Identifying genes as potential prognostic indicators in patients with serous ovarian cancer resistant to carboplatin using integrated bioinformatics analysis

Abstract

Serous ovarian cancer (SOC) accounts for >50% of all epithelial ovarian cancers. However, patients with SOC present with various degrees of response to platinum-based chemotherapy and, thus, their survival may differ. The present study aimed to identify the candidate genes involved in the carcinogenesis and drug resistance of SOC by analyzing the microarray datasets GDS1381 and GDS3592. GDS1381 and GDS3592 were downloaded from the Gene Expression Omnibus database (). A total of 219 differentially expressed genes (DEGs) were identified. Potential genes that may predict the response to carboplatin and, thus, the prognosis of SOC were analyzed. The enriched functions and pathways of DEGs included extracellular region, extracellular space and extracellular exosome, among others. Upon screening the upregulated and downregulated genes on the connectivity map, 10 small-molecule drugs were identified that may be helpful in improving drug sensitivity in patients with ovarian cancer. A total of 30 hub genes were screened for further analysis after constructing the protein-to-protein interaction network. Through survival analysis, comparison of genes across numerous analyses, and immunohistochemistry, GNAI1, non-structural maintenance of chromosomes (non-SMC) condensin I complex subunit H (NCAPH), matrix metallopeptidase 9 (MMP9), aurora kinase A (AURKA) and enhancer of zeste 2 polycomb repressive complex 2 subunit (EZH2) were identified as the key molecules that may be involved in the carcinogenesis and carboplatin resistance of SOC. In conclusion, GNAI1, NCAPH, MMP9, AURKA and EZH2 should be examined in further studies for the possibility of their participation in the carcinogenesis and carboplatin response of SOC.

Activation of the Anaphase Promoting Complex reverses multiple drug resistant cancer

“…Moreover, proteins that maintain chromosome condensation (the condensin complex) are also elevated (3 genes; marked by ***, Supplemental Table S5). Interestingly, a recent study comparing differentially expressed genes between normal human ovarian tissue and ovarian cancer, and carboplatin-sensitive and resistant ovarian tumors [46], identified a similar set of genes identified in our canine study; of the 5 top genes identified in their study (GNAI1, NCAPH, MMP9, AURKA and EZH2), three were identified in our study (NCAPH, AURKB (rather than AURKA) and EZH2). Taken together, our work suggests that MDR development in these 4 canines is associated with impaired APC activity.…”

“…Previous work has also demonstrated APC substrates to be elevated in cancer cells [80,82]. Furthermore, recent work comparing differential gene expression in drug sensitive and resistant ovarian tumor datasets [46] revealed a similar collection of genes that were identified by us; half of the 30 highly connected nodes they identified were associated with APC function or substrates. Consistent with these observations, remission and relapse of canine 4 following metformin treatment identified 27 genes that were upregulated in the tumor, downregulated following metformin treatment, then upregulated again following relapse (Fig.…”

“…The APC coactivator CDC20 is one of the mitotic substrates that is highly expressed. APC activity is inhibited by the SAC prior to mitosis via interactions with CDC20, which blocks CDC20's ability to interact with substrates, until all metaphase chromosomes are firmly attached to kinetochores [45][46][47][48][49]. It is interesting to note that many SAC components that are activated by incomplete attachment of microtubules to kinetochores, and kinetochore factors (BUB1, CENPL, CEP152, NUF2, SPC24, SPC25, NEK2, INCENP, SGO1L, MLF1IP, CASC5, NDC80, and ASPM), are all highly overexpressed in MDR canines ( Supplemental Tables S2 and S3).…”

Peer Review #2 of "Integrated bioinformatics analysis of As, Au, Cd, Pb and Cu heavy metal responsive marker genes through Arabidopsis thaliana GEO datasets (v0.1)"

“…Therefore, this approach has been applied extensively to the diagnosis and treatment of human cancers. For example, researchers believed that GNAI1, NCAPH, MMP9, AURKA and EZH2I were identified as the key molecules in patients with serous ovarian cancer resistant to carboplatin using integrated bioinformatics analysis (Zhan et al 2018). COL1A2 as a diagnostic biomarker was highly tissue specific and was expressed in human gastric cancer by integrating bioinformatics and meta-analysis (Rong et al 2018).…”

“…The identification of novel biomarkers is currently an efficient approach for large-scale screening and diagnosis (Liu et al 2018, Zhan et al 2018. Therefore, we performed analysis of 11 original microarray data to identify DEG response to different heavy metals in the present study.…”