Abstract: Methods described herein relate to constructing therapeutic fusion-specific vaccine libraries, selecting a therapeutic fusion-specific vaccine for a cancer patient, and/or constructing a de novo therapeutic fusion-specific vaccine for patients having a gene fusion that is absent from a fusion-specific vaccine library.

Abstract: Techniques for determining whether a subject is likely to respond to an immune checkpoint blockade therapy.

Abstract: Techniques for determining whether a subject is likely to respond to an immune checkpoint blockade therapy.

Abstract: Techniques for determining whether a subject is likely to respond to an immune checkpoint blockade therapy.

Abstract: Methods described herein relate to constructing therapeutic fusion-specific vaccine libraries, selecting a therapeutic fusion-specific vaccine for a cancer patient, and/or constructing a de novo therapeutic fusion-specific vaccine for patients having a gene fusion that is absent from a fusion-specific vaccine library.

Abstract: Techniques for determining whether a subject is likely to respond to an immune checkpoint blockade therapy.

Abstract: Methods described herein relate to constructing therapeutic fusion-specific vaccine libraries, selecting a therapeutic fusion-specific vaccine for a cancer patient, and/or constructing a de novo therapeutic fusion-specific vaccine for patients having a gene fusion that is absent from a fusion-specific vaccine library.

Abstract: Techniques for determining whether a subject is likely to respond to an immune checkpoint blockade therapy.

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: Provided herein are prognostic and diagnostic methods for predicting likelihood of clinical response of a subject having cancer to treatment with an immunotherapeutic agent. Also provided herein are methods for treating a subject having cancer with an immunotherapeutic agent after determining likelihood of clinical response of the subject to such treatment.

Abstract: The present invention provides a process for characterizing a glatiramer acetate related drug substance or drug product comprising the steps of: a) obtaining a batch of the glatiramer acetate related drug substance or drug product; b) immunizing a mammal with a predetermined amount of a glatiramer acetate related drug substance or drug product; c) preparing a culture of cells from the mammal of step b) at a predetermined time after immunization; d) incubating cells from the culture of step c) with a predetermined amount of the glatiramer acetate drug related substance or drug product of step a); and e) determining the level of expression of at least one gene disclosed herein or determining the level of biological activity of the cells of step c) as disclosed herein, thereby characterizing the glatiramer acetate related drug substance or drug product of step a).