# A prognostic matrix gene expression signature defines functional glioblastoma phenotypes and niches

## TL;DR

This study identifies a gene expression signature linked to glioblastoma survival and immune interactions, offering a new way to classify and treat the disease.

## Contribution

A novel 17-gene matrisome signature is introduced for GBM prognosis and treatment prediction.

## Key findings

- CMP expression levels divide GBM tumors into M-H and M-L groups with distinct survival outcomes.
- Matrisome gene expression is enriched in vascular and infiltrative niches linked to glioma stem cells.
- The M17 signature outperforms existing biomarkers in predicting survival and PD1 blockade response.

## Abstract

Interactions among tumor, immune, and vascular niches play major roles in driving glioblastoma (GBM) malignancy and treatment responses. The composition, heterogeneity, and localization of extracellular core matrix proteins (CMPs) that mediate such interactions, however, are not well understood.

Here, through computational genomics and proteomics approaches, we analyzed the functional and clinical relevance of CMP expression in GBM at bulk, single cell, and spatial anatomical resolution.

We identified genes encoding CMPs whose expression levels categorize GBM tumors into CMP expression-high (M-H) and CMP expression-low (M-L) groups. CMP enrichment is associated with worse patient survival, specific driver oncogenic alterations, mesenchymal state, infiltration of pro-tumor immune cells, and immune checkpoint gene expression. Anatomical and single-cell transcriptome analyses indicate that matrisome gene expression is enriched in vascular and leading edge/infiltrative niches that are known to harbor glioma stem cells driving GBM progression. Finally, we identified a 17-gene CMP expression signature, termed Matrisome 17 (M17) signature that further refines the prognostic value of CMP genes. The M17 signature is a significantly stronger prognostic factor compared to MGMT promoter methylation status as well as canonical subtypes, and importantly, potentially predicts responses to PD1 blockade.

The matrisome gene expression signature provides a robust stratification of GBM patients by survival and potential biomarkers of functionally relevant GBM niches that can mediate mesenchymal-immune cross talk. Patient stratification based on matrisome profiles can contribute to selection and optimization of treatment strategies.