 2.99E+07 0.500 1.85E+08 0.620 2.02E+08 0.573 Initial panel 2.19E+08 0.528 2.34E+08 0.496 2.55E+08 0.457 PLC 0.5% Optimized panel 2.19E+08 0.528 4.05E+08 0.293 4.19E+08 0.285 Initial panel 2.71E+08 0.431 2.87E+08 0.407 3.04E+08 0.385 PLC 0.1% Optimized panel 4.34E+08 0.276 4.50E+08 0.266 4.65E+08 0.257 Initial panel 3.21E+08 0.364 3.36E+08 0.348 3.56E+08 0.329
[0126] The optimized HBV panel was also examined for its performance in detecting known HBV-junctions (such as HBV junction at TERT, CCDCl57 and MVK). As shown in Table 6, the optimized panel showed a better performance, and can detect additional junction reads compared to the initial panel when the number of NGS reads are similar.
TABLE-US-00006 TABLE 6 Detection of known HBV-junctions using optimized vs initial HBV panel. Sample Description # HBV-JS Reads TERT CCDC57 MVK PLC 1% Optimized panel 121 3 4 7 160 0 19 9 144 0 18 8 Initial panel 20 1 3 0 21 0 0 0 70 0 6 30 PLC 0.5% Optimized panel 89 0 4 0 104 0 12 5 45 0 3 2 Initial panel 3 0 0 0 2 1 0 0 16 3 0 0 PLC 0.1% Optimized panel 22 0 4 0 23 0 0 2 13 0 0 0 Initial panel 2 0 0 0 3 1 0 0 2 0 0 0
[0127] In order to further evaluate whether an increased number of PEC enrichment can improve the enrichment result, a comparison experiment was carried out, which compare the two sequential PEC enrichment with three sequential PEC enrichment. Briefly, the workflow of a sequential PEC enrichment is illustrated in
TABLE-US-00007 P5truncblock (SEQIDNO:176) GTGTAGATCTCGGTGGTCGCCGTATCATT-PH P7truncblock (SEQIDNO:177) CAAGCAGAA+GACGGCATACGA+GAT-PH
[0128] First, reaction containing buffer, blockers, dNTP and library DNA was incubated at 95 C. for 5 mins to denature double-strand library DNA and facilitate binding of adapter blockers to prevent daisy chaining during enrichment. Next, the reaction was held at 72 C. for 5 mins before adding the biotinylated HBV primer mix to the reaction. The entire reaction was incubated at 60 C. for 1 hr. Lastly, 0.1 l of heat inactivated Herculase II Fusion polymerase was added to each reaction and incubated at 72 C. for 90 s. The captured DNA was collected by using hydrophilic streptavidin magnetic beads (New England Biolabs, Ipswich, Mass.), washed twice at 55 C. using 5 mM TrisHCl pH 7.5, 0.5 mM EDTA, 1M NaCl buffer. Captured library DNA was eluted using 10 l 0.1N NaOH and neutralized with 40 l 1M Trish-HCl pH7.5. Prior to post-enrichment amplification, eluted library DNA was purified using 1.8 AMPure XP beads. Library DNA amplification post-enrichment utilized 1 Herculase II Buffer, 250 M dNTP, and 30 pmol of P5/P7 Illumina adapter primers, and 0.3 l of Herculase II Fusion polymerase. Reaction was performed at 98 C. 2 mins, 98 C. 30 s, 60 C. 30 s, 72 C. 1 min for 10 cycles followed by 72 C. extension for 10 mins. Amplified library DNA was purified using 1.8 AMPure XP beads. Following purification, subsequent enrichments can be performed by repeating the above procedures or library DNA can be quantified and sequenced. The comparison results are shown in Table 7.
TABLE-US-00008 TABLE 7 Three sequential PEC improves detection of HBV-JS reads in optimized panel Two Enrichments Three Enrichments # # Reconstituted HBV-JS TERT-JS CCDC57-JS MVK-JS HBV-JS PLC Reads (UMI) (UMI) (UMI) Reads TERT-JS CCDC57-JS MVK-JS 1%-A 121 3 4 7 268 2 6 2 1%-B 160 0 19 9 266 1 18 5 1%-C 144 0 18 8 123 0 28 13 0.5%-A 89 1 3 0 349 1 5 1 0.5%-B 104 0 0 0 269 0 13 2 0.5%-C 45 0 6 30 374 0 8 3 0.1%-A 22 0 4 0 308 0 4 0 0.1%-B 23 0 12 5 287 0 1 2 0.1%-C 13 0 3 2 348 0 0 0
[0129]
Example 2: Detection of Recurrent HBV Integration Targeted Genes in Urine Identifies Potential Drivers of Hepatocellular Carcinoma
[0130] Chronic hepatitis B virus (HBV) infection is a major etiology of hepatocellular carcinoma (HCC), associated with over 50% of cases worldwide and up to 70-80% of cases in HBV-endemic areas. High mortality of HCC is mainly due to late detection and limited treatment options. HCC surveillance programs have been implemented to screen HBV-infected individuals, to facilitate earlier detection of HCC. Unfortunately, most cases of HBV-related HCC (HBV-HCC) remain undetected until late stages resulting in poor prognosis, due to lack of a sensitive and convenient screening method. In the past years, over 100 clinical trials for HCC therapy failed, Sorafenib, with a limited efficacy, remains the only available chemotherapy after its approval 9 years ago. Identification of HCC drivers has been suggested to be important for drug development and patient selection in clinical trial design due to high heterogeneity of the diseases (REF).
[0131] During the course of infection, HBV can integrate into the host chromosome, and this integrated viral DNA was detected in more than 85% of HBV-HCC. Although it is known that viral breakpoints predominately occur in the DR1-2 region of the HBV genome, the integration sites in the host DNA have been observed to vary. Thus, each HBV integration event generates a unique HBV-host integration site, which creates a specific fingerprint of each infected hepatocyte. During the tumorigenesis, uncontrolled clonal expansion can amplify this molecular signature becomes a major, most abundant, over other host junctions found in other noncancerous infected hepatocytes. Thus, the merging of this uncontrolled, clonally expanded major HBV-host junction can be a biomarker for carcinogenesis, and can be a biomarker for early detection of HCC if this major HBV-host junction can be detected in periphery.
[0132] In order to test the feasibility to detect HBV-host junctions in circulation, urine was resorted since it is limited, if any of virions thus facilitating detection of integrated HBV DNA. It has been shown that urine contains DNA from circulation that can be used for cancer detection if a tumor is present. Although HBV DNA has been detected in urine, it has not been entirely clear if HBV DNA detected in urine was derived from fragmented integrated DNA from infected liver. In this proof-of-concept study, a method is developed to prepare a DNA library for NGS enriched for HBV integration. Using this approach, identical, major HBV integration sites from matched HCC tissue and urine are detected, providing evidence that clonally expanded, integrated HBV DNA derived from the infected liver is present in the urine. Combining this data with other reports of HBV integration, it was found the recurrently targeted genes are mostly associated with carcinogenesis suggesting potential approach for HBV-HCC driver identification. In particular, the TERT gene seems to be highly targeted within a narrow range of the promoter region. Together, these results not only suggest the utility of urine as a body fluid to study HBV integration sites in circulation, but also describe a noninvasive means for potential HCC screening and genetic characterization.
Experimental Procedures
[0133] Study subjects: the HCC tissue and urine samples used were obtained with written informed consent from patients at the National Cheng-Kung University Medical Center, Taiwan, in accordance with the guidelines of the Institutional Review Board. Detailed sample information is provided in Table 8.
