Chondroitin sulfate proteoglycan 4, a targetable oncoantigen that promotes ovarian cancer growth, invasion, cisplatin resistance and spheroid formation
Bibliographic record
Abstract
Epithelial ovarian cancer (EOC) is a highly heterogeneous disease encompassing several distinct molecular subtypes and clinical entities. Despite the initial success of surgical debulking and adjuvant chemotherapy, recurrence with chemotherapy resistant tumors is common in patients with EOC and leads to poor overall survival. The extensive genetic and phenotypic heterogeneity associated with ovarian cancers has hindered the identification of effective prognostic and predictive biomarkers in EOC patients. In the current studies, we identify a tumor cell surface oncoantigen, chondroitin sulfate proteoglycan 4 (CSPG4), as an independent risk factor for decreased survival of patients with EOC. Our results show that CSPG4 promotes EOC cell invasion, cisplatin resistance and spheroid formation in vitro and tumor expansion in vivo. Mechanistically, spheroid formation and tumor cell invasion are due to CSPG4-stimulated expression of the mesenchymal transcription factor ZEB1. Furthermore, we have developed a novel monoclonal anti-CSGP4 antibody against the juxtamembrane domain of the core protein that limits CSPG4-stimulated ZEB1 expression, tumor cell invasion and promotes EOC apoptosis within spheroid cultures. We therefore propose that CSPG4 expression drives phenotypic heterogeneity and malignant progression in EOC tumors. These studies further demonstrate that CSPG4 expression levels are a potential diagnostic biomarker in EOC and indicate that targeting cells which express this oncoantigen could limit recurrence and improve outcomes in patients with EOC.
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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) | 0.000 | 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 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".