DIMEimmune: Robust estimation of infiltrating lymphocytes in CNS tumors from DNA methylation profiles

Sepehr Safaei; Malte Mohme; Judith Niesen; Ulrich Schüller; Michael Bockmayr

doi:10.1080/2162402X.2021.1932365

DIMEimmune: Robust estimation of infiltrating lymphocytes in CNS tumors from DNA methylation profiles

Oncoimmunology. 2021 Jun 17;10(1):1932365. doi: 10.1080/2162402X.2021.1932365. eCollection 2021.

Authors

Sepehr Safaei^{1

2

3}, Malte Mohme⁴, Judith Niesen^{1

2

5}, Ulrich Schüller^{1

2

3}, Michael Bockmayr^{1

2

5

6}

Affiliations

¹ Department of Pediatric Hematology and Oncology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
² Research Institute Children's Cancer Center Hamburg, Hamburg, Germany.
³ Institute of Neuropathology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
⁴ Department of Neurosurgery, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
⁵ Mildred Scheel Cancer Career Center HaTriCS4, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
⁶ Institute of Pathology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany.

Abstract

The interaction of CNS tumors with infiltrating lymphocytes plays an important role in their initiation and progression and might be related to therapeutic responses. Gene expression-based methods have been successfully used to characterize the tumor microenvironment. However, methylation data are now increasingly used for molecular diagnostics and there are currently only few methods to infer information about the microenvironment from this data type. Using an approach based on differential methylation and principal component analysis, we developed DIMEimmune (Differential Methylation Analysis for Immune Cell Estimation) to estimate CD4⁺ and CD8⁺ T cell abundance as well as tumor-infiltrating lymphocytes (TILs) scores from bulk methylation data. Well-established approaches based on gene expression data and immunohistochemistry-based lymphocyte counts were used as benchmarks. The comparison of DIMEimmune to the previously published MethylCIBERSORT and MeTIL algorithms showed an improved correlation with both gene expression-based and immunohistological results across different brain tumor types. Further, we applied our method to large datasets of glioma, medulloblastoma, atypical teratoid/rhabdoid tumors (ATRTs) and ependymoma. High-grade gliomas showed higher scores of tumor-infiltrating lymphocytes than lower-grade gliomas. There were overall only few tumor-infiltrating lymphocytes in medulloblastoma subgroups. ATRTs were highly infiltrated by lymphocytes, most prominently in the MYC subgroup. DIMEimmune-based estimates of TILs were a significant prognostic factor in the overall cohort of gliomas and medulloblastomas, but not within methylation-based diagnostic subgroups. To conclude, DIMEimmune allows for robust estimates of TIL abundance and might contribute to establishing them as a prognostic or predictive factor in future studies of CNS tumors.

Keywords: Brain tumor; DNA methylation; immune cells; microenvironment; tumor-infiltrating lymphocytes.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Brain Neoplasms* / genetics
Central Nervous System Neoplasms* / genetics
DNA Methylation / genetics
Glioma* / genetics
Humans
Lymphocytes, Tumor-Infiltrating
Tumor Microenvironment / genetics

Grants and funding

SS, US, and MB were supported by the Fördergemeinschaft Kinderkrebszentrum Hamburg. MM was supported by the Hamburger Krebsgesellschaft and the Else Kröner-Fresenius-Stiftung.