Cell line and patient-derived xenograft models reveal elevated CDCP1 as a target in high-grade serous ovarian cancer
Bibliographic record
Abstract
BACKGROUND: Development of targeted therapies for high-grade serous ovarian cancer (HGSC) remains challenging, as contributing molecular pathways are poorly defined or expressed heterogeneously. CUB-domain containing protein 1 (CDCP1) is a cell-surface protein elevated in lung, colorectal, pancreas, renal and clear cell ovarian cancer. METHODS: CUB-domain containing protein 1 was examined by immunohistochemistry in HGSC and fallopian tube. The impact of targeting CDCP1 on cell growth and migration in vitro, and intraperitoneal xenograft growth in mice was examined. Three patient-derived xenograft (PDX) mouse models were developed and characterised for CDCP1 expression. The effect of a monoclonal anti-CDCP1 antibody on PDX growth was examined. Src activation was assessed by western blot analysis. RESULTS: Elevated CDCP1 was observed in 77% of HGSC cases. Silencing of CDCP1 reduced migration and non-adherent cell growth in vitro and tumour burden in vivo. Expression of CDCP1 in patient samples was maintained in PDX models. Antibody blockade of CDCP1 significantly reduced growth of an HGSC PDX. The CDCP1-mediated activation of Src was observed in cultured cells and mouse xenografts. CONCLUSIONS: CUB-domain containing protein 1 is over-expressed by the majority of HGSCs. In vitro and mouse model data indicate that CDCP1 has a role in HGSC and that it can be targeted to inhibit progression of this cancer.
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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) | 0.002 | 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".