In a retrospective analysis reported in The Lancet Oncology, Black et al examined whether linking of comprehensive whole-genome sequencing (WGS) to mortality data could add prognostic value to standard clinical data and provide a rationale for use of targeted therapies.
Study Details
In the study, 2,445 breast cancer tumors (any stage or molecular subtype) were collected from 2,403 patients recruited through 13 National Health Service Genomic Medicine Centres or hospitals in England affiliated with the 100,000 Genomes Project (100kGP) between 2012 and 2018. A total of 2,208 cases (90%) had clinical data; mortality data were obtained for 1,188 patients. Using high-depth WGS of tumors and matched normal DNA, comprehensive WGS profiling was performed to identify driver mutations, mutational signatures, and compound algorithmic scores for homologous recombination repair deficiency (HRD), mismatch repair deficiency, and tumor mutational burden. Potential prognostic value of WGS features was evaluated in patients with stage I to III, estrogen receptor (ER)-positive, HER2-negative breast cancer with a cancer-specific mortality endpoint (~5-year follow-up).
Key Findings
Among 2,445 tumors in the 100kGP breast cancer cohort, genomic characteristics with immediate personalized medicine potential were found in 656 (26.8%), including 298 HRD cases (12.2%) and 76 ER-positive, HER2-negative cases (6.3%), highly individualized driver events, mutations associated with resistance to endocrine therapy, and mutational signatures indicating therapeutic vulnerabilities.
A total of 373 cases (15.2%) had WGS features indicating the potential for translational research, including compromised base excision repair and nonhomologous end-joining dependency.
Structural variation burden (hazard ratio [HR] = 3.9, 95% confidence interval [CI] = 2.4–6.2, P < .0001), high levels of APOBEC signatures (HR = 2.5, 95% CI = 1.6–4.1, P < .0001), and TP53 drivers (HR = 3.9, 95% CI = 2.4–6.2, P < .0001) provided prognostic information independent of standard clinical measures (eg, age at diagnosis and disease stage and grade) in patients with ER-positive, HER2-negative breast cancer. A prognosticator for ER-positive, HER2-negative breast cancer capable of identifying patients requiring either increased intervention or therapy de-escalation was devised.
The investigators concluded: “We show that breast cancer genomes are rich in predictive and prognostic value. We propose a two-step model for effective clinical application. First, the identification of candidates for targeted therapies or clinical trials using highly individualised genomic markers. Second, for patients without such features, the implementation of enhanced prognostication using genomic features alongside existing clinical decision-making factors.”
Serena Nik-Zainal, MD, PhD, of the Department of Genomic Medicine, University of Cambridge, is the corresponding author for The Lancet Oncology article.
Disclosure: The study was funded by the National Institute of Health Research, Breast Cancer Research Foundation, Cancer Research UK, Swedish Research Council, and others. For full disclosures of all study authors, visit thelancet.com.