TABLE-US-00009 TABLE 8 Clinical characteristics of HCC patients. Patient Age Gender Cirrhosis Tumor Tumor size ID (years) (M/F) (+/-) grade* (cm) 1 71 M + G1 3.5 2 68 M NA NA 3 44 F G3 3.5 4 43 M G2 3.0 5 68 M G2 6.5 6 58 M G2 15.0 7 57 M G2 4.0 8 41 M + G2 2.0 9 49 M + G2 3.4 10 61 M G3 2.3 11 75 F G2 3.0 12 63 F G2 4.0 13 39 F G2 10.0 14 59 F + G2 4.0 15 47 F + G2 1.5 16 63 F + NA NA 17 29 M + G2 7.0 18 33 F + G1 2.5 19 61 M + G3 7.0 20 57 M + G1 3.0 21 73 M + G2 11.0 22 42 M + G2-G3 6.0 23 75 M G2 1.9 55.5 13.6 15/8 11/12 (Avg. SD) (M/F) (/+) *denotes HCC tumors were staged using the tumor-node metastasis (TNM) staging system; NA, Not applicable
[0134] DNA isolation, urine collection, and low molecular weight (LMW) urine DNA fractionation: Tissue DNA was isolated using the Qiagen DNeasy Tissue kit (Valencia, Calif.) according to the manufacturer's instructions. Urine samples were collected and total urine DNA was isolated as previously described (Su Y H et al. 2004). Cell-free DNA (<1 kb) was obtained from total urine DNA using carboxylated magnetic beads, as previously developed (Su Y H et al. 2008).
[0135] Preparation of HBV DR1-2 enriched library DNA for NGS: Tissue DNA was fragmented by sonication and subjected to Next-Generation Sequencing (NGS) library DNA preparation as described by Ding et al. 2012. This involved minor modifications, including 10 cycles of library DNA amplification using Herculase II Fusion polymerase (Agilent Technologies, Santa Clara, Calif.). To enrich for DNA that contains HBV DR1-2 sequences, a multiplex biotin HBV primer extension reaction was performed using amplified library DNA in a reaction containing 1 Herculase II Buffer, 250 M dNTP, and 20 pmol of biotinylated HBV primers. The primer-extended DNA was collected, as described by Gnirke et al. 2009, subjected to three individual nested HBV DR1-2 PCR enrichment reactions, and followed by an indexing PCR. Each indexed library was quantified and pooled accordingly for one NGS. NGS was performed to generate 150 bp paired-end reads on the Illumina MiSeq platform (Penn State Hershey Genomics Sciences Facility at Penn State College of Medicine, Hershey, Pa.).
[0136] Identification and characterization of HBV-JS sequences: NGS data was analyzed using JBS ChimericSeq software (http://www.jbs-science.com/ChimericSeq.php, Jongeneel et al. manuscript submitted) to identify integration sites and major integration sites. For all the major integration sites identified, the software provided the annotation of breakpoints for both the HBV genome and human genome, human genes within 100 kb of the breakpoints, the number of overlapping viral and human nucleotides at the junction site and the Tm of the overlapping sequences.
[0137] Short amplicon PCR assays: Short amplicon junction PCR was performed using Hotstart Plus Taq Polymerase (Qiagen, Valencia, Calif.), junction primers, and the LMW urine DNA templates. Junction PCR products were visualized on a 2.2% FlashGel DNA Cassette (Lonza Group, Basel, Switzerland) and subsequently subjected to either a nested PCR reaction using a set of inner primers, or a restriction endonuclease (RE) digestion using RE obtained from New England Biolabs (Ipswich, Mass.), per the manufacturer's specifications to further compare the PCR products derived between tissue and urine.
[0138] Results:
[0139] Development of an NGS Library Enrichment Method for HBV Integrations:
[0140] To directly enrich for HBV integrated DNA, a primer extension capture (PEC) approach was adopted to the HBV DNA libraries. In short, this technique uses 5-biotinylated oligonucleotide primers to capture targeted regions, and then uses a DNA polymerase to extend the primers (
[0141] Identification of Major HBV Integration Sites from HCC Tumor Tissue Using PEC of HBV DR1-2:
[0142] In order to test whether the PEC approach was effective at enriching HBV integrated DNA from a biological sample, this technique was applied to an adapter-ligated tissue DNA library of 23 patients with chronic HBV infection and hepatocellular carcinoma (HCC). With the assumption that sampled tumors contain HBV integrated DNA at 1:1 ratio with human genomic DNA, A 10E4-fold enrichment would be necessary to obtain 1% HBV reads out of total reads. Through improving the specificity by PEC, it is able to obtain an average of 3.5% HBV reads of total NGS reads (data not shown).
[0143] Tumors are clonally expanded and most HBV-HCC tumors contain integrated HBV DNA (Ref), thus should contain at least one major, clonally expanded, HBV integration junction. In this study a major integration junction is defined as a distinctively identified sequence supported by at least 10% of the total HBV junction reads (minimum of 3 reads) within each DNA tissue sample. Reads containing HBV junctions were efficiently identified using the recently developed software program, ChimericSeq as described in Methods. The major HBV integration junctions identified in the NGS data by ChimericSeq are summarized in Table 9.
TABLE-US-00010 TABLE9 CharacterizationofmajorHBVintegrationsitesidentifiedinHBV-HCCtissue. HBV-hostjunction breakpointnucleotide(nt.) position Sanger Patient #of overlap sequencing ID HBVintegrationsitesequences SR/TR HBV Human nt./Tm(C.) confirmed 1 cgaccttgaggcatacttcaaagactgtttgtttaaagactgggaggagtt 20/20 1773 Chr5: 3/12 + gggggaggagattaggaggctgtaggcataaaGGAAGGGGAG (100%) 1295082 GGGCTGGGAGGGCCCGGAGGGGGCTGG(SEQ IDNO:178) 2 gggggaggagataaggttaaaggtctttgtactaggaggctgtaggcat 24/24 1801 Chr5: 1/10 + aaattggtctgCCCAGCCCCCTCCGGGCCCTCCCAGC (100%) 1295123 CCCTCCCCTTCCTTTCCGCGGCC(SEQIDNO: 179) 3 gaggagattaggctaaaggtctttgtactaggaggctgtaggcataaatt 76/77 1820 Chr19: 3/14 + ggtctgttcaccagcaccatgcaacGGAGCTCATAACCTGAT (98.7%) 29812873 CAGCTTTCTCTTCTTCTCTCTGTTTTTGTCTTGTTT GGTGTGTTTCCTTGGGGTCATGG(SEQIDNO: 180) 4 gggggaggagataaggttaaaggtctttgtactaggaggctgtaggcat 68/123 1827 Chr8: 1/10 + aaattggtctgttcaccagcaccatgcaactttttccTTTTCTATATC (55.2%) 64147161 AATTGTTGATACTCCAATAATATTAATTGCTAAG (SEQIDNO:181) gggggaggagataaggttaaaggtctttgtactaggaggctgtaggcat 30/123 1795 Chr.9: 0/0 