Abstract: Techniques for training a statistical model for determining whether a subject is likely to respond to a checkpoint blockade therapy. The techniques include obtaining, for each subject in a plurality of subjects having responders to a checkpoint blockade therapy and non-responders to the therapy, expression data indicating expression levels for a plurality of genes; determining, for the plurality of genes, expression level differences between the responders and the non-responders using the expression data; identifying, using the determined expression level differences, a subset of genes associated with a therapy in the plurality of genes; training, using the expression data, a statistical model for predicting efficacy of the therapy, the training comprising: identifying at least some of the subset of genes as a predictor set of genes to include in the statistical model; and estimating, using the expression data, parameters of the statistical model associated with the predictor set of genes.

Abstract: Techniques for determining predicted response of a subject to multiple therapies using the subject's sequencing data. The techniques include accessing biomarker information indicating a distribution of values for each biomarker in at least a reference subset of a plurality of biomarkers across a respective group of people, each of the plurality of biomarkers being associated with at least one therapy in a plurality of therapies; determining, using the sequencing data and the biomarker information, a normalized score for each biomarker in at least a subject subset of the plurality of biomarkers to obtain a set of normalized biomarker scores for the subject; and determining, using the set of normalized biomarker scores for the subject, therapy scores for the plurality of therapies, each of the therapy scores indicative of predicted response of the subject to administration of a respective therapy in the plurality of therapies.

Abstract: Various methods, systems, computer readable media, and graphical user interfaces (GUIs) are presented and described that enable a subject, doctor, or user to characterize or classify various types of cancer precisely. Additionally, described herein are methods, systems, computer readable media, and GUIs that enable more effective specification of treatment and improved outcomes for patients with identified types of cancer. Some embodiments of the methods, systems, computer readable media, and GUIs described herein comprise obtaining RNA expression data and/or whole exome sequencing (WES) data for a biological sample from a subject; determining a molecular-functional (MF) profile for the subject; identifying an MF profile cluster with which to associate the MF profile for the subject; and clustering the plurality of MF profiles to obtain the MF profile clusters.

Abstract: Various methods, systems, computer readable media, and graphical user interfaces (GUIs) are presented and described that enable a subject, doctor, or user to characterize or classify various types of cancer precisely. Additionally, described herein are methods, systems, computer readable media, and GUIs that enable more effective specification of treatment and improved outcomes for patients with identified types of cancer. Some embodiments of the methods, systems, computer readable media, and GUIs described herein comprise obtaining RNA expression data and/or whole exome sequencing (WES) data for a biological sample; determining a molecular-functional (MF) profile using the data; determining sets of visual characteristics for GUI elements using the data; generating a personalized GUI using the determined visual characteristics; and presenting the generated personalized GUI to a user.

Abstract: The present invention relates to the field of medicine, specifically, to the field of chemical and pharmaceutical industry and concerns ezrin-derived peptides, in particular, a peptide comprising an amino acid sequence of general formula (I) X1 EKKRRETVERE X2X3, wherein each X represents a non-polar amino acid residue. The use of the peptides as immunostimulatory agents, and more specifically, for use in treating and preventing antiviral, antibacterial and antifungal infections, and treatment of diseases of the GI tract, in particular ulcerative disorders of the GI tract. The present invention also relates to pharmaceutical compositions comprising the peptides. Further, the invention relates to methods of treatment of infection and ulcerative diseases of the GI tract comprising administering the peptides to patients in need thereof.

Abstract: The present invention relates to the field of medicine, specifically, to the field of chemical and pharmaceutical industry and concerns ezrin-derived peptides, in particular, a peptide comprising an amino acid sequence of general formula (I) X1 EKKRRETVERE X2X3, wherein each X represents a non-polar amino acid residue. The use of the peptides as immunostimulatory agents, and more specifically, for use in treating and preventing antiviral, antibacterial and antifungal infections, and treatment of diseases of the GI tract, in particular ulcerative disorders of the GI tract. The present invention also relates to pharmaceutical compositions comprising the peptides. Further, the invention relates to methods of treatment of infection and ulcerative diseases of the GI tract comprising administering the peptides to patients in need thereof.

Abstract: A peptide which has at least 80% identity to a fragment of Domain A or B of the Hepreceptor of ezrin, is used in the treatment of viral hepatitis.