GRAIL, LLC

Methods of identifying changes in genomic DNA copy number are disclosed. This disclosure provides methods for detecting chromosomal aberrations in a subject using Hidden Markov modeling. In some cases, methods provided herein use de novo sequence assembly to detect chromosomal aberrations in a subject. The methods can be used to detect copy number changes in cancerous tissue compared to normal tissue. The methods can be used to diagnose cancer and other diseases associated with chromosomal anomalies.

The present description provides a cancer assay panel for targeted detection of cancer-specific methylation patterns. Further provided herein are methods of designing, making, and using the cancer assay panel for the diagnosis of cancer.

The present disclosure relates generally to compositions and methods for determining cell type based on a methylation profile of associated DNA. For cell free DNA, such determination can be used to identify disease or conditions relating to the cell type. For tumor cells, such determination is useful for identifying their primary origin.

Provided herein are methods for enriching a biological sample for a target nucleic acid, and analyzing the nucleic acid. In some cases, a biological sample is enriched for target nucleic acids associated with a cancer or tumor. In some cases, a biological sample is enriched for target nucleic acids, and the target nucleic acids vary in length. In some cases, one or more probes are used to enrich the biological sample for the target nucleic acid. In some cases, one or more probes hybridize to one or more ends of a target nucleic acid.

The present description provides a cancer assay panel for targeted detection of cancer-specific methylation patterns. Further provided herein are methods of designing, making, and using the cancer assay panel for the diagnosis of cancer.

Technical solutions for classifying patients with respect to multiple cancer classes are provided. The classification can be done using cell-free whole genome sequencing information from subjects. A reference set of subjects is used to train classifiers to recognize genomic markers that distinguish such cancer classes. The classifier training includes dividing the reference genome into a set of non-overlapping bins, applying a dimensionality reduction method to obtain a feature set, and using the feature set to train classifiers. For subjects with unknown cancer class, the trained classifiers provide probabilities or likelihoods that the subject has a respective cancer class for each cancer in a set of cancer classes. The present disclosure thus describes methods to improve the screening and detection of cancer class from among several cancer classes. This serves to facilitate early and appropriate treatment for subjects afflicted with cancer.

Aspects of the invention include methods for preparing sequencing libraries, performing sequencing procedures that can correct for process-related errors, and identifying rare variants that are or may be indicative of cancer.

The present description provides a cancer assay panel for targeted detection of cancer-specific methylation patterns. Further provided herein are methods of designing, making, and using the cancer assay panel for the diagnosis of cancer.

Described herein are methods of preparing dual-indexed nucleic acid libraries for methylation profiling using bisulfite conversion sequencing. In various embodiments, the methods use a two-step indexing process to tag bisulfite-treated DNA with unique molecular identifiers (UMIs).

Provided herein are methods of enriching mutated cell free nucleic acids for detection and diagnosis of cancer. Also provided are methods using a CRISPR-Cas system to target and deplete unwanted more abundant cell free nucleic acid sequences thereby enriching for less abundant sequences.