Targeting N-Cadherin Enhances Antitumor Activity of Cytotoxic Therapies in Melanoma Treatment
Bibliographic record
Abstract
Malignant transformation in melanoma is characterized by a phenotype "switch" from E- to N-cadherin, which is associated with increased motility and invasiveness of the tumor and altered signaling, leading to decreased apoptosis. We hypothesized that the novel pentapeptide (ADH-1), which disrupts N-cadherin adhesion, could sensitize melanoma tumors to the cytotoxic effects of chemotherapy. N-cadherin-expressing human melanoma-derived cell lines were used to generate xenografts in animal models to study isolated limb infusion with melphalan and systemic chemotherapy with temozolomide. We report here that melphalan in combination with ADH-1 significantly reduced tumor growth up to 30-fold over melphalan alone. ADH-1 enhancement of response to melphalan was associated with increased formation of DNA adducts, increased apoptosis, and intracellular signaling changes associated with focal adhesions and fibroblast growth factor receptors. Targeted therapy using an N-cadherin antagonist can dramatically augment the antitumor effects of chemotherapy and is a novel approach to optimizing treatment for melanoma.
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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) | 0.001 | 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".