NA aaattTTATCTTCATATAAAATCTAGACGGAAGCAT (24.3%) 45073810 (SEQIDNO:182) 5 actaggaggctgtaggcataaattggtctgttcaccagcaccatgcaact 28/30 1801 Chr20: 5/18 + ttttcTTATGAATGTTTTCTATATTTCAAAGCCCTGCT (93.3%) 53437062 CAAACACCACCTCCTCCAGAAAGGCTCCTGGTAT CCTCTTTCTTTTCTAACCTAGAAAAGA(SEQID NO:183) 6 gcctaatcatgtcatgttcatgtcctactgttcaagcctccaagctgtgcctt 34/70 1901 Chr19: 1/10 + gggtggctttggggcatgCGGGTGCCCGGGTCGCGGGT (48.5%) 29812390 GACAGGCCACCCCGCCATCGGCCATCTTCCTGG CTCGCCCGGCCGCCCGCGCGCA(SEQIDNO: 184) gactctcagcaatgtcaacgaccgaccttgaggcatacttcaaagactg 28/70 1765 Chr.6: 0/0 NA tttgtttaaggactgggaggagttgggggaggagattaggttaaagaTT (40%) 17125139 ACCATGTTGCCCAGGCTGGTCTTGAACACCTGGC CTCAAGGGACGCTCCCAGC(SEQIDNO:185) 7 cacgtcgcatggagaccaccgtgaacgcccaccaagtcttgcccaag 13/21 1712 Chr.10: 9/28 + gtcttacataagcggactcttggactcccagcaatgtcaacgaccgacct (61.9%) 31192695 tgaggcgtacttcaaaACCCAGACCCAGCTCAGGCATC ACCACCTCCAGGCAGC(SEQIDNO:186) 8 tggactttcagcaatgtcaatgaccgaccttgaggcatacttcaaagact 27/27 1756 Chr.11: 6/24 + gtgtgtttactgagtgggaggagttgggggagggactagCTCATTA (100%) 92048629 ATCATTGTGTCAAACCTGGCACCGTGCCTGAAAC ACAGTAGCCTCTCAATAAATA(SEQIDNO:187) ttgcacaacaggactcttggacTTACACCAGTGGTTTGCC NA 1672 Chr.22: 13/46 + GGGGAATCTTGAGCCTTTGGCCACAGACTGAAG 34131795 GCTGCACTGTCAGCTTCCCTACTTTTGAGGCTTT CG(SEQIDNO:188) 9 actaggaggctgtaggcataaattggtctgttcaccagcaccatgcaact 4/4 1825 Chr.16: 1/8 + ttttTCCGAACCTGTGTACTAAACTGCCTGGGGGCA (100%) 29467674 GCTCTCATCACTGCTGTAGAACAAAGTCCCACAT AGAGCCAATGGCCAAGAACCAGTTAATAAAA (SEQIDNO:189) 10 gagtgggaggagttgggggaggagattaggttaaaggtctttgtactag 85/206 1783 Chr.5: 3/16 + gaggctgCATGGCCGGAAGTCTTACATGTCTTGGG (41.2%) 1292170 AGTTTGTGGGGAGGGGGTGAAATCGGGACTTCT TCTAGCTGCCACGG(SEQIDNO:190) 11 gggggaggagataaggttaaaggtctttgtactagtaggctgtaggcat 26/46 1796 Chr.14: 0/0 + aaattgCCTACAGCAATGTATAGATTTTAAATAAATG (56.5%) 67004392 CTTGCTGACTTACTATGACCTACTGGTAG(SEQID NO:191) 12 gactcttggactcccagcaatgtcaacgaccgaccttgaggcctacttca 50/71 1780 Chr.5: 8/32 + aagactgtgtgtttaaggactgggaggagctgggggaggagattaggtt (70.4%) 165559760 aatgatctttgtactaggaggAACATGCCCAAGAAATTGGC GACATACCAGC(SEQIDNO:192) 13 tcttgcataagaggactcttggactttcggcaatgtcaacgaccgaccttg 5/6 1726 Chr.14: 2/10 + aggcatacttcaaagactgtgtgtttaaCTCATCTGTCCAAACC (83.3%) 103176895 CAAAGAATGGACTCAGAGACCCAGAGAACAACGA AAGTGACGGTTTGTTCTT(SEQIDNO:193) ttgcacaacaggactcttggactctcagcaatgtcaacgaccgaccttga NA 1742 Chr.19: 9/9 + ggcatacttcaaagactgtttgtttaaagactgggaggagttgCATCT 53667608 AACTCAGGTTTTCAACTAGTCTTACCATTGAAAGA ACTATTGTGGCAAAGACGGAATG(SEQIDNO: 194) 14 aaagactgggaggagttgggggaggagattaggttaaaggtctttgtac 18/38 1803 Chr.7: 13/38 - taggaggctgtaggcataaattggtctgttTGAAGTTGTCCAG (47.3%) 4338599 AAACTGACCTTTGAATATCCGGATGCACGAGATT CCCTGAAAGGGGAACAATAAATGT(SEQIDNO: 195) caaggtcttacataagcggactcttggactctcagcaatgtcaacgacc 13/38 1713 Chr.X: 0/0 - gaccttgaggcgtacttcaaaggTGTTACAGGTAGTTAGAC (34.2%) 35786804 AGGCATGAGCAGGGCAGGAGAGAACGCTCCCCT GACTCACCAGGAATGTCAGGCAATCATTG(SEQ IDNO:196) 15 tgggaggagttgggggaggagattaggttaatgatctttgtactaggagg 9/9 1826 Chr.4: 9/22 - ctgtaggcataaattggtgtgttcacctgcaccatgcaactttttcTGGG (100%) 141291543 GATGGGGATGTGGCAGTTGTGGACTGAAGTTGTA CTGAGTGGTG(SEQIDNO:197) 16 ttaggttaatgatctttgtactaggaggctgtaggcataaattggtctgAC 22/23 1801 Chr.5: 1/10 NA CCGCCCTTCTCTGCCCAGCACTTTTCTGCCCCCC (95.6%) 1299125 TCCCTCTGGAACACAGAGTGGCAGTTTCCACAAG CACTAAGCATCCTCTTCCCAAAAGACCCAGC (SEQIDNO:198) 17 aacagtctttgaagtacgcctcaaggtcggtcgttgacattgctgagagtc 7/8 1623 Chr.9: 0/0 NA caagagtccgcttatgtaagaccttgggcaagacctggtgggcgttTG (88%) 16709453 GTGGCATTGCAAGTGTACTGTTTAA(SEQIDNO: 199) 18 cacaacaggactcttggactctcagcaatgtcaacgaccgaccttgagg 30/103 1814 Chr.5: 13/40 NA catacttcaaagactgtgtgtttaaagactgggaggagttgggggagga (29.1%) 1284093 gattaggttaaaggtctttgtactaggaggctgtaggcataaattggtctg gacctgcatcatCCGGACTCCATAC(SEQIDNO:200) tgcacaacaggactcttggactctcagcaatgtcaacgaccgaccttga 30/103 1802 Chr.19: 1/4 NA ggcatacttcaaagactgtgtgtttaaagactgggaggagttgggggag (29.1%) 29812598 gagattaggttaaaggtctttgtactaggaggctgtaggcataaattggtct gcCCGCGGCCCGGGCACTCACCGCTCCCTGCGC TCCCTCGGCATGATGGGGCTGCTCCGG(SEQID NO:201) tgcacaacaggactcttggactctcagcaatgtcaacgaccgaccttga 17/103 1765 Chr.4: 9/24 NA ggcatacttcaaagactgtgtgtttaaagactgggaggagttgggggag (16.5%) 116834523 gagattaggttaaaggtGTCTGGTATTATTTCTGGGTTCT CTATTCTGTTCC(SEQIDNO:202) tttaaagactgtgaggagttgggggaggagattaggttaacggtctttgtg 10/103 1781 Chr.14: 5/18 NA ctgtggaggGAAGACTAAGTAGAGACGCGGATGTTT (9.7%) 32527123 ATGGCAGTGAAACTGTTC(SEQIDNO:203) 19 cgaccttgaggcatacttcaaagactgtttCAAGAAACTGAGT 192/255 1720 Chr.9: 12/32 NA GAGTAGGCTCTGGAAATTGGAAGTGATCTTAGTA (75.2%) 22215960 TTTAAGTTCAGTCACTCAACTACAATCTCTGAAAC (SEQIDNO:204) cgaccttgaggcatacttcaaagactgtttTACCAGACACTCAC 14/255 1722 Chr.X: 7/18 NA ATGGCTTCCTCGCTGTCTTCCTGTGGTGGCACAC (5.4%) 130398440 GCCTGTAGTCCCAGCTACTTGGGAGGCTGAGGC AGGAGAATTGCTTGAACC(SEQIDNO:205) 20 gggggaggagataaggttaaaggtctttgtactaggaggctgtaggcat 20/20 1826 Chr.12: 0/0 NA aaattggtctgttcaccagcaccatgcaactttttcTGGTGAAAAGC (100%) 74945009 TAAACACAGGAGATATTTTTAAGCTTCACTCATAC AGAAAATACA(SEQIDNO:206) 21 gggggaggagataaggttaaaggtcttgtttgtactaggaggctgtagg 6/6 1800 Chr.10: 2/8 NA cataaattggCAGGACCCAGGGGAGCAGCCAGCACT (100%) 124355242 GCGCATGCTGGGAGTGTTCAATAAATACAGGCTG AATGAATGAATGAACTGATGCATCCAAAACTT (SEQIDNO:207) 22 cgaccttgaggcatacttcaaagactgtttgGAAAAAATGTAAA 10/86 1723 Chr.12: 9/26 NA CATATCAGCCCTGAGCAAGACAGCCAAACCAAAA (11.6%) 40055103 CAACCACAGCGAGGGATTCTGATTCCTTTGACAG ACTCTGTTTCT(SEQIDNO:208) cgaccttgaggcatacttcaaagactgtttgCCTTTTCCCCTAA 9/86 1731 Chr.2: 12/32 NA TCCCCTTTCCCCACTGGTACAGGGTGGAGAGGT (10.4%) 44149056 C(SEQIDNO:209) 23 gactcccagcaatgtcaacgaccgaccttgaggcctacttcaaagactg 7/25 1803 Chr.1: 0/0 NA tgtgtttaaggactgggaggagctgggggaggagattaggttaaaggtc (28%) 39524755 tttgtattaggaggctgtaggcataaattggtctgCGTCACCCTCC AGAAGGA(SEQIDNO:210) cacaacaggactcttggactcccagcaatgtcaacgaccgaccttgag 6/25 1811 Chr.14: 3/10 NA gcctacttcaaagactgtgtgtttaaggacttggaggagctgggggagg (24%) 95571897 agattaggttaaaggtctttgtattaggatgctgtaggcataaattggtctg cCTTGACTAAAGCCCATGGGCCA(SEQIDNO: 211)
