Whole genome and transcriptome sequencing of lung cancer: Options for personalized cancer treatment

Autor: Yongjun Zhao, Janessa Laskin, Cheryl Ho, Daniel J. Renouf, Marco A. Marra, Karen A. Gelmon, Negar Chooback, Howard John Lim, Andrew J. Mungall, Stephen Yip, Erica S Tsang, Steven J.M. Jones, Richard A. Moore, Yaoqing Shen
Rok vydání: 2017
Předmět:
Zdroj: Journal of Clinical Oncology. 35:e20567-e20567
ISSN: 1527-7755
0732-183X
DOI: 10.1200/jco.2017.35.15_suppl.e20567
Popis: e20567 Background: Targeted therapy against driver mutations has revolutionized lung cancer management. The Personalized OncoGenomics (POG) program uses whole genome and transcriptome derived information to build pathways and identify potential therapeutic targets. We examined the lung adenocarcinoma (LUAD) patients enrolled in POG in order to identify novel cancer drivers and correlate the findings with clinical characteristics. Methods: Patients with advanced LUAD and survival > 6 months were eligible. Blood, archival and fresh tumour specimens were subjected to comprehensive DNA and RNA sequencing. SNV data were compared to the TCGA-LUAD cohort using the cBioPortal platform. Whole tumor transcriptome data were compared to matched normal blood specimens. Clinical characteristics were collected by chart review. Results: 30 POG LUAD cases were analyzed. Baseline characteristics; 47% female, median age 60, 57% never/light smokers, biopsy site - 50% lung, 50% metastatic lesion. High mutations rates in TP53, KRAS, NF1 were comparable to the TCGA-LUAD cohort. Four genes ( GOLGA6L2, FAM186A, ARMCX4 and RBMXL3), were mutated 17-27% of the time in POG patients, while the rate in TCGA-LUAD was < 1%. Driver mutations ( KRAS and EGFR) and known fusions (ROS1 and RET) were present in 63%.Other potential drivers included ERBB3, ERBB2, SDC:NRG1 fusion were identified. Copy number alterations and expression data revealed variations in cell cycle, mTOR, androgen receptor,HSP90, MET and Wee1 proteins, all potential targets for therapy. PD-L1 over-expression and a strong smoking signature were not mutually exclusive to EGFR copy gain and FGFR3 overexpression. Conclusions: The molecular signature of NSCLC is complex and involves multiple key oncogenic drivers. Whole genome sequencing and transcriptome data should be used together to map out the pathways of carcinogenesis and reliably identify targets for therapy.
Databáze: OpenAIRE
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