Development of a four-gene prognostic model for pancreatic cancer based on transcriptome dysregulation.

ABSTRACT: We systematically developed a prognostic model for pancreatic cancer that was compatible across different transcriptomic platforms and patient cohorts. After performing quality control measures, we used seven microarray datasets and two RNA sequencing datasets to identify consistently dysregulated genes in pancreatic cancer patients. Weighted gene co-expression network analysis was performed to explore the associations between gene expression patterns and clinical features. The least absolute shrinkage and selection operator (LASSO) and Cox regression were used to construct a prognostic model. We tested the predictive power of the model by determining the area under the curve of the risk score for time-dependent survival. Most of the differentially expressed genes in pancreatic cancer were

SUBMITTER: Yan J 

PROVIDER: S-EPMC7066910 | biostudies-literature | 2020 Feb

REPOSITORIES: biostudies-literature