Identification of repurposed small molecule drugs for chordoma therapy
Why this work is in the frame
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Bibliographic record
Abstract
Chordoma is a rare, slow growing malignant tumor arising from remnants of the fetal notochord. Surgery is the first choice for chordoma treatment, followed by radiotherapy, although postoperative complications remain significant. Recurrence of the disease occurs frequently due to the anatomy of the tumor location and violation of the tumor margins at the initial surgery. Currently, there are no effective drugs available for patients with chordoma. Due to the rarity of the disease, there is limited opportunity to test agents in clinical trials and no concerted effort to develop agents for chordoma in the pharmaceutical industry. To rapidly and efficiently identify small molecules that inhibit chordoma cell growth, we screened the NCGC Pharmaceutical Collection (NPC) containing approximately 2800 clinically approved and investigational drugs at 15 different concentrations in chordoma cell lines, U-CH1 and U-CH2. We identified a group of drugs including bortezomib, 17-AAG, digitoxin, staurosporine, digoxin, rubitecan, and trimetrexate that inhibited chordoma cell growth, with potencies from 10 to 370 nM in U-CH1 cells, but less potently in U-CH2 cells. Most of these drugs also induced caspase 3/7 activity with a similar rank order as the cytotoxic effect on U-CH1 cells. Cantharidin, digoxin, digitoxin, staurosporine, and bortezomib showed similar inhibitory effect on cell lines and 3 primary chordoma cell cultures. The combination treatment of bortezomib with topoisomerase I and II inhibitors increased the therapeutic potency in U-CH2 and patient-derived primary cultures. Our results provide information useful for repurposing currently approved drugs for chordoma and potential approach of combination therapy.
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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 it