Analysis of cancer-promoting genes related to chemotherapy resistance in esophageal squamous cell carcinoma.

ABSTRACT

Background: According to histopathology, esophageal cancer can be divided into squamous cell carcinoma (SCC) and esophageal adenocarcinoma (adeno arcinoma). In China, 90% of esophageal cancer patients are squamous cell carcinoma. Cisplatin and fluaziridine are the main chemotherapy before and after surgery. Long-term drug treatment is often accompanied by the emergence of drug resistance of tumor cells. There are many mechanisms for the emergence of drug resistance of tumor cells, including the increase of drug efflux, the decrease of drug intake, the inhibition of cell apoptosis, and so on. This study aimed to investigate the key cancer-promoting genes related to chemotherapy resistance in esophageal squamous cell carcinoma (ESCC). Methods: Two datasets from the Gene Expression Omnibus (GEO) database (GSE86099 and GSE50224) were retrieved. We performed microRNA (miRNA) and messenger RNA (mRNA) expression analysis to identify differentially expressed genes (DEGs). The intersection of the downregulated miRNA targets and the upregulated mRNAs were used for Gene Ontology (GO) enrichment analysis, and survival risk was assessed using data from The Cancer Genome Atlas (TCGA). Results: There were 35 common genes, of which, based on GO enrichment, most were related to the cardiac muscle cell action. Four genes showed significant association with the estimated half-maximal inhibitory concentration (IC50) of paclitaxel bone morphogenetic protein 1 (BMP1), dumbbell former 4 protein (DBF4), angiogenin (ANG), and MAP7 domain containing 2 (MAP7D2). Four risk factors (MP1, HIP1, ANG, and MAP7D2) were selected to generate a signature using least absolute shrinkage and selection operator (LASSO) regression. Protein-protein interaction (PPI) analysis showed guanine nucleotide-binding protein subunit beta 4 (GNB4), calcium voltage-gated channel auxiliary subunit beta 2 (CACNB2), and sodium voltage-gated channel alpha subunit 1 (SCN1A) were located at key positions of the network. Among potential risk genes, only the high expression of dedicator of cytokinesis 8 (DOCK8) was associated with poorer survival. Conclusions: The 35 oncogenes may be involved in mechanisms of chemotherapy resistance in ESCC, as well as the corresponding enrichment and regulatory network. The signature containing 4 key risk genes merits further investigation and may provide a deeper understanding of the molecular mechanisms in ESCC treatment failure.