Shedding of Distinct Cryptic Collagen Epitope (HU177) in Sera of Melanoma Patients
Bibliographic record
Abstract
PURPOSE: Extracellular matrix remodeling during tumor growth plays an important role in angiogenesis. Our preclinical data suggest that a newly identified cryptic epitope (HU177) within collagen type IV regulates endothelial and melanoma cell adhesion in vitro and angiogenesis in vivo. In this study, we investigated the clinical relevance of HUI77 shedding in melanoma patient sera. EXPERIMENTAL DESIGN: Serum samples from 291 melanoma patients prospectively enrolled at the New York University Medical Center and 106 control subjects were analyzed for HU177 epitope concentration by a newly developed sandwich ELISA assay. HU177 serum levels were then correlated with clinical and pathologic parameters. RESULTS: Mean HU177 epitope concentration was 5.8 ng/mL (range, 0-139.8 ng/mL). A significant correlation was observed between HU177 concentration and nodular melanoma histologic subtype [nodular, 10.3 +/- 1.6 ng/mL (mean +/- SE); superficial spreading melanoma, 4.5 +/- 1.1 ng/mL; all others, 6.1 +/- 2.1 ng/mL; P = 0.01 by ANOVA test]. Increased HU177 shedding also correlated with tumor thickness (< or =1.00 mm, 3.8 +/- 1.1 ng/mL; 1.01-3.99 mm, 8.7 +/- 1.3 ng/mL; > or =4.00 mm, 10.3 +/- 2.4 ng/mL; P = 0.003 by ANOVA). After multivariate analysis controlling for thickness, the correlation between higher HU177 concentration and nodular subtype remained significant (P = 0.03). The mean HU177 epitope concentration in control subjects was 2.4 ng/mL. CONCLUSIONS: We report that primary melanoma can induce detectable changes in systemic levels of cryptic epitope shedding. Our data also support that nodular melanoma might be biologically distinct compared with superficial spreading type melanoma. As targeted interventions against cryptic collagen epitopes are currently undergoing phase I clinical trial testing, these findings indicate that patients with nodular melanoma may be more susceptible to such targeted therapies.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| 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 teacher head, 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".