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Risk Stratification of Cytogenetically Normal Acute Myeloid Leukemia With Biallelic CEBPA Mutations Based on a Multi-Gene Panel and Nomogram Model

BACKGROUND: Approximately 30% of Chinese individuals with cytogenetically normal acute myeloid leukemia (CN-AML) have biallelic CEBPA (biCEBPA) mutations. The prognosis and optimal therapy for these patients are controversial in clinical practice. METHODS: In this study, we performed targeted region...

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Autores principales: Wu, Li-Xin, Jiang, Hao, Chang, Ying-Jun, Zhou, Ya-Lan, Wang, Jing, Wang, Zi-Long, Cao, Lei-Ming, Li, Jin-Lan, Sun, Qiu-Yu, Cao, Shan-Bo, Lou, Feng, Zhou, Tao, Liu, Li-Xia, Wang, Cheng-Cheng, Wang, Yu, Jiang, Qian, Xu, Lan-Ping, Zhang, Xiao-Hui, Liu, Kai-Yan, Huang, Xiao-Jun, Ruan, Guo-Rui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8415912/
https://www.ncbi.nlm.nih.gov/pubmed/34485141
http://dx.doi.org/10.3389/fonc.2021.706935
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author Wu, Li-Xin
Jiang, Hao
Chang, Ying-Jun
Zhou, Ya-Lan
Wang, Jing
Wang, Zi-Long
Cao, Lei-Ming
Li, Jin-Lan
Sun, Qiu-Yu
Cao, Shan-Bo
Lou, Feng
Zhou, Tao
Liu, Li-Xia
Wang, Cheng-Cheng
Wang, Yu
Jiang, Qian
Xu, Lan-Ping
Zhang, Xiao-Hui
Liu, Kai-Yan
Huang, Xiao-Jun
Ruan, Guo-Rui
author_facet Wu, Li-Xin
Jiang, Hao
Chang, Ying-Jun
Zhou, Ya-Lan
Wang, Jing
Wang, Zi-Long
Cao, Lei-Ming
Li, Jin-Lan
Sun, Qiu-Yu
Cao, Shan-Bo
Lou, Feng
Zhou, Tao
Liu, Li-Xia
Wang, Cheng-Cheng
Wang, Yu
Jiang, Qian
Xu, Lan-Ping
Zhang, Xiao-Hui
Liu, Kai-Yan
Huang, Xiao-Jun
Ruan, Guo-Rui
author_sort Wu, Li-Xin
collection PubMed
description BACKGROUND: Approximately 30% of Chinese individuals with cytogenetically normal acute myeloid leukemia (CN-AML) have biallelic CEBPA (biCEBPA) mutations. The prognosis and optimal therapy for these patients are controversial in clinical practice. METHODS: In this study, we performed targeted region sequencing of 236 genes in 158 individuals with this genotype and constructed a nomogram model based on leukemia-free survival (LFS). Patients were randomly assigned to a training cohort (N =111) and a validation cohort (N =47) at a ratio of 7:3. Risk stratification was performed by the prognostic factors to investigate the risk-adapted post-remission therapy by Kaplan–Meier method. RESULTS: At least 1 mutated gene other than CEBPA was identified in patients and mutation number was associated with LFS (61.6% vs. 39.0%, P =0.033), survival (85.6% vs. 62.9%, P =0.030) and cumulative incidence of relapse (CIR) (38.4% vs. 59.5%, P =0.0496). White blood cell count, mutations in CFS3R, KMT2A and DNA methylation related genes were weighted to construct a nomogram model and differentiate two risk subgroups. Regarding LFS, low-risk patients were superior to the high-risk (89.3% vs. 33.8%, P <0.001 in training cohort; 87.5% vs. 18.2%, P =0.009 in validation cohort). Compared with chemotherapy, allogenic hematopoietic stem cell transplantation (allo-HSCT) improved 5-year LFS (89.6% vs. 32.6%, P <0.001), survival (96.9% vs. 63.6%, P =0.001) and CIR (7.2% vs. 65.8%, P <0.001) in high-risk patients but not low-risk patients (LFS, 77.4% vs. 88.9%, P =0.424; survival, 83.9% vs. 95.5%, P =0.173; CIR, 11.7% vs. 11.1%, P =0.901). CONCLUSIONS: Our study indicated that biCEBPA mutant-positive CN-AML patients could be further classified into two risk subgroups by four factors and allo-HSCT should be recommended for high-risk patients as post-remission therapy. These data will help physicians refine treatment decision-making in biCEBPA mutant-positive CN-AML patients.
