Effects of HIV Protease Inhibitor Ritonavir on Akt-Regulated Cell Proliferation in Breast Cancer
Bibliographic record
Abstract
PURPOSE: These studies were designed to determine whether ritonavir inhibits breast cancer in vitro and in vivo and, if so, how. EXPERIMENTAL DESIGN: Ritonavir effects on breast cancer cell growth were studied in the estrogen receptor (ER)-positive lines MCF7 and T47D and in the ER-negative lines MDA-MB-436 and MDA-MB-231. Effects of ritonavir on Rb-regulated and Akt-mediated cell proliferation were studied. Ritonavir was tested for inhibition of a mammary carcinoma xenograft. RESULTS: ER-positive estradiol-dependent lines (IC50, 12-24 micromol/L) and ER-negative (IC50, 45 micromol/L) lines exhibit ritonavir sensitivity. Ritonavir depletes ER-alpha levels notably in ER-positive lines. Ritonavir causes G1 arrest, depletes cyclin-dependent kinases 2, 4, and 6 and cyclin D1 but not cyclin E, and depletes phosphorylated Rb and Ser473 Akt. Ritonavir induces apoptosis independent of G1 arrest, inhibiting growth of cells that have passed the G1 checkpoint. Myristoyl-Akt, but not activated K-Ras, rescues ritonavir inhibition. Ritonavir inhibited a MDA-MB-231 xenograft and intratumoral Akt activity at a clinically attainable serum Cmax of 22 +/- 8 micromol/L. Because heat shock protein 90 (Hsp90) substrates are depleted by ritonavir, ritonavir effects on Hsp90 were tested. Ritonavir binds Hsp90 (K(D), 7.8 micromol/L) and partially inhibits its chaperone function. Ritonavir blocks association of Hsp90 with Akt and, with sustained exposure, notably depletes Hsp90. Stably expressed Hsp90alpha short hairpin RNA also depletes Hsp90, inhibiting proliferation and sensitizing breast cancer cells to low ritonavir concentrations. CONCLUSIONS: Ritonavir inhibits breast cancer growth in part by inhibiting Hsp90 substrates, including Akt. Ritonavir may be of interest for breast cancer therapeutics and its efficacy may be increased by sustained exposure or Hsp90 RNA interference.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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".