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Consensus of gene expression phenotypes and prognostic risk predictors in primary lung adenocarcinoma

  • Markus Ringnér
  • Johan Staaf
Publishing year: 2016-07-16
Language: English
Pages: 52957-52973
Publication/Series: Oncotarget
Volume: 7
Issue: 33
Document type: Journal article
Publisher: Impact Journals, LLC

Abstract english

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.


  • Medical Genetics
  • Cancer and Oncology
  • lung adenocarcinoma
  • molecular subtype
  • gene expression
  • prognostic
  • risk predictor


  • Research Group Lung Cancer
  • ISSN: 1949-2553
Markus Ringnér
E-mail: markus [dot] ringner [at] biol [dot] lu [dot] se

Research engineer

Molecular Cell Biology


Sölvegatan 35, Lund