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

Author

Cheng-Hong Tsai, Chi-Yuan Yao, Feng-Min Tien, Jih-Luh Tang, Yuan-Yeh Kuo, Yu-Chiao Chiu, Chien-Chin Lin, Mei-Hsuan Tseng, Yen-Ling Peng, Ming-Chih Liu, Chia-Wen Liu, Ming Yao, Liang-In Lin, Wen-Chien Chou, Chien-Yu Chen, Hsin-An Hou, and Hwei-Fang Tien

Subjects
Medicine, Medicine (General), R5-920
Abstract

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. Keywords: lncRNA, AML, Risk stratification, Prognostication

Published
2019
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2. Incorporation of long non-coding RNA expression profile in the 2017 ELN risk classification can improve prognostic prediction of acute myeloid leukemia patients

Author

Chiawen Liu, Ming Yao, Yen-Ling Peng, Hwei-Fang Tien, Chien-Chin Lin, Ming-Chih Liu, Chien-Yu Chen, Chi-Yuan Yao, Jih-Luh Tang, Yu-Chiao Chiu, Feng-Min Tien, Yuan-Yeh Kuo, Wen-Chien Chou, Liang-In Lin, Mei-Hsuan Tseng, Hsin-An Hou, and Cheng-Hong Tsai

Subjects
0301 basic medicine, Oncology, Adult, Male, medicine.medical_specialty, Multivariate analysis, Research paper, Adolescent, medicine.medical_treatment, Hematopoietic stem cell transplantation, Kaplan-Meier Estimate, Prognostication, Gene mutation, Risk Assessment, General Biochemistry, Genetics and Molecular Biology, 03 medical and health sciences, European LeukemiaNet, Young Adult, 0302 clinical medicine, lncRNA, AML, Internal medicine, medicine, Humans, Risk stratification, Aged, Proportional Hazards Models, Aged, 80 and over, Chromosome Aberrations, business.industry, Gene Expression Profiling, Myeloid leukemia, Hematopoietic stem cell, General Medicine, Middle Aged, medicine.disease, Prognosis, Long non-coding RNA, Leukemia, Leukemia, Myeloid, Acute, 030104 developmental biology, medicine.anatomical_structure, 030220 oncology & carcinogenesis, Mutation, Female, RNA, Long Noncoding, Risk classification, business, Transcriptome
Abstract

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 into 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. Funding Statement: This work was supported Ministry of Science and Technology, and Ministry of Health and Welfare of Taiwan. Declaration of Interests: The authors declare no competing interests. Ethics Approval Statement: This study was approved by the Research Ethics Committee of the NTUH in accordance with the Declaration of Helsinki.

Published
2018

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