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Incorporation of long non-coding RNA expression profile in the 2017 ELN risk classification can improve prognostic prediction of acute myeloid leukemia patients

BACKGROUND: Expression of long non-coding RNAs (lncRNAs) has recently been recognized as a potential prognostic marker in acute myeloid leukemia (AML). However, it remains unclear whether incorporation of the lncRNAs expression in the 2017 European LeukemiaNet (ELN) risk classification can further i...

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Autores principales: Tsai, Cheng-Hong, Yao, Chi-Yuan, Tien, Feng-Min, Tang, Jih-Luh, Kuo, Yuan-Yeh, Chiu, Yu-Chiao, Lin, Chien-Chin, Tseng, Mei-Hsuan, Peng, Yen-Ling, Liu, Ming-Chih, Liu, Chia-Wen, Yao, Ming, Lin, Liang-In, Chou, Wen-Chien, Chen, Chien-Yu, Hou, Hsin-An, Tien, Hwei-Fang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6413345/
https://www.ncbi.nlm.nih.gov/pubmed/30662003
http://dx.doi.org/10.1016/j.ebiom.2019.01.022
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author Tsai, Cheng-Hong
Yao, Chi-Yuan
Tien, Feng-Min
Tang, Jih-Luh
Kuo, Yuan-Yeh
Chiu, Yu-Chiao
Lin, Chien-Chin
Tseng, Mei-Hsuan
Peng, Yen-Ling
Liu, Ming-Chih
Liu, Chia-Wen
Yao, Ming
Lin, Liang-In
Chou, Wen-Chien
Chen, Chien-Yu
Hou, Hsin-An
Tien, Hwei-Fang
author_facet Tsai, Cheng-Hong
Yao, Chi-Yuan
Tien, Feng-Min
Tang, Jih-Luh
Kuo, Yuan-Yeh
Chiu, Yu-Chiao
Lin, Chien-Chin
Tseng, Mei-Hsuan
Peng, Yen-Ling
Liu, Ming-Chih
Liu, Chia-Wen
Yao, Ming
Lin, Liang-In
Chou, Wen-Chien
Chen, Chien-Yu
Hou, Hsin-An
Tien, Hwei-Fang
author_sort Tsai, Cheng-Hong
collection PubMed
description BACKGROUND: Expression of long non-coding RNAs (lncRNAs) has recently been recognized as a potential prognostic marker in acute myeloid leukemia (AML). However, it remains unclear whether incorporation of the lncRNAs expression in the 2017 European LeukemiaNet (ELN) risk classification can further improve the prognostic prediction. METHODS: We enrolled 275 newly diagnosed non-M3 AML patients and randomly assigned them to the training (n = 183) and validation cohorts (n = 92). In the training cohort, we formulated a prognostic lncRNA scoring system composed of five lncRNAs with significant prognostic impact from the lncRNA expression profiling. FINDINGS: Higher lncRNA scores were significantly associated with older age and adverse gene mutations. Further, the higher-score patients had shorter overall and disease-free survival than lower-score patients, which were also confirmed in both internal and external validation cohorts (TCGA database). The multivariate analyses revealed the lncRNA score was an independent prognosticator in AML, irrespective of the risk based on the 2017 ELN classification. Moreover, in the 2017 ELN intermediate-risk subgroup, lncRNA scoring system could well dichotomize the patients into two groups with distinct prognosis. Within the ELN intermediate-risk subgroup, we found that allogeneic hematopoietic stem cell transplantation could provide better outcome on patients with higher lncRNA scores. Through bioinformatics approach, we identified high lncRNA scores were correlated with leukemia/hematopoietic stem cell signatures. INTERPRETATION: Incorporation of lncRNA scoring system in 2017 ELN classification can improve risk-stratification of AML patients and help clinical decision-making. FUND: This work was supported Ministry of Science and Technology, and Ministry of Health and Welfare of Taiwan.
