Abstract: Omics patient data are analyzed using sequences or diff objects of tumor and matched normal tissue to identify patient and disease specific mutations, using transcriptomic data to identify expression levels of the mutated genes, and pathway analysis based on the so obtained omic data to identify specific pathway characteristics for the diseased tissue. Most notably, many different tumors have shared pathway characteristics, and identification of a pathway characteristic of a tumor may thus indicate effective treatment options ordinarily not considered when tumor analysis is based on anatomical tumor type only.

Abstract: cfRNA is used to identify and quantitate expression levels of disease related genes and further allows for non-invasive monitoring of changes in such genes. Moreover, quantitative analysis of disease related genes will enable prediction of treatment response where the treatment is dependent on the presence of the disease related gene.

Abstract: Methods for targeting a tumor antigen for immunotherapy based on HLA allele type and the mutations present in the tumor antigen are presented. A patient's HLA allele type and a tumor antigen derived from a mutation in cancer driver gene can be matched with a majority allele type having a minimum affinity to the same tumor antigen or with those of a plurality of patients with a history of cancer treatment. Upon matching, a cancer treatment against the tumor antigen can be selected and administered to the patient to achieve a desired effect.

Abstract: Various compounds, compositions, and methods for inhibition of Rit1 are presented. In especially preferred aspects, contemplated compounds and compositions are suitable for treatment of cancers and other diseases associated with Rit1 signaling.

Abstract: Cancer is treated via a coordinated treatment regimen that use various compounds and compositions that employ a combination vaccination together with immune modulatory treatment and biasing of an immune response towards a Th1 profile.

Abstract: A probabilistic graphical pathway model is modified to include miRNA regulation by adding RISC as a regulatory factor. Most preferably, the pathway model is built using factor graphs, and the RISC includes DICER, TARBP2, and AGO2 or AGO1/3/4. So constructed pathway models can be used to infer RISC activity, which can be associated with various clinically relevant parameters to build various predictors or diagnostic tests.

Abstract: Compositions and methods are contemplated for treatment of a wound, and especially a sterile or TLR/NOD ligand-poor wound in which contemporaneous administration of a Ca2+-flux agonist (CFA) and a pattern recognition receptor (PRR) ligand improves wound healing.

Abstract: Detection of under-expression of selected genes in NK cells is used to confirm a hypoxic tumor microenvironment that is ordinarily suppressive with respect to ADCC and cytotoxic cell killing of NK cells. Most notably, while hypoxia is known to upregulate HIF-1? and genes under the control of HIF-1?, hypoxia in a tumor microenvironment led to under-expression of selected genes, including HIF-1?. Thus, gene expression analysis of certain genes on NK cells can be used to detect conditions in a tumor that would indicate use of haNK cells.

Abstract: Contemplated treatments and methods produce substantially increased quantities of memory T-cells and a persistent immune response by subcutaneous and/or subdermal co-administration of (1) a vector comprising a recombinant nucleic acid that encodes a cancer associated epitope, a cancer specific epitope, and/or a neoepitope, (2) an immune stimulating cytokine, and (3) a checkpoint inhibitor. Most typically, the co-administration is performed at substantially the same location, preferably within 1-21 days from each other, and the vector is an adenoviral expression vector, for example, included in a viral particle such as an AdV5 virus with a deletion of the E2b gene.

Abstract: Cancer is treated via a coordinated treatment regimen that use various compounds and compositions that employ prime-boost vaccination in combination with immune modulatory treatment and biasing of an immune response towards a Th1 profile.

Abstract: Cancer immunotherapy using genetically engineered NK cells is enhanced by expression of recombinant co-stimulatory molecules to deliver co-stimulatory signals to a recipient host's immune cells to enhance an immune response.

Abstract: Systems and methods for predicting an immune response against a tumor in a patient having the tumor are provided. The relative mass or changes of mass of tumor cells or immune cell in the tumor can be ex vivo observed, and an immune status of the tumor can be determined based on the mass of tumor cells or immune cell. The immune status can provide a guidance to predict the immune response against the tumor in the patient.

Abstract: Various compounds, compositions, and methods for inhibition of Rit1 are presented. In especially preferred aspects, contemplated compounds and compositions are suitable for treatment of cancers and other diseases associated with Rit1 signaling.

Abstract: Techniques are provided for predicting DNA accessibility. DNase-seq data files and RNA-seq data files for a plurality of cell types are paired by assigning DNase-seq data files to RNA-seq data files that are at least within a same biotype. A neural network is configured to be trained using batches of the paired data files, where configuring the neural network comprises configuring convolutional layers to process a first input comprising DNA sequence data from a paired data file to generate a convolved output, and fully connected layers following the convolutional layers to concatenate the convolved output with a second input comprising gene expression levels derived from RNA-seq data from the paired data file and process the concatenation to generate a DNA accessibility prediction output. The trained neural network is used to predict DNA accessibility in a genomic sample input comprising RNA-seq data and whole genome sequencing for a new cell type.

Abstract: Contemplated systems and methods employ chimeric reference sequences that include a plurality of viral genome sequences to identify/quantify integration and co-amplification events. Most typically, the viral genome sequences are organized in the chimeric reference sequences as single chromosomes and the chimeric reference sequences are in BAM format.

Abstract: Cancer is treated using coordinated treatment regimens that uses various compounds and compositions that drive a tumor from the escape phase of cancer immunoediting to the elimination and equilibrium phase of cancer immunoediting.

Abstract: The invention provides a method of validating a predicted pathway activity of a pathway in a solid tumor of a subject, with a digital computer, the method comprising: a) obtaining a tumor associated sample from the subject; b) obtaining omics data from the tumor associated sample obtained in (a); c) applying the omics data obtained in (b) to a digital computer programmed with a pathway analysis engine configured to generate predicted tumor cell pathway activities in silico, to provide a prediction of one or more pharmaceutically active anticancer compounds effective for treating the subject's tumor; d) obtaining enriched viable tumor cells from the subject, and interrogating the enriched viable tumor cells with at least one pharmaceutically active compound known to interact with a pathway element of one or more of the pathways predicted by (c), to measure anticancer activity of the at least one pharmaceutically active compound with respect to the subject's enriched viable tumor cells.

Abstract: Contemplated systems and methods verify a patient's likely immune response to a neoepitope-based treatment by (a) assessing whether or not the patient's immune system is ready to mount an immune response, (b) determining prior response by patient immune-competent cells, and (c) determining the capability for patient immune-competent cells to respond to a future immune stimulus.

Abstract: Compounds and compositions are presented that inhibit K-ras, and especially mutant K-ras. Certain compounds preferentially or even selectively inhibit specific forms of mutant K-Ras, and particularly the G12D mutant form.

Abstract: Techniques are provided for predicting DNA accessibility. DNase-seq data files and RNA-seq data files for a plurality of cell types are paired by assigning DNase-seq data files to RNA-seq data files that are at least within a same biotype. A neural network is configured to be trained using batches of the paired data files, where configuring the neural network comprises configuring convolutional layers to process a first input comprising DNA sequence data from a paired data file to generate a convolved output, and fully connected layers following the convolutional layers to concatenate the convolved output with a second input comprising gene expression levels derived from RNA-seq data from the paired data file and process the concatenation to generate a DNA accessibility prediction output. The trained neural network is used to predict DNA accessibility in a genomic sample input comprising RNA-seq data and whole genome sequencing for a new cell type.