A prognostic matrix code defines functional glioblastoma phenotypes and niches.
Anil KorkutMonika VishnoiZeynep DereliZheng YinElisabeth KongMeric KinaliKisan ThapaOzgun BaburKyuson YunNourhan AbdelfattahXubin LiBehnaz BozorguiRobert C RostomilyPublished in: Research square (2023)
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, we characterize functional and clinical relevance of genes encoding CMPs in GBM at bulk, single cell, and spatial anatomical resolution. We identify a "matrix code" for genes encoding CMPs whose expression levels categorize GBM tumors into matrisome-high and matrisome-low groups that correlate with worse and better patient survival, respectively. The matrisome enrichment is associated with 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 anatomic structures that are known to harbor glioma stem cells driving GBM progression. Finally, we identified a 17-gene matrisome signature that retains and further refines the prognostic value of genes encoding CMPs and, importantly, potentially predicts responses to PD1 blockade in clinical trials for GBM. The matrisome gene expression profiles provide potential biomarkers of functionally relevant GBM niches that contribute to mesenchymal-immune cross talk and patient stratification which could be applied to optimize treatment responses.
Keyphrases
- single cell
- gene expression
- genome wide
- stem cells
- genome wide identification
- dna methylation
- rna seq
- clinical trial
- bone marrow
- copy number
- case report
- high throughput
- poor prognosis
- bioinformatics analysis
- transcription factor
- randomized controlled trial
- long non coding rna
- anti inflammatory
- study protocol
- double blind