Elucidating Isoform Specific Roles of Calpain-1 and Calpain-2 in Breast Cancer
Bibliographic record
Abstract
Breast cancer is the most frequently diagnosed women’s cancer in Canada. Average patient survival rates are high, but they are significantly reduced for those patients whose cancer reaches stage IV – metastatic disease. This study investigated the roles of calpain-1 and calpain-2 in metastatic breast cancer. Genetic knockout of CAPN1, CAPN2, and CAPNS1 genes allowed us to analyze the functions of these two calpain isoforms in the MDA-MB-231 triple negative breast cancer model cell line and to determine which isoform is responsible for the CAPNS1-knockdown related cancer cell phenotypes seen previously. We used the panel of knockout and rescue cell lines for in vitro studies and showed that both calpain isoforms play roles in protective effects against select chemotherapeutics, suggesting that calpain inhibition could enhance the efficacy of these commonly used breast cancer therapeutics. We also showed that genetic disruption of calpain-1 reduces the in vitro cell migration rate on collagen substrates. Our in vivo studies provide evidence that calpain-1 and calpain-2 have essential non-redundant roles in the metastatic process, suggesting that inhibition of either isoform could have therapeutic benefits by reducing the metastatic potential of breast cancer. I also discuss future studies aimed at identification and characterization of calpain-1 and calpain-2 specific physiological substrates with mechanistic relevance to the observed phenotypes and describe a biosensor to screen for allosteric inhibitors of calpain-1 and calpain-2.
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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 | 0.001 |
| 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".