Histone methylation modification patterns and relevant M-RiskScore in acute myeloid leukemia
Objective: We tried to identify novel molecular subtypes of acute myeloid leukemia (AML) associated with histone methylation and established a relevant scoring system to predict treatment response and prognosis of AML. Methods: Gene expression data and clinical characteristics of patients with AML w...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2022-09-01
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| Series: | Heliyon |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2405844022018989 |
| _version_ | 1811254993053810688 |
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| author | Dade Rong Xiaomin Chen Jing Xiao Daiyuan Liu Xiangna Ni Xiuzhen Tong Haihe Wang |
| author_facet | Dade Rong Xiaomin Chen Jing Xiao Daiyuan Liu Xiangna Ni Xiuzhen Tong Haihe Wang |
| author_sort | Dade Rong |
| collection | DOAJ |
| description | Objective: We tried to identify novel molecular subtypes of acute myeloid leukemia (AML) associated with histone methylation and established a relevant scoring system to predict treatment response and prognosis of AML. Methods: Gene expression data and clinical characteristics of patients with AML were obtained from The Cancer Genome Atlas (TCGA) database and Gene Expression Omnibus (GEO) database. Molecular subtyping was carried out by consensus clustering analysis, based on the expression of 24 histone methylation modification regulators (HMMRs). The clinical and biological features of each clustered pattern were taken into account. The scoring system was constructed by using differential expression analysis, Cox regression method and lasso regression analysis. Subsequently, the scoring system in the roles of prognostic and chemotherapeutic prediction of AML were explored. Finally, an independent GSE dataset was used for validating the established clustering system. Results: Two distinct subtypes of AML were identified based on the expression of the 24 HMMRs, which exhibited remarkable differences in several clinical and biological characteristics, including HMMRs expression, AML-M0 distribution, NPM1 mutation, tumor mutation burden, somatic mutations, pathway activation, immune cell infiltration and patient survival. The scoring system, M-RiskScore, was established. Integrated analysis demonstrated that patients with the low M-RiskScore displayed a prominent survival advantage and a good response to decitabine treatment, while patients with high M-RiskScore have resistance to decitabine, but they could benefit from IA regimen therapy. Conclusion: Detection of HMMRs expression would be a potential strategy for AML subtyping. Meanwhile, targeting histone methylation would be a preferred strategy for either AML-M0 or NPM1 mutant patients. M-RiskScore was a useful prognostic biomarker and a guide for the choice of appropriate chemotherapy strategy. |
| first_indexed | 2024-04-12T17:16:55Z |
| format | Article |
| id | doaj.art-903b1fb5ba894ca49e7ad3a97476bc68 |
| institution | Directory Open Access Journal |
| issn | 2405-8440 |
| language | English |
| last_indexed | 2024-04-12T17:16:55Z |
| publishDate | 2022-09-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Heliyon |
| spelling | doaj.art-903b1fb5ba894ca49e7ad3a97476bc682022-12-22T03:23:37ZengElsevierHeliyon2405-84402022-09-0189e10610Histone methylation modification patterns and relevant M-RiskScore in acute myeloid leukemiaDade Rong0Xiaomin Chen1Jing Xiao2Daiyuan Liu3Xiangna Ni4Xiuzhen Tong5Haihe Wang6The First Affiliated Hospital, Sun Yat-sen University, 58 Second Zhongshan Road, Guangzhou, 510080, China; Department of Biochemistry, Zhongshan School of Medicine, Sun Yat-sen University, 74 Second Zhongshan Road, Guangzhou, 510080, China; Faculty of Health Sciences, University of Macau, Macau, ChinaThe First Affiliated Hospital, Sun Yat-sen University, 58 Second Zhongshan Road, Guangzhou, 510080, China; GenePlus, Beijing, ChinaZhuhai Interventional Medical Center, Zhuhai Precision Medical Center, Department of Clinical Laboratory, Zhuhai People's Hospital (Zhuhai Hospital Affiliated with Jinan University), Zhuhai, 519000, ChinaDepartment of Biochemistry, Zhongshan School of Medicine, Sun Yat-sen University, 74 Second Zhongshan Road, Guangzhou, 510080, ChinaThe First Affiliated Hospital, Sun Yat-sen University, 58 Second Zhongshan Road, Guangzhou, 510080, ChinaThe First Affiliated Hospital, Sun Yat-sen University, 58 Second Zhongshan Road, Guangzhou, 510080, China; Corresponding author.Department of Biochemistry, Zhongshan School of Medicine, Sun Yat-sen University, 74 Second Zhongshan Road, Guangzhou, 510080, China; Corresponding author.Objective: We tried to identify novel molecular subtypes of acute myeloid leukemia (AML) associated with histone methylation and established a relevant scoring system to predict treatment response and prognosis of AML. Methods: Gene expression data and clinical characteristics of patients with AML were obtained from The Cancer Genome Atlas (TCGA) database and Gene Expression Omnibus (GEO) database. Molecular subtyping was carried out by consensus clustering analysis, based on the expression of 24 histone methylation modification regulators (HMMRs). The clinical and biological features of each clustered pattern were taken into account. The scoring system was constructed by using differential expression analysis, Cox regression method and lasso regression analysis. Subsequently, the scoring system in the roles of prognostic and chemotherapeutic prediction of AML were explored. Finally, an independent GSE dataset was used for validating the established clustering system. Results: Two distinct subtypes of AML were identified based on the expression of the 24 HMMRs, which exhibited remarkable differences in several clinical and biological characteristics, including HMMRs expression, AML-M0 distribution, NPM1 mutation, tumor mutation burden, somatic mutations, pathway activation, immune cell infiltration and patient survival. The scoring system, M-RiskScore, was established. Integrated analysis demonstrated that patients with the low M-RiskScore displayed a prominent survival advantage and a good response to decitabine treatment, while patients with high M-RiskScore have resistance to decitabine, but they could benefit from IA regimen therapy. Conclusion: Detection of HMMRs expression would be a potential strategy for AML subtyping. Meanwhile, targeting histone methylation would be a preferred strategy for either AML-M0 or NPM1 mutant patients. M-RiskScore was a useful prognostic biomarker and a guide for the choice of appropriate chemotherapy strategy.http://www.sciencedirect.com/science/article/pii/S2405844022018989Acute myeloid leukemiaHistoneMethylationClassificationChemotherapy |
| spellingShingle | Dade Rong Xiaomin Chen Jing Xiao Daiyuan Liu Xiangna Ni Xiuzhen Tong Haihe Wang Histone methylation modification patterns and relevant M-RiskScore in acute myeloid leukemia Heliyon Acute myeloid leukemia Histone Methylation Classification Chemotherapy |
| title | Histone methylation modification patterns and relevant M-RiskScore in acute myeloid leukemia |
| title_full | Histone methylation modification patterns and relevant M-RiskScore in acute myeloid leukemia |
| title_fullStr | Histone methylation modification patterns and relevant M-RiskScore in acute myeloid leukemia |
| title_full_unstemmed | Histone methylation modification patterns and relevant M-RiskScore in acute myeloid leukemia |
| title_short | Histone methylation modification patterns and relevant M-RiskScore in acute myeloid leukemia |
| title_sort | histone methylation modification patterns and relevant m riskscore in acute myeloid leukemia |
| topic | Acute myeloid leukemia Histone Methylation Classification Chemotherapy |
| url | http://www.sciencedirect.com/science/article/pii/S2405844022018989 |
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