A monoclonal antibody targeting melanoma-associated chondroitin sulfate proteoglycan demonstrates antitumor activity in human melanoma, ovarian and breast cancer models.
Bibliographic record
Abstract
B40 Melanoma-associated chondroitin sulfate proteoglycan (MCSP) is a glycoprotein-proteoglycan complex present on the surface of melanoma cells, and has been reported to have a role in cancer progression by enhancing adhesion and invasion of melanoma cells through multiple mechanisms. MCSP, also known as the high molecular weight-melanoma associated antigen (HMW-MAA), has been shown recently to be expressed in human breast cancer stem cells. AR11BD-2E11-2, a monoclonal antibody that targets MCSP was discovered using the FunctionFIRST™ platform. Briefly, human breast cancer tissue was used to immunize mice and hybridomas were screened for cytotoxicity against a variety of cancer cell lines. For example, AR11BD-2E11-2 showed cytotoxicity in breast and ovarian cancer cell lines. When AR11BD-2E11-2 was evaluated in vivo, anti-tumor activity was apparent not only in breast and ovarian tumor models, but in a model of human melanoma as well. In the MCF-7 xenograft breast cancer model, AR11BD-2E11-2 was shown to significantly reduce tumor volume by 79% compared to isotype control treated mice (p=0.048), as well as confer a significant survival benefit (p=0.03). A 49% (p=0.0004) reduction in tumor volume was also observed in a second breast cancer xenograft model MDA-MB-231. In an OVCAR-3 xenograft ovarian cancer model, the increase in body weight due to ascites can be used as a marker of disease progression. In this model, the mice in the control treated group showed a 60% tumor-related weight gain, while the AR11BD-2E11-2 treated mice showed a significantly lower weight gain of 40% (p=0.03) corresponding to decreased ascites formation, as well as having a significantly longer mean survival time (p
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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".