Antiproliferative, antiangiogenic and proapoptotic activity of h‐R3: A humanized anti‐EGFR antibody
Bibliographic record
Abstract
The epidermal growth factor receptor (EGFR) proto-oncogene is frequently overexpressed in tumors of epithelial origin. This event is thought to be causative for tumor development and progression and henceforth associated with poor prognosis. The recent considerable interest in developing EGFR-targeting agents resulted in derivation of the monoclonal, humanized, neutralizing antibody h-R3, which binds to the extracellular domain of EGFR with high affinity and strongly inhibits EGFR-dependent cellular transformation. Thus, treatment of A431 squamous cell carcinoma cells with h-R3 in either 2-dimensional or 3-dimensional culture resulted in appreciable antimitotic effects through induction of the G1 arrest. Although h-R3 does not appear to have a direct proapoptotic activity in this setting, it inhibits production of the vascular endothelial growth factor (VEGF) by A431 cells both in vitro and in vivo. In the latter case, h-R3 treatment (0.25-1 mg/mouse; every other day per 2 weeks) not only significantly reduced VEGF mRNA expression of A431 tumors growing subcutaneously in SCID mice but also resulted in reduction of the overall microvascular density (MVD), disappearance of dilated "mother vessels," as well as in suppression of tumor growth followed by regression of established tumors. This apparent antiangiogenic activity of h-R3 was associated with reduction in Ki67-positive tumor cell fraction and (unlike in vitro) also with an elevated apoptotic index, the latter indicative of a cytotoxic mode of action in vivo. Taken together, h-R3 is a promising new antagonist of the EGFR oncogene, the anticancer properties of which are associated with combined and potent antiproliferative, antiangiogenic and proapoptotic activity.
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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) | 0.001 | 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".