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Eight-lncRNA signature of cervical cancer were identified by integrating DNA methylation, copy number variation and transcriptome data
BACKGROUND: Copy number variation (CNV) suggests genetic changes in malignant tumors. Abnormal expressions of long non-coding RNAs (lncRNAs) resulted from genomic and epigenetic abnormalities play a driving role in tumorigenesis of cervical cancer. However, the role of lncRNAs-related CNV in cervica...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8045209/ https://www.ncbi.nlm.nih.gov/pubmed/33557879 http://dx.doi.org/10.1186/s12967-021-02705-9 |
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author | Zhong, Qihang Lu, Minzhen Yuan, Wanqiong Cui, Yueyi Ouyang, Hanqiang Fan, Yong Wang, Zhaohui Wu, Congying Qiao, Jie Hang, Jing |
author_facet | Zhong, Qihang Lu, Minzhen Yuan, Wanqiong Cui, Yueyi Ouyang, Hanqiang Fan, Yong Wang, Zhaohui Wu, Congying Qiao, Jie Hang, Jing |
author_sort | Zhong, Qihang |
collection | PubMed |
description | BACKGROUND: Copy number variation (CNV) suggests genetic changes in malignant tumors. Abnormal expressions of long non-coding RNAs (lncRNAs) resulted from genomic and epigenetic abnormalities play a driving role in tumorigenesis of cervical cancer. However, the role of lncRNAs-related CNV in cervical cancer remained largely unclear. METHODS: The data of messenger RNAs (mRNAs), DNA methylation, and DNA copy number were collected from 292 cervical cancer specimens. The prognosis-related subtypes of cervical cancer were determined by multi-omics integration analysis, and protein-coding genes (PCGs) and lncRNAs with subtype-specific expressions were identified. The CNV pattern of the subtype-specific lncRNAs was analyzed to identify the subtype-specific lncRNAs. A prognostic risk model based on lncRNAs was established by least absolute shrinkage and selection operator (LASSO). RESULTS: Multi-omics integration analysis identified three molecular subtypes incorporating 617 differentially expressed lncRNAs and 1395 differentially expressed PCGs. The 617 lncRNAs were found to intersect with disease-related lncRNAs. Functional enrichment showed that 617 lncRNAs were mainly involved in tumor metabolism, immunity and other pathways, such as p53 and cAMP signaling pathways, which are closely related to the development of cervical cancer. Finally, according to CNV pattern consistent with differential expression analysis, we established a lncRNAs-based signature consisted of 8 lncRNAs, namely, RUSC1-AS1, LINC01990, LINC01411, LINC02099, H19, LINC00452, ADPGK-AS1, C1QTNF1-AS1. The interaction of the 8 lncRNAs showed a significantly poor prognosis of cervical cancer patients, which has also been verified in an independent dataset. CONCLUSION: Our study expanded the network of CNVs and improved the understanding on the regulatory network of lncRNAs in cervical cancer, providing novel biomarkers for the prognosis management of cervical cancer patients. |
format | Online Article Text |
id | pubmed-8045209 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-80452092021-04-14 Eight-lncRNA signature of cervical cancer were identified by integrating DNA methylation, copy number variation and transcriptome data Zhong, Qihang Lu, Minzhen Yuan, Wanqiong Cui, Yueyi Ouyang, Hanqiang Fan, Yong Wang, Zhaohui Wu, Congying Qiao, Jie Hang, Jing J Transl Med Research BACKGROUND: Copy number variation (CNV) suggests genetic changes in malignant tumors. Abnormal expressions of long non-coding RNAs (lncRNAs) resulted from genomic and epigenetic abnormalities play a driving role in tumorigenesis of cervical cancer. However, the role of lncRNAs-related CNV in cervical cancer remained largely unclear. METHODS: The data of messenger RNAs (mRNAs), DNA methylation, and DNA copy number were collected from 292 cervical cancer specimens. The prognosis-related subtypes of cervical cancer were determined by multi-omics integration analysis, and protein-coding genes (PCGs) and lncRNAs with subtype-specific expressions were identified. The CNV pattern of the subtype-specific lncRNAs was analyzed to identify the subtype-specific lncRNAs. A prognostic risk model based on lncRNAs was established by least absolute shrinkage and selection operator (LASSO). RESULTS: Multi-omics integration analysis identified three molecular subtypes incorporating 617 differentially expressed lncRNAs and 1395 differentially expressed PCGs. The 617 lncRNAs were found to intersect with disease-related lncRNAs. Functional enrichment showed that 617 lncRNAs were mainly involved in tumor metabolism, immunity and other pathways, such as p53 and cAMP signaling pathways, which are closely related to the development of cervical cancer. Finally, according to CNV pattern consistent with differential expression analysis, we established a lncRNAs-based signature consisted of 8 lncRNAs, namely, RUSC1-AS1, LINC01990, LINC01411, LINC02099, H19, LINC00452, ADPGK-AS1, C1QTNF1-AS1. The interaction of the 8 lncRNAs showed a significantly poor prognosis of cervical cancer patients, which has also been verified in an independent dataset. CONCLUSION: Our study expanded the network of CNVs and improved the understanding on the regulatory network of lncRNAs in cervical cancer, providing novel biomarkers for the prognosis management of cervical cancer patients. BioMed Central 2021-02-08 /pmc/articles/PMC8045209/ /pubmed/33557879 http://dx.doi.org/10.1186/s12967-021-02705-9 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Zhong, Qihang Lu, Minzhen Yuan, Wanqiong Cui, Yueyi Ouyang, Hanqiang Fan, Yong Wang, Zhaohui Wu, Congying Qiao, Jie Hang, Jing Eight-lncRNA signature of cervical cancer were identified by integrating DNA methylation, copy number variation and transcriptome data |
title | Eight-lncRNA signature of cervical cancer were identified by integrating DNA methylation, copy number variation and transcriptome data |
title_full | Eight-lncRNA signature of cervical cancer were identified by integrating DNA methylation, copy number variation and transcriptome data |
title_fullStr | Eight-lncRNA signature of cervical cancer were identified by integrating DNA methylation, copy number variation and transcriptome data |
title_full_unstemmed | Eight-lncRNA signature of cervical cancer were identified by integrating DNA methylation, copy number variation and transcriptome data |
title_short | Eight-lncRNA signature of cervical cancer were identified by integrating DNA methylation, copy number variation and transcriptome data |
title_sort | eight-lncrna signature of cervical cancer were identified by integrating dna methylation, copy number variation and transcriptome data |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8045209/ https://www.ncbi.nlm.nih.gov/pubmed/33557879 http://dx.doi.org/10.1186/s12967-021-02705-9 |
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