Distinguishing methylation levels in complex biological samples

Abstract

Provided herein is a method for distinguishing an aberrant methylation level for DNA from a first cell type, including steps of (a) providing a test data set that includes (i) methylation states for a plurality of sites from test genomic DNA from at least one test organism, and (ii) coverage at each of the sites for detection of the methylation states; (b) providing methylation states for the plurality of sites in reference genomic DNA from one or more reference individual organisms, (c) determining, for each of the sites, the methylation difference between the test genomic DNA and the reference genomic DNA, thereby providing a normalized methylation difference for each site; and (d) weighting the normalized methylation difference for each site by the coverage at each of the sites, thereby determining an aggregate coverage-weighted normalized methylation difference score. Also provided herein are sensitive methods for using genomic DNA methylation levels to distinguish cancer cells from normal cells and to classify different cancer types according to their tissues of origin.

Description

CROSS-REFERENCE TO RELATED APPLICATIONS[0001]This application claims the benefit of U.S. Provisional Application Ser. No. 62 / 401,591, filed Sep. 29, 2016, and U.S. Provisional Application Ser. No. 62 / 268,961, filed Dec. 17, 2015, each of which is incorporated by reference herein.BACKGROUND[0002]The present disclosure relates to determination of methylation patterns in genomic DNA. Specific embodiments relate to prediction, diagnosis, prognosis and monitoring of various conditions based on genomic methylation patterns.[0003]Changes in cellular genetic information, such as mutations in gene sequences which can affect gene expression and / or protein sequence, are associated with many diseases and conditions. However, changes can also occur to genes that affect gene expression; changes caused by mechanisms other than genetic mutations. Epigenetics is the study of changes in gene expression caused by mechanisms other than changes in the underlying DNA sequence, the methylation of DNA bein...

AI Technical Summary

Benefits of technology

This approach enables sensitive and cost-effective detection of aberrant methylation patterns, improving the accuracy of cancer diagnosis and monitoring by distinguishing tumor DNA from non-tumor DNA in blood samples, reducing the need for invasive biopsy procedures.

Problems solved by technology

Several technical challenges hinder development of methylation detection techniques into a robust and cost efficient screening tool.

For example, the accuracy and affordability of currently available techniques can be compromised by impurities in samples that are to be tested.

As a result, cumbersome and expensive purification techniques are often employed to purify a genomic sample from background nucleic acids.

Depending upon the depth of the tissue in the body of an individual, biopsy can require unpleasant and risky harvesting procedures such as needle biopsy, endoscopy, bronchoscopy, colonoscopy or surgery.

However, circulating tumor DNA is typically present in low quantities and in a background of a relatively large quantity of non-tumor DNA.

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