Transcriptomic and Proteomic Spatial Profiling of Pediatric and Adult Diffuse Midline Glioma H3 K27-Altered, Reveals Region Specific Differences and Limited Overlap between mRNA and Protein

TL;DR

This study compares gene and protein activity in brain tumors of children and adults, finding age-related differences and limited match between RNA and protein levels.

Contribution

The study reveals region-specific transcriptomic and proteomic differences in H3 K27-altered gliomas and highlights limited mRNA-protein correlation.

Findings

Genetic alterations in H3 K27M tumors vary by patient age and spatial location.

The H3 K27M mutation significantly affects tumor cell transcriptomics.

Transcriptomic and proteomic profiles show limited overlap in tumor samples.

Abstract

Diffuse midline glioma, H3 K27-altered (DMG-Alt) are highly aggressive malignancies of the central nervous system (CNS) that primarily affect the pediatric population. Large scale spatial transcriptomic studies have implicated that tumor microenvironmental landscape plays an important role in determining the phenotypic differences in tumor presentation and clinical course, however, data connecting overall transcriptomic changes to the protein level is lacking.

The NanoString GeoMx™ Digital Spatial Profiler platform was used to determine the spatial transcriptomic and proteomic landscape in a cohort of both pediatric and adult H3 K27-altered DMG biopsy samples. Three fluorescently labeled antibodies targeting immune cells (CD45), epithelial cells (PanCK), tumor cells (H3 K27M) and a nucleic acid stain (SYTO-13) were used to establish regions of interest (ROI) for genomic and proteomic analysis.

We found genetic alterations within the tumor which can be delineated across patient age and spatial location. We show that the H3 K27M mutation itself has a profound impact on tumor cells transcriptomics and interestingly we found limited fidelity between overall transcriptome and proteome. Our data also validate the previously described OPC like precursor signature at the proteomic level and reveal a special shift in the signature based on the local TME composition.

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