Brian Pedro1, Manali Rupji2, Bhakti Dwivedi2, Jeanne Kowalski2,3, Jessica M Konen1, Taofeek K Owonikoko2,4, Suresh S Ramalingam2,4, Paula M Vertino5,6, Adam I Marcus2,4. 1. Graduate Program in Cancer Biology, Emory University, Atlanta, Georgia. 2. Winship Cancer Institute, Emory University, Atlanta, Georgia. 3. Department of Biostatistics and Bioinformatics, Emory University, Atlanta, Georgia. 4. Department of Hematology and Medical Oncology, Emory University, Atlanta, Georgia. 5. Department of Radiation Oncology, Emory University, Atlanta, Georgia. 6. Department of Biomedical Genetics and Wilmot Cancer Institute, University of Rochester Medical Center, Rochester, New York.
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.
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 H1299NSCLC 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.
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