Abstract: Systems and methods for validating immune therapy that targets patient- and tumor-specific neoepitopes are presented in which cellular components are identified and/or used that present patient- and tumor-specific neoepitopes. Presence of these neoepitopes confirms the suitability of the neoepitopes. Advantageously, synthetic antibodies are created based on in silico analysis of the tumor genome and RNA or phage display, and can be used to isolate cellular components, and especially circulating tumor cells, metastatic cells, and/or exosomes and microvesicles.

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 and methods for validating immune therapy that targets patient- and tumor-specific neoepitopes are presented in which cellular components are identified and/or used that present patient- and tumor-specific neoepitopes. Presence of these neoepitopes confirms the suitability of the neoepitopes. Advantageously, synthetic antibodies are created based on in silico analysis of the tumor genome and RNA or phage display, and can be used to isolate cellular components, and especially circulating tumor cells, metastatic cells, and/or exosomes and microvesicles.

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: 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: Techniques are provided for determining classifications based on WSIs. A varied-size feature map is generated for each training WSI by generating a grid of patches for the training WSI, segmenting the training WSI into tissue and non-tissue areas, and converting patches comprising the tissue areas into tensors. Bounding boxes are generated based on the patches comprising tissue areas and segmented into feature map patches. A fixed-size feature map is generated based on a subset of the feature map patches. A classifier model is trained to process fixed-size feature maps corresponding to the training WSIs such that, for each fixed-size feature map, the classifier model is operable to assign a WSI-level tissue or cell morphology classification or regression based on the tensors. A classification engine is configured to use the trained classifier model to determine a WSI-level tissue or cell morphology classification or regression for a test WSI.

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 method of determining a region of interest in an image of tissue of an individual by an apparatus including processing circuitry may include executing, by the processing circuitry, instructions that cause the apparatus to partition an image of tissue of an individual into a set of areas, identify a tissue type of each area of the image, and apply a classifier to the image to determine a region of interest, the classifier being configured to determine regions of interest based on the tissue types of the set of areas of the image.

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: Techniques are provided for determining classifications based on WSIs. A varied-size feature map is generated for each training WSI by generating a grid of patches for the training WSI, segmenting the training WSI into tissue and non-tissue areas, and converting patches comprising the tissue areas into tensors. Bounding boxes are generated based on the patches comprising tissue areas and segmented into feature map patches. A fixed-size feature map is generated based on a subset of the feature map patches. A classifier model is trained to process fixed-size feature maps corresponding to the training WSIs such that, for each fixed-size feature map, the classifier model is operable to assign a WSI-level tissue or cell morphology classification or regression based on the tensors. A classification engine is configured to use the trained classifier model to determine a WSI-level tissue or cell morphology classification or regression for a test WSI.

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 method of determining a region of interest in an image of tissue of an individual by an apparatus including processing circuitry may include executing, by the processing circuitry, instructions that cause the apparatus to partition an image of tissue of an individual into a set of areas, identify a tissue type of each area of the image, and apply a classifier to the image to determine a region of interest, the classifier being configured to determine regions of interest based on the tissue types of the set of areas of the image.

Abstract: Systems and methods for prediction of the treatment outcome for immune therapy are presented in which omics data of a patient tumor sample are used. Most typically, the omics data are processed to identify mutational signatures (especially APOBEC/POLE signatures), immune checkpoint expression, and MSI status as leading indicators to predict the treatment outcome for immune therapy. Such prediction advantageously integrates various parameters that would otherwise, when individually considered, skew prediction outcome.

Abstract: Disclosed herein are methods for inducing immunity against a virus such as a coronavirus in the mucosal tissue of a patient, include administering a vaccine composition to the patient by oral administration (e.g., nasal injection, nasal inhalation, oral inhalation, and/or oral ingestion). Also disclosed are compositions for assaying the presence of anti-viral antibodies induced by the administered vaccine or the presence of viral proteins in a saliva sample include a stabilizing solution and may also include the use of aragonite particle beads. Compositions and methods are presented for prevention and/or treatment of a coronavirus disease wherein the composition comprises comprises a recombinant entity. The recombinant entity is bivalent, comprising a nucleic acid encoding a coronavirus 2 nucleocapsid protein CoV2 nucleocapsid protein fused to an endosomal targeting sequence, and a nucleic acid encoding a CoV2 spike protein sequence optimized for cell surface expression.

Abstract: Methods for analyzing omics data and using the omics data to determine prognosis of a cancer, to predict an outcome of a treatment, and/or to determine an effectiveness of a treatment are presented. In preferred methods, blood from a patient having a cancer or suspected to have a cancer is obtained and blood omics data for a plurality of cancer-related, inflammation-related, or DNA repair-related genes are obtained. A cancer score can be calculated based on the omics data, which then can be used to provide a cancer prognosis, a therapeutic recommendation, an effectiveness of a treatment.

Abstract: Systems and methods for prediction of the treatment outcome for immune therapy are presented in which omics data of a patient tumor sample are used. Most typically, the omics data are processed to identify mutational signatures (especially APOBEC/POLE signatures), immune checkpoint expression, and MSI status as leading indicators to predict the treatment outcome for immune therapy. Such prediction advantageously integrates various parameters that would otherwise, when individually considered, skew prediction outcome.

Abstract: Disclosed herein are methods for inducing immunity against a virus such as a coronavirus in the mucosal tissue of a patient, include administering a vaccine composition to the patient by oral administration (e.g., nasal injection, nasal inhalation, oral inhalation, and/or oral ingestion). Also disclosed are compositions for assaying the presence of antiviral antibodies induced by the administered vaccine or the presence of viral proteins in a saliva sample include a stabilizing solution and may also include the use of aragonite particle beads. Compositions and methods are presented for prevention and/or treatment of a coronavirus disease wherein the composition comprises comprises a recombinant entity. The recombinant entity is bivalent, comprising a nucleic acid encoding a coronavirus 2 nucleocapsid protein CoV2 nucleocapsid protein fused to an endosomal targeting sequence, and a nucleic acid encoding a CoV2 spike protein sequence optimized for cell surface expression.

Abstract: Methods for analyzing omics data and using the omics data to determine prognosis of a cancer, to predict an outcome of a treatment, and/or to determine an effectiveness of a treatment are presented. In preferred methods, blood from a patient having a cancer or suspected to have a cancer is obtained and blood omics data for a plurality of cancer-related, inflammation-related, or DNA repair-related genes are obtained. A cancer score can be calculated based on the omics data, which then can be used to provide a cancer prognosis, a therapeutic recommendation, an effectiveness of a treatment.

Abstract: Circulating free RNA (cfRNA) is used for monitoring status and/or treatment response for neural tumors, and especially glioma, glioblastoma, and neuroblastoma. Particularly preferred cfRNAs include those that encode a marker that is specific to a neural tumor, but also markers that are specific to DNA repair status and/or immune status.

Abstract: An immune gene expression signature is associated with favorable clinical features in Treg-enriched tumor samples and can be used to predict immunogenicity of a tumor, overall survival, and/or chemosensitivity.