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Role of lncRNAs in ovarian cancer: defining new biomarkers for therapeutic purposes.

ABSTRACT: Long noncoding RNAs (lncRNAs) are a class of noncoding RNA, involved in regulation of diverse physiological and pathological processes. Ovarian cancer is the leading cause of death among all gynecological malignancies in the world and its underlying mechanism is still unclear. LncRNAs exhibit multiple biological functions in various stages of ovarian cancer development. We will discuss and summarize the new and important lncRNAs and their involvement in disease, which might represent promising therapeutic targets. Therapeutic intervention based on silencing or functional inhibition of target lncRNAs will be beneficial for ovarian cancer patients.

SUBMITTER: Tripathi MK

PROVIDER: S-EPMC6139057 | biostudies-literature | 2018 Sep

REPOSITORIES: biostudies-literature

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Role of lncRNAs in ovarian cancer: defining new biomarkers for therapeutic purposes.

Tripathi Manish K MK Doxtater Kyle K Keramatnia Fatemeh F Zacheaus Chidi C Yallapu Murali M MM Jaggi Meena M Chauhan Subhash C SC

Drug discovery today 20180423 9

Long noncoding RNAs (lncRNAs) are a class of noncoding RNA, involved in regulation of diverse physiological and pathological processes. Ovarian cancer is the leading cause of death among all gynecological malignancies in the world and its underlying mechanism is still unclear. LncRNAs exhibit multiple biological functions in various stages of ovarian cancer development. We will discuss and summarize the new and important lncRNAs and their involvement in disease, which might represent promising t ...[more]

PMID: 29698834

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Project description:Background: Increasing evidences have shown that abnormal alternative splicing (AS) events are closely related to the prognosis of various tumors. However, the role of AS in ovarian cancer (OV) is poorly understood. This study aims to explore the correlation between AS and the prognosis of OV and establish a prognostic model for OV. Methods: We downloaded the RNA-seq data of OV from The Cancer Genome Atlas databases and assessed cancer-specific AS through the SpliceSeq software. Then systemically investigated the overall survival (OS)-related AS and splicing factors (SFs) by bioinformatics analysis. The nomogram was established based on the clinical information, and the clinical practicability of the nomogram was verified through the calibration curve. Finally, a splicing correlation network was constructed to reveal the relationship between OS-related AS and SFs. Results: A total of 48,049 AS events were detected from 10,582 genes, of which 1523 were significantly associated with OS. The area under the curve of the final prediction model was 0.785, 0.681, and 0.781 in 1, 3, and 5 years, respectively. Moreover, the nomogram showed high calibration and discrimination in OV patients. Spearman correlation analysis was used to determine 8 SFs significantly related to survival, including major facilitator superfamily domain containing 11, synaptotagmin binding cytoplasmic RNA interacting protein, DEAH-box helicase 35, CWC15, integrator complex subunit 1, LUC7 like 2, cell cycle and apoptosis regulator 1, and heterogeneous nuclear ribonucleoprotein A2/B1. Conclusion: This study provides a prognostic model related to AS in OV, and constructs an AS-clinicopathological nomogram, which provides the possibility to predict the long-term prognosis of OV patients. We have explored the wealth of RNA splicing networks and regulation patterns related to the prognosis of OV, which provides a large number of biomarkers and potential targets for the treatment of OV. Put forward the potential possibility of interfering with the AS of OV in the comprehensive treatment of OV.

Dataset Information

Role of lncRNAs in ovarian cancer: defining new biomarkers for therapeutic purposes.

Publications

Role of lncRNAs in ovarian cancer: defining new biomarkers for therapeutic purposes.

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