Identification of the key genes associated with chemotherapy sensitivity in ovarian cancer patients

Abstract

Background: Ovarian cancer (OC) is the deadliest gynecological cancer. The absence of biomarkers in early detection and chemotherapy resistance is a principal cause of treatment failure in OC. Methods: In this study, next generation sequencing (NGS) was used to sequence the mRNA of 44 OC patients including 14 chemotherapy insensitive and 18 sensitive patients. Differentially expressed genes (DEGs) from OC patients (compared with healthy controls) and chemotherapy sensitive patients (compared with chemotherapy insensitive patients) were identified by edgeR v3.12.0 in R v3.2.2, which were enriched using Gene Ontology (GO) database and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG). The common DEGs in cancer occurring and chemotherapy sensitivity were further screened. Among them, genes participating in chemotherapy sensitivity associated pathways were regarded as chemotherapy sensitivity-related key genes. Quantitative real-time PCR (qPCR) and immunohistochemistry (IHC) were used to verify the expression of the key genes. Results: We found 1588 DEGs between OC patients and healthy controls (HCs), which were mainly enriched in cell cycle pathway. Meanwhile, 249 DEGs were identified between chemotherapy sensitive and insensitive OC patients, which were mainly enriched in MAPK signaling pathway, ERBB signaling pathway, TNF signaling pathway, and IL-17 signaling pathway. Thirty-five DEGs were shared in chemotherapy sensitivity group and cancer occurring group. Among them, there are five genes (JUND, JUNB, MUC5B, NRG1, and NR4A1) participating in the above four chemotherapy sensitivity-related pathways. It is remarkable that JUND is in the upstream of MUC5B in IL-17 signaling pathway and their expressions were verified by qPCR and IHC. Conclusions: The expression levels of the key genes related to chemotherapy sensitivity might be used as biomarkers to predict the treatment outcome and as a target to improve prognosis.