Metastatic NSCLCs With Limited Tissues: How to Effectively Identify Driver Alterations to Guide Targeted Therapy in Chinese Patients

Abstract

Introduction Molecular diagnostics of newly diagnosed patients with metastatic NSCLC (mNSCLC) with limited tissue samples often face several obstacles in routine practice using next-generation sequencing (NGS), mainly owing to insufficient tissue or DNA; thus, how to effectively identify the molecular profiling of these cases to accurately guide targeted therapy remains elusive. We evaluated whether an optimized workflow with the combined use of multiple technologies could be helpful. Methods Tissue NGS was used as the frontline method. Amplification refractory mutation system polymerase chain reaction, immunohistochemistry, fluorescence in situ hybridization, and plasma NGS were used as supplements. Results Among 208 mNSCLC cases with limited tissue (cohort 1), molecular genotyping using single-tissue NGS failed in 42 (20.2%) and actionable alterations were identified in only 112 of 208 cases (53.8%). In comparison, the optimized workflow in 1184 additional mNSCLC cases with limited tissue (cohort 2) increased the discovery rate of actionable alterations from 59.7% detected by tissue NGS to 70.4%. It was because that driver alterations were identified using amplification refractory mutation system polymerase chain reaction plus immunohistochemistry or fluorescence in situ hybridization in 53 of 78 (67.9%) tissue NGS-failed cases, and using plasma NGS in 73 of 143 (51.0%) tissue NGS-failed cases, which led to matched targeted therapies in 57 cases with clinical response. Moreover, the median turnaround time of the optimized workflow was significantly shorter than that of repeated biopsy for tissue NGS (p < 0.001). Conclusions The optimized workflow can improve mutation detection and may avoid repeated biopsy, thus allowing the timely initiation of targeted therapies for patients with newly diagnosed mNSCLC.