CJ Peters, JRE Rees, RH Hardwick, JS Hardwick, SL Vowler, C-AJ Ong, C Zhang, V Save, M O'Donovan, D Rassl, D Alderson, C Caldas, RC Fitzgerald, Oesophageal Cancer Clinical and Molecular Stratification (OCCAMS) Study Group
Journal name: 
Citation info: 
BACKGROUND & AIMS: The incidence of esophageal and junctional adenocarcinoma has increased 6-fold in the past 30 years and 5-year survival remains approximately 20%. Current staging is limited in its ability to predict survival which has ramifications for treatment choices. The aim of this study was to generate and validate a molecular prognostic signature for esophageal adenocarcinoma. METHODS: Gene expression profiling was performed and the resulting 42,000 gene signatures correlated with clinical and pathologic features for 75 snap-frozen esophageal and junctional resection specimens. External validation of selected targets was performed on 371 independent cases using immunohistochemistry to maximize clinical applicability. RESULTS: A total of 119 genes were associated significantly with survival and 270 genes with the number of involved lymph nodes. Filtering of these lists resulted in a shortlist of 10 genes taken forward to validation. Four genes proved to be prognostic at the protein level (deoxycytidine kinase [DCK], 3'-phosphoadenosine 5'-phosphosulfate synthase 2 [PAPSS2], sirtuin 2 [SIRT2], and tripartite motif-containing 44 [TRIM44]) and were combined to create a molecular prognostic signature. This 4-gene signature was highly predictive of survival in the independent external validation cohort (0/4 genes dysregulated 5-year survival, 58%; 95% confidence interval [CI], 36%-80%; 1-2/4 genes dysregulated 5-year survival, 26%; 95% CI, 20%-32%; and 3-4/4 genes dysregulated 5-year survival, 14%; 95% CI, 4%-24% (P = .001). Furthermore, this 4-gene signature was independently prognostic in a multivariable model together with the existing clinical TNM staging system (P = .013). CONCLUSIONS: This study has generated a clinically applicable prognostic gene signature that independently predicts survival in an external validation cohort and may inform management decisions.
Research group: 
Caldas Group
E-pub date: 
31 Dec 2010
Users with this publication listed: 
Carlos Caldas