A machine learning model identifies M3-like subtype in AML based on PML/RARα targets-Reference-Cited by-同舟云学术

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A machine learning model identifies M3-like subtype in AML based on PML/RARα targets

Published:2024-02 Issue:2 Volume:27 Page:108947
ISSN:2589-0042
Container-title:iScience
language:en
Short-container-title:iScience

Author:

Shao Tingting,Li Jianing,Su Minghai,Yang Changbo,Ma Yingying,Lv Chongwen,Wang Wei,Xie Yunjin,Xu Gang,Shi Ce,Zhou Xinying,Fan Huitao,Li Yongsheng,Xu Juan^ORCID

Funder

National Natural Science Foundation of China

Publisher

Elsevier BV

Reference69 articles.

1. Genomic Classification and Prognosis in Acute Myeloid Leukemia;Papaemmanuil;N. Engl. J. Med.,2016

2. Spectrum and prognostic relevance of driver gene mutations in acute myeloid leukemia;Metzeler;Blood,2016

3. A distinct immunophenotype identifies a subset of NPM1-mutated AML with TET2 or IDH1/2 mutations and improved outcome;Mason;Am. J. Hematol.,2018

4. Integration of Genomic and Transcriptomic Markers Improves the Prognosis Prediction of Acute Promyelocytic Leukemia;Lin;Clin. Cancer Res.,2021

5. A PML/RARalpha direct target atlas redefines transcriptional deregulation in acute promyelocytic leukemia;Tan;Blood,2021

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