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A 13-gene signature prognostic of HPV-negative OSCC: discovery and external validation

ABSTRACT: OSCC is associated with substantial mortality and morbidity. In this study, we built on our previous molecular work to identify and validate a prognostic 13-gene signature that showed a higher ability than tumor stage in predicting survival for patients with HPV-negative oral squamous cell carcinoma (OSCC).

ORGANISM(S): Homo sapiens

PROVIDER: GSE41613 | GEO | 2013/03/07

SECONDARY ACCESSION(S): PRJNA177687

REPOSITORIES: GEO

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A 13-gene signature prognostic of HPV-negative OSCC: discovery and external validation

Project description:OSCC is associated with substantial mortality and morbidity. In this study, we built on our previous molecular work to identify and validate a prognostic 13-gene signature that showed a higher ability than tumor stage in predicting survival for patients with HPV-negative oral squamous cell carcinoma (OSCC). We previously reported 131 genes to be associated with survival in OSCC patients. In this study, we applied L1/L2-penalized Cox regression models to the Affymetrix array data from 97 HPV-negative OSCC patients on the 131 gene to identify a model for prediction of OSCC-specific survival. We then tested the model in an independent dataset and compared to tumor stage.

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Project description:To identify a prognostic gene signature for patients with human papilloma virus (HPV)-negative oral squamous cell carcinomas (OSCC).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.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).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.

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