The TH1902 Docetaxel Peptide-Drug Conjugate Inhibits Xenografts Growth of Human SORT1-Positive Ovarian and Triple-Negative Breast Cancer Stem-like Cells
Bibliographic record
Abstract
Background: Breast and ovarian cancer stem cells (CSC) can contribute to the invasive and chemoresistance phenotype of tumors. TH1902, a newly developed sortilin (SORT1)-targeted peptide-docetaxel conjugate is currently in phase-1 clinical trial. Whether TH1902 impacts the chemoresistance phenotype of human triple-negative breast CSC (hTNBCSC) and ovarian CSC (hOvCSC) is unknown. Methods and Results: Immunophenotyping of hTNBCSC and hOvCSC was performed by flow cytometry and confirmed the expression of SORT1, and of CSC markers CD133, NANOG, and SOX2. Western blotting demonstrated the expression of the drug efflux pumps from the P-gp family members, ABCB1 and ABCB5. The cellular uptake of the fluorescent Alexa488-peptide from TH1902 was inhibited upon siRNA-mediated repression of SORT1 or upon competition with SORT1 ligands. In contrast to docetaxel, TH1902 inhibited in vitro migration, induced cell apoptosis and lead to G2/M cell cycle arrest of the hTNBCSC. These events were unaffected by the presence of the P-gp inhibitors cyclosporine A or PSC-833. In vivo, using immunosuppressed nude mice xenografts, TH1902 significantly inhibited the growth of hTNBCSC and hOvCSC xenografts (~80% vs. ~35% for docetaxel) when administered weekly as intravenous bolus for three cycles at 15 mg/kg, a dose equivalent to the maximal tolerated dose of docetaxel. Therapeutic efficacy was further observed when carboplatin was combined to TH1902. Conclusions: Overall, TH1902 exerts a superior anticancer activity than the unconjugated docetaxel, in part, by circumventing the CSC drug resistance phenotype that could potentially reduce cancer recurrence attributable to CSC.
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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 | 0.000 |
| 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".