Abstract: Provided herein are methods for determining the chance of a tumor not responding to an anti-cancer therapy (e.g., a T cell-based immunotherapy) based on the presence, density, number, and/or location of certain three-cell structures as described herein. The three-cell structures may comprise a T cell, an immunosuppressive tumor-associated macrophage, and an immunosuppressive regulatory T cell. Such methods may be useful for identifying patients not likely to respond to T cell-based immunotherapy. Also provided herein are methods for determining the prognosis and/or invasiveness of a tumor. The present disclosure also encompasses methods for treating a tumor, as well as kits for performing the methods disclosed herein.

Abstract: Methods are provided for treating, managing, diagnosing and monitoring myelodysplastic syndrome and other hematologic malignancies. These methods comprise the next generation sequencing analysis conducted on cell-free DNA from peripheral blood plasma or serum.

Abstract: Compositions and fragment length analysis methods are provided for detecting CALR mutations and determining tumor load in patients with myeloproliferative neoplasms.

Abstract: A method for detecting a low-occurrence mutation in isolated DNA adds a blocking probe to reagents during amplification of the isolated DNA. The blocking probe is an oligonucleotide complementary to wild-type DNA corresponding to the sample. The blocking probe spans a site of a suspected mutation within a region of interest in the isolated DNA. After amplification, fragments of the amplified DNA is sequenced using next generating sequencing and an output is generated to display the sequenced fragments. In some embodiments, the blocking probe is locked nucleic acid (LNA).

Abstract: A method for predicting resistance to BTK inhibitors in patients with chronic lymphocytic leukemia (CLL) enhances the sensitivity of Sanger sequencing and NGS by using wild-type blocking of genes that are relevant for detecting resistance to ibrutinib. Further enhancement of sensitivity can be achieved by using cell-free DNA.

Abstract: A method for increasing sensitivity for detecting minority mutations in MYD88 uses a locked nucleic acid oligo to block amplification of wild-type DNA in DNA isolated from patient FFPE tissue, bone marrow aspirate or peripheral blood samples during PCR while still allowing sequencing and visualization of the PCR product. Further improvement to the sensitivity may be achieved by using a uracil DNA-glycosylase treatment to remove sequence artifacts commonly found in formalin-fixed, paraffin-embedded tissue.

Abstract: An automated reader for reading fluorescence in-situ hybridization signals includes one or more computer processors for receiving a digitized FISH image and executing the steps of converting colors within the image to a hue value, separately for each color extracting quantitative values to detect the presence of signals corresponding to spots and applying a plurality of algorithms to extract features from the signals to determine cell shapes and segment cells within the FISH image. After recombining the signals, the extracted features for the colors learning machines are used to classify the spots according to the color and separate merged signals of classified spots that are in close proximity to each other within the image. The classified spots are counted to determine relative frequency of colors and a report is generated providing the number of classified spots of each color.

Abstract: The present disclosure provides methods of detecting and determining the aggressiveness of prostate cancer. These methods can be used to determine whether or not a patient needs a biopsy as well as guide treatment selection.

Abstract: The present invention relates to a method for screening, predicting or prognosing esophageal adenocarcinoma/high grade dysplasia in a subject.

Abstract: An automated reader for reading fluorescence in-situ hybridization signals includes one or more computer processors for receiving a digitized FISH image and executing the steps of converting colors within the image to a hue value, separately for each color extracting quantitative values to detect the presence of signals corresponding to spots and applying a plurality of algorithms to extract features from the signals to determine cell shapes and segment cells within the FISH image. After recombining the signals, the extracted features for the colors learning machines are used to classify the spots according to the color and separate merged signals of classified spots that are in close proximity to each other within the image. The classified spots are counted to determine relative frequency of colors and a report is generated providing the number of classified spots of each color.