[0144] To confirm the junction sequences obtained from the NGS analysis, PCR primers were designed for the major HBV integration junctions of 15 patients and performed amplification from the corresponding tissue DNA for Sanger sequencing. The respective tissue NGS library DNA was used as a positive control (+) for the junction sequence identified by NGS and HepG2 cell line DNA as a negative control () for each DNA tissue sample. Encouragingly, it was able to generate PCR products for 13 out of 15 of the tissue DNA samples tested. Only 2 of the 15 samples (patients 7 and 8) were unable to generate a PCR product using custom primers (data not shown). Further Sanger sequencing of each PCR product revealed matching HBV integrated sequences to their corresponding NGS-identified integration sequence, thus confirming the 13 samples. In total, it was able to validate 87% (13/15) of the major NGS identified HBV integration sites.
[0145] Detection of Tissue Identified Major HBV Integration Sites in Matched Urine:
[0146] Next it is examined whether major HBV integration sites can be detected in the circulation. As previously demonstrated, urine contains circulation derived DNA. The use of urine over serum collection is also advantageous, as it does not contain high amounts HBV DNA from virions in the circulation. In order to test the feasibility of detecting HBV integration junction sequences in the urine, seven patients (ID 9, 10, 11, 12, 13, 14, and 15) that have major HBV integration junctions identified by NGS study from this study were selected for this experiment based on the availability of matched urine DNA. For each major HBV integration site, primers were custom designed to amplify short products of less than 60 bp (illustrated in
[0147] Interestingly, for patient 7, the PCR product generated from urine DNA was larger than the one obtained from the tissue by PCR amplification (
[0148] Major HBV Integrations in HCC Recurrently Target TERT and CCNE1:
[0149] In HBV-infected individuals, integration into the host genome is thought to be random, having the potential to become oncogenic by insertional mutagenesis. The HBV DR1-2 sequences contain enhancer elements that may up-regulate host genes within a proximity of 100 kb, independently of position and orientation. With the identified locations of major HBV integration sites in HCC patients, host genes within 100 kb of these major sites were searched. ChimericSeq is used to identify the genes and positions of each breakpoint in both HBV and human genomes from the NGS data from tissue DNA. Out of the 34 major integration sites that were identified in 23 patients, 4 were not in a 100 kb proximity of a gene. Among these genes, TERT and CCNE1 were targeted in more than 1 patient; TERT was targeted in 5 of the 23 patients from this study, and CCNE1 was targeted in 3. Interestingly, both genes were found to be associated with carcinogenesis. Indeed, TERT is a suggested gatekeeper of hepatocarcinogenesis as the promoter region is frequently mutated in certain cancers. It thus was wondered whether identification of recurrent integration targeted genes could be a potential approach to identify drivers involved in hepatocarcinogenesis.
[0150] To explore this hypothesis, a meta-analysis of data reported from 15 studies, 446 patients, and 1554 HBV integrations was compiled. ChimericSeq was used again on this data set to identify genes within 100 kb of the integration site. From the 51 genes that were identified in at least 2 HCC patients, 12 were from at least two separate studies, defined as HBV integration recurrently targeted genes in HCC (
[0151] In alignment with this study of 23 HCC tumor tissues, TERT and CCNE1 were among the most common recurrent integration sites. Because of the presence of the most data for integrations near TERT, these 67 integration sites were compiled for further study. First, the location of the TERT integration breakpoints in the host genome was mapped against their locations in the HBV genome (
[0152] Promoter mutations and upstream rearrangements of the TERT gene including HBV integration, are known factors that drive carcinogenesis. It was of interest to investigate the distribution of these two events in the same tumor. The TERT promoter region of 20 of 23 tissue samples was successfully sequenced from the study, and identified 5 mutations of which 3 are of the major TERT hotspot mutation (124) (
[0153] Discussion:
[0154] This is the first study demonstrating that liver-derived HBV integration junction sequences can be detected in urine. This was enabled through the identification of the major integration site(s) in HCC tissue, followed by validation using tailored primers for these major sites from urine. The novel sequence created by HBV integration was taken advantage of, using it as a unique marker to trace for the HBV-integrated DNA that was released into circulation, and demonstrated the detection of identical integration sequences between the tumor tissues and corresponding urine samples. Detection of such unique sequences in the urine provides unambiguous evidence that HBV integrated DNA from the liver is released into circulation, and is filtered into urine as fragmented, cell-free DNA.
[0155] Two important features of HBV integration are foundations of this proof-of-concept study. First is the appearance of over-represented or major HBV integration sites in HCC due to uncontrolled clonal expansion, as demonstrated in earlier studies. While proliferation of infected hepatocytes can occur in non-HCC liver disease, mostly within 10.sup.5 cells, clonal expansion observed in HCC tumors is uncontrolled. This results in expansion of 10.sup.9 cells (1-3 cm tumor size), and results in preferentially abundant HBV integrated sequences in the infected liver or in the HCC nodule. This is shown in the supporting reads, which describes as the major HBV integrations in the NGS study (Table 9). Because of their high abundance, it was reasoned that these major HBV integration sites in the infected liver would most likely to be predominantly detected in urine. As predicted, major HBV integrations sites were detected in matching urine samples in six of nine HCC patients tested.
