Co-vulnerabilities of inhibiting carbonic anhydrase IX in ferroptosis-mediated tumor cell death
Bibliographic record
Abstract
The tumour-associated carbonic anhydrases (CA) IX and XII are upregulated by cancer cells to combat cellular and metabolic stress imparted by hypoxia and acidosis in solid tumours. Owing to its tumour-specific expression and function, CAIX is an attractive therapeutic target and this has driven intense efforts to develop pharmacologic agents to target its activity, including small molecule inhibitors. Many studies in multiple solid tumour models have demonstrated that targeting CAIX activity with the selective CAIX/XII inhibitor, SLC-0111, results in anti-tumour efficacy, particularly when used in combination with chemotherapy or immune checkpoint blockade, and has now advanced to the clinic. However, it has been observed that sustainability and durability of CAIX inhibition, even in combination with chemotherapy agents, is limited by the occurrence of adaptive resistance, resulting in tumour recurrence. Importantly, the data from these models demonstrates that CAIX inhibition may sensitize tumour cells to cytotoxic drugs and evidence now points to ferroptosis, an iron-dependent form of regulated cell death (RCD) that results from accumulation of toxic levels of phospholipid peroxidation as a major mechanism involved in CAIX-mediated sensitization to cancer therapy. In this mini-review, we discuss recent advances demonstrating the mechanistic role CAIX plays in sensitizing cancer cells to ferroptosis.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".