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Updated: May 4, 2026
Comprehensive DNA Methylation Analysis Using a Methyl-CpG-binding Domain Capture-based Method in Chronic Lymphocytic Leukemia Patients
Published on: June 16, 2017
DNA methylation profiling can classify HIV-associated lymphomas
Akihiro Matsunaga1, Tsunekazu Hishima, Noriko Tanaka
1aDepartment of Intractable Diseases, Research Institute, National Center for Global Health and Medicine, Shinjuku bDepartment of Pathology, Tokyo Metropolitan Cancer and Infectious Diseases Center, Komagome Hospital, Honkomagome, Bunkyo cBiostatistics Section, Department of Clinical Research and Informatics, Clinical Research Center, National Center for Global Health and Medicine, Shinjuku dDepartment of Human Genetic, School of Medicine, The University of Tokyo, Bunkyo, Tokyo eGraduate School of Frontier Sciences, The University of Tokyo, Kashiwa, Chiba fDepartment of Pathology gAIDS Clinical Center hDivision of Hematology, Internal Medicine, National Center for Global Health and Medicine Hospital, Shinjuku iDepartment of Pathology, School of Medicine, Kyorin University, Mitaka, Tokyo, Japan.
Background:
HIV-positive patients have a 60-fold to 200-fold increased incidence of non-Hodgkin lymphomas, including Burkitt lymphoma, diffuse large B-cell lymphoma, and primary central nervous system lymphoma. HIV-associated lymphomas frequently have features such as extranodal involvement, decreased responses to standard chemotherapy, and high relapse rates, which indicate a poor prognosis. General pathological features do not clearly differentiate HIV-associated lymphomas from non-HIV lymphomas.
Methods:
To investigate the features of HIV-associated lymphomas, we performed genome-wide DNA methylation profiling of HIV and non-HIV lymphomas using Illumina GoldenGate Methylation Cancer Panel I and Illumina Infinium HumanMethylation450 BeadChip microarrays. DNA methylation profiles in HIV-associated and non-HIV lymphomas were characterized using unsupervised hierarchical clustering analyses.
Results:
The analyses of promoter regions revealed unique DNA methylation profiles in HIV-associated lymphomas, suggesting profile differences compared with non-HIV lymphomas, which implies specific gene regulation in HIV-associated lymphoma involving DNA methylation. Based on HumanMethylation450 BeadChip data, 2541 target sites were selected as differing significantly in comparisons between HIV-associated and non-HIV-associated lymphomas using Wilcoxon's rank-sum test (P <0.05) and Δβ values more than 0.30. Recurrent cases of HIV-associated lymphoma had different profiles compared with nonrecurrent HIV lymphomas.
Conclusion:
DNA methylation profiling indicated that 2541 target sites differed significantly in HIV-associated lymphoma, which may partly explain the poor prognosis. Our data indicate that the methylation profiles of target genes have potential in elucidating HIV-associated lymphomagenesis and can serve as new prognostic markers.
