Profiling the effects of carbonic anhydrase 9/12 inhibition on tumor associated macrophage/microglia polarization in glioma
Bibliographic record
Abstract
Abstract Brain tumor microenvironments, including hypoxia and acidic stress, contain a subset of stem-like neoplastic cells termed brain tumor initiating cells (BTICs) that are resistant to chemo- and radiotherapy, providing a reservoir for tumor recurrence and a desirable target for glioma treatments. In prior studies, we have shown that inhibition of carbonic anhydrases 9 and 12 (CA9/12) in combination with chemotherapeutic temozolomide effectively delayed in vivo growth in a BTIC xenograft model. CA9/12 are hypoxia-responsive genes shown to be elevated in tumors that modulate the intra- and extracellular pH in tumor microenvironments. Importantly, downstream effects of hypoxia have shown CSF-1R induction, which can polarize tumor associated macrophages/microglia (TAM) toward an immunosuppressive phenotype and further exacerbate tumor progression. We have profiled CA9/12 inhibitor-treated GBM tumors using integrative omics (kinomics/transcriptomics) and discovered a shift in kinomic activity and gene expression that suggests an immunosuppressive transition in TAMs. Validating this observation, we characterized surface expression of CD11b+ TAMs post-treatment and discovered decreased expression of MHCII (inflammatory) and increased expression of CD206 (immunosuppressive). Together, our data suggest that by understanding the immunophenotypic shift that happens in response to CA9/12 inhibition in glioma, we may be able design a treatment strategy to improve upon the effectiveness of inhibitor therapy.
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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".