TMIC-82. SPATIAL AND SINGLE-CELL PROTEOMIC LANDSCAPING OF THE HYPOXIC MICROENVIRONMENT IN GLIOBLASTOMA
Bibliographic record
Abstract
Abstract Glioblastoma (GBM) is a fatal adult solid tumour with median overall survival of 18-20 months post-diagnosis; contributing factors to therapeutic inefficacy include acquisition of genomic alterations post-therapy, immune evasion, deregulated hypervascularization, and tumor microenvironmental factors such as hypoxia. Combined with extensive inter- and intra-tumoral heterogeneity at bulk and single-cell level, hypoxia contributes to a gradient of molecular alterations that are specific to different cell populations that make up tumour bulk and reside in specific niches. Hitherto, high-dimensional histopathologic analyses of hypoxic regions within GBM tissue have not been performed. We took a combined spatial and single-cell proteomic profiling approach to investigate the histopathologic features of hypoxia by leveraging a unique clinical study wherein the exogenous hypoxia marker, pimonidazole (PIMO), was administered to GBM-patients preoperatively. Tissue specimens were subjected to imaging mass cytometry, high-resolution imaging, and serial immunohistochemistry using a panel of markers associated with cellular hallmarks of hypoxia, metabolism, proliferation, stemness, angiogenesis, and immune cell types. Our findings showed that PIMO staining is associated with histopathologic features of hypoxia and correlates with specific metabolic, immune, and stemness markers in GBM; specific lymphocyte populations were depleted from hypoxic regions alongside alterations in macrophagic and microglial landscape in a niche-specific manner; hypoxia reduced the proportion of proliferating glioma initiating cells and altered the proliferative, transcriptional, and translational capacity of different cell populations; microvessel density was reduced in hypoxic microenvironment. Cytometry by time-of-flight further validated the altered proportions of specific immune cell types enriched in hypoxic populations of GBM microenvironment. Our study is the first to report use of PIMO to interrogate spatial, single-cell, and phenotypic architecture associated with tissue hypoxia and altered expression of biomarkers associated with hypoxia/glycolysis, immune infiltration, proliferation, and stemness. Identification of targetable biomarkers and mediators of hypoxia-driven habitats in GBM may provide direction for future immunotherapeutic research.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".