A stepwise integrated approach to personalized risk predictions in stage III colorectal cancer

Salvucci, M. et al. (2017) A stepwise integrated approach to personalized risk predictions in stage III colorectal cancer. Clinical Cancer Research, 23(5), pp. 1200-1212. (doi: 10.1158/1078-0432.CCR-16-1084) (PMID:27649552)

Abstract

Purpose: Apoptosis is essential for chemotherapy responses. In this discovery and validation study, we evaluated the suitability of a mathematical model of apoptosis execution (APOPTO-CELL) as a stand-alone signature and as a constituent of further refined prognostic stratification tools. Experimental Design: Apoptosis competency of primary tumor samples from patients with stage III colorectal cancer (n = 120) was calculated by APOPTO-CELL from measured protein concentrations of Procaspase-3, Procaspase-9, SMAC, and XIAP. An enriched APOPTO-CELL signature (APOPTO-CELL-PC3) was synthesized to capture apoptosome-independent effects of Caspase-3. Furthermore, a machine learning Random Forest approach was applied to APOPTO-CELL-PC3 and available molecular and clinicopathologic data to identify a further enhanced signature. Association of the signature with prognosis was evaluated in an independent colon adenocarcinoma cohort (TCGA COAD, n = 136). Results: We identified 3 prognostic biomarkers (P = 0.04, P = 0.006, and P = 0.0004 for APOPTO-CELL, APOPTO-CELL-PC3, and Random Forest signatures, respectively) with increasing stratification accuracy for patients with stage III colorectal cancer. The APOPTO-CELL-PC3 signature ranked highest among all features. The prognostic value of the signatures was independently validated in stage III TCGA COAD patients (P = 0.01, P = 0.04, and P = 0.02 for APOPTO-CELL, APOPTO-CELL-PC3, and Random Forest signatures, respectively). The signatures provided further stratification for patients with CMS1-3 molecular subtype. Conclusions: The integration of a systems-biology–based biomarker for apoptosis competency with machine learning approaches is an appealing and innovative strategy toward refined patient stratification. The prognostic value of apoptosis competency is independent of other available clinicopathologic and molecular factors, with tangible potential of being introduced in the clinical management of patients with stage III colorectal cancer.

• Item Type: Articles
• Additional Information: The authors acknowledge support for their work by the European Union Framework Programme 7 (FP7 APO-DECIDE) under contract no. 306021. J.H.M. Prehn is supported by a Science Foundation Ireland Investigator Award (13/IA/1881) and by the Irish Cancer Society BreastPredict Collaborative Research Centre (CCRC13GAL). J.H.M. Prehn, M. Rehm, and D.B. Longley are supported by a Science Foundation Ireland/Department of Enterprise and Learning Partnership Award (14/IA/2582). E. Zink was supported by a Health Research Board Translational Research Supplementary Award (TRA/2007/26). L.M. Scholler was supported by the European Community Action Scheme for € the Mobility of University Students (ERASMUS).
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Wilson, Professor Richard
• Authors: Salvucci, M., Würstle, M. L., Morgan, C., Curry, S., Cremona, M., Lindner, A. U., Bacon, O., Resler, A. J., Murphy, Á. C., O'Byrne, R., Flanagan, L., Dasgupta, S., Rice, N., Pilati, C., Zink, E., Schöller, L. M., Toomey, S., Lawler, M., Johnston, P. G., Wilson, R., Camilleri-Broët, S., Salto-Tellez, M., McNamara, D. A., Kay, E. W., Laurent-Puig, P., Van Schaeybroeck, S., Hennessy, B. T., Longley, D. B., Rehm, M., and Prehn, J. H.M.
• College/School: College of Medical Veterinary and Life Sciences > School of Cancer Sciences
• Journal Name: Clinical Cancer Research
• Publisher: American Association for Cancer Research
• ISSN: 1078-0432
• ISSN (Online): 1557-3265
• Published Online: 20 September 2016