The integration of differentially expressed genes based on multiple microarray datasets for prediction of the prognosis in oral squamous cell carcinoma.

ABSTRACT: Oral squamous cell carcinoma (OSCC) is a common human malignancy. However, its pathogenesis and prognostic information are poorly elucidated. In the present study, we aimed to probe the most significant differentially expressed genes (DEGs) and their prognostic performance in OSCC. Multiple microarray datasets from the Gene Expression Omnibus (GEO) database were aggregated to identify DEGs between OSCC tissue and control tissue. Least absolute shrinkage and selection operator (LASSO) Cox model was constructed to determine the prognostic performance of the aggregated DEGs based on The Cancer Genome Atlas (TCGA) OSCC cohort. Ten datasets with 341 OSCC samples and 283 control samples were included. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment revealed that the integrated

SUBMITTER: Zhao Y 

PROVIDER: S-EPMC8806768 | biostudies-literature | 2021 Dec

REPOSITORIES: biostudies-literature