The identification of six risk genes for ovarian cancer platinum response based on global network algorithm and verification analysis

Abstract

Ovarian cancer is the most lethal gynaecological cancer, and resistance of platinum‐based chemotherapy is the main reason for treatment failure. The aim of the present study was to identify candidate genes involved in ovarian cancer platinum response by analysing genes from homologous recombination and Fanconi anaemia pathways. Associations between these two functional genes were explored in the study, and we performed a random walk algorithm based on reconstructed gene‐gene network, including protein‐protein interaction and co‐expression relations. Following the random walk, all genes were ranked and GSEA analysis showed that the biological functions focused primarily on autophagy, histone modification and gluconeogenesis. Based on three types of seed nodes, the top two genes were utilized as examples. We selected a total of six candidate genes (FANCA, FANCG, POLD1, KDM1A, BLM and BRCA1) for subsequent verification. The validation results of the six candidate genes have significance in three independent ovarian cancer data sets with platinum‐resistant and platinum‐sensitive information. To explore the correlation between biomarkers and clinical prognostic factors, we performed differential analysis and multivariate clinical subgroup analysis for six candidate genes at both mRNA and protein levels. And each of the six candidate genes and their neighbouring genes with a mutation rate greater than 10% were also analysed by network construction and functional enrichment analysis. In the meanwhile, the survival analysis for platinum‐treated patients was performed in the current study. Finally, the RT‐qPCR assay was used to determine the performance of candidate genes in ovarian cancer platinum response. Taken together, this research demonstrated that comprehensive bioinformatics methods could help to understand the molecular mechanism of platinum response and provide new strategies for overcoming platinum resistance in ovarian cancer treatment.

BECN1 and BRCA1 Deficiency Sensitizes Ovarian Cancer to Platinum Therapy and Confers Better Prognosis

“…The stratification of HGSOC patients in poor and good responders to the platinum-based first-line therapy is crucial for implementation of personalized ovarian cancer treatment, and for this it is important to genotyping the tumor for critical risk genes [ 46 , 47 ]. Dysfunction of tumor suppressor genes (low expression or loss-of-function mutations) has been associated with tumor development and progression, and with poor clinical outcome.…”

“…Dysfunction of tumor suppressor genes (low expression or loss-of-function mutations) has been associated with tumor development and progression, and with poor clinical outcome. However, the contribution of one single risk gene is influenced by the concurrent mutation of other risk genes involved in the same or intersected processes [ 46 ], and this is likely to affect the final outcome.…”

Identification of Biomarkers for Cervical Cancer Radiotherapy Resistance Based on RNA Sequencing Data

“…Different gene expression characteristics may lead to different types of tumors with varying degrees of sensitivity to radiotherapy ( Jiang et al, 2017 ; Prevo et al, 2017 ; Zhou et al, 2017 ). With the development of bioinformatics, gene expression microarrays have been widely used in studying cancer-related genes and considered promising tools for molecular prediction ( Cheng et al, 2017 ; Liu et al, 2019a ; Xing et al, 2020 ).…”

What is new about ovarian malignancies?

“…Moreover, notable relationships between these genes and both overall survival and disease free survival were detected. The real-time polymerase chain reaction assay confirmed that those candidate genes’ expression levels in platinum sensitive ovarian cancer cell lines were higher than those in platinum resistant ones [ 29 ].…”