Dataset Information

Profiling the Mutational Landscape in Known Driver Genes and Novel Genes in African American Non-Small Cell Lung Cancer Patients.

ABSTRACT: PURPOSE:Identifying novel driver genes and mutations in African American non-small cell lung cancer (NSCLC) cases can inform targeted therapy and improve outcomes for this traditionally underrepresented population. EXPERIMENTAL DESIGN:Tumor DNA, RNA, and germline DNA were collected from African American NSCLC patients who participated in research conducted at the Karmanos Cancer Institute (KCI) in Detroit, Michigan. Known mutations were ascertained through the Sequenom LungCarta panel of 214 mutations in 26 genes, RET/ROS1 fusions, amplification of FGFR1, and expression of ALK. Paired tumor and normal DNA was whole-exome sequenced for a subset of cases without known driver mutations. RESULTS:Of the 193 tumors tested, 77 known driver mutations were identified in 66 patients (34.2%). Sixty-seven of the 127 patients without a known driver mutation were sequenced. In 54 of these patients, 50 nonsynonymous mutations were predicted to have damaging effects among the 26 panel genes, 47 of which are not found in The Cancer Genome Atlas NSCLC white or African American samples. Analyzing the whole-exome sequence data using MutSig2CV identified a total of 88 genes significantly mutated at FDR q < 0.1. Only 5 of these genes were previously reported as oncogenic. CONCLUSIONS:These findings suggest that broader mutation profiling including both known and novel driver genes in African Americans with NSCLC will identify additional mutations that may be useful in treatment decision-making.

SUBMITTER: Lusk CM

PROVIDER: S-EPMC6635071 | biostudies-literature | 2019 Jul

REPOSITORIES: biostudies-literature

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Profiling the Mutational Landscape in Known Driver Genes and Novel Genes in African American Non-Small Cell Lung Cancer Patients.

Lusk Christine M CM Watza Donovan D Dyson Greg G Craig Douglas D Ratliff Valerie V Wenzlaff Angela S AS Lonardo Fulvio F Bollig-Fischer Aliccia A Bepler Gerold G Purrington Kristen K Gadgeel Shirish S Schwartz Ann G AG

Clinical cancer research : an official journal of the American Association for Cancer Research 20190412 14

<h4>Purpose</h4>Identifying novel driver genes and mutations in African American non-small cell lung cancer (NSCLC) cases can inform targeted therapy and improve outcomes for this traditionally underrepresented population.<h4>Experimental design</h4>Tumor DNA, RNA, and germline DNA were collected from African American NSCLC patients who participated in research conducted at the Karmanos Cancer Institute (KCI) in Detroit, Michigan. Known mutations were ascertained through the Sequenom LungCarta p ...[more]

PMID: 30979741

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Project description:BackgroundIdentifying actionable driver mutations via tissue-based comprehensive genomic profiling (CGP) is paramount in treatment decisions for metastatic non-squamous, non-small-cell lung cancer (NSCLC). However, the role of CGP remains elusive in resectable NSCLC. Here, we elucidate the feasibility of CGP in early-stage NSCLC Korean patients and compare the tumor mutational burden (TMB) and mutation landscape using three different platforms.MethodsAll surgically resected NSCLC samples (N = 96) were analyzed to assess the concordance in TMB calculation and targetable mutations using whole-exome sequencing (WES) and TruSight Oncology 500 (TSO500). In all, 26 samples were analyzed with Foundation One CDx Assay (F1CDx). Programmed death-ligand 1 (PD-L1) expression was evaluated using Vectra Polaris.ResultsStage distribution post-surgery was 80% I (N = 77) and 20% II (N = 19). Ninety-nine percent (N = 95) were adenocarcinoma. The median TMB with WES and TSO500 was 1.6 and 4.7 mut/Mb, respectively (p < 0.05). Using all three platforms, the median TMB was 1.9, 5.5, and 4 mut/Mb for WES, TSO500, and F1CDx, respectively (p = 0.0048). Linear regression analysis of TMB values calculated between WES and TSO500 resulted in a concordance correlation coefficient of 0.83. For the PD-L1 tumor proportion score of <1% (negative, N = 18), 1-49% (low, N = 68), and ⩾50% (high, N = 10), the R2 values were 0.075, 0.79, and 0.95, respectively. The R2 values for TMB concordance were variable between the three platforms. Mutation landscape revealed EGFR mutation (51%, N = 49) as the most common actionable driver mutation, comprising L858R (N = 22), E19del (N = 20), and other non-common EGFR mutations (N = 7).ConclusionTSO500 and F1CDx showed robust analytical performance for TMB assessment with TSO500 showing stronger concordance of TMB with high PD-L1 expression. As the paradigm for the management of early-resected NSCLC continues to evolve, understanding TMB and the mutation landscape may help advance clinical outcomes for this subset of patients.

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Dataset Information

Profiling the Mutational Landscape in Known Driver Genes and Novel Genes in African American Non-Small Cell Lung Cancer Patients.

Publications

Profiling the Mutational Landscape in Known Driver Genes and Novel Genes in African American Non-Small Cell Lung Cancer Patients.

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