The Influence of Methylating Mutations on Acute Myeloid Leukemia: Preliminary Analysis on 56 Patients
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 subtyp...
| Main Authors: | , , , , , , , , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2020-04-01
|
| Series: | Diagnostics |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2075-4418/10/5/263 |
| _version_ | 1797569374145478656 |
|---|---|
| author | Sergiu Pasca Cristina Turcas Ancuta Jurj Patric Teodorescu Sabina Iluta Ionut Hotea Anca Bojan Cristina Selicean Bogdan Fetica Bobe Petrushev Vlad Moisoiu Alina-Andreea Zimta Valentina Sas Catalin Constantinescu Mihnea Zdrenghea Delia Dima Ciprian Tomuleasa |
| author_facet | Sergiu Pasca Cristina Turcas Ancuta Jurj Patric Teodorescu Sabina Iluta Ionut Hotea Anca Bojan Cristina Selicean Bogdan Fetica Bobe Petrushev Vlad Moisoiu Alina-Andreea Zimta Valentina Sas Catalin Constantinescu Mihnea Zdrenghea Delia Dima Ciprian Tomuleasa |
| author_sort | Sergiu Pasca |
| collection | DOAJ |
| description | 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 <i>DNMT3A, TET2, IDH1/2, ASXL1, WT1, and KMT2A</i>. 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 <i>TET2, IDH1/2,</i> and <i>WT1</i> presented a high degree of similarity, indicating the equivalence that these mutations present between themselves. Nonetheless, we did not observe this similarity between <i>DNMT3A-</i> and <i>KMT2A</i>-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 <i>TET2</i>, <i>IDH1/2,</i> and <i>WT1</i> 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. |
| first_indexed | 2024-03-10T20:09:55Z |
| format | Article |
| id | doaj.art-db30dca80f8143bea58c6b078d68ab23 |
| institution | Directory Open Access Journal |
| issn | 2075-4418 |
| language | English |
| last_indexed | 2024-03-10T20:09:55Z |
| publishDate | 2020-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Diagnostics |
| spelling | doaj.art-db30dca80f8143bea58c6b078d68ab232023-11-19T23:01:01ZengMDPI AGDiagnostics2075-44182020-04-0110526310.3390/diagnostics10050263The Influence of Methylating Mutations on Acute Myeloid Leukemia: Preliminary Analysis on 56 PatientsSergiu Pasca0Cristina Turcas1Ancuta Jurj2Patric Teodorescu3Sabina Iluta4Ionut Hotea5Anca Bojan6Cristina Selicean7Bogdan Fetica8Bobe Petrushev9Vlad Moisoiu10Alina-Andreea Zimta11Valentina Sas12Catalin Constantinescu13Mihnea Zdrenghea14Delia Dima15Ciprian Tomuleasa16Department of Hematology, Iuliu Hatieganu University of Medicine and Pharmacy, 400124 Cluj Napoca, RomaniaDepartment of Hematology, Iuliu Hatieganu University of Medicine and Pharmacy, 400124 Cluj Napoca, RomaniaResearch Center for Functional Genomics and Translational Medicine, Iuliu Hatieganu University of Medicine and Pharmacy, 400124 Cluj Napoca, RomaniaDepartment of Hematology, Iuliu Hatieganu University of Medicine and Pharmacy, 400124 Cluj Napoca, RomaniaDepartment of Hematology, Iuliu Hatieganu University of Medicine and Pharmacy, 400124 Cluj Napoca, RomaniaDepartment of Hematology, Iuliu Hatieganu University of Medicine and Pharmacy, 400124 Cluj Napoca, RomaniaDepartment of Hematology, Iuliu Hatieganu University of Medicine and Pharmacy, 400124 Cluj Napoca, RomaniaDepartment of Hematology, Ion Chiricuta Clinical Cancer Center, 400006 Cluj Napoca, RomaniaDepartment of Hematology, Ion Chiricuta Clinical Cancer Center, 400006 Cluj Napoca, RomaniaDepartment of Hematology, Iuliu Hatieganu University of Medicine and Pharmacy, 400124 Cluj Napoca, RomaniaDepartment of Hematology, Iuliu Hatieganu University of Medicine and Pharmacy, 400124 Cluj Napoca, RomaniaMedfuture Research Center for Advanced Medicine, Iuliu Hatieganu University of Medicine and Pharmacy, 400124 Cluj Napoca, RomaniaDepartment of Hematology, Iuliu Hatieganu University of Medicine and Pharmacy, 400124 Cluj Napoca, RomaniaDepartment of Hematology, Iuliu Hatieganu University of Medicine and Pharmacy, 400124 Cluj Napoca, RomaniaDepartment of Hematology, Iuliu Hatieganu University of Medicine and Pharmacy, 400124 Cluj Napoca, RomaniaDepartment of Hematology, Ion Chiricuta Clinical Cancer Center, 400006 Cluj Napoca, RomaniaDepartment of Hematology, Iuliu Hatieganu University of Medicine and Pharmacy, 400124 Cluj Napoca, RomaniaAcute 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 <i>DNMT3A, TET2, IDH1/2, ASXL1, WT1, and KMT2A</i>. 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 <i>TET2, IDH1/2,</i> and <i>WT1</i> presented a high degree of similarity, indicating the equivalence that these mutations present between themselves. Nonetheless, we did not observe this similarity between <i>DNMT3A-</i> and <i>KMT2A</i>-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 <i>TET2</i>, <i>IDH1/2,</i> and <i>WT1</i> 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.https://www.mdpi.com/2075-4418/10/5/263acute myeloid leukemiamethylationclassificationTCGAmutations |
