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Alternative Splicing: A New Therapeutic Target for Ovarian Cancer
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 es...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
SAGE Publications
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8966091/ https://www.ncbi.nlm.nih.gov/pubmed/35343831 http://dx.doi.org/10.1177/15330338211067911 |
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author | Yao, Shijie Yuan, Cheng Shi, Yuying Qi, Yuwen Sridha, Radhakrishnan Dai, Mengyuan Cai, Hongbing |
author_facet | Yao, Shijie Yuan, Cheng Shi, Yuying Qi, Yuwen Sridha, Radhakrishnan Dai, Mengyuan Cai, Hongbing |
author_sort | Yao, Shijie |
collection | PubMed |
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. |
format | Online Article Text |
id | pubmed-8966091 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | SAGE Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-89660912022-03-31 Alternative Splicing: A New Therapeutic Target for Ovarian Cancer Yao, Shijie Yuan, Cheng Shi, Yuying Qi, Yuwen Sridha, Radhakrishnan Dai, Mengyuan Cai, Hongbing Technol Cancer Res Treat A New Generation of Cancer Therapy 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. SAGE Publications 2022-03-28 /pmc/articles/PMC8966091/ /pubmed/35343831 http://dx.doi.org/10.1177/15330338211067911 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by-nc/4.0/This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage). |
spellingShingle | A New Generation of Cancer Therapy Yao, Shijie Yuan, Cheng Shi, Yuying Qi, Yuwen Sridha, Radhakrishnan Dai, Mengyuan Cai, Hongbing Alternative Splicing: A New Therapeutic Target for Ovarian Cancer |
title | Alternative Splicing: A New Therapeutic Target for Ovarian Cancer |
title_full | Alternative Splicing: A New Therapeutic Target for Ovarian Cancer |
title_fullStr | Alternative Splicing: A New Therapeutic Target for Ovarian Cancer |
title_full_unstemmed | Alternative Splicing: A New Therapeutic Target for Ovarian Cancer |
title_short | Alternative Splicing: A New Therapeutic Target for Ovarian Cancer |
title_sort | alternative splicing: a new therapeutic target for ovarian cancer |
topic | A New Generation of Cancer Therapy |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8966091/ https://www.ncbi.nlm.nih.gov/pubmed/35343831 http://dx.doi.org/10.1177/15330338211067911 |
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