Development of a small anti‐cancer molecule targeting both the intrinsic and extrinsic pathways of apoptosis
Bibliographic record
Abstract
Our chemical genetic screen for small molecules that increase lifespan in yeast cellular models of aging by targeting mitochondria‐controlled apoptosis identified lithocholic acid (LCA) as one of such molecules. Aging is one of the major risk factors of cancer, an age‐related disease whose onset can be delayed and incidence reduced by certain pharmacological antiaging interventions. We therefore sought to examine if LCA exhibits an anti‐tumor effect in cultured human cancer cells by activating certain anti‐cancer processes that may play an essential role in cellular aging. We found that LCA, at concentrations that are not cytotoxic to primary cultures of human neurons, kills the neuroblastoma (NB) cell lines BE(2)‐m17, SK‐n‐SH, SK‐n‐ MCIXC and Lan‐1. In the case of BE(2)‐m17, SK‐n‐SH and SK‐n‐ MCIXC cells, the LCA anti‐tumor effect is due to apoptotic cell death. In contrast, the LCA‐triggered death of Lan‐1 cells is not caused by apoptosis. Our findings imply that LCA kills BE(2)‐m17 and SK‐n‐MCIXC cell lines by triggering not only the intrinsic (mitochondrial) apoptotic cell death pathway driven by mitochondrial outer membrane permeabilization and initiator caspase‐9 activation, but also the extrinsic (death receptor) pathway of apoptosis involving activation of the initiator caspase‐ 8. Our data suggest a molecular mechanism underlying a potent and selective anti‐tumor effect of LCA in cultured human NB cells. Importantly, we found that a similar mechanism underlies a broad anti‐tumor effect of LCA in cultured mammalian cancer cells derived from different tissues and organisms. Supported by NSERC of Canada.
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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".