The Interplay between Long Noncoding RNAs and Proteins of the Epigenetic Machinery in Ovarian Cancer

SIMPLE SUMMARY: Epithelial ovarian cancer is an aggressive disease associated with relapse, resistance to chemotherapy, and high mortality rates. Recent discoveries have pointed out that long noncoding RNAs (lncRNAs) are potential biomarkers or therapeutic targets in several tumor types. However, fundamental knowledge about their functions and regulation is still lacking. Here, we present the current understanding of the interplay between lncRNAs and the epigenetic machinery influencing ovarian carcinogenesis. We also provide an overview of bioinformatics tools and databases that can be exploited for lncRNAs investigations. Altogether, this information can support the development of clinical initiatives to monitor disease progression or discover new strategies for the therapeutic management of ovarian cancer. ABSTRACT: Comprehensive large-scale sequencing and bioinformatics analyses have uncovered a myriad of cancer-associated long noncoding RNAs (lncRNAs). Aberrant expression of lncRNAs is associated with epigenetic reprogramming during tumor development and progression, mainly due to their ability to interact with DNA, RNA, or proteins to regulate gene expression. LncRNAs participate in the control of gene expression patterns during development and cell differentiation and can be cell and cancer type specific. In this review, we described the potential of lncRNAs for clinical applications in ovarian cancer (OC). OC is a complex and heterogeneous disease characterized by relapse, chemoresistance, and high mortality rates. Despite advances in diagnosis and treatment, no significant improvements in long-term survival were observed in OC patients. A set of lncRNAs was associated with survival and response to therapy in this malignancy. We manually curated databases and used bioinformatics tools to identify lncRNAs implicated in the epigenetic regulation, along with examples of direct interactions between the lncRNAs and proteins of the epigenetic machinery in OC. The resources and mechanisms presented herein can improve the understanding of OC biology and provide the basis for further investigations regarding the selection of novel biomarkers and therapeutic targets.