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spelling pubmed-84159122021-09-04 Risk Stratification of Cytogenetically Normal Acute Myeloid Leukemia With Biallelic CEBPA Mutations Based on a Multi-Gene Panel and Nomogram Model Wu, Li-Xin Jiang, Hao Chang, Ying-Jun Zhou, Ya-Lan Wang, Jing Wang, Zi-Long Cao, Lei-Ming Li, Jin-Lan Sun, Qiu-Yu Cao, Shan-Bo Lou, Feng Zhou, Tao Liu, Li-Xia Wang, Cheng-Cheng Wang, Yu Jiang, Qian Xu, Lan-Ping Zhang, Xiao-Hui Liu, Kai-Yan Huang, Xiao-Jun Ruan, Guo-Rui Front Oncol Oncology BACKGROUND: Approximately 30% of Chinese individuals with cytogenetically normal acute myeloid leukemia (CN-AML) have biallelic CEBPA (biCEBPA) mutations. The prognosis and optimal therapy for these patients are controversial in clinical practice. METHODS: In this study, we performed targeted region sequencing of 236 genes in 158 individuals with this genotype and constructed a nomogram model based on leukemia-free survival (LFS). Patients were randomly assigned to a training cohort (N =111) and a validation cohort (N =47) at a ratio of 7:3. Risk stratification was performed by the prognostic factors to investigate the risk-adapted post-remission therapy by Kaplan–Meier method. RESULTS: At least 1 mutated gene other than CEBPA was identified in patients and mutation number was associated with LFS (61.6% vs. 39.0%, P =0.033), survival (85.6% vs. 62.9%, P =0.030) and cumulative incidence of relapse (CIR) (38.4% vs. 59.5%, P =0.0496). White blood cell count, mutations in CFS3R, KMT2A and DNA methylation related genes were weighted to construct a nomogram model and differentiate two risk subgroups. Regarding LFS, low-risk patients were superior to the high-risk (89.3% vs. 33.8%, P <0.001 in training cohort; 87.5% vs. 18.2%, P =0.009 in validation cohort). Compared with chemotherapy, allogenic hematopoietic stem cell transplantation (allo-HSCT) improved 5-year LFS (89.6% vs. 32.6%, P <0.001), survival (96.9% vs. 63.6%, P =0.001) and CIR (7.2% vs. 65.8%, P <0.001) in high-risk patients but not low-risk patients (LFS, 77.4% vs. 88.9%, P =0.424; survival, 83.9% vs. 95.5%, P =0.173; CIR, 11.7% vs. 11.1%, P =0.901). CONCLUSIONS: Our study indicated that biCEBPA mutant-positive CN-AML patients could be further classified into two risk subgroups by four factors and allo-HSCT should be recommended for high-risk patients as post-remission therapy. These data will help physicians refine treatment decision-making in biCEBPA mutant-positive CN-AML patients. Frontiers Media S.A. 2021-08-17 /pmc/articles/PMC8415912/ /pubmed/34485141 http://dx.doi.org/10.3389/fonc.2021.706935 Text en Copyright © 2021 Wu, Jiang, Chang, Zhou, Wang, Wang, Cao, Li, Sun, Cao, Lou, Zhou, Liu, Wang, Wang, Jiang, Xu, Zhang, Liu, Huang and Ruan https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Oncology
Wu, Li-Xin
Jiang, Hao
Chang, Ying-Jun
Zhou, Ya-Lan
Wang, Jing
Wang, Zi-Long
Cao, Lei-Ming
Li, Jin-Lan
Sun, Qiu-Yu
Cao, Shan-Bo
Lou, Feng
Zhou, Tao
Liu, Li-Xia
Wang, Cheng-Cheng
Wang, Yu
Jiang, Qian
Xu, Lan-Ping
Zhang, Xiao-Hui
Liu, Kai-Yan
Huang, Xiao-Jun
Ruan, Guo-Rui
Risk Stratification of Cytogenetically Normal Acute Myeloid Leukemia With Biallelic CEBPA Mutations Based on a Multi-Gene Panel and Nomogram Model
title Risk Stratification of Cytogenetically Normal Acute Myeloid Leukemia With Biallelic CEBPA Mutations Based on a Multi-Gene Panel and Nomogram Model
title_full Risk Stratification of Cytogenetically Normal Acute Myeloid Leukemia With Biallelic CEBPA Mutations Based on a Multi-Gene Panel and Nomogram Model
title_fullStr Risk Stratification of Cytogenetically Normal Acute Myeloid Leukemia With Biallelic CEBPA Mutations Based on a Multi-Gene Panel and Nomogram Model
title_full_unstemmed Risk Stratification of Cytogenetically Normal Acute Myeloid Leukemia With Biallelic CEBPA Mutations Based on a Multi-Gene Panel and Nomogram Model
title_short Risk Stratification of Cytogenetically Normal Acute Myeloid Leukemia With Biallelic CEBPA Mutations Based on a Multi-Gene Panel and Nomogram Model
title_sort risk stratification of cytogenetically normal acute myeloid leukemia with biallelic cebpa mutations based on a multi-gene panel and nomogram model
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8415912/
https://www.ncbi.nlm.nih.gov/pubmed/34485141
http://dx.doi.org/10.3389/fonc.2021.706935
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