Abstract: Novel fusion molecules and uses are disclosed.

Abstract: Provided herein are HLA-PEPTIDE targets and multispecific antigen binding proteins that bind HLA-PEPTIDE targets. Provided herein is an isolated multispecific antigen binding protein (ABP), comprising: a first antigen binding domain (ABD) that specifically binds to a human leukocyte antigen (HLA)-PEPTIDE target; and an additional ABD that specifically binds an additional antigen, wherein the HLA-PEPTIDE target comprises an HLA-restricted peptide complexed with an HLA Class I molecule, wherein the HLA-restricted peptide is located in the peptide binding groove of an ?1/?2 heterodimer portion of the HLA Class I molecule, and wherein the HLA-PEPTIDE target is selected from Table A, Table A1, or Table A2.

Abstract: 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.

Abstract: The present invention provides therapeutic and diagnostic methods and compositions for cancer, for example, bladder cancer. The invention provides methods of treating bladder cancer, methods of determining whether a patient suffering from bladder cancer is likely to respond to treatment comprising a PD-L1 axis binding antagonist, methods of predicting responsiveness of a patient suffering from bladder cancer to treatment comprising a PD-L1 axis binding antagonist, and methods of selecting a therapy for a patient suffering from bladder cancer, based on somatic mutation levels of genes of the invention (e.g., somatic mutation levels in a tumor sample obtained from the patient).

Abstract: A method for identifying neoantigens that are likely to be presented on a surface of tumor cells of a subject. Peptide sequences of tumor neoantigens are obtained by sequencing the tumor cells of the subject. The peptide sequence of each of the neoantigens is associated with one or more k-mer blocks of a plurality of k-mer blocks of the nucleotide sequencing data of the subject; The peptide sequences and the associated k-mer blocks 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 an MHC allele on the surfaces of the tumor cells of the subject. A subset of the neoantigens is selected based on the presentation likelihoods.

Abstract: The present invention provides therapeutic and diagnostic methods and compositions for cancer, for example, lung cancer (e.g., NSCLC), bladder cancer (e.g., UC), kidney cancer (e.g., RCC), breast cancer (e.g., TNBC), or melanoma. The invention provides methods of treating cancer (e.g., lung cancer (e.g., NSCLC), bladder cancer (e.g., UC), kidney cancer (e.g., RCC), breast cancer (e.g., TNBC), or melanoma), methods of determining whether a patient suffering from cancer (e.g., lung cancer (e.g., NSCLC), bladder cancer (e.g., UC), kidney cancer (e.g., RCC), breast cancer (e.g., TNBC), or melanoma) is likely to respond to treatment comprising a PD-L1 axis binding antagonist, methods of predicting responsiveness of a patient suffering from cancer (e.g., lung cancer (e.g., NSCLC), bladder cancer (e.g., UC), kidney cancer (e.g., RCC), breast cancer (e.g., TNBC), or melanoma) to treatment comprising a PD-L1 axis binding antagonist, and methods of selecting a therapy for a patient suffering from cancer (e.g.

Abstract: Methods of treating a head and neck cancer are disclosed.

Abstract: Novel mutant ESR1 molecules and uses are disclosed.

Abstract: The present invention provides therapeutic and diagnostic methods and compositions for cancer, for example, bladder cancer. The invention provides methods of treating bladder cancer, methods of determining whether a patient suffering from bladder cancer is likely to respond to treatment comprising a PD-L1 axis binding antagonist, methods of predicting responsiveness of a patient suffering from bladder cancer to treatment comprising a PD-L1 axis binding antagonist, and methods of selecting a therapy for a patient suffering from bladder cancer, based on somatic mutation levels of genes of the invention (e.g., somatic mutation levels in a tumor sample obtained from the patient).

Abstract: A method for identifying neoantigens that are likely to be presented on a surface of tumor cells of a subject. Peptide sequences of tumor neoantigens are obtained by sequencing the tumor cells of the subject. The peptide sequence of each of the neoantigens is associated with one or more k-mer blocks of a plurality of k-mer blocks of the nucleotide sequencing data of the subject; The peptide sequences and the associated k-mer blocks 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 an MHC allele on the surfaces of the tumor cells of the subject. A subset of the neoantigens is selected based on the presentation likelihoods.

Abstract: Novel fusion molecules and uses are disclosed.

Abstract: Novel ALK and NTRK1 fusion molecules and uses are disclosed.

Abstract: Disclosed herein is a system and methods for determining the alleles, neoantigens, and vaccine composition as determined on the basis of an individual's tumor mutations. Also disclosed are systems and methods for obtaining high quality sequencing data from a tumor. Further, described herein are systems and methods for identifying somatic changes in polymorphic genome data. Finally, described herein are unique cancer vaccines.

Abstract: A method of analyzing a tumor sample comprising: (a) acquiring a library comprising a plurality of tumor members from a tumor sample; (b) contacting the library with a bait set to provide selected members; (c) acquiring a read for a subgenomic interval from a tumor member from said library; (d) aligning said read; and (e) assigning a nucleotide value (e.g., calling a mutation) from said read for the preselected nucleotide position, thereby analyzing said tumor sample.

Abstract: A method of analyzing a tumor sample comprising: (a) acquiring a library comprising a plurality of tumor members from a tumor sample; (b) contacting the library with a bait set to provide selected members; (c) acquiring a read for a subgenomic interval from a tumor member from said library; (d) aligning said read; and (e) assigning a nucleotide value (e.g., calling a mutation) from said read for the preselected nucleotide position, thereby analyzing said tumor sample.

Abstract: Novel ALK and NTRK1 fusion molecules and uses are disclosed.

Abstract: Methods of treating a head and neck cancer are disclosed.

Abstract: Disclosed herein are compositions that include antigen-encoding nucleic acid sequences and/or antigen peptides. Also disclosed are nucleotides, cells, and methods associated with the compositions including their use as vaccines.

Abstract: Disclosed herein is a system and methods for determining the alleles, neoantigens, and vaccine composition as determined on the basis of an individual's tumor mutations. Also disclosed are systems and methods for obtaining high quality sequencing data from a tumor. Further, described herein are systems and methods for identifying somatic changes in polymorphic genome data. Finally, described herein are unique cancer vaccines.

Abstract: Provided herein are HLA-PEPTIDE targets and antigen binding proteins that bind HLA-PEPTIDE targets. Also disclosed are methods for identifying the HLA-PEPTIDE targets as well as identifying one or more antigen binding proteins that bind a given HLA-PEPTIDE target.