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.
| Original language | English |
|---|---|
| Pages (from-to) | 489-496 |
| Number of pages | 8 |
| Journal | International Journal of Radiation Oncology Biology Physics |
| Volume | 75 |
| Issue number | 2 |
| DOIs | |
| State | Published - Oct 1 2009 |
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Keywords
- Chemoradiation
- Gene expression
- Intrinsic radiosensitivity
- Predictive assay
- Systems biology
ASJC Scopus subject areas
- Oncology
- Radiology Nuclear Medicine and imaging
- Radiation
- Cancer Research
Cite this
A Gene Expression Model of Intrinsic Tumor Radiosensitivity : Prediction of Response and Prognosis After Chemoradiation. / Eschrich, Steven A.; Pramana, Jimmy; Zhang, Hongling; Zhao, Haiyan; Boulware, David; Lee, Ji Hyun; Bloom, Gregory; Rocha-Lima, Caio; Kelley, Scott; Calvin, Douglas P.; Yeatman, Timothy J.; Begg, Adrian C.; Torres-Roca, Javier F.
In: International Journal of Radiation Oncology Biology Physics, Vol. 75, No. 2, 01.10.2009, p. 489-496.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - A Gene Expression Model of Intrinsic Tumor Radiosensitivity
T2 - Prediction of Response and Prognosis After Chemoradiation
AU - Eschrich, Steven A.
AU - Pramana, Jimmy
AU - Zhang, Hongling
AU - Zhao, Haiyan
AU - Boulware, David
AU - Lee, Ji Hyun
AU - Bloom, Gregory
AU - Rocha-Lima, Caio
AU - Kelley, Scott
AU - Calvin, Douglas P.
AU - Yeatman, Timothy J.
AU - Begg, Adrian C.
AU - Torres-Roca, Javier F.
PY - 2009/10/1
Y1 - 2009/10/1
N2 - 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.
AB - 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.
KW - Chemoradiation
KW - Gene expression
KW - Intrinsic radiosensitivity
KW - Predictive assay
KW - Systems biology
UR - http://www.scopus.com/inward/record.url?scp=69549116364&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=69549116364&partnerID=8YFLogxK
U2 - 10.1016/j.ijrobp.2009.06.014
DO - 10.1016/j.ijrobp.2009.06.014
M3 - Article
C2 - 19735873
AN - SCOPUS:69549116364
VL - 75
SP - 489
EP - 496
JO - International Journal of Radiation Oncology Biology Physics
JF - International Journal of Radiation Oncology Biology Physics
SN - 0360-3016
IS - 2
ER -