A study led by investigators from Weill Cornell Medicine and NewYork-Presbyterian suggests that a whole-genome sequencing (WGS) approach holds potential for improved identification of cancer patients who could benefit from PARP inhibitor treatments. The research indicates that this method may offer advantages over current commercial techniques in detecting a specific DNA-repair defect known as homologous recombination deficiency (HRD). The findings, published in Communications Medicine, propose that further development of this approach is warranted.
Background on Cancer Treatment and DNA Repair
Homologous recombination deficiency (HRD) is a type of DNA-repair defect that makes tumors more susceptible to certain therapies. Cancers exhibiting HRD tend to respond more effectively to PARP inhibitors, which disrupt DNA repair and lead to cancer cell death, as well as to platinum-based chemotherapies.
Traditionally, clinicians have focused primarily on mutations in the BRCA1 and BRCA2 genes as indicators for PARP inhibitor benefit. These mutations are common in breast, ovarian, pancreatic, and prostate cancers. However, other gene mutations can also disrupt this repair process. Whole-genome sequencing, which can detect a broader range of genetic alterations across the entire genome, has become more accessible for routine use.
A Novel Whole-Genome Sequencing Algorithm
The study involved performing whole-genome sequencing analysis on hundreds of tumor samples. This data was utilized to train and validate an algorithm designed to detect HRD. The algorithm, developed by Isabl, a medical diagnostics company, aims to identify a wide range of genome-wide DNA defects linked to HRD. The precision medicine initiative by Weill Cornell, NewYork-Presbyterian, and Illumina, Inc., contributed to obtaining the tumor samples.
Dr. Juan Miguel Mosquera, a senior author of the study and director of research pathology at the Englander Institute for Precision Medicine at Weill Cornell, highlighted that a comprehensive analysis of the entire genome provides advantages over traditional, targeted detection strategies for identifying HRD.
Study Methodology and Key Findings
Researchers trained the algorithm using 305 samples from patients with various cancers. It was subsequently validated using a cohort of 556 cancers and compared against commercial methods with an additional 212 tumor samples.
The algorithm identified HRD in a notable percentage of samples, including:
- 21% of breast tumors
- 20% of pancreatic and bile duct tumors
- 17% of gynecological tumors
Notably, 24% of the HRD cases detected by the algorithm did not involve BRCA1 or BRCA2 mutations, indicating the presence of diverse underlying genetic causes. In some instances, the algorithm appeared to identify discrepancies compared to predictions made by commercial methods when evaluated against patient outcomes. Initial assessments suggested the algorithm exhibited higher accuracy in predicting PARP-inhibitor treatment responses than existing methods.
Future Directions
Investigators plan to conduct larger studies to further evaluate the new detection algorithm as a general tool for guiding cancer treatment strategies.