Unknown

Dataset Information

Identification of a chemoresistance-related prognostic gene signature by comprehensive analysis and experimental validation in pancreatic cancer.


ABSTRACT:

Background

Chemoresistance is a major hurdle to improving the prognosis of pancreatic cancer (PC). This study aimed to identify key genes regulating chemoresistance and develop a chemoresistance-related gene signature for prognosis prediction.

Methods

A total of 30 PC cell lines were subtyped according to gemcitabine sensitivity data from the Cancer Therapeutics Response Portal (CTRP v2). Differentially expressed genes (DEGs) between gemcitabine-resistant and gemcitabine-sensitive cells were subsequently identified. These upregulated DEGs associated with prognostic values were incorporated to build a LASSO Cox risk model for The Cancer Genome Atlas (TCGA) cohort. Four datasets (GSE28735, GSE62452, GSE85916, and GSE102238) from the Gene Expression Omnibus (GEO) were used as a

SUBMITTER: Chen J 

PROVIDER: S-EPMC10213255 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature