Determinants of sensitivity to lovastatin-induced apoptosis in multiple myeloma
Bibliographic record
Abstract
Statins, commonly used to treat hypercholesterolemia, have been shown to trigger tumor-specific apoptosis in certain cancers, including multiple myeloma (MM), a plasma cell malignancy with poor prognosis. In this article, we show that of a panel of 17 genetically distinct MM cell lines, half were sensitive to statin-induced apoptosis and, despite pharmacodynamic evidence of drug uptake and activity, the remainder were insensitive. Sensitive cells were rescued from lovastatin-induced apoptosis by mevalonate, geranylgeranyl PPi, and partially by farnesyl PPi, highlighting the importance of isoprenylation. Expression profiling revealed that Rho GTPase mRNAs were differentially expressed upon lovastatin exposure in sensitive cells, yet ectopic expression of constitutively active Rho or Ras proteins was insufficient to alter sensitivity to lovastatin-induced apoptosis. This suggests that sensitivity involves more than one isoprenylated protein and that statins trigger apoptosis by blocking many signaling cascades, directly or indirectly deregulated by the oncogenic lesions of the tumor cell. Indeed, clustering on the basis of genetic abnormalities was shown to be significantly associated with sensitivity (P = 0.003). These results suggest that statins may be a useful molecular targeted therapy in the treatment of a subset of MM.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".