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Derivation and Validation of a Necroptosis-Related lncRNA Signature in Patients with Ovarian Cancer
BACKGROUND: Ovarian cancer (OC) is the leading cause of gynecologic malignant tumors. The role of necroptosis-related lncRNAs (NRLs) in OC remains unclear. This study aims to explore the association between NRLs and prognosis in OC patients. METHODS: The Cancer Genome Atlas (TCGA) and GTEx datasets...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9152429/ https://www.ncbi.nlm.nih.gov/pubmed/35656337 http://dx.doi.org/10.1155/2022/6228846 |
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author | Zhu, Linling He, Jiaoyan Yang, Xinyun Zheng, Jianfeng Liu, Wenhua Chen, Hao |
author_facet | Zhu, Linling He, Jiaoyan Yang, Xinyun Zheng, Jianfeng Liu, Wenhua Chen, Hao |
author_sort | Zhu, Linling |
collection | PubMed |
description | BACKGROUND: Ovarian cancer (OC) is the leading cause of gynecologic malignant tumors. The role of necroptosis-related lncRNAs (NRLs) in OC remains unclear. This study aims to explore the association between NRLs and prognosis in OC patients. METHODS: The Cancer Genome Atlas (TCGA) and GTEx datasets were used to obtain OC's data. A NRLs signature associated with overall survival (OS) was constructed by Cox-LASSO regression analysis in training cohort for calculating risk score and then validated in testing cohort. Subsequently, the area under the curve (AUC) and Kaplan–Meier survival analysis were used to evaluate the predictive accuracy of the risk score. Finally, the immune infiltration and functional enrichment were compared between different risk groups. RESULTS: A 8-NRLs signature including AC245128.3, AL355488.1, AC092794.1, AC068888.2, AL590652.1, AC008982.2, FOXP4-AS1, and Z94721.1 was identified to assess the OS of OC. Kaplan–Meier survival analysis, AUC value, and Cox regression analysis confirmed its predictive value and showed that the clinical outcomes were worse for high-risk patients. There were also differences in immunological functioning and immune pathways between the high-risk and low-risk groups. CONCLUSIONS: The signature based on eight NRLs has significant values in predicting prognostic prediction in OC, as well as providing a new sight for targeted therapies. |
format | Online Article Text |
id | pubmed-9152429 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-91524292022-06-01 Derivation and Validation of a Necroptosis-Related lncRNA Signature in Patients with Ovarian Cancer Zhu, Linling He, Jiaoyan Yang, Xinyun Zheng, Jianfeng Liu, Wenhua Chen, Hao J Oncol Research Article BACKGROUND: Ovarian cancer (OC) is the leading cause of gynecologic malignant tumors. The role of necroptosis-related lncRNAs (NRLs) in OC remains unclear. This study aims to explore the association between NRLs and prognosis in OC patients. METHODS: The Cancer Genome Atlas (TCGA) and GTEx datasets were used to obtain OC's data. A NRLs signature associated with overall survival (OS) was constructed by Cox-LASSO regression analysis in training cohort for calculating risk score and then validated in testing cohort. Subsequently, the area under the curve (AUC) and Kaplan–Meier survival analysis were used to evaluate the predictive accuracy of the risk score. Finally, the immune infiltration and functional enrichment were compared between different risk groups. RESULTS: A 8-NRLs signature including AC245128.3, AL355488.1, AC092794.1, AC068888.2, AL590652.1, AC008982.2, FOXP4-AS1, and Z94721.1 was identified to assess the OS of OC. Kaplan–Meier survival analysis, AUC value, and Cox regression analysis confirmed its predictive value and showed that the clinical outcomes were worse for high-risk patients. There were also differences in immunological functioning and immune pathways between the high-risk and low-risk groups. CONCLUSIONS: The signature based on eight NRLs has significant values in predicting prognostic prediction in OC, as well as providing a new sight for targeted therapies. Hindawi 2022-05-23 /pmc/articles/PMC9152429/ /pubmed/35656337 http://dx.doi.org/10.1155/2022/6228846 Text en Copyright © 2022 Linling Zhu et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Zhu, Linling He, Jiaoyan Yang, Xinyun Zheng, Jianfeng Liu, Wenhua Chen, Hao Derivation and Validation of a Necroptosis-Related lncRNA Signature in Patients with Ovarian Cancer |
title | Derivation and Validation of a Necroptosis-Related lncRNA Signature in Patients with Ovarian Cancer |
title_full | Derivation and Validation of a Necroptosis-Related lncRNA Signature in Patients with Ovarian Cancer |
title_fullStr | Derivation and Validation of a Necroptosis-Related lncRNA Signature in Patients with Ovarian Cancer |
title_full_unstemmed | Derivation and Validation of a Necroptosis-Related lncRNA Signature in Patients with Ovarian Cancer |
title_short | Derivation and Validation of a Necroptosis-Related lncRNA Signature in Patients with Ovarian Cancer |
title_sort | derivation and validation of a necroptosis-related lncrna signature in patients with ovarian cancer |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9152429/ https://www.ncbi.nlm.nih.gov/pubmed/35656337 http://dx.doi.org/10.1155/2022/6228846 |
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