期刊
CLINICAL CANCER RESEARCH
卷 19, 期 5, 页码 1197-1203出版社
AMER ASSOC CANCER RESEARCH
DOI: 10.1158/1078-0432.CCR-12-2647
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资金
- NIH, National Cancer Institute [NIH NCI R01CA095419]
- National Center for Research Resources grant [1KL2RR025015-01]
- Amos Medical Faculty Development Program Award from the Robert Wood Johnson Foundation
- Fred Hutchinson Cancer Research Center
- Specialized Program of Research Excellence in Head and Neck Cancer Grant from the National Cancer Institute [P50CA97007]
- Clinician Investigator Program in Translational Research [K12CA088084]
- Clinical Research Program [2 L30CA117652-02A1]
- THANC Foundation Young Investigator Award
Purpose: To identify a prognostic gene signature for patients with human papilloma virus (HPV)negative oral squamous cell carcinomas (OSCC). Experimental Design: Two gene expression datasets were used: a training dataset from the Fred Hutchinson Cancer Research Center (FHCRC, Seattle, WA; n = 97) and a validation dataset from the MD Anderson Cancer Center (MDACC, Houston, TX; n = 71). We applied L1/L2-penalized Cox regression models to the FHCRC data on the 131-gene signature previously identified to be prognostic in patients with OSCCs to identify a prognostic model specific for patients with high-risk HPV-negative OSCCs. The models were tested with the MDACC dataset using a receiver operating characteristic (ROC) analysis. Results: A 13-gene model was identified as the best predictor of HPV-negative OSCC-specific survival in the training dataset. The risk score for each patient in the validation dataset was calculated from this model and dichotomized at the median. The estimated 2-year mortality (+/- SE) of patients with high-risk scores was 47.1% (+/- 9.24%) compared with 6.35% (+/- 4.42) for patients with low-risk scores. ROC analyses showed that the areas under the curve for the age, gender, and treatment modality-adjusted models with risk score [0.78; 95% confidence interval (CI), 0.74-0.86] and risk score plus tumor stage (0.79; 95% CI, 0.75-0.87) were substantially higher than for the model with tumor stage (0.54; 95% CI, 0.48-0.62). Conclusions: We identified and validated a 13-gene signature that is considerably better than tumor stage in predicting survival of patients with HPV-negative OSCCs. Further evaluation of this gene signature as a prognostic marker in other populations of patients with HPV-negative OSCC is warranted. Clin Cancer Res; 19(5); 1197-203. (C) 2012 AACR.
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