Developing High-Accuracy Sequencing Methods for Use in Early Cancer Detection, Disease Stratification, and Chemotherapy Resistance With Cell-Free DNA
Abstract
Recent efforts to understand the mutational landscape of tumors has resulted in a detailed cataloguing of diagnostic, prognostic, and clinically actionable mutations. Previous studies have identified a number of “driver” mutations that are thought to be responsible for tumor formation and are present in a significant proportion of non-small cell lung cancer patients. Detection of these mutations can help with early cancer detection, initial stratification of treatment options, or alerting to the emergence of chemotherapy resistance, all of which could be harnessed to significantly improve survival. As with most other cancers in the chest cavity, access to tumor tissue by biopsy or surgical resection is often extremely limited or unobtainable, as well as not necessarily representative of the entire tumor. For this reason, DNA shed by the tumor into the bloodstream, often referred to as circulating tumor DNA (ctDNA), holds the promise of yielding detailed information about a tumor via a simple, minimally invasive, blood test. The concept of a “liquid biopsy” has been exploited for many cancer applications, including detection of minimal residual disease, evaluation of therapy response, prediction of relapse, prognosis, and personalized therapy selection. The advent of next-generation sequencing technology (NGS) has opened up the possibility of clinically exploiting ctDNA. Unfortunately, ctDNA from cancer comprises only a small fraction of the overall amount of cell-free DNA in the bloodstream. This issue, in conjunction with the high error rates of NGS technology, has proven to be a major impediment in developing minimally invasive tests to look for rare tumor specific mutations in the sea of normal cell-free DNA. To overcome this issue, we previously developed Duplex Sequencing, which is capable of detecting these low-frequency mutations. However, this method requires more DNA than is generally found as cell-free DNA in the blood. As part of previous funding from the Department of Defense, we recently developed a method we call SPLiT-Seq (Separated PCRs [polymerase chain reactions] of Linked Templates for Sequencing), a simple PCR-based target enrichment method that maintains the accuracy of Duplex Sequencing while offering reduced costs and increased efficiency and scalability on the low amounts of DNA frequently encountered with cell-free DNA applications. The objective of our proposal is to develop SPLiT-Seq for high-accuracy detection of low-frequency, clinically informative ctDNA mutations in non-small cell lung cancer patients. As such, our proposal addresses two Areas of Emphasis: (1) Develop a minimally invasive method for early detection of lung cancer and (2) Develop a predictive or prognostic marker to identify responders and non-responders. After completion of this project, we will have developed a gene panel for high-accuracy detection of the most clinically useful mutations found in non-small cell lung cancer. These mutations are found in over 60% of all non-small cell lung cancer patients. The presence of several of these mutations is very important to therapy decisions, as the use of certain chemotherapies depends on the presence or absence of these mutations. Being able to include or exclude treatment options will help all patients avoid the “try and see” treatment approach that is all too common in lung oncology. It is estimated that the per-patient expenditure for non-small cell lung cancer drug treatments ranges between $50,000 and $143,000 annually. These high costs put a heavy financial and emotional burden on patients, patients’ families, and the military healthcare system. Additionally, several of these treatments only work with certain tumor subtypes with specific mutations. Therapy-resistant mutations frequently occur, necessitating changes in therapy. Development of a rapid, minimally invasive test for tumor genotyping and early detection of therapy resistance will al
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Oct 29, 2018
- Source ID
- W81XWH1810339
Entities
People
- Scott Kennedy
Organizations
- United States Army
- University of Washington