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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\u2010gene network, including protein\u2010protein interaction and co\u2010expression 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\u2010resistant and platinum\u2010sensitive 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\u2010treated patients was performed in the current study. Finally, the RT\u2010qPCR 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.<\/jats:p>","DOI":"10.1111\/jcmm.15567","type":"journal-article","created":{"date-parts":[[2020,8,7]],"date-time":"2020-08-07T00:15:59Z","timestamp":1596759359000},"page":"9839-9852","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["The identification of six risk genes for ovarian cancer platinum response based on global network algorithm and verification analysis"],"prefix":"10.1111","volume":"24","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7325-6726","authenticated-orcid":false,"given":"Linan","family":"Xing","sequence":"first","affiliation":[{"name":"Department of Gynecology Harbin Medical University Cancer Hospital Harbin 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