J Cancer 2017; 8(7):1113-1122. doi:10.7150/jca.17872 This issue
1. Department of Molecular Biology and Genetics, Bilkent University, Cankaya, Ankara, Turkey;
2. Department of Gastroenterological Surgery, Antalya Education and Research Hospital, Antalya, Turkey;
3. Faculty of Medicine, Izmir University of Economics, Izmir, Turkey;
4. Fifth Department of Surgery, Ankara Numune Training and Research Hospital, Ankara, Turkey;
5. Department of Gastroenterological Surgery, Yuksek Ihtisas Training and Research Hospital, Ankara, Turkey;
6. Department of General and Oncological Surgery - Surgery C, The Chaim Sheba Medical Center, Tel Hashomer, Israel;
7. Department of Pathology, Yuksek Ihtisas Training and Research Hospital, Ankara, Turkey;
8. Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
Background: Prognostic biomarkers for cancer have the power to change the course of disease if they add value beyond known prognostic factors, if they can help shape treatment protocols, and if they are reliable. The aim of this study was to identify such biomarkers for colon cancer and to understand the molecular mechanisms leading to prognostic stratifications based on these biomarkers.
Methods and Findings: We used an in house R based script (SSAT) for the in silico discovery of stage-independent prognostic biomarkers using two cohorts, GSE17536 and GSE17537, that include 177 and 55 colon cancer patients, respectively. This identified 2 genes, ULBP2 and SEMA5A, which when used jointly, could distinguish patients with distinct prognosis. We validated our findings using a third cohort of 48 patients ex vivo. We find that in all cohorts, a combined ULBP2/SEMA5A classification (SU-GIB) can stratify distinct prognostic sub-groups with hazard ratios that range from 2.4 to 4.5 (p≤0.01) when overall- or cancer-specific survival is used as an end-measure, independent of confounding prognostic parameters. In addition, our preliminary analyses suggest SU-GIB is comparable to Oncotype DX colon(®) in predicting recurrence in two different cohorts (HR: 1.5-2; p≤0.02). SU-GIB has potential as a companion diagnostic for several drugs including the PI3K/mTOR inhibitor BEZ235, which are suitable for the treatment of patients within the bad prognosis group. We show that tumors from patients with worse prognosis have low EGFR autophosphorylation rates, but high caspase 7 activity, and show upregulation of pro-inflammatory cytokines that relate to a relatively mesenchymal phenotype.
Conclusions: We describe two novel genes that can be used to prognosticate colon cancer and suggest approaches by which such tumors can be treated. We also describe molecular characteristics of tumors stratified by the SU-GIB signature.
Keywords: Colon Cancer, Prognosis, Biomarker.