Abstract

Abstract It is increasingly recognized that the tumor microenvironment (TME) plays a critical role in the biology of cancer. To better understand the role of non-neoplastic immune cellular components in CNS tumors, we applied a deconvolution approach to bulk DNA methylation array data using methylCIBERSORT on 450k/850k methylation data from a set (n= 4057) of high- and low-grade glial and glioneuronal tumors. Using the cell type proportion data as input, we used dimension reduction (UMAP) to visualize sample-wise patterns of that emerge from the cell type proportion estimations. In glioblastomas (n= 2076) we identified distinct tumor clusters based on immune cell proportion and, interestingly, TME-based cluster groups demonstrated an association with specific genetic alterations such as EGFR amplification and/or CDKN2A/B homozygous deletion. Among 1178 IDH-mutant gliomas, clustering of tumors according to immune cell proportions led to 2 major subgroups, which largely aligned with 1p/19q co-deletion status. Among the non-codeleted tumors (IDH-mutant astrocytomas, N=734), clustering of immune cell decomposition revealed clusters which showed distinct proportions of a key genomic aberration in these tumors (CDKN2A/B loss). To investigate the possible role of monocyte proportion-relative gene expression and promoter methylation of the immune checkpoint PD-L1 and PD-L2 genes, we used a data subset (n=594) samples with matched gene expression profiles. We observed significantly high positive correlations (R=0.54 and 0.68, respectively) between monocyte proportion and expression of PD-L1 and PD-L2, in line with prior reports that monocytic cells can express these immune markers. Consistent with this, we found high negative correlations (R= -0.51 and -0.61, respectively) between monocytes and promoter methylation of PD-L1 and PD-L2, respectively. Overall, the findings highlight specific roles of the TME in biology and classification of adult CNS tumors, where specific immune cell admixtures correlate with tumor types and genomic aberrations.

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