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spelling pubmed-64133452019-03-21 Incorporation of long non-coding RNA expression profile in the 2017 ELN risk classification can improve prognostic prediction of acute myeloid leukemia patients Tsai, Cheng-Hong Yao, Chi-Yuan Tien, Feng-Min Tang, Jih-Luh Kuo, Yuan-Yeh Chiu, Yu-Chiao Lin, Chien-Chin Tseng, Mei-Hsuan Peng, Yen-Ling Liu, Ming-Chih Liu, Chia-Wen Yao, Ming Lin, Liang-In Chou, Wen-Chien Chen, Chien-Yu Hou, Hsin-An Tien, Hwei-Fang EBioMedicine Research paper BACKGROUND: Expression of long non-coding RNAs (lncRNAs) has recently been recognized as a potential prognostic marker in acute myeloid leukemia (AML). However, it remains unclear whether incorporation of the lncRNAs expression in the 2017 European LeukemiaNet (ELN) risk classification can further improve the prognostic prediction. METHODS: We enrolled 275 newly diagnosed non-M3 AML patients and randomly assigned them to the training (n = 183) and validation cohorts (n = 92). In the training cohort, we formulated a prognostic lncRNA scoring system composed of five lncRNAs with significant prognostic impact from the lncRNA expression profiling. FINDINGS: Higher lncRNA scores were significantly associated with older age and adverse gene mutations. Further, the higher-score patients had shorter overall and disease-free survival than lower-score patients, which were also confirmed in both internal and external validation cohorts (TCGA database). The multivariate analyses revealed the lncRNA score was an independent prognosticator in AML, irrespective of the risk based on the 2017 ELN classification. Moreover, in the 2017 ELN intermediate-risk subgroup, lncRNA scoring system could well dichotomize the patients into two groups with distinct prognosis. Within the ELN intermediate-risk subgroup, we found that allogeneic hematopoietic stem cell transplantation could provide better outcome on patients with higher lncRNA scores. Through bioinformatics approach, we identified high lncRNA scores were correlated with leukemia/hematopoietic stem cell signatures. INTERPRETATION: Incorporation of lncRNA scoring system in 2017 ELN classification can improve risk-stratification of AML patients and help clinical decision-making. FUND: This work was supported Ministry of Science and Technology, and Ministry of Health and Welfare of Taiwan. Elsevier 2019-01-17 /pmc/articles/PMC6413345/ /pubmed/30662003 http://dx.doi.org/10.1016/j.ebiom.2019.01.022 Text en © 2019 The Authors http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Research paper
Tsai, Cheng-Hong
Yao, Chi-Yuan
Tien, Feng-Min
Tang, Jih-Luh
Kuo, Yuan-Yeh
Chiu, Yu-Chiao
Lin, Chien-Chin
Tseng, Mei-Hsuan
Peng, Yen-Ling
Liu, Ming-Chih
Liu, Chia-Wen
Yao, Ming
Lin, Liang-In
Chou, Wen-Chien
Chen, Chien-Yu
Hou, Hsin-An
Tien, Hwei-Fang
Incorporation of long non-coding RNA expression profile in the 2017 ELN risk classification can improve prognostic prediction of acute myeloid leukemia patients
title Incorporation of long non-coding RNA expression profile in the 2017 ELN risk classification can improve prognostic prediction of acute myeloid leukemia patients
title_full Incorporation of long non-coding RNA expression profile in the 2017 ELN risk classification can improve prognostic prediction of acute myeloid leukemia patients
title_fullStr Incorporation of long non-coding RNA expression profile in the 2017 ELN risk classification can improve prognostic prediction of acute myeloid leukemia patients
title_full_unstemmed Incorporation of long non-coding RNA expression profile in the 2017 ELN risk classification can improve prognostic prediction of acute myeloid leukemia patients
title_short Incorporation of long non-coding RNA expression profile in the 2017 ELN risk classification can improve prognostic prediction of acute myeloid leukemia patients
title_sort incorporation of long non-coding rna expression profile in the 2017 eln risk classification can improve prognostic prediction of acute myeloid leukemia patients
topic Research paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6413345/
https://www.ncbi.nlm.nih.gov/pubmed/30662003
http://dx.doi.org/10.1016/j.ebiom.2019.01.022
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