Loss of MAGEC3 Expression Is Associated with Prognosis in Advanced Ovarian Cancers

Abstract

Rare variants in MAGEC3 are associated with BRCA negative, early-onset ovarian cancers. Given this association, we evaluated the impact of MAGEC3 protein expression on prognosis and transcription. We quantified normal and tumor protein expression of MAGEC3 via immunohistochemistry in n = 394 advanced ovarian cancers, assessed the correlation of these values with clinicopathologic and immunological features and modeled survival using univariate and multivariate models. To extend these results, we quantified MAGEC3 protein expression in n = 180 cancers and used matching RNA sequencing data to determine MAGEC3-associated differentially expressed genes and to build an RNA-based model of MAGEC3 protein levels. This model was tested in a third independent cohort of patients from TCGA’s OV dataset (n = 282). MAGEC3 protein was sporadically lost in ovarian cancers, with half of the cases falling below the 9.5th percentile of normal tissue expression. Cases with MAGEC3 loss demonstrated better progression-free survival [HR = 0.71, p = 0.004], and analyses performed on predicted protein scores were consistent [HR = 0.57 p = 0.002]. MAGEC3 protein was correlated with CD8 protein expression [Pearson’s r = 0.176, p = 0.011], NY-ESO-1 seropositivity, and mRNA expression of tumor antigens at Xq28. Results of gene set enrichment analysis showed that genes associated with MAGEC3 protein expression cluster around G2/M checkpoint (NES = 3.20, FDR < 0.001) and DNA repair (NES = 2.28, FDR < 0.001) hallmark pathways. These results show that MAGEC3 is a prognostic biomarker in ovarian cancer.

Keywords

• MAGEC3
• ovarian cancer
• prognostic biomarker
• machine learning