Patent classifications
G01N33/57407
SALIVARY BIOMARKERS FOR THE DETECTION OF EPIDERMOID CANCER OF THE HEAD AND NECK
Present invention relates to the in vitro use of the level or concentration in a salivary or breath sample of bacteria belonging to the Alloprevotella, Prevotella, Campylobacter, Rothia, Catonella, Porphyromona, Fretibacterium genus, or any combination thereof, for the diagnosis of carcinomas or epidermoid cancers, especially epidermoid cancer of the head and neck, in a patient, or to obtain useful data that allow such a diagnosis.
Methods for computer processing sequence reads to detect molecular residual disease
Disclosed herein are methods for use in detection of molecular residual disease. The methods may comprise deep sequencing a panel of genomic regions in cell-free DNA molecules and computer processing sequence reads to detect variants that are indicative of molecular residual disease.
DETECTING NEOPLASM
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.
METHODS FOR PHOTOIMMUNOTHERAPY AND RELATED BIOMARKERS
Provided are methods involving the use of biomarkers, in relation to photoimmunotherapy, such as photoimmunotherapy induced by activation of a phthalocyanine dye conjugated to a targeting molecule that binds a protein on tumor cell, for example, an IR700-antibody conjugate, and combination therapies, for example, that include photoimmunotherapy and an additional therapeutic agent, such as an immune modulating agent. In some aspects, the provided embodiments can be used to identify or select subjects for photoimmunotherapy and/or the combination therapy, or to assess the likelihood of response to photoimmunotherapy and/or to the additional therapeutic agents. Features of the methods and uses provide various advantages, such as improved efficacy. In some aspects, the provided embodiments can be used to provide personalized medicine and tailored therapy regimens for subjects. Also provided are therapeutic methods involving the use of biomarkers in the treatment of diseases and conditions, including tumors or cancers.
Methods and Compositions for Diagnosing and Treating Cancer
The present invention includes methods for detecting B-cell like neutrophils (“BNeuts”) comprising: obtaining a biological sample from a subject; and detecting whether BNeuts are present or increased in the biological sample by contacting the biological sample with an agent capable of detecting CD3− CD56−CD79b.sup.+CD66b.sup.+ PAX5.sup.+CD19− cells, CD3−CD56−CD79a.sup.+CD79b.sup.+CD66b.sup.+ PAX5.sup.+CD19− cells, or both, and detecting the increase of BNeuts in the biological sample.
MAGEA1 IMMUNOGENIC PEPTIDES, BINDING PROTEINS RECOGNIZING MAGEA1 IMMUNOGENIC PEPTIDES, AND USES THEREOF
Provided herein are MAGEA1 immunogenic peptides, binding proteins recognizing MAGEA1 immunogenic peptides, and uses thereof.
Methods of spectroscopic analysis
A method of selecting wavelengths of radiation for discriminating a first cell or tissue type from a different cell or tissue type is described. First and second sets of absorption spectra are obtained, each set comprising spectra obtained at a plurality of different spatial regions of the first cell or tissue type and of the different cell or tissue type, respectively. Sets of corresponding metrics are defined for the first and second sets of absorption spectra for each spatial region. Each metric comprises information corresponding to the absorption for at least two different wavelengths. The metrics in each set comprise different combinations of wavelengths. A characteristic value is generated for each metric. Distributions are generated for each metric using corresponding characteristic values for the first cell or tissue type and for the different cell or tissue type and compared to determine an extent of similarity. The metrics are ranked based on the extent of similarity and wavelengths associated with higher ranked metrics, having higher similarities, are selected.
Articles of manufacture and methods related to toxicity associated with cell therapy
Provided are methods and articles of manufacture for use with cell therapy for the treatment of diseases or conditions, e.g., cancer, including for predicting and treating a toxicity. In some embodiments, the toxicity is a neurotoxicity or cytokine release syndrome (CRS), such as a severe neurotoxicity or a severe CRS. The methods generally involve detecting a marker by assaying a biological sample from a subject that is a candidate for treatment, optionally with a cell therapy, to determine if the subject is at risk for developing the toxicity, such as neurotoxicity or CRS or severe neurotoxicity or severe CRS. In some embodiments, the methods and articles of manufacture further includes a regent for assaying the biological sample and instructions for determining the percentage or number of cells positive for the marker in the biological sample.
Engineered vaccinia virus
An engineered vaccinia virus, a pharmaceutical composition containing the same, and methods for use in treating a subject in need using the same are provided. The engineered vaccinia virus includes a mutated viral sequence and a heterologous sequence. The mutated viral sequence is used for selective replication in tumor cells and/or activation of immune cells. The heterologous sequence encodes an immune co-stimulatory pathway activating molecule, immunomodulator gene, a truncated viral envelope gene, and/or a tumor suppressor. The heterologous sequence is stably incorporated into the genome of the engineered vaccinia virus. The pharmaceutical composition includes an effective amount of the engineered vaccinia virus and a pharmaceutical acceptable vehicle. The methods for use in treating the subject in need include administering the engineered vaccinia virus to the subject.
PREDICTING RESPONSE TO PD-1 AXIS INHIBITORS
The invention is concerned with a method of predicting response to a PD-1 axis inhibitor such as anti-PD-L1 antibody by determining the abundance of dendritic cells (DCs) in a tumor tissue sample. The abundance of DCs characterized by enhanced expressions of XCR1, IRF8, BATF3 and FLT3 predicts clinical response to the PD-L1 blockade treatment.