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

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.

• Authors: 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, Hwei-Fang Tien
• Journal: EBioMedicine (EBioMedicine) Vol. 40 Pg. 240-250 (Feb 2019) ISSN: 2352-3964 [Electronic] Netherlands
• PMID: 30662003 (Publication Type: Journal Article)
• Copyright: Copyright © 2019 The Authors. Published by Elsevier B.V. All rights reserved.

Chemical References

• RNA, Long Noncoding

Topics

• Adolescent
• Adult
• Aged
• Aged, 80 and over
• Chromosome Aberrations
• Female
• Gene Expression Profiling
• Humans
• Kaplan-Meier Estimate
• Leukemia, Myeloid, Acute (diagnosis, genetics, mortality, therapy)
• Male
• Middle Aged
• Mutation
• Prognosis
• Proportional Hazards Models
• RNA, Long Noncoding (genetics)
• Risk Assessment
• Transcriptome
• Young Adult