ARH460–16-2: a therapeutic monoclonal antibody targeting CD44 in Her2/neu negative breast cancer
Bibliographic record
Abstract
2622 Background: ARH460–16-2 is a potent anti-CD44 antibody that has been shown to suppress and delay tumor growth and increase survival in a xenograft model of Her2/neu-negative breast cancer. CD44, a cancer-related membrane glycoprotein, is believed to play a critical role in cellular adhesion, migration, invasion and tumorigenicity. Current results describe the prevalence of this epitope in a survey of cancer tissues. Methods: Distribution of the ARH460–16-2 CD44 epitope in breast cancer was determined by the immunohistochemistry of breast cancer sections from 50 individual patients in an array format. Prevalence of the antigen in a range of human cancers was determined by immunohistochemistry of multiple tumors in an array format. Samples were scored according staining intensity, tissue specificity, cellular localization, and section score. Results: Overall, 62% of breast cancer patient samples tested were positive for ARH460–16-2 antigen, while only 4/10 normal breast tissue samples from those patients were positive. Expression of ARH460–16-2 within patient samples appeared specific for cancer cells as staining was restricted to malignant cells. There was no correlation of the ARH460–16-2 binding to the estrogen or progesterone receptor status of the patient. 62% of the sections that were negative for Her2/neu were positive for ARH460–16-2. 23% of sections expressed both the ARH460–16-2 antigen and Her2/neu, suggesting potential for additive therapeutic effects through independent mechanisms of action. To examine the potential therapeutic benefits of ARH460–16-2, the frequency and localization of the antigen within various human cancer tissues was determined. The majority of tumor types including skin, lung, liver, stomach and kidney, in addition to breast cancer, expressed the ARH460–16-2 antigen. Conclusions: CD44, the antigen recognized by the therapeutic antibody ARH460–16-2, is widely distributed in human cancers. In particular, this epitope is present in samples from breast cancer patients that are negative for Her2/neu, and thus may be a target for antibody therapy to provide options for this group of breast cancer patients. Author Disclosure Employment or Leadership Consultant or Advisory Stock Ownership Honoraria Research Funding Expert Testimony Other Remuneration ARIUS Research, Inc. ARIUS Research, Inc. ARIUS Research, Inc.
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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) | 0.003 | 0.001 |
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".