Exploring the association between somatic molecular features and tumor mutation burden in 513 non–small-cell lung cancer.

Authors

null

Chenchen Zhu

Geneplus-Beijing Institute, Changping District, Beijing, China

Chenchen Zhu , Jun Zhao , Qichao Xie , Pingping Dai , Liyun Miao , Shuanying Yang , Renhua Guo , Yan Zhang , Gen Lin , Jiang Liu , Huaxia Yang , Yan-Fang Guan , Ling Yang , Xin Yi , Xuefeng Xia

Organizations

Geneplus-Beijing Institute, Changping District, Beijing, China, Beijing University School of Oncology Beijing Institute for Cancer Research, Beijing, China, Department of Oncology,the third affiliated hospital of Chongqing Medical University, Chongqing, China, Nanjing Drum Tower Hospital The Affiliated Hospital of Nanjing University Medical School, Nanjing, China, Sencond Affiliated Hospital Of Xi'an Jiaotong University, Xi'an, Shaanxi, China, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China, Fujian Cancer Hospital, Fujian Medical University Cancer Hospital, Fuzhou, China, Xinjiang Uygur Autonomous Region People's Hospital, Urumqi, Xinjiang, China, Department of Rheumatology and Clinical Immunology,Peking Union Medical College Hospital,Chinese Academy of Medical Sciences & Peking Union Medical College, Dongcheng District, Beijing, China, Geneplus-Beijing Institute, Beijing, China, Houston Methodist Research Institute, Weill Cornell School of Medicine, Houston, TX

Research Funding

Other

Background: Tumor mutation burden (TMB) is new clinical marker that predicts responses to immunotherapy, but the molecular basis of TMB is unknown. Understand the association between genomic landscape and TMB may help to a better guidance of immunotherapy. Methods: We performed a retrospective review of 513 non–small-cell lung cancers (NSCLC) patients. Tumor tissues were acquired from initial diagnosis before any drug treatment and sequenced by Next Generation Sequencing (NGS) of 1021 genes. TMB (mutations/Mb) was analyzed as the number of somatic non-synonymous base substitution and indel per Mb in coding region. The top quartile was classified as TMB high. Results: A total of 513 patients had an average TMB of 7.5 mut/Mb. The median TMB was 5.8 mut/Mb (range, 1 to 67.68 mut/Mb). 128 patients were assessed as TMB high (TMB-H) and 385 patients were TMB low (TMB-L). The median TMB was 14 and 4.32 mut/Mb for patients with TMB-H and TMB-L respectively. EGFR mutations were detected in 28 patients with TMB-H (21.9%) compared with 228 with TMB-L (59.2%; P< 0.01). And other known drivers were significantly more common in patients with TMB-L than with TMB-H, which included ALK fusion, ROS1 fusion, MET splice and BRAF V600E (P< 0.01). KRAS and TP53 mutations were more common in patients with TMB-H than with TMB-L, but no significant difference of KRAS mutations were found between TMB-H and TMB-L (12.5% vs 7.8%; P = 0.15). Significant differences of TP53 mutations were found between TMB-H and TMB-L (81.3% vs 54.8%; P < 0.01). In addition, alterations of homologous recombination repair and mismatch repair gene were more likely to be the high TMB, e.g. alterations in BRCA1, BRCA2, ATM, ATR, PMS2 and MSH2 were significantly enriched in patients with TMB-H. Conclusions: TMB-H is associated with lack of current druggable oncogenic drivers, such as EGFR mutations/ ALK or ROS1 fusion. TMB detection provides a clinically useful predictor of response to immunotherapy. TP53 and KRAS mutations specifically enriched in patients with TMB-H, may be served as potential predictive factors in guiding immunotherapy. Lastly, DNA damage repair mutations strongly correlated with high TMB, and may be a primary molecular mechanism for TMB.

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Abstract Details

Meeting

2018 ASCO Annual Meeting

Session Type

Poster Session

Session Title

Tumor Biology

Track

Tumor Biology

Sub Track

Tumor-Based Biomarkers

Citation

J Clin Oncol 36, 2018 (suppl; abstr 12101)

DOI

10.1200/JCO.2018.36.15_suppl.12101

Abstract #

12101

Poster Bd #

214

Abstract Disclosures

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