Details

Autor(en) / Beteiligte

• Folkvord, Sigurd, M.D., Ph.D
• Flatmark, Kjersti, M.D., Ph.D
• Dueland, Svein, M.D., Ph.D
• de Wijn, Rik, Ph.D
• Grøholt, Krystyna Kotanska, M.D
• Hole, Knut H., M.D
• Nesland, Jahn M., M.D., Ph.D
• Ruijtenbeek, Rob, Ph.D
• Boender, Piet J., Ph.D
• Johansen, Marianne, R.N
• Giercksky, Karl-Erik, M.D., Ph.D
• Ree, Anne Hansen, M.D., Ph.D

Titel

Prediction of Response to Preoperative Chemoradiotherapy in Rectal Cancer by Multiplex Kinase Activity Profiling

Ist Teil von

• International journal of radiation oncology, biology, physics, 2010-10, Vol.78 (2), p.555-562

Ort / Verlag

New York, NY: Elsevier Inc

Erscheinungsjahr

2010

Quelle

MEDLINE

Beschreibungen/Notizen

• Purpose Tumor response of rectal cancer to preoperative chemoradiotherapy (CRT) varies considerably. In experimental tumor models and clinical radiotherapy, activity of particular subsets of kinase signaling pathways seems to predict radiation response. This study aimed to determine whether tumor kinase activity profiles might predict tumor response to preoperative CRT in locally advanced rectal cancer (LARC). Methods and Materials Sixty-seven LARC patients were treated with a CRT regimen consisting of radiotherapy, fluorouracil, and, where possible, oxaliplatin. Pretreatment tumor biopsy specimens were analyzed using microarrays with kinase substrates, and the resulting substrate phosphorylation patterns were correlated with tumor response to preoperative treatment as assessed by histomorphologic tumor regression grade (TRG). A predictive model for TRG scores from phosphosubstrate signatures was obtained by partial-least-squares discriminant analysis. Prediction performance was evaluated by leave-one-out cross-validation and use of an independent test set. Results In the patient population, 73% and 15% were scored as good responders (TRG 1–2) or intermediate responders (TRG 3), whereas 12% were assessed as poor responders (TRG 4–5). In a subset of 7 poor responders and 12 good responders, treatment outcome was correctly predicted for 95%. Application of the prediction model on the remaining patient samples resulted in correct prediction for 85%. Phosphosubstrate signatures generated by poor-responding tumors indicated high kinase activity, which was inhibited by the kinase inhibitor sunitinib, and several discriminating phosphosubstrates represented proteins derived from signaling pathways implicated in radioresistance. Conclusions Multiplex kinase activity profiling may identify functional biomarkers predictive of tumor response to preoperative CRT in LARC.