[0156] Second, the HBV integration events are random, and HCC-derived integration sites have previously been used as a cellular signature of the clonality of HBV-HCC tumors. Among over a thousand HBV integration sites identified in recent NGS-based studies, the most frequently reported recurrent integration targeted gene is TERT. Strikingly, with over 60 HBV-TERT junction sequences reported, no two are identical at both viral and host breakpoints. This further supports the hypothesis that HBV integration sites created by integration could serve as a molecular signature of the infected hepatocyte. Therefore, detection of an emerging, predominant integration site in the urine could be a potential biomarker for an early clonal expansion or HCC in a chronic HBV infected individual, as illustrated in
[0157] The mechanistic links between HBV integration and hepatocarcinogenesis have been suggested to include activation of oncogenic genes and induction of chromosomal instability. By analyzing 34 major integration sites from 23 HBV-HCC patients, five were targeted in proximity of the TERT gene, and three within range of the CCNE1 gene, both commonly recognized oncogenes. Three additional integration sites at TSHZ2, GPHN, and miR512-1 have also been reported to be associated with carcinogenesis. The integration site identified from patient #7 showed chromosomal rearrangement, a common event in cancer. This high frequency of integration in oncogenic genes and the evidence of chromosomal instability detected in this study led people to study and compare other reports. Therefore, a meta-analysis of data reported from 15 studies, 446 patients, and 1554 HBV integrations was carried out. In line with this study, it was found that TERT and CCNE1 are among the most frequently reported targeted genes by HBV. Interestingly, it was observed that 10 other genes were targeted by separate studies from different groups, and most had previously reported association with cancer while other two functions are unknown. This indicated that while HBV integration may be random, disruption of particular regions might have more of an impact on development of HCC. Since TERT was by far the most commonly targeted gene, both the human and HBV genomic locations of each integration site were mapped. Strikingly, it was found that HBV integration is frequently observed in a narrow region of the TERT promoter, despite every integration site being unique. Since TERT promoter mutations are recognized drivers of carcinogenesis and TERT promoter integrations are mutually exclusive with these mutations, it is suggested that HBV integrations have the potential to act as drivers of carcinogenesis. Of note, the cohort in this small study was mostly of HBV-HCC patients that were predominantly non-cirrhotic (77%). This could imply that HBV integration plays a more direct role in HCC carcinogenesis in non-cirrhotic patients.
[0158] In moving forward, a more thorough analysis of HBV integration sites is needed to better assess the role of integration with carcinogenesis. While disruptions in TERT and CCNE1 appear to be well implicated in connection with development of HCC, there are likely several other important genes that are less frequently targeted. It was previously reported for. The detection of circulation derived DNA in the urine, and it thus believed that urine will be the best source to profile HBV integrations of the liver because unlike blood, urine contains limited (if any) infectious HBV particles. Even though HBV integrated DNA in the urine makes up only a very small fraction of total cfDNA, with advance in sensitivity of technology of detecting cfDNA, detection of major HBV integration sites in urine is plausible. As 85% of HBV-HCC samples were found to contain integrated HBV DNA, detection of the major HBV integration sites in urine could serve as a specific and sensitive marker for HCC screening of the chronic HBV infected population.
Example 3: Landscape of Recurrently Targeted Genes by HBV Integration in Hepatocellular Carcinoma Patients: Potential Biomarkers for Disease Management
1. Introduction
[0159] Hepatocellular carcinoma (HCC) is the 2nd leading cause of cancer deaths worldwide [1-3], and suffers from poor prognosis in part due to lack of effective treatment options. The major etiology of this multifactorial disease is chronic hepatitis B virus (HBV) infection, which is associated with approximately 50% of HCC cases worldwide [4]. During the course of infection, HBV can integrate into the host genome. It has been believed that integration events mostly occur through non-homologous end joining (NHEJ) [5], as well as through micro-homologous recombination [6-9]. While HBV DNA integration into the host genome is considered rare, with an estimate of one integration event per ten thousand HBV-infected hepatocytes [10], the integrated viral DNA has been reported in more than 85% of HBV-related HCCs (HBV-HCC), suggesting a significant association of HBV integration in hepatocarcinogenesis. Mechanisms of HBV integration in HCC carcinogenesis could vary in patients and include insertional mutagenesis of HCC-associated genes, induction of chromosomal instability, and continuous expression of viral proteins [11,12]. Understanding the impact of integrated HBV DNA on carcinogenesis and potentially identifying HCC driver genes as personalized biomarkers could pave the way for precision disease management in HBV-HCC patients.
[0160] With the advent of next generation sequencing (NGS), thousands of HBV integration sites have been identified across the human genome. Over 15,000 HBV integration sites have been reported from PCR and NGS-based approaches from tumors [6,13-36]. While no known host sequence preference or specificity [5,37-41] was identified, integration can activate known HCC driver genes and has been reported in TERT, CCNE1, and MLL4 [42]. Integration in these genes has been reported in a recurrent manner (i.e. in more than one HCC patient) and have become known as recurrently targeted genes (RTGs). Interestingly, no RTG has been identified from non-HCC livers of chronically HBV-infected patients (n=90, 960 integration sites) [11, 27, 43, 44], suggesting its specificity for HBV-HCC. Similar to the approach of identifying BRAF V600E driver mutations by the identification of recurrent hotspot mutations, here we take advantage of the large amount of reported integration sites from literatures and our in-house study reported here to test the hypothesis that HCC drivers can be identified by characterizing RTGs.
[0161] In this study, we compared integrations sites identified in tumor and adjacent-to-tumor (adj-tumor) tissue and defined RTGs. By characterizing the top 10% most frequent RTGs, we demonstrate the potential of identifying HCC drivers for HCC precision medicine and drug development.
2. Results
[0162] 2.1. Identification of RTGs in 22 HBV-HCC Tumors
[0163] The HBV DR1-2 region is a known integration hotspot. To identify HBV integration sites in a cost-effective manner, we applied an HBV DR1-2 enrichment NGS assay, as described in Materials and Methods, to enrich for HBV DNA in the DR1-2 region. NGS libraries prepared from archived DNA isolated from a cohort of 22 HBV-HCC formalin-fixed paraffin-embedded (FFPE) tissue specimens were used. NGS reads were analyzed using ChimericSeq [45]. We aimed to detect HBV junction sequences (HBV-JS) in 1-10 million NGS reads. Table 10 summarizes the NGS results and the major HBV-JS identified. Major HBV-JSs were defined as the most abundant HBV-JS in each tested sample that has at least 2 supporting reads and having more than 10% of total junction sequences. Assuming a 1:1 copy ratio of HBV to human genomic DNA, we obtained at least 1,000-fold enrichment resulting in an average of 1.00.3% on-target HBV reads (Table 10). Encouragingly, integrated HBV DNA was detected in 91% of HBV-HCC tumors from a 1-10 million NGS reads per sample (Table 10). Interestingly, of 27 major HBV-JS identified, seven junctions were found in frequently reported HCC driver genes (TERT and CCNE1) [46]. Junction-specific PCR primers were designed for 16 junctions with the most supporting reads and amplified in respective tissue DNA. PCR products for 14 of 16 tissue DNA samples were obtained and the junction sequences were confirmed by Sanger sequencing for an 88% validation rate (data not shown).
