A gene expression model of intrinsic tumor radiosensitivity: prediction of response and prognosis after chemoradiation

Abstract

Purpose: Development of a radiosensitivity predictive assay is a central goal of radiation oncology. We reasoned a gene expression model could be developed to predict intrinsic radiosensitivity and treatment response in patients.

Methods and materials: Radiosensitivity (determined by survival fraction at 2 Gy) was modeled as a function of gene expression, tissue of origin, ras status (mut/wt), and p53 status (mut/wt) in 48 human cancer cell lines. Ten genes were identified and used to build a rank-based linear regression algorithm to predict an intrinsic radiosensitivity index (RSI, high index = radioresistance). This model was applied to three independent cohorts treated with concurrent chemoradiation: head-and-neck cancer (HNC, n = 92); rectal cancer (n = 14); and esophageal cancer (n = 12).

Results: Predicted RSI was significantly different in responders (R) vs. nonresponders (NR) in the rectal (RSI R vs. NR 0.32 vs. 0.46, p = 0.03), esophageal (RSI R vs. NR 0.37 vs. 0.50, p = 0.05) and combined rectal/esophageal (RSI R vs. NR 0.34 vs. 0.48, p = 0.001511) cohorts. Using a threshold RSI of 0.46, the model has a sensitivity of 80%, specificity of 82%, and positive predictive value of 86%. Finally, we evaluated the model as a prognostic marker in HNC. There was an improved 2-year locoregional control (LRC) in the predicted radiosensitive group (2-year LRC 86% vs. 61%, p = 0.05).

Conclusions: We validate a robust multigene expression model of intrinsic tumor radiosensitivity in three independent cohorts totaling 118 patients. To our knowledge, this is the first time that a systems biology-based radiosensitivity model is validated in multiple independent clinical datasets.

Fig. 1

Radiosensitivity index (RSI) is correlated with clinical response to concurrent radiochemotherapy in rectal and esophageal cancer patients. (A) The mean predicted RSI of responders is significantly lower than in nonresponders in both clinical cohorts (esophageal: p = 0.05, rectal: p = 0.03). (B) Predicted RSI of each individual patient in the cohorts (combined: p = 0.001511).

Fig. 2

Receiver-operating characteristic curve using predicted radiosensitivity index (RSI) for radiosensitivity predictions. Using a threshold RSI of 0.4619592, the predictor has an 80% sensitivity and 82% specificity, with positive predictive value (PPV) of 86%. The estimated area under the curve (AUC) is 0.84.

Fig. 3

Radiosensitivity index (RSI) distinguishes clinical populations with different disease-related outcomes in a head-and-neck cancer (HNC) cohort of 92 patients treated with definitive concurrent radiochemotherapy. Using the 25th percentile (RSI < 0.023), there is a superior 2-year locoregional control (LRC) in the predicted radiosensitive group (86% vs. 61%, p = 0.05).