Abstract: A method at a computing device for classifying elements within an input, the method including breaking the input into a plurality of patches; for each patch: creating a vector output; applying a characterization map to select a classification bin from a plurality of classification bins; and utilizing the selected classification bin to classify the vector output to create a classified output; and compiling the classified output from each patch.

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: Effectiveness of a neoepitope-based immunotherapeutic composition against a tumor can be increased by predicting the surface presentation of the neoepitope bound to the HLA molecule of the tumor cell. Surface presentation levels of neoepitopes can be predicted by identifying any changes in omics data of the tumor cell that may affect the expression or surface trafficking of the HLA molecule and that may affect binding affinities of neoepitopes to the HLA molecule.

Abstract: A method at a computing device for classifying elements within an input, the method including breaking the input into a plurality of patches; for each patch: creating a vector output; applying a characterization map to select a classification bin from a plurality of classification bins; and utilizing the selected classification bin to classify the vector output to create a classified output; and compiling the classified output from each patch.

Abstract: RNA from a biological fluid is stabilized during isolation and/or storage using DNA. In especially preferred aspects, the RNA is cfRNA and/or ctRNA, and the biological fluid is blood.

Abstract: Systems and methods are presented that allow for selection of tumor neoepitopes that are then used to generate a recombinant polytope that is optimized for proper trafficking and processing. In preferred methods, the polytope is encoded in a viral expression system that is used as a therapeutic agent.

Abstract: Contemplated systems and methods allow for prediction of chemotherapy outcome for patients diagnosed with high-grade bladder cancer. In particularly preferred aspects, the prediction is performed using a model based on machine learning wherein the model has a minimum predetermined accuracy gain and wherein a thusly identified model provides the identity and weight factors for omics data used in the outcome prediction.

Abstract: Techniques are provided for predicting MHC-peptide binding affinity. A plurality of training peptide sequences is obtained, and a neural network model is trained to predict MHC-peptide binding affinity using the training peptide sequences. An encoder of the neural network model comprising an RNN is configured to process an input training peptide sequence to generate a fixed-dimension encoding output by applying a final hidden state of the RNN at intermediate state outputs of the RNN to generate attention weighted outputs, and linearly combining the attention weighted outputs. A fully connected layer following the encoder is configured to process the fixed-dimension encoding output to generate an MHC-peptide binding affinity prediction output. A computing device is configured to use the trained neural network to predict MHC-peptide binding affinity for a test peptide sequence.

Abstract: The present inventive subject matter provides apparatus, systems, and methods in which a diagnostic test is identified, where the diagnostic test is for determining whether a particular treatment is effective for a particular patient based on one or more characteristics of a patient's cells. When a treatment is developed with the potential to treat one or more diseases, the drug can have different effects on different cell lines related to the diseases. A machine learning system is programmed to infer a measurable cell characteristic, out of many different measurable cell characteristics, that has a desirable correlation with the sensitivity data of different cell lines to a treatment. The machine learning system is programmed to then determine, based on the correlation, a threshold level of the cell characteristic the patient should exhibit in order to recommend administering the treatment.

Abstract: The invention provides a method of validating the therapeutic composition that is prepared for immunotherapy of a tumor or cancer. The method includes, triggering of an immune response to a neoepitope of a subject's tumor by: a) obtaining neoepitope sequence data from the tumor of a subject; b) obtaining immune competent cells; c) using the neoepitope sequence data to generate a neoepitope presentation system; d) triggering an immune response by contacting the immune competent cells with the neoepitope presentation system; and e) quantifying the triggering of the immune response from the contacted immune competent cells.

Abstract: Systems, methods, and devices for generating synthetic genomic datasets and validating bioinformatic pipelines for genomic analysis are disclosed. In preferred embodiments, synthetic maternal and paternal datasets with known variants are used with matched normal synthetic datasets to validate various bioinformatic pipelines. Bioinformatic pipelines are evaluated using the synthetic datasets to assess design changes and improvements. Accuracy, PPV, specificity, sensitivity, reproducibility, and limit of detection of the pipelines in calling variants in synthetic datasets is reported.

Abstract: Techniques are provided for determining a cell count within a whole slide pathology image. The image is segmented using a global threshold value to define a tissue area. A plurality of patches comprising the tissue area are selected. Stain intensity vectors are determined within the plurality of patches to generate a stain intensity image. The stain intensity image is iteratively segmented to generate a cell mask using a local threshold value that is and gradually reduced after each iteration. A chamfer distance transform is applied to the cell mask to generate a distance map. Cell seeds are determined on the distance map. Cell segments are determined using a watershed transformation, and a whole cell count is calculated for the plurality of patches based on the cell segments. A client device may be configured for real-time cell counting based on the whole cell count.

Abstract: A computer implemented method of generating at least one shape of a region of interest in a digital image is provided.

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: 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: Improved methods for treating cancer are provided herein by determining if a cancer patient, particularly a colon cancer patient or a gastric cancer patient, will clinically respond in a favorable manner to a therapeutic strategy comprising the FOLFOX regimen (fluorouracil, leucovorin, and oxaliplatin) or a combination of capecitabine and cisplatin. Diagnostic methods for measuring the OPRT, TYMP, and/or UCK2 proteins in a tissue sample, such as a tumor sample, from the patient are provided.

Abstract: Methods are provided herein for identifying whether a cancer patient, for example a colorectal cancer patient, will be responsive to treatment with a therapeutic strategy comprising administration of the FOLFOX regimen (5-fluorouracil, leucovorin, and oxaliplatin). Specified TYMP and UCK2 fragment peptides are precisely detected and quantitated by SRM-mass spectrometry directly in tumor cells, for example colorectal cancer tumor cells, that are collected from tumor tissue obtained from a cancer patient and compared to reference levels in order to determine if the cancer patients will positively respond to treatment with the combination treatment of FOLFOX (5-fluorouracil, leucovorin, and oxaliplatin).

Abstract: Methods are provided for treating a cancer patient suffering from a glioblastoma (GBM) by administering to the patient an effective amount of temozolomide, wherein a mass spectrometry analysis of a protein digest of a formalin-fixed tumor sample from the patient evidences an amount of a MGMT fragment peptide less than or substantially equal to 150 amol/?g.

Abstract: A computer implemented method of generating at least one shape of a region of interest in a digital image is provided.

Abstract: Methods are provided for quantifying the cyclin-dependent kinase inhibitor 2A protein (p16) p16 protein directly in biological samples that have been fixed in formalin by SRM/MRM mass spectrometry. A protein sample is prepared from the biological sample using, for example, the Liquid Tissue reagents and protocol and the p16 protein is quantitated in the resulting sample by quantitating in the protein sample at least one fragment peptide from p16. Peptides can be quantitated in modified or unmodified form. An example of a modified form of a p16 peptide is phosphorylation of a tyrosine, threonine, serine, and/or other amino acid residues within the peptide sequence.