Prognostic significance of an invasive leader cell-derived mutation cluster on chromosome 16q

• Type of Material: Article
• Authors: Brian Pedro, Emory University; Manali Rupji, Emory University; Bhakti Dwivedi, Emory University; Jeanne Kowalski, Emory University; Jessica Konen, Emory University; Taofeek Owonikoko, Emory University; Suresh Ramalingam, Emory University; Paula Vertino, Emory University; Adam Marcus, Emory University
• Language: English
• Date: 2020-04-21
• Publisher: WILEY
• Publication Version: Author Accepted Manuscript (After Peer Review)
• Copyright Statement: © 2020 American Cancer Society
• Final Published Version (URL): http://dx.doi.org/10.1002/cncr.32903
• Title of Journal or Parent Work: CANCER
• Volume: 126
• Issue: 13
• Start Page: 3140
• End Page: 3150
• Grant/Funding Information: B.P. was support by NIH Predoctoral Fellowship 1F31CA225049.; This project was funded in part by National Institute of Health grants R01CA201340-01 and 1U54CA209992 (to A.I.M.).; Support of the Emory Integrated Genomics Core Shared Resource and the Biostatistics and Bioinformatics Shared Resource were provided by the Winship Cancer Institute of Emory University core grant under award number 2P30CA138292.
• Keywords: TRACKING; leader cells; Science & Technology; INTRATUMOR HETEROGENEITY; hepatocellular carcinoma; lung cancer; survival; Life Sciences & Biomedicine; mutations; CANCER EVOLUTION; INSTABILITY; METASTASIS; LUNG ADENOCARCINOMA; SURVIVAL; Oncology; CLASSIFICATION; PREDICTION; ABNORMALITIES

Abstract

Background: Intratumoral heterogeneity is defined by subpopulations with varying genotypes and phenotypes. Specialized, highly invasive leader cells and less invasive follower cells are phenotypically distinct subpopulations that cooperate during collective cancer invasion. Because leader cells are a rare subpopulation that would be missed by bulk sequencing, a novel image-guided genomics platform was used to precisely select this subpopulation. This study identified a novel leader cell mutation signature and tested its ability to predict prognosis in non–small cell lung cancer (NSCLC) patient cohorts. Methods: Spatiotemporal genomic and cellular analysis was used to isolate and perform RNA sequencing on leader and follower populations from the H1299 NSCLC cell line, and it revealed a leader-specific mutation cluster on chromosome 16q. Genomic data from patients with lung squamous cell carcinoma (LUSC; n = 475) and lung adenocarcinoma (LUAD; n = 501) from The Cancer Genome Atlas were stratified by 16q mutation cluster (16qMC) status (16qMC+ vs 16qMC−) and compared for overall survival (OS), progression-free survival (PFS), and gene set enrichment analysis (GSEA). Results: Poorer OS, poorer PFS, or both were found across all stages and among early-stage patients with 16qMC+ tumors within the LUSC and LUAD cohorts. GSEA revealed 16qMC+ tumors to be enriched for the expression of metastasis- and survival-associated gene sets. Conclusions: This represents the first leader cell mutation signature identified in patients and has the potential to better stratify high-risk NSCLC and ultimately improve patient outcomes.