Screening and verification of potential gene targets in esophageal carcinoma by bioinformatics analysis and immunohistochemistry.

ABSTRACT:

Background

To evaluate the potential of candidate proteins as diagnostic markers or drug targets in esophageal carcinoma (ESCA).

Methods

GSE20347, GSE17351, and GSE45670 were downloaded from Gene Expression Omnibus (GEO). Differently expressed genes (DEGs) between ESCA and normal esophageal tissues from patients were obtained. Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed. The genes commonly featured in ESCA were screened by least absolute shrinkage and selection operator (LASSO) logistic regression and Boruta feature selection algorithm. The transcriptome data and corresponding clinical data of ESCA were downloaded from The Cancer Genome Atlas (TCGA) public database. Kaplan-Meier survival analysis w

SUBMITTER: Wen P 

PROVIDER: S-EPMC8848373 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature