Glioma immune microenvironment composition calculator (GIMiCC): a method of estimating the proportions of eighteen cell types from DNA methylation microarray data

A scalable platform for cell typing in the glioma microenvironment can improve tumor subtyping and immune landscape detection as successful immunotherapy strategies continue to be sought and evaluated. DNA methylation (DNAm) biomarkers for molecular classification of tumor subtypes have been developed for clinical use. However, tools that predict the cellular landscape of the tumor are not well-defined or readily available. We developed the Glioma Immune Microenvironment Composition Calculator (GIMiCC), an approach for deconvolution of cell types in gliomas using DNAm data. Using data from 17 isolated cell types, we describe the derivation of the deconvolution libraries in the biological context of selected genomic regions and validate deconvolution results using independent datasets. We utilize GIMiCC to illustrate that DNAm-based estimates of immune composition are clinically relevant and scalable for potential clinical implementation. In addition, we utilize GIMiCC to identify composition-independent DNAm alterations that are associated with high immune infiltration. Our future work aims to optimize GIMiCC and advance the clinical evaluation of glioma.

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Publication Details

Journal
Acta Neuropathologica Communications
Published
2024-10-28
DOI
https://doi.org/10.1186/s40478-024-01874-0
Citations
3
Primary Topic
MicroRNA in disease regulation
Type
article
Field-Weighted Citation Impact
0.86

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article

Glioma immune microenvironment composition calculator (GIMiCC): a method of estimating the proportions of eighteen cell types from DNA methylation microarray data

Steven C. Pike, Ze Zhang, John K. Wiencke, Annette M. Molinaro et al.
3 citations
Acta Neuropathologica Communications
MicroRNA in disease regulation
0.86
article

Glioma immune microenvironment composition calculator (GIMiCC): a method of estimating the proportions of eighteen cell types from DNA methylation microarray data

Steven C. Pike, Ze Zhang, John K. Wiencke, Annette M. Molinaro, Helen M. Hansen, Devin C. Koestler, Karl T. Kelsey, Brock C. Christensen, Lucas A. Salas
article en
3 citations

Abstract

A scalable platform for cell typing in the glioma microenvironment can improve tumor subtyping and immune landscape detection as successful immunotherapy strategies continue to be sought and evaluated. DNA methylation (DNAm) biomarkers for molecular classification of tumor subtypes have been developed for clinical use. However, tools that predict the cellular landscape of the tumor are not well-defined or readily available. We developed the Glioma Immune Microenvironment Composition Calculator (GIMiCC), an approach for deconvolution of cell types in gliomas using DNAm data. Using data from 17 isolated cell types, we describe the derivation of the deconvolution libraries in the biological context of selected genomic regions and validate deconvolution results using independent datasets. We utilize GIMiCC to illustrate that DNAm-based estimates of immune composition are clinically relevant and scalable for potential clinical implementation. In addition, we utilize GIMiCC to identify composition-independent DNAm alterations that are associated with high immune infiltration. Our future work aims to optimize GIMiCC and advance the clinical evaluation of glioma.

Acta Neuropathologica CommunicationsVol. 12(1)
Dartmouth College (US), Dartmouth–Hitchcock Medical Center (US), University of California, San Francisco (US), Brown University (US), University of Kansas Medical Center (US), Neurological Surgery (US)
National Institutes of Health, National Cancer Institute, National Institute of General Medical Sciences
Zero hunger
Openalex Percentile: Top 25%
MicroRNA in disease regulation
0.86
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