Conserved recurrent gene mutations correlate with pathway deregulation and clinical outcomes of lung adenocarcinoma in never-smokers
1 Department of Health Sciences Research, Mayo Clinic, 200 First St SW, Rochester, MN 55905, USA
2 Department of Pathology, Medical College of Wisconsin, Milwaukee, WI 53226, USA
3 Medical Genome Facility, Mayo Clinic, Rochester, MN 55905, USA
4 Department of Pharmacology and Toxicology, Medical College of Wisconsin, Milwaukee, Wisconsin 53226, USA
5 Thoracic Surgery Department, Institute of Surgery Research, Daping Hospital, Third Military Medical University, Chongqing, People’s Republic of China
6 Division of Preventive Medicine, School of Environmental Science and Public Health, Wenzhou Medical University, Wenzhou, Zhejiang, China
BMC Medical Genomics 2014, 7:32 doi:10.1186/1755-8794-7-32Published: 4 June 2014
Novel and targetable mutations are needed for improved understanding and treatment of lung cancer in never-smokers.
Twenty-seven lung adenocarcinomas from never-smokers were sequenced by both exome and mRNA-seq with respective normal tissues. Somatic mutations were detected and compared with pathway deregulation, tumor phenotypes and clinical outcomes.
Although somatic mutations in DNA or mRNA ranged from hundreds to thousands in each tumor, the overlap mutations between the two were only a few to a couple of hundreds. The number of somatic mutations from either DNA or mRNA was not significantly associated with clinical variables; however, the number of overlap mutations was associated with cancer subtype. These overlap mutants were preferentially expressed in mRNA with consistently higher allele frequency in mRNA than in DNA. Ten genes (EGFR, TP53, KRAS, RPS6KB2, ATXN2, DHX9, PTPN13, SP1, SPTAN1 and MYOF) had recurrent mutations and these mutations were highly correlated with pathway deregulation and patient survival.
The recurrent mutations present in both DNA and RNA are likely the driver for tumor biology, pathway deregulation and clinical outcomes. The information may be used for patient stratification and therapeutic target development.