TABLE-US-00011 TABLE 10 Characterization of HBV-JSs identified in an in-house HBV-HCC tissue cohort. On- HBV-host junction target breakpoint nucleotide Patient Total NGS HBV (nt.) position ID Reads Read % HBV Human Gene 1 6.12E+06 1.1% 1773 Chr5: 1295082 TERT 2 6.24E+06 1.1% 1801 Chr5: 1295123 TERT 3 6.35E+06 1.1% 1801 Chr5: 1299125 TERT 4 3.55E+06 0.8% 1820 Chr19: 29812873 CCNE1 5 5.19E+06 1.2% 1827 Chr8: 64147161 LOC102724623 1795 Chr9: 45073810 Unknown 6 7.24E+06 1.4% 1801 Chr20: 53437062 LINE2 7 7.62E+06 1.3% 1901 Chr19: 29812390 CCNE1 1765 Chr6: 17125139 STMND1 8 2.11E+06 1.0% 1712 Chr10: 31192627 LOC101929352 9 2.26E+06 1.0% 1623 Chr9: 16709453 BNC2 10 1.17E+06 1.0% 1756 Chr11: 92048629 LINE1 11 2.64E+06 1.1% 1814 Chr5: 1284093 TERT 1802 Chr19: 29812598 CCNE1 1765 Chr4: 116834523 HAVCR1P2 1781 Chr14: 32527123 AKAP6 12 8.71E+06 1.3% 1826 Chr2: 74945009 LOC105369842 1722 ChrX: 130398440 RBMX2 13 5.78E+06 1.2% 1800 Chr10: 124355242 OAT 14 3.46E+06 0.9% 1825 Chr16: 29467674 LOC388242 15 1.67E+06 1.2% 1783 Chr5: 1299170 TERT 16 3.73E+06 0.8% 1796 Chr14: 67004392 GPHN 17 4.42E+06 0.8% 1772 Chr19: 35403632 LINC01531 18 1.22E+06 1.0% N.D. 19 5.04E+06 1.2% 1803 Chr1: 39524755 Unknown 1811 Chr14: 95571897 LOC100506999 20 5.37E+06 1.2% 1713 ChrX: 35786804 LTR Element 21 9.00E+06 1.3% N.D. 22 3.84E+05 0.04% 1727 Chr14: 103176826 LOC105370685 Avg. 4.36E+06 1.0% SD 2.60E+06 0.3% The nucleotide positions of the HBV (NC_003977.1) and human (GRCh38.p2) genome sequences at the HBV-human junction breakpoints. Within 150 kb of the HBV integration site breakpoint, the closest genes were identified by ChimericSeq software and listed as defined by NCBI's RefSeq gene database. Integration sites where no known gene was present within 150 kb are listed as Unknown. N.D., no detectable HBV-host junctions; Avg. SD, average standard deviation.
[0164] 2.2 Overview of the Studies for RTG Identification
[0165] The studies included in RTG identification are summarized in Table 11, where 19 studies utilize NGS-based and 8 studies utilize PCR-based approaches for HBV integration identification. For each study, the sample size and the number and percentage of HCC tumor or adj-tumor tissue that had detectable integration sites are listed. Note, most of the studies did not examine the DNA from the adj-tumor. Together, we compiled a total of 15,749 integration sites: 8,491 from tumor tissues and 7,258 from the adj-tumor, from 1,023 HCC patients. We found 80% of tumor tissues (n=1,276) and 50% of adj-tumor tissues (n=760) contained detectable integration sites. Of the seven studies that enriched for the whole HBV genome, on average 81% (range 57%-100%) of the tumors examined were found to have integrated HBV DNA (n=7) [6,22-24, 26, 27]. In two studies, 65% [28] and 91% (our study) of tumors examined were positive for integrated HBV DNA.
TABLE-US-00012 TABLE 11 Summary of HBV integration junction studies included in this analysis. # of subjects with integrated DNA* Information HCC identified, # of junctions* availability patients (% of total) identified in subjects Junction Clinical Study (n) Tumor Adj. Tumor Adj. Total sequence variables NGS- WGS [13] 3 3 (100%) 3 (100%) 15 33 48 Yes Yes based [14, 15] 91.sup.1 64 (45%) NA 223 NA 223 Yes Yes [16, 17] 81 76 (94%) 27 (33%) 344 55 399 Yes Yes [18] 2 2 (100%) NA 5 NA 5 Yes Yes [19] 5.sup.1,2 5 (100%) 4 (33%) 92 54 146 Yes [20] 5 5 (1005) NA 21 NA 21 Yes Yes [21] 3 2 (67%) NA 11 NA 11 Yes Yes Whole [22] 48 26 (54%) 13 (27%) 57 40 97 HBV [23] 60 51 (85%) NA 156 NA 156 Yes Yes Genome [6] 426 344 (81%) 159 (37%) 3486 739 4225 Yes.sup.3 [24] 49 28 (57%) NA 121 0 121 Yes Yes [25] 40 35 (90%) 40 (100%) 257 1425 1682 Yes Yes [26] 101 94 (93%) NA 510 NA 510 Yes Yes [27] 54 54 (100%) 52 (96%) 2870 4466 7336 Yes Yes DR1-2 [28] 40 26 (65%) 32 (80%) 42 254 296 Yes Yes this study 22 20 (91%) NA 27 NA 27 Yes Yes PCR- [29] 13 2 (15%) NA 2 NA 2 Yes based [30] 14 14 (100%) NA 14 NA 14 Yes Yes [31] 15 15 (100%) NA 15 NA 15 Yes [32] 60 55 (92%) NA 60 NA 60 Yes [33] 10 7 (70%) NA 8 NA 8 Yes Yes [34] 60 41 (68%) 43 (72%) 101 186 287 Yes Yes [35] 59.sup.4 45 (76%) 6.sup.5 (30%) 45 6 51 [36] 15 9 (60%) NA 9 NA 9 Total 1,276 1,023 (81%) 379 (50%) 8,491 7,258 15,749 .sup.1HBV (+) HCC cohorts-only; .sup.2three patients overlapping with Jiang 2012 [13] were removed, while the cumulative number of integration sites were compiled and considered unique integration sites due to different reported assay parameters; .sup.3only human chromosome sequence position provided; .sup.4cohorts of HBsAg ()/occult (+) and HBsAg (+) HCC patients; .sup.5out of 20 paired non-tumor tissue analyzed; *denote HBV DNA integration sites; WGS, whole genome next generation sequencing; Whole HBV genome, whole HBV genome enrichment was performed prior to NGS; DR1-2, HBV DR1-2 integration hotspot region was enriched prior to NGS; Adj. denotes adjacent HCC tumor DNA; NA denotes not available.
[0166] 2.3 Clinical Characteristics of HBV-HCC Patients with Integrated HBV DNA
[0167] The major clinical factors associated with HCC, such as age, gender, HBV genotype, and whether the HCC arose in a cirrhotic liver, designated as cirrhotic HCC, are summarized in Table 12. We categorize HCC patients based on the detectability of integrated HBV DNA in tumor tissue. The general characteristics of the HBV-HCC population [4, 47, 48] are also summarized. Analysis of each parameter was performed as available. The sample sizes that were available for data analysis of each parameter in each cohort are noted in parentheses. Overall, there is no significant difference between the two cohorts as compared to the overall HBV-HCC population for age and gender. The male:female ratio across the cohorts was not significantly different. Of the three reported HBV genotypes, genotype C was the most frequently reported in the integration-detectable tumor cohort (73%), while the tumor cohort with no detectable integration had only 2 patients with genotype reported and both were genotype C. In this cohort, 62% of HCC was derived from the cirrhotic liver in the integration-detectable tumor cohort, which is less than the 70-80% range found in the HBV-HCC population, reported from the literature [4]. 47% of patients with cirrhotic HCCs in the tumor cohort with no detectable integration were reported from 15 patients with available cirrhosis information.
TABLE-US-00013 TABLE 12 Overview of the major clinical features of HBV-HCC populations with and without detectable integrated HBV DNA in tumor tissue. eral Integrated HBV DNA in study cohort HBV-HCC Not Detectable Detectable populat (n = 381) (n = 1,025) Age (years) Range NA 33-83 11-85 Avg. SD 55-65 NA 59.9 13.3 54.9 11.6 (n = 37) (n = 359) Gender (Total) (n = 55) (n = 525) Male NA 40 395 Female 15 130 Male/Female 4:1 3.6:1 4:1 ratio Genotype (Total) (n = 2) (n = 84) B NA 0 22 C 2 61 D 0 1 Cirrhosis % 70-90% 46.7% 62.3% (n = NA) (n = 7/15) (n = 105/279) .sup.1, characteristics of the general HBV-HCC population obtained from the following references [4, 47, 48]; NA denotes not available; (n) denotes the number of patients available for the analysis; Avg. SD denotes average standard deviation (SD).
