Provided herein are binding proteins recognizing HPV16 E7 antigen and uses thereof.

A method for selecting cancer patient for treatment with Seneca Valley Virus (SVV) by determining expression of ANTXR1 in a cancerous tissue in a cancer patient; and designating the cancer patient as a candidate for treatment with SVV if normal levels or elevated levels of ANTXR1 expression is detected in the cancerous tissue. Also a method for treating a cancer patient with SVV is disclosed.

This invention relates to methods for predicting a prognosis of a patient with cancer in need of an anti-cancer treatment comprising measuring a cytokine score from a sample obtained from the patient. In some embodiments, the subject is administered an anti-cancer treatment, e.g., an anti-PD-1 antibody, following the cytokine score measurement. In some embodiments, the cancer is lung cancer.

A method of treating lung cancer is disclosed. The method comprises administering to the subject a therapeutically effective amount of an agent that downregulates an amount or activity of a polypeptide selected from the group consisting of CASC5, MYOF, CTNS, FCGR2B, PCDHGC5, POMGNT2, ACSL1, CTAGE5, TECPR2, WDR48, MCPH1, PPP2R3C, ADRB1, JAG2, GEMIN7, PTPRB, PRMT9, PSME4, Ube2L3, TP53RK and PSME3.

The present disclosure provides technologies for target entity detection. One aspect of the present disclosure provides technologies for detection (e.g., early detection) of a disease, disorder, or condition (e.g., cancer). In another aspect, technologies provided herein are useful for selecting and/or monitoring and/or evaluating efficacy of, a treatment administered to a subject in need thereof, e.g., a subject determined to have or susceptible to cancer. In some embodiments, technologies provided herein are useful for development of companion diagnostics, e.g., by measuring tumor burdens and changes in tumor burdens in conjunction with therapeutics.

A method for identifying T-cells that are antigen-specific for at least one neoantigen that is likely to be presented by class II MHC alleles on surfaces of tumor cells of a subject. Peptide sequences of tumor neoantigens are obtained by sequencing the tumor cells of the subject. The peptide sequences are input into a machine-learned presentation model to generate presentation likelihoods for the tumor neoantigens, each presentation likelihood representing the likelihood that a neoantigen is presented by the class II MHC alleles on the surfaces of the tumor cells of the subject. A subset of the neoantigens is selected based on the presentation likelihoods. T-cells that are antigen-specific for at least one of the neoantigens in the subset are identified. These T-cells can be expanded for use in T-cell therapy. TCRs of these identified T-cells can also be sequenced and cloned into new T-cells for use in T-cell therapy.

Disclosed are methods, components, and systems for diagnosing, prognosing, and treating a cell proliferative disease or disorder such as cancer. The methods, components, and systems relate to identifying markers that may be utilized to diagnose and/or prognose a subject and optionally treat the diagnosed and/or prognosed subject by administering a topoisomerase poison to the subject based on the marker having been identified. Markers identified in the methods may include ribosomal subunit proteins and genes encoding ribosomal subunit proteins. Based on the marker being identified in the subject, the subject may be identified as having responsiveness to a topoisomerase poison, such as etoposide and/or doxombicin. As such, the subject may be treated by administering the topoisomerase poison to treat the cell proliferative disease or disorder after the marker has been identified.

The present invention is directed to methods of diagnosing, prognosing, and managing treatment of cancer in a subject. These methods involve selecting a subject having cancer and obtaining, from the selected subject, a population of either exomeres having a diameter less than 50 nm, small exosomes having a diameter of 60-80 nm, or large exosomes having a diameter of 90-120 nm. The exomeres, small exosomes, or large exosomes are recovered from the sample, and the exomeres, small exosomes, or large exosomes or portions thereof are contacted with one or more reagents suitable to detect: (1) higher or lower levels, relative to a standard for subjects not having cancer, or the presence or absence, of one or more proteins contained in said exomeres, small exosomes, or large exosomes, (2) higher or lower levels, relative to a standard for subjects not having cancer, or the presence or absence, of one or more N-glycans contained in said exomeres, small exosomes, or large exosomes, (3) higher or lower levels, relative to a standard for subjects not having cancer, or the presence or absence, of one or more lipids contained in said exomeres, small exosomes, or large exosomes, (4) the presence or absence of one or more genetic mutations in nucleic acid molecules associated with cancer and contained in said exomeres, small exosomes, or large exosomes, or (5) combinations thereof. Cancer is then diagnosed, prognosed, or treatment is modified based on this information.

Disclosed herein are a method and a biomarker for predicting efficacy and prognosis of or resistance to an immunotherapy. The use of the biomarkers (TCTP, EGFR, AKT, MCL1, and/or CXCL10) of the present disclosure allows the prediction of resistance to or prognosis of a cancer immunotherapeutic agent and the selection of a therapy guaranteeing therapeutic benefit, thereby finding advantageous applications in treating cancers or tumors resistant to cancer immunotherapeutic agents.

The present invention relates generally to the field of antibody detection, and in particular relates to methods involving the detection of autoantibodies relating to lung cancer in a sample comprising patient bodily fluid. In particular, the present invention relates to a method of detecting lung cancer in a mammalian subject by detecting three or more autoantibodies in a test sample, wherein three of the autoantibodies are immunologically specific for the tumour marker antigens p53, SSX1, and either p62 or KOC. The invention also relates to in vitro methods of determining an autoantibody profile, methods of diagnosing and treating lung cancer, methods of predicting response to a lung cancer treatment, use of a panel of three or more tumour marker antigens for the detection of lung cancer, and kits for the detection of autoantibodies.