Immunohistochemical markers of advanced basal cell carcinoma: CD56 is associated with a lack of response to vismodegib
Bibliographic record
Abstract
Vismodegib is an effective treatment for advanced basal cell carcinoma (BCC), but primary resistance to vismodegib remains to be elucidated. Alternative approaches are warranted to help selecting patients most likely to be responsive to treatment. The identification of immunohistochemical markers may support this perspective, as well as better understanding of resistance mechanisms. To determine the level of expression of CD56, PDGF-R, CD117, MMP9, TIMP3, and CXCR4 in advanced BCC, and explore whether expression levels are associated with non-response to vismodegib. A cross-sectional study was conducted. Immunohistochemical markers were selected based on their roles in tumour proliferation and/or migration in skin tumours. Tissue samples included pretreatment advanced BCC samples from patients treated with vismodegib, with an available response after six months of treatment. Regression optimised models were used to build hypotheses regarding a possible association between expression levels and non-response to vismodegib, which was then tested by logistic regression. Twenty-three patients were included. The percentage of samples expressing markers ranged from 43.5% (CD117) to 91.3% (CXCR4). CD56 expression was significantly associated with an increased risk of non-response to vismodegib (OR = 5.5; CI 95%: 3.4-29.8; p = 0.0488); a similar association was suggested for CXCR4 (p = 0.066), but not identified for other markers. These results provide a better understanding of the expression of immunohistochemical markers in advanced BCC. Further detailed analysis of CD56 expression may provide insights into guiding further investigation of the correlation between this marker and non-response to vismodegib.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".