[0168] 2.4 Recurrent Sites of HBV DNA Integration
[0169] Next, we identified RTGs in the compiled HCC cohort and explored their associations with carcinogenesis. Of the 15,749 integration sites examined, 6,249 integration sites were found within 150 kb of gene coding sequences in HCC tumors, and 2,800 genes were identified. Among these 2,800 genes, we considered an integrated gene as a RTG if it was detected from at least two HCC patients and from two independent studies, as described in Materials and Methods. A total of 358 genes were found in 556 HCC patients, constituting 54% of the HBV-HCC patients with detectable HBV integration (n=1,023) and 43% of all HBV-HCC patients (n=1,276) in this cohort. The top 10% of the most frequently recurrent genes (n=36) are listed with summaries of their counts, identified integration sites, and associations with carcinogenesis in Table 13. Interestingly, these 36 genes either have previously suggested associations with carcinogenesis (28/36, 78%) or have no known function (8/36, 22%). As expected, TERT and MLL4 are the two most recurrent genes.
TABLE-US-00014 TABLE 13 The top 10% frequently reported recurrent HBV DNA integrated genes in tumors of HCC patients. Subjects Junctions RTGs (n) (n) Cancer associated [ref] TERT 257 415 Multiple cancers [49] MLL4 (KMT2B) 102 178 HCC [50, 51], Spindle cell sarcoma [52], Gastric cancer [53] PLEKHG4B 38 115 Neuroblastoma [54] LOC100288778 34 79 SCLC [55] DDX11L1 32 56 Function unknown SNTG1 25 27 Lung adenocarcinoma [56] CCNE1 23 41 Multiple cancers [57] PGBD2 21 50 Function unknown DUX4L4 20 35 DUX4 Ewing's sarcoma [58], ALL [59] ROCK1P1 19 34 Prostate cancer [60] ANKRD26P1 19 72 Breast cancer [61] PARD6G 18 41 Breast, kidney, liver, lung, ovary, and pancreatic cancers [62] CCNA2 18 31 Multiple cancers [63] FAM157A 14 22 Function unknown CWH43 14 73 CRC and TSHomas [64] LOC728323 13 22 Oral cancer [65] TPTE 13 30 HCC [66], prostate cancer [67] FN1 13 14 Multiple cancers [68] OR4C6 12 22 Pancreatic cancer [69] PRMT2 12 15 Glioblastoma [70] ROCK1 12 23 HCC [71-74], CRC [75] EMBP1 12 27 Oropharyngeal carcinoma [76], multiple primary cancers [77] ANHX 11 16 Function unknown DDX11L9 11 16 Function unknown SENP5 11 11 HCC[78], breast cancer [79] ZNF595 11 14 Lung cancer [80], Gastric cancer [81] CDRT7 10 10 Glioma[82] CTNND2 9 12 HCC [83, 84], prostate cancer [85], lung cancer [86] DDX11L5 9 16 Function unknown DUX2 9 9 Function unknown IL9R 9 45 HCC[87], lymphoma[88, 89] LINGO2 9 15 Gastric cancer[90] PARK2 9 14 Colorectal cancer [91] IPCEF1 8 9 CLL [92], thyroid cancers [93, 94] LLPH 8 10 Modulates neuronal growth [95] LOC100505817 8 11 Function unknown RTGs, integration recurrently targeted genes; HCC, Hepatocellular carcinoma; NSCLC, Non-small cell lung cancer; SCLC, Small cell lung cancer; ALL, Acute lymphocytic leukemia; CRC, Colorectal cancer; TSHoma, Thyrotropin-secreting Pituitary Adenoma; CLL, Chronic lymphocytic leukemia; RCC, Renal cell carcinoma.
[0170] Next, the 358 RTGs were queried for significantly enriched Gene Ontology (GO) pathways using Enrichr [96]. The top enriched biological pathway of the RTGs was chromatin-mediated maintenance of transcription with a combined score of 17.27 (p<0.05), suggesting possible links with oncogenesis (
[0171] 2.5 Integration Breakpoints in the HBV Genome
[0172] To investigate the distribution patterns of the integration breakpoints in the HBV genomes, we analyzed the HBV breakpoints in tumors (n=3,052) and adj-tumors (n=5,259), where available. We omitted studies that enriched for HBV DR1-2 sequences to assess HBV breakpoints distribution in a non-biased manner. Consistent with previous reports, we observed that 37% of breakpoints were within nt. 1300-1900 region in tumors and 56% in adj-tumors. This region covers the 3 end of the HBx gene and is where the initiation site of viral replication/transcription are located [6, 23, 27]. Also consistent with previous reporting [16], we observed a breakpoint hotspot in the HBV DR1-2 region, representing 15% for HCC tumors and 28% for adj-tumors of all HBV breakpoints (
[0173] 2.6 Genomic Breakpoints of TERT, MLL4 and PLEKHG4B RTGs
[0174] As HBV integration is believed to be non-sequence-specific, it was of interest to examine all RTG coordinates for similarity to each other. To do so, we plotted the available human and HBV breakpoint coordinates of the three most frequent RTGs identified, TERT, MLL4, and PLEKHG4B (
[0175] For TERT, the most frequently recurring RTG, 219 of 415 junctions from 161 HCC patients have both human and HBV breakpoint coordinates available. As expected, most of these breakpoints were centered between DR2 and DR1 of the viral genome and were highly concentrated at the promoter region of the TERT gene (
[0176] MLL4 is the second most frequently reported RTG with 102 junctions identified from 178 HCC patients studied. Among them, 115 breakpoints from 64 HCC patients have both human and viral coordinates available and are plotted in
[0177] The third most reported RTG is PLEKHG4B. The reported breakpoints were interestingly all centered within a 3 kb region that is around 131 kb away from the PLEKHG4B coding region. A total of 47 of 116 breakpoints from eight HCC patients have both viral and human coordinates available, as shown in
[0178] TERT hotspot promoter mutations (124, 146) are the most frequently reported mutations in HCC, found in about 50% of cases [99-104]. In HBV-HCC, up-regulation of TERT expression could also be caused by HBV integration at or near the TERT promoter region [14, 16, 22, 28, 29, 105]. Next, we compared the incidence of TERT promoter mutation and HBV integration. For our in-house cohort (n=22), shown in
3. Discussion
[0179] In this study, we compiled and studied over 15,000 HBV DNA integration sites from 1,276 HCC patients reported from 26 previous studies and our in-house study, to test our hypothesis that frequent recurrently targeted genes (RTGs) by HBV integration are HCC driver gene candidates. By using three criteria for RTG identification, we identified 358 RTGs. Encouragingly, the top 10% of the most frequent RTGs (n=36) either have known involvement in carcinogenesis (28/36, 78%) or have unknown function (8/36, 22%). By gene ontology analysis, RTGs were mapped to functions related to carcinogenesis. Together, we demonstrate the potential of HCC driver identification by characterization of frequent RTGs. More studies are needed to define the association of carcinogenesis with the frequency of RTGs.
[0180] Three criteria were applied to identify 358 RTGs from HBV integration sites in this study: (1) gene annotation within 150 kb of the breakpoint, the distance previously reported where host genes can be impacted by integration [105,106], (2) reports from 2 HCC patients to define recurrent, and (3) by 2 independent laboratories to avoid the possibility of contamination within a laboratory. We are aware that identification of RTGs across multiple studies is complex in nature, with multi-faceted underlying variables such as integration detection methodologies and patient populations. For instance, some studies do not contain any of 358 RTGs that we identified [35,36], while others have a high detection rate of a particular RTG, such as MLL4 [50], and cMYC [23]. We are also aware that different methodologies for identifying integrations may have different sensitivities that can result in detection of different integration site profiles. Despite these limitations, that may result in missing some RTGs, detection of RTGs constitute a potential HCC driver gene identification that maybe clinically useful for HCC patients.
