Dataset Information


Integration of molecular gene signatures with clinicopathological variables improves staging and outcome prediction of oral cancer.

ABSTRACT: The aim of this study is to identify and validate clinically implementable gene signatures for outcome prediction of patients with oral squamous cell carcinoma. Overall design: Tumor gene expression profiles of surgical specimen of patients with oral squamous cell carcinoma (OSCC)

INSTRUMENT(S): Agilent-014850 Whole Human Genome Microarray 4x44K G4112F (Probe Name version)

SUBMITTER: Nicoletta Bertani  

PROVIDER: GSE84846 | GEO | 2017-08-23



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Accurate staging and outcome prediction is a major problem in clinical management of oral cancer patients, hampering high precision treatment and adjuvant therapy planning. Here, we have built and validated multivariable models that integrate gene signatures with clinical and pathological variables to improve staging and survival prediction of patients with oral squamous cell carcinoma (OSCC). Gene expression profiles from 249 human papillomavirus (HPV)-negative OSCCs were explored to identify a  ...[more]

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