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Expression profile analysis of prognostic long non-coding RNA in adult acute myeloid leukemia by weighted gene co-expression network analysis (WGCNA)

Background: Long non-coding RNAs (lncRNAs), which are over 200 nt in length, have a key role in tumorigenesis and disease progression. To explore the role of prognostic lncRNAs in adult acute myeloid leukemia (AML), the expression profiles of lncRNAs and mRNAs in AML were analyzed. Methods: The RNAs...

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Autores principales: Chen, Cun-Te, Wang, Pei-Pei, Mo, Wen-Jian, Zhang, Yu-Ping, Zhou, Wei, Deng, Ting-Fen, Zhou, Ming, Chen, Xiao-Wei, Wang, Shun-Qing, Wang, Cai-Xia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Ivyspring International Publisher 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6746144/
https://www.ncbi.nlm.nih.gov/pubmed/31528236
http://dx.doi.org/10.7150/jca.31234
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author Chen, Cun-Te
Wang, Pei-Pei
Mo, Wen-Jian
Zhang, Yu-Ping
Zhou, Wei
Deng, Ting-Fen
Zhou, Ming
Chen, Xiao-Wei
Wang, Shun-Qing
Wang, Cai-Xia
author_facet Chen, Cun-Te
Wang, Pei-Pei
Mo, Wen-Jian
Zhang, Yu-Ping
Zhou, Wei
Deng, Ting-Fen
Zhou, Ming
Chen, Xiao-Wei
Wang, Shun-Qing
Wang, Cai-Xia
author_sort Chen, Cun-Te
collection PubMed
description Background: Long non-coding RNAs (lncRNAs), which are over 200 nt in length, have a key role in tumorigenesis and disease progression. To explore the role of prognostic lncRNAs in adult acute myeloid leukemia (AML), the expression profiles of lncRNAs and mRNAs in AML were analyzed. Methods: The RNAseq data of 167 adult AML patients and the corresponding clinical information were downloaded from The Cancer Genome Atlas (TCGA), which is a publicly available database. The RPKM values of the RNAseq data were subjected to weighted gene co-expression network analysis (WGCNA) in modularization. Results: We identified survival specific lncRNAs and mRNAs, which were divided into modules by coexpression analysis. The lncRNAs were mainly annotated into “Fc gamma R-mediated phagocytosis”. The hub lncRNA and co-expressed mRNAs were further selected for analysis of risk stratification. LncRNA-LOC646762 may contribute to AML through the "endocytosis" signaling pathway. Finally, the expression levels of LOC646762 and co-expressed CCND3, CBR1, C10orf54, CD97 and BLOC1S1 in the adult AML patients and healthy volunteers were validated by qRT-PCR, and then their roles in prognosis and risk stratification were identified. Conclusions: Prognostic lncRNA-LOC646762, which may contribute to AML through the "endocytosis" signaling pathway, may act as a biomarker for predicting the survival of adult AML patients, as well as for risk stratification.
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spelling pubmed-67461442019-09-16 Expression profile analysis of prognostic long non-coding RNA in adult acute myeloid leukemia by weighted gene co-expression network analysis (WGCNA) Chen, Cun-Te Wang, Pei-Pei Mo, Wen-Jian Zhang, Yu-Ping Zhou, Wei Deng, Ting-Fen Zhou, Ming Chen, Xiao-Wei Wang, Shun-Qing Wang, Cai-Xia J Cancer Research Paper Background: Long non-coding RNAs (lncRNAs), which are over 200 nt in length, have a key role in tumorigenesis and disease progression. To explore the role of prognostic lncRNAs in adult acute myeloid leukemia (AML), the expression profiles of lncRNAs and mRNAs in AML were analyzed. Methods: The RNAseq data of 167 adult AML patients and the corresponding clinical information were downloaded from The Cancer Genome Atlas (TCGA), which is a publicly available database. The RPKM values of the RNAseq data were subjected to weighted gene co-expression network analysis (WGCNA) in modularization. Results: We identified survival specific lncRNAs and mRNAs, which were divided into modules by coexpression analysis. The lncRNAs were mainly annotated into “Fc gamma R-mediated phagocytosis”. The hub lncRNA and co-expressed mRNAs were further selected for analysis of risk stratification. LncRNA-LOC646762 may contribute to AML through the "endocytosis" signaling pathway. Finally, the expression levels of LOC646762 and co-expressed CCND3, CBR1, C10orf54, CD97 and BLOC1S1 in the adult AML patients and healthy volunteers were validated by qRT-PCR, and then their roles in prognosis and risk stratification were identified. Conclusions: Prognostic lncRNA-LOC646762, which may contribute to AML through the "endocytosis" signaling pathway, may act as a biomarker for predicting the survival of adult AML patients, as well as for risk stratification. Ivyspring International Publisher 2019-08-19 /pmc/articles/PMC6746144/ /pubmed/31528236 http://dx.doi.org/10.7150/jca.31234 Text en © The author(s) This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/). See http://ivyspring.com/terms for full terms and conditions.
spellingShingle Research Paper
Chen, Cun-Te
Wang, Pei-Pei
Mo, Wen-Jian
Zhang, Yu-Ping
Zhou, Wei
Deng, Ting-Fen
Zhou, Ming
Chen, Xiao-Wei
Wang, Shun-Qing
Wang, Cai-Xia
Expression profile analysis of prognostic long non-coding RNA in adult acute myeloid leukemia by weighted gene co-expression network analysis (WGCNA)
title Expression profile analysis of prognostic long non-coding RNA in adult acute myeloid leukemia by weighted gene co-expression network analysis (WGCNA)
title_full Expression profile analysis of prognostic long non-coding RNA in adult acute myeloid leukemia by weighted gene co-expression network analysis (WGCNA)
title_fullStr Expression profile analysis of prognostic long non-coding RNA in adult acute myeloid leukemia by weighted gene co-expression network analysis (WGCNA)
title_full_unstemmed Expression profile analysis of prognostic long non-coding RNA in adult acute myeloid leukemia by weighted gene co-expression network analysis (WGCNA)
title_short Expression profile analysis of prognostic long non-coding RNA in adult acute myeloid leukemia by weighted gene co-expression network analysis (WGCNA)
title_sort expression profile analysis of prognostic long non-coding rna in adult acute myeloid leukemia by weighted gene co-expression network analysis (wgcna)
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6746144/
https://www.ncbi.nlm.nih.gov/pubmed/31528236
http://dx.doi.org/10.7150/jca.31234
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