Loading…

Loading grant details…

Active NON-SBIR/STTR RPGS NIH (US)

Multi-cancer early detection using cell-free DNA methylome analysis

$8.79M USD

Funder NATIONAL CANCER INSTITUTE
Recipient Organization University of California Los Angeles
Country United States
Start Date Sep 19, 2023
End Date Aug 31, 2028
Duration 1,808 days
Number of Grantees 3
Roles Co-Investigator; Principal Investigator
Data Source NIH (US)
Grant ID 10931587
Grant Description

PROJECT SUMMARY Detecting cancer early is the best way to fight against cancer. The development of the Multi-Cancer Early Detection (MCED) liquid biopsy tests holds great promise for integrating early cancer detection into routine clinical care. However, the current MCED tests have unsatisfactory performance for early-stage cancers.

Recently, we have developed a sensitive and cost-effective technology, named cell-free DNA Methylome Sequencing (cfMethyl-Seq), which uses the cell-free DNA methylome for early cancer detection. cfMethyl-Seq provides >12-fold enrichment over whole genome bisulfite sequencing in CpG islands. We performed the proof-

of-principle study by applying cfMethyl-seq to a cohort of colon, liver, lung, and stomach cancer patients and controls, and obtained promising results in detecting and locating these cancer types. Here, we will further improve the cfMethyl-seq technology and apply it to detect and locate colon, gastric, liver, and lung cancer. We

will validate this MCED test in multiple clinical cohorts. Our multidisciplinary team proposes the following aims: (1) Continued improvement of the cfMethyl-seq assay for early cancer detection. (2) Continued improvement of our computational method to analyze the cfDNA methylome assay data. (3) Clinically validate the cfDNA

Methylome assay as an MCED assay with colon/gastric/liver/lung cancers as the first indications. (4) Contribute to Collaborative Trans-consortium Activities. We have a long-standing collaboration with the industry partner, EarlyDiagnostics, which will optimize the cfMethyl-seq assay to facilitate its clinical adoption and implement the

computational algorithm in a secure cloud computing platform to facilitate data sharing and decentralized testing.

All Grantees

University of California Los Angeles

Advertisement
Apply for grants with GrantFunds
Advertisement
Browse Grants on GrantFunds
Interested in applying for this grant?

Complete our application form to express your interest and we'll guide you through the process.

Apply for This Grant