The invention relates to a collection of signature peptides representing at least 10 proteins for use in cancer diagnosis and/or prognosis, to an artificial protein comprising signature peptides representing at least 10 proteins and to a nucleic acid construct encoding for such an artificial protein. The invention further relates to a collection of at least 10 proteins for use in cancer diagnosis and/or prognosis. Additionally, the invention relates to a method for cancer diagnosis and/or prognosis comprising the step of analyzing at least 10 proteins in a urine sample of a subject. Finally, the invention relates to an immunoassay product comprising antibodies for detecting at least 10 proteins.

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 expression levels of a biomarker of the invention (e.g., PD-L1 expression levels in tumor-infiltrating immune cells in a tumor sample obtained from the patient) and/or based on the determination of a tumor sample subtype.

This document relates to methods and materials for detecting premalignant and malignant neoplasms. For example, methods and materials for determining whether or not a stool sample from a mammal contains nucleic acid markers or polypeptide markers of a neoplasm are provided.

The disclosure provides novel personalized therapies, kits, transmittable forms of information and methods for use in treating patients having cancer, wherein the cancer is amenable to therapeutic treatment with an inhibitor, e.g., an inhibitor of any of the targets disclosed herein. Kits, methods of screening for candidate inhibitors, and associated methods of treatment are also provided.

The present description relates to the use of a SRSF3 agent for regulating the function of a myeloid cell, such as a microglial cell and/or monocyte, for treating neurological conditions, cancers, bacterial infections and viral infections wherein the SRSF3 agent inhibits expression or function of SRSF3.

Provided herein are methods for detecting a Ewing sarcoma breakpoint region 1 (EWSR1) fusion gene encoding a neoantigen (e.g., in a patient sample), as well as methods of prognosis and treatment related thereto, in some embodiments, the methods further comprise administering a cancer immunotherapy. In some embodiments, the EWSR1 fusion gene is a fusion gene between EWSR1 and WT1, Fill, ERG, FEV, NR4A3, ATF1, CREB1, CREM, CREB3L/CREB3L2, PA7Z1, NFATC2, KLFI5, C11orf93, ZNF444, PBX1, DDIT3, or TFCP2 that encodes a neoantigen.

The disclosure features systems and methods for measuring and diagnosing target constituents bound to labeling particles in a sample. The systems include a radiation source, a sample holder, a detector configured to obtain one or more diffraction patterns of the sample each including information corresponding to optical properties of sample constituents, and an electronic processor configured to, for each of the one or more diffraction patterns: (a) analyze the diffraction pattern to obtain amplitude information and phase information corresponding to the sample constituents; (b) identify one or more particle-bound target sample constituents based on at least one of the amplitude information and the phase information; and (c) determine an amount of at least one of the particle-bound target sample constituents in the sample based on at least one of the amplitude information and the phase information.

Provided herein are B7-H3 antibodies, fragments of such antibodies, and compositions comprising the same. The antibodies, antibody fragments and compositions are useful in a number of analytical methods, including immunohistochemical and immunocytochemical detection and analysis of B7-H3. Also provided herein are isolated peptides and fusion proteins containing immunogenic determinants for said B7-H3 antibodies, animals immunized with the peptides and fusion proteins, isolated B cells obtained from the animals, and hybridomas made from the isolated B cells.

Disclosed herein are diagnostic and therapeutic methods for the treatment of hematologic cancers, including multiple myeloma (MM), as well as related compositions. In particular, the invention relates to diagnostic and therapeutic methods for treatments involving a PD-L1 axis binding antagonist (e.g., an anti-PD-L1 antibody, e.g., atezolizumab) and an anti-CD38 antibody (e.g., an anti-CD38 antagonist antibody, e.g., daratumumab) for use in treating hematologic cancer (e.g., a multiple myeloma (MM), e.g., a relapsed or refractory MM).

A deep learning based diagnostic model capable of diagnosing multi-cancer using biomarker group-related value information is trained by using a method including steps of: in response to acquiring training data including the biomarker group-related value information and GT (Ground Truth) cancer information for each of patients, inputting the training data into the diagnostic model and then instructing the diagnostic model to (i) allow each hidden layer, among a first hidden layer to a K-th hidden layer, to perform a fully connected operation on its previous sub input values for training obtained from its previous hidden layer, wherein K is an integer greater than or equal to 1, and then (ii) allow an output layer to perform a fully connected operation on K-th sub input values for training obtained from the K-th hidden layer, to thereby output multi-cancer diagnosis information for training as a result of predicting multi-cancer.