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Identification of a six-lncRNA signature associated with recurrence of ovarian cancer

Ovarian cancer (OvCa) is the leading cause of death among all gynecological malignancies, and recurrent OvCa is almost always incurable. In this study, we developed a signature based on long non-coding RNAs (lncRNAs) associated with OvCa recurrence to facilitate personalized OvCa therapy. lncRNA exp...

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Autores principales: Yang, Kai, Hou, Yan, Li, Ang, Li, Zhenzi, Wang, Wenjie, Xie, Hongyu, Rong, Zhiwei, Lou, Ge, Li, Kang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5429632/
https://www.ncbi.nlm.nih.gov/pubmed/28389671
http://dx.doi.org/10.1038/s41598-017-00763-y
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author Yang, Kai
Hou, Yan
Li, Ang
Li, Zhenzi
Wang, Wenjie
Xie, Hongyu
Rong, Zhiwei
Lou, Ge
Li, Kang
author_facet Yang, Kai
Hou, Yan
Li, Ang
Li, Zhenzi
Wang, Wenjie
Xie, Hongyu
Rong, Zhiwei
Lou, Ge
Li, Kang
author_sort Yang, Kai
collection PubMed
description Ovarian cancer (OvCa) is the leading cause of death among all gynecological malignancies, and recurrent OvCa is almost always incurable. In this study, we developed a signature based on long non-coding RNAs (lncRNAs) associated with OvCa recurrence to facilitate personalized OvCa therapy. lncRNA expression data were extracted from GSE9891 and GSE30161. LASSO (least absolute shrinkage and selection operator) penalized regression was used to identify an lncRNA-based signature using the GSE9891 training cohort. The signature was then validated in GSE9891 internal and GSE30161 external validation cohorts. The Database for Annotation, Visualization and Integrated Discovery (DAVID) was used to explore the possible functions of identified lncRNAs. A six-lncRNA signature (RUNX1-IT1, MALAT1, H19, HOTAIRM1, LOC100190986 and AL132709.8) was identified in the training cohort and validated in internal and external validation cohorts using the LASSO method (P < 0.05). This signature was also independent of other clinical factors according to multivariate and sub-group analyses. The identified lncRNAs are involved in cancer-related biological processes and pathways. We selected a highly reliable signature based on six lncRNAs associated with OvCa recurrence. This six-lncRNA signature is a promising method to personalize ovarian cancer therapy and may improve patient quality of life quality according to patients’ condition in the future.
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spelling pubmed-54296322017-05-15 Identification of a six-lncRNA signature associated with recurrence of ovarian cancer Yang, Kai Hou, Yan Li, Ang Li, Zhenzi Wang, Wenjie Xie, Hongyu Rong, Zhiwei Lou, Ge Li, Kang Sci Rep Article Ovarian cancer (OvCa) is the leading cause of death among all gynecological malignancies, and recurrent OvCa is almost always incurable. In this study, we developed a signature based on long non-coding RNAs (lncRNAs) associated with OvCa recurrence to facilitate personalized OvCa therapy. lncRNA expression data were extracted from GSE9891 and GSE30161. LASSO (least absolute shrinkage and selection operator) penalized regression was used to identify an lncRNA-based signature using the GSE9891 training cohort. The signature was then validated in GSE9891 internal and GSE30161 external validation cohorts. The Database for Annotation, Visualization and Integrated Discovery (DAVID) was used to explore the possible functions of identified lncRNAs. A six-lncRNA signature (RUNX1-IT1, MALAT1, H19, HOTAIRM1, LOC100190986 and AL132709.8) was identified in the training cohort and validated in internal and external validation cohorts using the LASSO method (P < 0.05). This signature was also independent of other clinical factors according to multivariate and sub-group analyses. The identified lncRNAs are involved in cancer-related biological processes and pathways. We selected a highly reliable signature based on six lncRNAs associated with OvCa recurrence. This six-lncRNA signature is a promising method to personalize ovarian cancer therapy and may improve patient quality of life quality according to patients’ condition in the future. Nature Publishing Group UK 2017-04-07 /pmc/articles/PMC5429632/ /pubmed/28389671 http://dx.doi.org/10.1038/s41598-017-00763-y Text en © The Author(s) 2017 Open Access This 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Yang, Kai
Hou, Yan
Li, Ang
Li, Zhenzi
Wang, Wenjie
Xie, Hongyu
Rong, Zhiwei
Lou, Ge
Li, Kang
Identification of a six-lncRNA signature associated with recurrence of ovarian cancer
title Identification of a six-lncRNA signature associated with recurrence of ovarian cancer
title_full Identification of a six-lncRNA signature associated with recurrence of ovarian cancer
title_fullStr Identification of a six-lncRNA signature associated with recurrence of ovarian cancer
title_full_unstemmed Identification of a six-lncRNA signature associated with recurrence of ovarian cancer
title_short Identification of a six-lncRNA signature associated with recurrence of ovarian cancer
title_sort identification of a six-lncrna signature associated with recurrence of ovarian cancer
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5429632/
https://www.ncbi.nlm.nih.gov/pubmed/28389671
http://dx.doi.org/10.1038/s41598-017-00763-y
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