Comprehensive genomic profiling reveals distinct patterns of driver mutations and chromosomal alterations in acral and mucosal melanomas.
Bibliographic record
Abstract
9576 Background: The incidence of melanoma subtypes differs significantly among ethnicities. Ultraviolet (UV) radiation-driven melanomas are common in Caucasians, while non-cutaneous melanomas including acral and mucosal melanomas are more frequent in Asians. It will be of great interest and clinical relevance to decipher the molecular pathogenesis of different melanoma subtypes. Methods: We retrospectively studied a cohort of 89 Chinese melanoma patients who underwent surgical resection of their primary tumors followed by chemotherapy. Genomic profiling of primary melanomas was performed using next generation sequencing by targeting 422 cancer-relevant genes. The Kaplan-Meier method and logrank test were used for survival analysis, and a cox model was used for multivariate survival analysis. Results: Acral melanomas (54/89, 60%) were the most common subtype of this cohort, while cutaneous and mucosal subtypes accounted for 25% and 15%, respectively. Mutation profiling revealed that BRAF was most frequently mutated in cutaneous melanomas, but aberrant BRAF, RAS, KIT, and NF1 were almost evenly represented in acral and mucosal melanomas; of note, mucosal melanomas had a propensity for concurrent driver mutations. Chromosomal alterations were detected across all subtypes, and chr7p amplification significantly correlated with poor prognosis while independently of melanoma subtypes. Furthermore, acral and mucosal melanomas demonstrated higher rates of focal copy number variations (CNVs) than cutaneous melanomas. The amplification of CDK4/CCND1 and NOTCH2 was observed predominantly in acral melanomas , and RAD51 loss was significantly enriched in mucosal melanomas correlating with poor survival. In addition, the tumor mutation burden (TMB) was significantly lower in acral or mucosal melanomas than in cutaneous melanomas. Conclusions: Our findings revealed distinct patterns of driver mutations and chromosomal alterations in acral and mucosal melanomas in contrast to cutaneous melanoma, and highlighted the association of chromosome 7p amplification and RAD51 deletion with unfavourable survival in melanoma patients treated with standard chemotherapy.
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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 | 0.001 | 0.001 |
| 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".