Calpain as a therapeutic target in cancer
Bibliographic record
Abstract
INTRODUCTION: Calpain-1 and calpain-2 are prototypical classical isoforms of the calpain family of calcium-activated cysteine proteases. Their substrate proteins participate in a wide range of cellular processes, including transcription, survival, proliferation, apoptosis, migration, and invasion. Dysregulated calpain activity has been implicated in tumorigenesis, suggesting that calpains may be promising therapeutic targets. AREAS COVERED: This review covers clinical and basic research studies implicating calpain-1 and calpain-2 expression and activity in tumorigenesis and metastasis. We highlight isoform specific functions and provide an overview of substrates and cancer-related signalling pathways affected by calpain-mediated proteolytic cleavage. We also discuss efforts to develop clinically relevant calpain specific inhibitors and spotlight the challenges facing inhibitor development. EXPERT OPINION: Rationale for targeting calpain-1 and calpain-2 in cancer is supported by pre-clinical and clinical studies demonstrating that calpain inhibition has the potential to attenuate carcinogenesis and block metastasis of aggressive tumors. The wide range of substrates and cleavage products, paired with inconsistencies in model systems, underscores the need for more complete understanding of physiological substrates and how calpain cleavage alters their functions in cellular processes. The development of isoform specific calpain inhibitors remains an important goal with therapeutic potential in cancer and other diseases.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".