Abstract
Transcriptional profiling of lung adenocarcinomas has identified numerous gene expression phenotype (GEP) and risk prediction (RP) signatures associated with patient outcome. However, classification agreement between signatures, underlying transcriptional programs, and independent signature validation are less studied. We classified 2395 transcriptional adenocarcinoma profiles, assembled from 17 public cohorts, using 11 GEP and seven RP signatures, finding that 16 signatures were associated with patient survival in the total cohort and in multiple individual cohorts. For significant signatures, total cohort hazard ratios were ~2 in univariate analyses (mean=1.95, range=1.4-2.6). Strong classification agreement between signatures was observed, especially for predicted low-risk patients by adenocarcinoma-derived signatures. Expression of proliferation-related genes correlated strongly with GEP subtype classifications and RP scores, driving the gene signature association with prognosis. A three-group consensus definition of samples across 10 GEP classifiers demonstrated aggregation of samples with specific smoking patterns, gender, and EGFR/KRAS mutations, while survival differences were only significant when patients were divided into low- or high-risk. In summary, our study demonstrates a consensus between GEPs and RPs in lung adenocarcinoma through a common underlying transcriptional program. This consensus generalizes reported problems with current signatures in a clinical context, stressing development of new adenocarcinoma-specific single sample predictors for clinical use.
Highlights
Lung cancer is the leading cause of cancer death worldwide, with adenocarcinoma as the largest histological subtype [1, 2]
Our results provide increased understanding of gene expression phenotype (GEP) and risk prediction (RP) gene signatures performance, consensus, and www.impactjournals.com/oncotarget prognostic values in lung adenocarcinoma
Cases classified as lowrisk by different GEP and RP signatures showed lower expression of proliferation-related genes, and coincided well with a 50/50% split of cases by a breast cancer derived proliferation score, or as we demonstrated with proliferation signatures derived in other diseases [32, 33]
Summary
Lung cancer is the leading cause of cancer death worldwide, with adenocarcinoma as the largest histological subtype [1, 2]. Significant advances have been made in understanding the molecular characteristics of lung adenocarcinoma Some of these discoveries have been translated into new therapeutic options, with targeted treatments for patients with tumors harboring EGFR mutations or ALK gene fusions representing success stories. Even for NSCLC patients with the best prognosis, resectable stage I disease, approximately 30% will relapse with a 5-year survival rate of 58-73% [3]. This heterogeneity in the clinical course of patients with the same tumor stage stresses the need for additional biomarkers that can improve prognostication and prediction of response to therapy in lung adenocarcinoma
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