title: A multi-gene signature predicts outcome in patients with pancreatic ductal adenocarcinoma.
abstract: BACKGROUND
  Improved usage of the repertoires of pancreatic ductal adenocarcinoma (PDAC) profiles is crucially needed to guide the development of predictive and prognostic tools that could inform the selection of treatment options.
  
  
  METHODS
  Using publicly available mRNA abundance datasets, we performed a large retrospective meta-analysis on 466 PDAC patients to discover prognostic gene signatures. These signatures were trained on two clinical cohorts (n = 70), and validated on four independent clinical cohorts (n = 246). Further validation of the identified gene signature was performed using quantitative real-time RT-PCR.
  
  
  RESULTS
  We identified 225 candidate prognostic genes. Using these, a 36-gene signature was discovered and validated on fully independent clinical cohorts (hazard ratio (HR) = 2.06, 95% confidence interval (CI) = 1.51 to 2.81, P = 3.62 × 10(-6), n = 246). This signature serves as a good alternative prognostic stratification marker compared to tumour grade (HR = 2.05, 95% CI = 1.45 to 2.88, P = 3.18 × 10(-5)) and tumour node metastasis (TNM) stage (HR = 1.13, 95% CI = 0.66 to 1.94, P = 0.67). Upon multivariate analysis with adjustment for TNM stage and tumour grade, the 36-gene signature remained an independent prognostic predictor of clinical outcome (HR = 2.21, 95% CI = 1.17 to 4.16, P = 0.01). Univariate assessment revealed higher expression of ITGA5, SEMA3A, KIF4A, IL20RB, SLC20A1, CDC45, PXN, SSX3 and TMEM26 was correlated with shorter survival while B3GNT1, NOSTRIN and CADPS down-regulation was associated with poor outcome.
  
  
  CONCLUSIONS
  Our 36-gene classifier is able to prognosticate PDAC independent of patient cohort and microarray platforms. Further work on the functional roles, downstream events and interactions of the signature genes is likely to reveal true molecular candidates for PDAC therapeutics.
authors.affiliation: Centre for Molecular Oncology, Barts Cancer Institute, London, United Kingdom.
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authors.affiliation: Centre for Molecular Oncology, Barts Cancer Institute, London, United Kingdom.
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authors.affiliation: Centre for Molecular Oncology, Barts Cancer Institute, London, United Kingdom.
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authors.affiliation: Centre for Tumour Biology, Barts Cancer Institute, London, United Kingdom.
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authors.affiliation: Centre for Cancer and Inflammation, Barts Cancer Institute, London, United Kingdom.
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authors.affiliation: Centre for Tumour Biology, Barts Cancer Institute, London, United Kingdom.
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authors.affiliation: Centre for Tumour Biology, Barts Cancer Institute, London, United Kingdom.
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authors.affiliation: Centre for Molecular Oncology, Barts Cancer Institute, London, United Kingdom.
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authors.affiliation: ARC-Net Research Centre and Department of Pathology and Diagnostics, University and Hospital Trust of Verona, Verona, Italy.
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authors.affiliation: Centre for Molecular Oncology, Barts Cancer Institute, London, United Kingdom.
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authors.affiliation: Centre for Molecular Oncology, Barts Cancer Institute, London, United Kingdom.
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