Hybrid capture (HC)-based next-generation sequencing (NGS) can identify targetable oncogenic drivers to improve response rates in patients with lung cancer, according to a study published in the Journal of Thoracic Oncology.
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Therapies that target genomic alterations driving cancer growth significantly prolongs survival for patients with lung cancer. However, the current technologies used for detecting GAs are unable to identify all alterations in EGFR exons and introns or all variations of ALK arrangements. HC-based NGS, with its broad gene sequencing, extensive information regarding GAs, exon and intron mutations, and gene rearrangements, may aid the current technologies in detecting GAs and improving decisions to use target therapy for patients with lung cancer.
The retrospective study, led by Nir Peled, MD, PhD, FCCP, and a group of Israeli researchers, sampled a cohort of 101 patients with advanced lung cancer who underwent HC-based NGS between November 2011 and October 2015 at the Davidoff Cancer Center (Israel). Demographic characteristics, variations in treatments, and outcome data were collected in the study. Of the 101 patients sampled, the median age at diagnosis was 63 years. 53% were women. 45% were never smokers. 85% had adenocarcinoma.
HC-based NGS was performed either before standard EGFR/ALK testing (15% of patients) or after testing revealed negative or inconclusive results (85% of patients). HC-based NGS was performed before treatment with 1st-line therapy in 51.5% of patients and after treatment failure in 48.5% of patients. It identified clinically actionable GAs in 50% of patients and identified EGFR/ALK aberrations not detected in the standard screening process in 15 total patients. HC-based NGS results caused alterations in treatment strategies in 43 of the patients (42.6%). Overall response rate to the targeted therapies in these sampled patients was 65% (complete, 14.7%; partial 50%).
“The high impact of HC-based NGS on treatment strategy, and the high overall response rate observed in this study, highlight the need for identifying molecular drivers and support the implementation of HC-based NGS in lung cancer," the authors wrote.
The authors acknowledged limiting factors of their study, including its retrospective nature, small sample size, and demographic characteristics of the patients representing a selection bias for existence of driver mutation, and they emphasized the need for future prospective trials for HC-based NGS.
