Meta-Analysis of EGF-Stimulated Normal and Cancer Cell Lines to Discover EGF-Associated Oncogenic Signaling Pathways and Prognostic Biomarkers.

ABSTRACT:

Background

Although epidermal growth factor (EGF) controls many crucial processes in the human body, it can increase the risk of developing cancer when overexpresses.

Objectives

This study focused on detecting cancer-associated genes that are dysregulated by EGF overexpression.

Materials and methods

To identify differentially expressed genes (DEGs), two independent meta-analyses with normal and cancer RNA-Seq samples treated by EGF were conducted. The new DEGs detected only via two meta-analyses were used in all downstream analyses. To reach count data, the tools of FastQC, Trimmomatic, HISAT2, SAMtools, and HTSeq-count were employed. DEGs in each individual RNA-Seq study and the meta-analysis of RNA-Seq studies were identified using DESeq2 and metaSeq R package, resp

SUBMITTER: Garousi S 

PROVIDER: S-EPMC9618017 | biostudies-literature | 2022 Jul

REPOSITORIES: biostudies-literature