Supervised learning methods for the prediction of tumor radiosensitivity to preoperative radiochemotherapy

Abstract

Disclosed is a gene expression panel that can predict radiation sensitivity (radiosensitivity) of a tumor in a subject. A method of predicting radiation sensitivity is provided that is based on cellular clonogenic survival after 2 Gy (SF2) for 48 cell lines. Gene expression is used as the basis of the prediction model. The radiosensitivity cell-based prediction model is validated using clinical patient data from rectal and esophagus cancer patients that received RT before surgery. The radiosensitivity genomic-based pre-diction model identifies patients with rectal cancer that may benefit from RT treatment by assigning higher values of SF2 to radio-resistant patients and lower values of SF2 to radio-sensitive patients.

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