[0181] Encouragingly, the most frequent 10% of RTGs (n=36) identified using the three criteria defined in this study either have known involvement in carcinogenesis (28/36, 78%) or have no known function (8/36, 22%). Although more studies are needed to explore the association of the genes that have unknown functions in hepatocarcinogenesis, of the genes that have known functions, all have been associated with either liver cancer or other cancers. Together with RTG ontology analysis where a significant mapping of genes to functions related to carcinogenesis was observed, our data suggests the potential to not only identify known HCC drivers, but to discover new HCC driver genes by characterization of frequent RTGs for precision disease management. More studies are needed to define the degree of association of carcinogenesis with the frequency of RTGs.
[0182] By detailing the three most frequent RTG junction coordinates (TERT, MLL4, and PLEKHG4B), we reveal three important features. First, as expected, the majority of junction coordinates are different, confirming the non-sequence-specific integration in the host genome. The overlapping identical junctions identified in the TERT promoter region highlight the potential importance of the site on impairing the expression of the TERT gene. Second, an interesting pattern was observed in PLEKH4G4B junctions. Although a microhomology search did not suggest the homologous recombination was the cause of this interesting pattern, a highly repetitive sequence, satellite sequences, and a motif of TAAACCCTAAC were identified in these regions. Together suggest possible repeated breakpoints in the region. This supports a possibility of occasional homologous recombination in addition to the non-homologous end-joining mechanism of HBV integration. Since these unique integration pattern sequences was reported from one study and was not reported to be validated in the original tissue DNA, an artifact has not been excluded. Lastly, the mutually exclusive detection of TERT promoter mutations and TERT integration is shown by our small cohort of 22 HCC patients and confirmed by a larger compiled cohort of 151 HCC patients [24,26]. When describing the TERT genetic alterations as an HCC driver, TERT promoter mutations only account for 50% of alterations, indicating the importance of identifying TERT integration. This further emphasizes the need for analysis of frequent RTGs to better characterize HCC.
[0183] Most HCC cases develop in a cirrhotic background, though up to 30% of HBV-HCC cases were reported in the absence of cirrhosis (non-cirrhotic HCC) [4,48]. In our study cohort, we identified slightly (but not significant) lower rates (62%) of cirrhotic HCC when integration was detected. In the case of TERT-integrated HCC (n=257) in this study cohort, 51 had information to assess whether the HCC was rising in a cirrhotic background. We identified a significant association (p=0.01) of TERT integrations with cirrhotic HCCs compared to non-cirrhotic HCCs (data not shown). While this cannot be applied to the remaining 206 TERT-integrated HCC patients, in which there was no available information to assess the existence of cirrhosis, it is in line with the association of TERT hotspot promoter mutations with cirrhosis [107].
4. Materials and Methods
[0184] 4.1. Data Mining/Search Strategy
[0185] We searched PubMed (2000-Dec. 1, 2018) databases using Medical Subject Heading (MeSH) terms hepatitis B virus, HBV integration, hepatitis B integration sites to identify the literature that have reported HBV integration sites by either NGS- or PCR-based approaches. Additional studies were obtained by cross-referencing from the literature. We included only studies in English and studies that included HCC subjects. We included all studies that identified HBV integration sites using NGS-based approaches. For the studies using PCR-based methods, we only included the studies that analyzed a study sample size of 10 or more HCC patients. HBV integration sites identified by RNA-seq or transcriptome NGS [7, 8, 109] were not included as expression of integrated sequences can be due to many host cellular factors that enable expression of integrated sequences and thus are not within the scope of this study. We filtered out repeated integration sites to ensure each integration site was included only once in our study, with the exception of two studies that utilized different methods on overlapping samples [13,19]. A total of 26 reported studies in addition to our study are included as summarized in Table 2.
[0186] 4.2. In-House HCC Specimens and HBV Integration Analysis
[0187] Archived FFPE tumor tissue DNA (Table 14), as described previously [110,111], from stage I-IIIB patients (n=32) was obtained from the National Cheng-Kung University Medical Center, Taiwan, collected in accordance with the guidelines of the Institutional Review Board. An HBV enrichment NGS assay (JBS Science, Inc) was used. Briefly, NGS libraries were generated, enriched for HBV DR1-2 sequences through two rounds of a multiplex biotinylated HBV primer extension capture (PEC). Libraries were sequenced on the Illumina MiSeq platform (Penn State Hershey Genomics Sciences Facility at Penn State College of Medicine, Hershey, Pa.) and analyzed using ChimericSeq [45] to identify HBV-host junction sequences. Tailored junction-specific PCR-Sanger sequencing was designed and used to validate each HBV integration site of interest, identified by HBV-enriched NGS assay.
TABLE-US-00015 TABLE 14 Clinical characteristics of in-house HBV-HCC patient cohort (n = 22). Age Gender Cirrhosis Tumor Tumor size Patient ID (years) (M/F) (/+) stage* (cm) 1 71 M + 1 3.5 2 68 M NA 9.0 3 63 F + NA 3.7 4 44 F 1 3.5 5 43 M 2 3.0 6 68 M 1 6.5 7 58 M 2 15.0 8 57 M 1 4 9 29 M + 2 7 10 41 M + 1 2 11 33 F + 1 2.5 12 57 M + 1 3 13 73 M + 4 11.0 14 49 M + 2 3.4 15 61 M 2 2.3 16 75 F 1 3.0 17 47 M 2 4.5 18 74 F + 3A 5.5 19 75 M 1 1.9 20 55 F + 1 4.0 21 46 F + 4 1.5 22 39 F 2 10 *denotes HCC tumors were staged using the tumor-node-metastasis (TNM) staging system.
[0188] 4.3 TERT Promoter Mutation Analysis by PCR-Sanger Sequencing
[0189] HCC tissue DNA was used to amplify a 163-bp region (Chr5:1295151-1295313) of the TERT promoter by using HotStart Plus Taq Polymerase (Qiagen, Valencia, Calif.) with forward primer 5-CAGCGCTGCCTGAAACTC-3 (SEQ ID NO: 212) and reverse primer 5-GTCCTGCCCCTTCACCTT-3 (SEQ ID NO: 213). The PCR products were sequenced at the NAPCore Facility at the Children's Hospital of Philadelphia (Philadelphia, Pa.) and analyzed using ClustalW software [112].
[0190] 4.4 Identification of Integration Recurrently Targeted Host Genes (RTGs)
[0191] To identify host genes that maybe affected by HBV DNA integration in a universal manner across all studies, we identify the closest gene within 150 kb of the integration event, the distance previously reported where host genes can be impacted by integration [105,106]. To define the status of a RTG, we assessed whether the reported gene was identified in tumors from (A) two or more HCC patients and (B) two or more independent studies to avoid potential cross contamination within a study. The full list of identified RTGs can be provided upon request.
[0192] 4.5 Gene Functional Enrichment Pathway Analysis
[0193] 358 RTGs were subjected to enrichment pathway analysis using Enrichr (http://amp.pharm.mssm.edu/Enrichr), to identify significantly (p<0.05) enriched pathways as determined by gene ontology.
5. Conclusions
[0194] This HBV integration study using an in-house HBV-HCC cohort, in conjunction with previously reported HBV integration sites, allows us to test the hypothesis that HCC drivers can be identified by characterizing frequent recurrent targeted genes (RTGs) by HBV integration. By analyzing over 15,000 HBV integration sites, we bring forth a RTG consensus and demonstrate that characterization of frequent RTGs can be a novel approach to discover or identify HCC drivers for HBV-HCC precision medicine and drug development/discovery.
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