A gene expression model of intrinsic tumor radiosensitivity: prediction of response and prognosis after chemoradiation.
OBJECTIVE
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
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.
Eschrich
Steven A
SA
H Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA.
Pramana
Jimmy
J
Zhang
Hongling
H
Zhao
Haiyan
H
Boulware
David
D
Lee
Ji-Hyun
JH
Bloom
Gregory
G
Rocha-Lima
Caio
C
Kelley
Scott
S
Calvin
Douglas P
DP
Yeatman
Timothy J
TJ
Begg
Adrian C
AC
Torres-Roca
Javier F
JF
D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D000970:Antineoplastic Agents / Q000008:administration & dosage; D045744:Cell Line, Tumor; D004938:Esophageal Neoplasms / Q000188:drug therapy / Q000235:genetics / Q000532:radiotherapy; D005260:Female; D015870:Gene Expression / Q000235:genetics*; D006258:Head and Neck Neoplasms / Q000188:drug therapy / Q000235:genetics / Q000532:radiotherapy; D006801:Humans; D016014:Linear Models; D008297:Male; D008875:Middle Aged; D008957:Models, Genetic; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods; D011379:Prognosis; D011446:Prospective Studies; D011836:Radiation Tolerance / Q000235:genetics*; D012004:Rectal Neoplasms / Q000188:drug therapy / Q000235:genetics / Q000532:radiotherapy; D019772:Topotecan / Q000008:administration & dosage
D000970:Antineoplastic Agents; D019772:Topotecan