Gene expression profiling of epithelial ovarian cancer reveals key genes and pathways associated with chemotherapy resistance

Abstract

ABSTRACT. The aim of this study is to analyze gene expression data to identify key genes and pathways associated with resistance to platinumbased chemotherapy in epithelial ovarian cancer (EOC) and to improve clinical treatment strategies. The gene expression data set was downloaded from Gene Expression Omnibus and included 12 chemotherapy-resistant EOC samples and 16 chemotherapy-sensitive EOC samples. A differential analysis was performed to screen out differentially expressed genes (DEGs). A functional enrichment analysis was conducted for the DEGs using the database for annotation, visualization, and integration discovery. A protein-protein interaction (PPI) network was constructed with information from the human protein reference database. Pathway-pathway interactions were determined with a test based on the hypergeometric distribution. A total of 1564 DEGs were identified in chemotherapy-sensitive EOC, including 654 upregulated genes and 910 downregulated genes. The top three upregulated genes were HIST1H3G, AKT3, and RTN3, while the top three downregulated genes were NBLA00301, TRIM62, and EPHA5. A Gene Ontology enrichment analysis showed that cell adhesion, biological adhesion, and intracellular signaling cascades were significantly enriched in the DEGs. A KEGG pathway enrichment analysis revealed that the calcium, mitogen-activated protein kinase, and B cell receptor signaling pathways were significantly over-represented in the DEGs. A PPI network containing 101 interactions was acquired. The top three hub genes were RAC1, CAV1, and BCL2. Five modules were identified from the PPI network. Taken together, these findings could advance the understanding of the molecular mechanisms underlying intrinsic chemotherapy resistance in EOC.

Identification and analysis of long non-coding RNA related miRNA sponge regulatory network in bladder urothelial carcinoma

“…For example, IL6, HIST1H3C, and HIST1H3G, which were classified with high degrees are present in pathways associated with transcriptional dysregulation in cancer. In addition, these three genes have been previously reported to be closely associated with tumorigenesis and development [71–73].…”

Urine proteomics of primary membranous nephropathy using nanoscale liquid chromatography tandem mass spectrometry analysis

“…We performed gene ontology (GO) bioinformatics analysis on the differentially expressed proteins with a 1.5-fold change to catalog the molecular functions, cellular components and biological processes [ 26 ]. The enrichment analysis of the proteins was conducted with all proteins GO biological processes database information from our study using the following formula [ 27 ]: where N is the number of all proteins within the GO annotation information, n is the number of differentially regulated proteins within GO annotation information, M is the number of proteins for a given GO annotation, and m is the number of differentially regulated proteins following a given GO annotation. Significant GO enrichment was defined as P ≤ 0.05.…”

Hypoxia and Selective Autophagy in Cancer Development and Therapy

“…Moreover, studies performed in cancer tissues from patients point toward an oncogenic role of RTN3, as it was shown that increased RTN3 levels are observed in astrocytoma whereas no expression was observed in healthy glial cells (Huang et al, 2004 ). Furthermore, RTN3 was one of the top three upregulated genes in chemotherapy-sensitive epithelial ovarian cancer samples pointing toward an anti-tumor role under these conditions (Zhang and Luo, 2016 ). These findings highlight the need for tight regulation of selective autophagy components within the tumor microenvironment.…”