Actionable mutation detection by targeted multiple gene panel sequencing is increasingly becoming a routine test in the clinical treatment of non-small cell lung cancer. Although it helps patients choose their own personalized drugs, most mainly focused on single actionable event and ignored the other driver variation which could affect the efficacy of the targetable drugs and patients’ outcome.
Fresh frozen tumors, pleural effusion or FFPE tumors with matched peripheral blood were collected from 235 patients with lung adenocarcinoma (LUAD) before therapy. All of the samples were sequenced using commercial gene panel OseqTM series. The genetic molecular profiles, correlations between genetic variations and patient's prognosis were analyzed.
A total of 1713 somatic variations were detected in our cohort including single-nucleotide variants, insertion/deletions, copy number alterations and structural variations. Over 50% of patients carried either EGFR or TP53 alteration. The tumor variant allele frequency of TP53 was a prognostic indicator for LUAD patient. The co-occurring genomic alterations were associated with patients' outcome, especially for genes co-mutated with EGFR, ERBB2 and KDR in the EGFR tyrosine kinase inhibitor resistance pathway. In addition, MYC amplification alone was insufficient as an independent prognostic predictor for LUAD. Moreover, the DNA damage repair genes including ATM, BRCA1and BRCA2 were more likely to alter in patients with wild-type TP53 (TP53wt). The alterations on STK11 and KRAS were enriched in TP53wt and DDRmut individuals and slightly corelated with prognosis of LUAD patients.
We presented an integrated analysis of genetic and clinical outcome features in LUAD cohort. Several novel pairs of concurrent gene variation were found which associated with patients' survival and could be prognostic predictors for treatment evaluation. Our work also shed further light on the genomic subtyping based on DDR genes as promising prognostic biomarkers in LUAD and provide a larger picture of multiple gene sequencing for helping to find optimal treatment in precision anticancer therapy.
The authors.
Has not received any funding.
All authors have declared no conflicts of interest.