The Influence of Methylating Mutations on Acute Myeloid Leukemia: Preliminary Analysis on 56 Patients

Diagnostics

Bogdan Fetica¹  Delia Dima¹  Cristina Selicean¹  Vlad Moisoiu²  Patric Teodorescu²  Sergiu Pasca²  Catalin Constantinescu²  Ciprian Tomuleasa²  Bobe Petrushev²  Valentina Sas²  Ionut Hotea²  Cristina Turcas²  Sabina Iluta²  Anca Bojan²  Mihnea Zdrenghea²  Alina-Andreea Zimta³  Ancuta Jurj⁴ 

[1] Department of Hematology, Ion Chiricuta Clinical Cancer Center, 400006 Cluj Napoca, Romania;Department of Hematology, Iuliu Hatieganu University of Medicine and Pharmacy, 400124 Cluj Napoca, Romania;Medfuture Research Center for Advanced Medicine, Iuliu Hatieganu University of Medicine and Pharmacy, 400124 Cluj Napoca, Romania;Research Center for Functional Genomics and Translational Medicine, Iuliu Hatieganu University of Medicine and Pharmacy, 400124 Cluj Napoca, Romania;

关键词: acute myeloid leukemia;    methylation;    classification;    TCGA;    mutations;   

DOI  :  10.3390/diagnostics10050263

来源: DOAJ

【 摘 要 】

Acute myeloid leukemia (AML) is a hematologic malignancy characterized by abnormal proliferation and a lack of differentiation of myeloid blasts. Considering the dismal prognosis this disease presents, several efforts have been made to better classify it and offer a tailored treatment to each subtype. This has been formally done by the World Health Organization (WHO) with the AML classification schemes from 2008 and 2016. Nonetheless, there are still mutations that are not currently included in the WHO AML classification, as in the case of some mutations that influence methylation. In this regard, the present study aimed to determine if some of the mutations that influence DNA methylation can be clustered together regarding methylation, expression, and clinical profile. Data from the TCGA LAML cohort were downloaded via cBioPortal. The analysis was performed using R 3.5.2, and the necessary packages for classical statistics, dimensionality reduction, and machine learning. We included only patients that presented mutations in DNMT3A, TET2, IDH1/2, ASXL1, WT1, and KMT2A. Afterwards, mutations that were present in too few patients were removed from the analysis, thus including a total of 57 AML patients. We observed that regarding expression, methylation, and clinical profile, patients with mutated TET2, IDH1/2, and WT1 presented a high degree of similarity, indicating the equivalence that these mutations present between themselves. Nonetheless, we did not observe this similarity between DNMT3A- and KMT2A-mutated AML. Moreover, when comparing the hypermethylating group with the hypomethylating one, we also observed important differences regarding expression, methylation, and clinical profile. In the current manuscript we offer additional arguments for the similarity of the studied hypermethylating mutations and suggest that those should be clustered together in further classifications. The hypermethylating and hypomethylating groups formed above were shown to be different from each other considering overall survival, methylation profile, expression profile, and clinical characteristics. In this manuscript, we present additional arguments for the similarity of the effect generated by TET2, IDH1/2, and WT1 mutations in AML patients. Thus, we hypothesize that hypermethylating mutations skew the AML cells to a similar phenotype with a possible sensitivity to hypermethylating agents.

【 授权许可】

Unknown