Abstract
BackgroundThe heterogeneous subtypes and stages of epithelial ovarian cancer (EOC) differ in their biological features, invasiveness, and response to chemotherapy, but the transcriptional regulators causing their differences remain nebulous.MethodsIn this study, we compared high-grade serous ovarian cancers (HGSOCs) to low malignant potential or serous borderline tumors (SBTs). Our aim was to discover new regulatory factors causing distinct biological properties of HGSOCs and SBTs.ResultsIn a discovery dataset, we identified 11 differentially expressed genes (DEGs) between SBTs and HGSOCs. Their expression correctly classified 95% of 267 validation samples. Two of the DEGs, TMEM30B and TSPAN1, were significantly associated with worse overall survival in patients with HGSOC. We also identified 17 DEGs that distinguished stage II vs. III HGSOC. In these two DEG promoter sets, we identified significant enrichment of predicted transcription factor binding sites, including those of RARA, FOXF1, BHLHE41, and PITX1. Using published ChIP-seq data acquired from multiple non-ovarian cell types, we showed additional regulatory factors, including AP2-gamma/TFAP2C, FOXA1, and BHLHE40, bound at the majority of DEG promoters. Several of the factors are known to cooperate with and predict the presence of nuclear hormone receptor estrogen receptor alpha (ER-alpha). We experimentally confirmed ER-alpha and PITX1 presence at the DEGs by performing ChIP-seq analysis using the ovarian cancer cell line PEO4. Finally, RNA-seq analysis identified recurrent gene fusion events in our EOC tumor set. Some of these fusions were significantly associated with survival in HGSOC patients; however, the fusion genes are not regulated by the transcription factors identified for the DEGs.ConclusionsThese data implicate an estrogen-responsive regulatory network in the differential gene expression between ovarian cancer subtypes and stages, which includes PITX1. Importantly, the transcription factors associated with our DEG promoters are known to form the MegaTrans complex in breast cancer. This is the first study to implicate the MegaTrans complex in contributing to the distinct biological trajectories of malignant and indolent ovarian cancer subtypes.
Highlights
Epithelial ovarian cancer (EOC) accounts for over 90% of ovarian cancer cases [1] and results in 14,000 deaths in the United States every year, making it the leading cause of death attributed to gynecological cancers [2]
The transcription factors associated with our differentially expressed genes (DEGs) promoters are known to form the MegaTrans complex in breast cancer
Because our ability to molecularly characterize epithelial ovarian cancer (EOC) subtypes has improved since that time, we analyzed gene variants and methylation in these samples to verify that the sample characteristics were consistent with what is known about serous borderline tumors (SBTs)
Summary
Epithelial ovarian cancer (EOC) accounts for over 90% of ovarian cancer cases [1] and results in 14,000 deaths in the United States every year, making it the leading cause of death attributed to gynecological cancers [2]. Current scientific advances provide hope that new treatments—immunotherapies, PARP inhibitors, and small molecules tailored to tumor characteristics—can improve patient survival [3] These new treatments have not yet increased the 5-year survival rate for late-stage, invasive EOC, which has been near 30% for several decades [4]. LGSOCs comprise 4–10% of EOCs, are less responsive to chemotherapy, and predict a longer OS, of 82–126 months [7, 8] Both HGSOCs and LGSOCs are invasive and can progress to late-stage, untreatable disease; whereas 5-year survival rates favor LGSOCs (62.3% vs 43.9% for HGSOCs [8]), 10-year survival rates for HGSOCs and LGSOCs are not statistically different (21.2% vs 22.7%, respectively; P = 0.17 [8]). The heterogeneous subtypes and stages of epithelial ovarian cancer (EOC) differ in their biological features, invasiveness, and response to chemotherapy, but the transcriptional regulators causing their differences remain nebulous
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