Nearly quarter of a million Americans will be diagnosed with lung cancer in 2018, according to new estimates published by the American Cancer Society, and lung cancer will be responsible for more deaths than the next three most common cancers (breast, prostate, colon) combined.
Cancer arises due to genetic mutations – changes in the patient’s DNA. By figuring out precisely which genetic variants instructed their patient’s lung cells to change from normal to cancerous, doctors can select personalized therapies targeted to these mutations and minimize non-specific side-effects.
Sema4 and Mount Sinai scientists recently profiled the range of mutations found in non-small cell lung cancer (NSCLC), the most common form of lung cancer. They examined DNA from 932 NSCLC tumors and found nearly 3,000 mutations in cancer-associated genes, demonstrating the clinical utility of targeted next-generation sequencing with a focused oncology hotspot panel in NSCLC. The study, published in Genome Medicine, provides a comprehensive overview of not only the genetics but also potential treatment options for NSCLC, as actionable mutations were present in 65% of the patients.
In addition to detecting known mutations, the Sema4 team also identified novel lung cancer mutations by combing through the large volume of sequencing data generated during panel analysis. An activating somatic mutation was detected in the JAK2 gene in one in every 100 patients. This genetic variant would be expected to cause over-activity of the JAK-STAT cell signaling pathway, so the Sema4 researchers trawled publicly available pharmacogenomic data to investigate potential therapies, and found that the mutation could confer sensitivity to both JAK inhibitors and anti-PD1 immunotherapy. They also detected activating germline mutations in the JAK3 gene, in 7% of patients, that would be predicted to render tumors susceptible to anti-PD1 treatment.
“These novel mutations define a unique disease mechanism that has not been previously described in lung cancer, therefore facilitating the development of personalized treatments for patients with these variants,” says lead author Dan Li, PhD. “Going forward, we will continue to perform integrative analyses of cancer genetic data and patient clinical data to discover novel predictive biomarkers for treatment response. We will also develop and implement improved cancer genetic testing platforms for diagnosis.” Sema4’s current testing platform, the Oncology Hotspot Panel, analyzes 207 mutational hotspots across the genome that are known to be associated with cancer.
The clinical implications of the novel mutations were identified through an integrative analysis of genetic, genomic, and pharmacogenomic data. Mining large, multidisciplinary data sets is a central element of Sema4’s research ethos and one that successfully uncovers information that can directly impact clinical decision-making, as shown by this study and another recent study on glioblastoma. Our team is committed to using this approach to improve diagnosis, treatment, and outcomes for cancer patients, including the one in 16 Americans who will be diagnosed with lung cancer in their lifetime.