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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...
Autores principales: | , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2019
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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. |
format | Online Article Text |
id | pubmed-6413345 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
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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