Abstract
In this study, we identified prognostic biomarkers in ovarian carcinoma by integrating multi-omics DNA copy number variation (CNV) and methylation variation (MET) data. CNV, MET, and messenger RNA (mRNA) expression were examined in 351 ovarian carcinoma patients. Genes for which expression was correlated with DNA copy-number or DNA methylation were identified; three ovarian carcinoma gene subtypes were defined based on these correlations. Overall survival and B cell scores were lower, while the macrophage cell score was higher, in the DNA imprinting centre 1 (iC1) subtype than in the iC2 and iC3 subtypes. Comparison of CNV, MET, and mRNA expression among the subtypes identified two genes, ubiquitin B (UBB) and interleukin 18 binding protein (IL18BP), that were associated with prognosis. Mutation spectrum results based on subtype indicated that UBB and IL18BP expression may be influenced by mutation loci. Mutation levels were higher in iC1 samples than in iC2 or iC3 samples, indicating that the iC1 subtype is associated with disease progression. This integrated multi-omics analysis of genomics, epigenomics, and transcriptomics provides new insight into the molecular mechanisms of ovarian carcinoma and may help identify biomolecular markers for early disease diagnosis.
Highlights
Ovarian carcinoma is the third most common type of gynecological malignancy [1]
In the z-value distribution, CNVcor gene correlations were significantly shifted to the right, while METcor gene correlations were significantly shifted to the left (Figure 1A) (D'Agostino test: p < 1e-5)
These results indicate a positive correlation between CNVcor genes and gene expression and a negative correlation between METcor genes and gene expression
Summary
70% of patients present with advanced cancer with distant metastasis upon diagnosis, and ovarian carcinoma is the leading cause of death among malignant gynecological tumors [2, 3]. Both early detection biomarkers for ovarian carcinoma and effective therapies for recurrent cases are lacking [4]. CNV is a crucial regulator of genomic and epigenomic dysregulation that contribute to tumor progression and transcriptional dysregulation These public, large-scale, multi-omics data sets make it possible to conduct an integrated multi-omics analysis of the impacts of genomics, epigenomics, and transcriptomics on tumor occurrence and progression in ovarian carcinoma [10]
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