Integrative prognostic subtype discovery in high-grade serous ovarian cancer.

OBJECTIVE

We sought to identify novel molecular subtypes of high-grade serous ovarian cancer (HGSC) by the integration of gene expression and proteomics data and to find the underlying biological characteristics of ovarian cancer to improve the clinical outcome.

METHODS

The iCluster method was utilized to analysis 131 common HGSC samples between TCGA and Clinical Proteomic Tumor Analysis Consortium databases. Kaplan-Meier survival curves were used to estimate the overall survival of patients, and the differences in survival curves were assessed using the log-rank test.

RESULTS

Two novel ovarian cancer subtypes with different overall survival (P = .00114) and different platinum status (P = .0061) were identified. Eighteen messenger RNAs and 38 proteins were selected as differential molecules between subtypes. Pathway analysis demonstrated arrhythmogenic right ventricular cardiomyopathy pathway played a critical role in the discrimination of these two subtypes and desmosomal cadherin DSG2, DSP, JUP, and PKP2 in this pathway were overexpression in subtype I compared with subtype II.

CONCLUSION

Our study extended the underlying prognosis-related biological characteristics of high-grade serous ovarian cancer. Enrichment of desmosomal cadherin increased the risk for HGSC prognosis among platinum-sensitive patients, the results guided the revision of the treatment options for platinum-sensitive ovarian cancer patients to improve outcomes.