The present invention relates to the field of cancer. More specifically, the present invention provides compositions and methods useful for detecting and treating esophageal cancer. In a specific embodiment, a method for identifying a subject having esophageal adenocarcinoma (EAC) comprises (a) extracting genomic DNA from a sample obtained from the subject; (b) performing a conversion reaction on the genomic DNA in vitro to convert unmethylated cytosine to uracil by deamination; and (c) detecting nucleic acid methylation of one or more genes in the converted genomic DNA, wherein detecting nucleic acid methylation identifies the subject as having EAC. The one or more genes can comprise ABCB1, BMP3, COL23A1, FBN1, FADS1 and PRDM2. In a more specific embodiment, the one or more genes comprise at least three of ABCB1, BMP3, COL23A1, FBN1, FADS1 and PRDM2.

Disclosed are methods for determining copy number variation (CNV) known or suspected to be associated with a variety of medical conditions. In some embodiments, methods are provided for determining copy number variation of fetuses using maternal samples comprising maternal and fetal cell free DNA. In some embodiments, methods are provided for determining CNVs known or suspected to be associated with a variety of medical conditions. Some embodiments disclosed herein provide methods to improve the sensitivity and/or specificity of sequence data analysis by deriving a fragment size parameter. In some implementations, information from fragments of different sizes are used to evaluate copy number variations. In some implementations, one or more t-statistics obtained from coverage information of the sequence of interest is used to evaluate copy number variations. In some implementations, one or more fetal fraction estimates are combined with one or more t-statistics to determine copy number variations.

An improved diagnostic assay and methods relating to the same that are directed to mutation focused disease diagnosis and surveillance biomarker panels wherein potential genomic regions are selected based on their ability to encompass the genomic diversity of a patient population, maximize the number of unique markers monitored within each patient are maximized while balancing these factors with empirical sequencing performance, geographic clustering of events with a region across diverse patients, and size and cost associated with measuring the respective genomic region. The methods also include quality control steps to reduce noise and

Provided herein are systems and methods for detection of an epigenetic modification in a nucleic acid sequence. The systems and methods as described herein may provide a substantially unbiased approach in detecting an epigenetic modification. The systems and method as described herein may provide a substantially unbiased approach in detecting an epigenetic modification in comparison to systems and methods that amplify sequences having a label or a moiety associated with an epigenetic modification.

A method is provided for probabilistically assigning a tissue of origin to a nucleic acid in a sample, e.g., DNA in a cell-free fluid sample obtained from a human subject. A hydroxymethylation profile is generated for the sample DNA and then compared across a reference data set of hydroxymethylation profile vectors, where each hydroxymethylation profile vector identifies the hydroxymethylation profile at a specific reference locus, the tissue-specific gene associated with the reference locus, and the tissue with which the gene and reference locus are associated. A tissue of origin can be probabilistically assigned to the sample nucleic acid using the results of the comparison. Other methods of use are also provided.

The present disclosure provides methods and systems for screening or detecting a colorectal cancer or following colorectal disease progression that may be applied to cell-free nucleic acids such as cell-free DNA. The method may use detection of methylation signals within a single sequencing read in identified genomic regions as input features to train a machine learning model and generate a classifier useful for stratifying populations of individuals. The method may comprise extracting DNA from a cell-free sample obtained from a subject, converting the DNA for methylation sequencing, generating sequencing reads, and detecting colon proliferative cell disorder-associated signals in the sequencing information and training a machine learning model to provide a discriminator capable of distinguishing groups in a subject population such as healthy, cancer or distinguishing disease subtype or stage. The method may be used for, e.g., predicting, prognosticating, and/or monitoring response to treatment, tumor load, relapse, or colorectal cancer development.

Provided is a reagent combination for detecting a liver cancer. The reagent combination includes any one of the following detection reagents: 1) a detection reagent for detecting methylation level of at least one of the following methylation sites of the PAK1 gene: cg17202086, cg26996201, and cg18309286; 2) a detection reagent for detecting methylation level of at least one of the following methylation sites of the OTX1 gene: cg23229261 and cg10122865; and 3) a detection reagent for detecting methylation level of methylation site cg16657538 of the ZNF397OS gene. Further provided are use of the reagent combination, and a kit including the reagent combination. By using the reagent combination of the present invention, a liver cancer may be detected clinically in a tissue sample with fewer markers, and may be detected sensitively and specifically by detecting methylation sites, and the cost and time are saved.

The invention relates to a method for diagnosing or identifying gastric cancer in a subject. The inventors indeed identified three DNA methylation biomarkers that, alone, or preferably in combination, can help diagnosing or following-up gastric cancer patients very specifically, discriminating with other type of cancers. Further, it can be used for determining, and/or adapting a suitable therapeutic regimen for a subject diagnosed for gastric cancer. The present invention also relates to kits comprising primers or probes to detect, diagnose, or identify hypermethylated genes.

A method of determining a percentage of cell-types in a saliva specimen includes the steps of obtaining genomic DNA from the saliva specimen, observing cytosine methylation at specific CG loci in the genomic DNA of the saliva specimen, comparing the observed methylation with the methylation observed in genomic DNA collected from a reference group of saliva specimens and correlating the CG loci methylation observed in the genomic DNA of the saliva specimen with the methylation observed in the genomic DNA of the reference group of saliva specimens to determine the percentage of cell-types in the saliva specimen.

The present invention provides a method for detecting a target nucleic acid that discriminates the target nucleic acid from a non-target nucleic acid having a nucleotide sequence or modification state that differs from a portion of the target nucleic acid, the method comprising conducting a nucleic acid amplification reaction using a region in the non-target nucleic acid that differs from the target nucleic acid as a target region, using a region in the target nucleic acid that differs from the non-target nucleic acid as a corresponding target region, using a nucleic acid test sample as a template, and using a primer that hybridizes with both the target nucleic acid and the non-target nucleic acid, with the nucleic acid amplification reaction conducted in the presence of a molecule capable of binding specifically to the target region in the non-target nucleic acid, under temperature conditions under which the molecule can bind to the non-target nucleic acid, and then detecting the target nucleic acid on the basis of the presence or absence of an amplification product.