A comprehensive genome‐wide analysis of melanoma Breslow thickness identifies interaction between <i>CDC42</i> and <i>SCIN</i> genetic variants
Bibliographic record
Abstract
Breslow thickness (BT) is a major prognostic factor of cutaneous melanoma (CM), the most fatal skin cancer. The genetic component of BT has only been explored by candidate gene studies with inconsistent results. Our objective was to uncover the genetic factors underlying BT using an hypothesis-free genome-wide approach. Our analysis strategy integrated a genome-wide association study (GWAS) of single nucleotide polymorphisms (SNPs) for BT followed by pathway analysis of GWAS outcomes using the gene-set enrichment analysis (GSEA) method and epistasis analysis within BT-associated pathways. This strategy was applied to two large CM datasets with Hapmap3-imputed SNP data: the French MELARISK study for discovery (966 cases) and the MD Anderson Cancer Center study (1,546 cases) for replication. While no marginal effect of individual SNPs was revealed through GWAS, three pathways, defined by gene ontology (GO) categories were significantly enriched in genes associated with BT (false discovery rate ≤5% in both studies): hormone activity, cytokine activity and myeloid cell differentiation. Epistasis analysis, within each significant GO, identified a statistically significant interaction between CDC42 and SCIN SNPs (pmeta-int =2.2 × 10(-6) , which met the overall multiple-testing corrected threshold of 2.5 × 10(-6) ). These two SNPs (and proxies) are strongly associated with CDC42 and SCIN gene expression levels and map to regulatory elements in skin cells. This interaction has important biological relevance since CDC42 and SCIN proteins have opposite effects in actin cytoskeleton organization and dynamics, a key mechanism underlying melanoma cell migration and invasion.
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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 | 0.000 | 0.000 |
| 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) | 0.000 | 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".