| spellingShingle | Sergiu Pasca Cristina Turcas Ancuta Jurj Patric Teodorescu Sabina Iluta Ionut Hotea Anca Bojan Cristina Selicean Bogdan Fetica Bobe Petrushev Vlad Moisoiu Alina-Andreea Zimta Valentina Sas Catalin Constantinescu Mihnea Zdrenghea Delia Dima Ciprian Tomuleasa The Influence of Methylating Mutations on Acute Myeloid Leukemia: Preliminary Analysis on 56 Patients Diagnostics acute myeloid leukemia methylation classification TCGA mutations |
| title | The Influence of Methylating Mutations on Acute Myeloid Leukemia: Preliminary Analysis on 56 Patients |
| title_full | The Influence of Methylating Mutations on Acute Myeloid Leukemia: Preliminary Analysis on 56 Patients |
| title_fullStr | The Influence of Methylating Mutations on Acute Myeloid Leukemia: Preliminary Analysis on 56 Patients |
| title_full_unstemmed | The Influence of Methylating Mutations on Acute Myeloid Leukemia: Preliminary Analysis on 56 Patients |
| title_short | The Influence of Methylating Mutations on Acute Myeloid Leukemia: Preliminary Analysis on 56 Patients |
| title_sort | influence of methylating mutations on acute myeloid leukemia preliminary analysis on 56 patients |
| topic | acute myeloid leukemia methylation classification TCGA mutations |
| url | https://www.mdpi.com/2075-4418/10/5/263 |
| work_keys_str_mv | AT sergiupasca theinfluenceofmethylatingmutationsonacutemyeloidleukemiapreliminaryanalysison56patients AT cristinaturcas theinfluenceofmethylatingmutationsonacutemyeloidleukemiapreliminaryanalysison56patients AT ancutajurj theinfluenceofmethylatingmutationsonacutemyeloidleukemiapreliminaryanalysison56patients AT patricteodorescu theinfluenceofmethylatingmutationsonacutemyeloidleukemiapreliminaryanalysison56patients AT sabinailuta theinfluenceofmethylatingmutationsonacutemyeloidleukemiapreliminaryanalysison56patients AT ionuthotea theinfluenceofmethylatingmutationsonacutemyeloidleukemiapreliminaryanalysison56patients AT ancabojan theinfluenceofmethylatingmutationsonacutemyeloidleukemiapreliminaryanalysison56patients AT cristinaselicean theinfluenceofmethylatingmutationsonacutemyeloidleukemiapreliminaryanalysison56patients AT bogdanfetica theinfluenceofmethylatingmutationsonacutemyeloidleukemiapreliminaryanalysison56patients AT bobepetrushev theinfluenceofmethylatingmutationsonacutemyeloidleukemiapreliminaryanalysison56patients AT vladmoisoiu theinfluenceofmethylatingmutationsonacutemyeloidleukemiapreliminaryanalysison56patients AT alinaandreeazimta theinfluenceofmethylatingmutationsonacutemyeloidleukemiapreliminaryanalysison56patients AT valentinasas theinfluenceofmethylatingmutationsonacutemyeloidleukemiapreliminaryanalysison56patients AT catalinconstantinescu theinfluenceofmethylatingmutationsonacutemyeloidleukemiapreliminaryanalysison56patients AT mihneazdrenghea theinfluenceofmethylatingmutationsonacutemyeloidleukemiapreliminaryanalysison56patients AT deliadima theinfluenceofmethylatingmutationsonacutemyeloidleukemiapreliminaryanalysison56patients AT cipriantomuleasa theinfluenceofmethylatingmutationsonacutemyeloidleukemiapreliminaryanalysison56patients AT sergiupasca influenceofmethylatingmutationsonacutemyeloidleukemiapreliminaryanalysison56patients AT cristinaturcas influenceofmethylatingmutationsonacutemyeloidleukemiapreliminaryanalysison56patients AT ancutajurj influenceofmethylatingmutationsonacutemyeloidleukemiapreliminaryanalysison56patients AT patricteodorescu influenceofmethylatingmutationsonacutemyeloidleukemiapreliminaryanalysison56patients AT sabinailuta influenceofmethylatingmutationsonacutemyeloidleukemiapreliminaryanalysison56patients AT ionuthotea influenceofmethylatingmutationsonacutemyeloidleukemiapreliminaryanalysison56patients AT ancabojan influenceofmethylatingmutationsonacutemyeloidleukemiapreliminaryanalysison56patients AT cristinaselicean influenceofmethylatingmutationsonacutemyeloidleukemiapreliminaryanalysison56patients AT bogdanfetica influenceofmethylatingmutationsonacutemyeloidleukemiapreliminaryanalysison56patients AT bobepetrushev influenceofmethylatingmutationsonacutemyeloidleukemiapreliminaryanalysison56patients AT vladmoisoiu influenceofmethylatingmutationsonacutemyeloidleukemiapreliminaryanalysison56patients AT alinaandreeazimta influenceofmethylatingmutationsonacutemyeloidleukemiapreliminaryanalysison56patients AT valentinasas influenceofmethylatingmutationsonacutemyeloidleukemiapreliminaryanalysison56patients AT catalinconstantinescu influenceofmethylatingmutationsonacutemyeloidleukemiapreliminaryanalysison56patients AT mihneazdrenghea influenceofmethylatingmutationsonacutemyeloidleukemiapreliminaryanalysison56patients AT deliadima influenceofmethylatingmutationsonacutemyeloidleukemiapreliminaryanalysison56patients AT cipriantomuleasa influenceofmethylatingmutationsonacutemyeloidleukemiapreliminaryanalysison56patients |