Next Generation Sequencing in Differential Diagnosis of Childhood Melanoma From Spitz Nevus: A Case Report
Bibliographic record
Abstract
Melanomas are uncommon in children and share many of the characteristics of benign Spitz nevi in their clinical presentation as well as histopathology. Therefore, the diagnosis could be challenging. Currently, molecular diagnostic tools are being explored to aid the diagnosis in the pediatric melanoma. Melanomas often harbor multiple gene mutations and gene number variations, including BRAF (7q34), CCND1 (11q13), RREB1 (6p25), Cep 6, MYB (6q23), PIK3CA (3q26), PTEN (10q23), CDKN2A (9p21), c-KIT (4q12) and MYC (8q24), but these changes are rare in benign melanocytic nevi, including Spitz nevus of which the signature gene abnormalities had been recently revealed. Next generation sequencing (NGS) is a new molecular technique allowing the detection of a broad spectrum of genome abnormalities simultaneously, thus providing a potential powerful tool for assisting the diagnosis of childhood melanoma. We herein present a 12-year-old female with a melanocytic neoplasm showing histopathologic features highly suggestive of malignant melanoma. A variety of molecular analysis studies were employed including NGS, which revealed BRAF mutation, BRAF copy number addition, and CDKN2A and PTEN deletion. Fluorescence in situ hybridization studies were also used, which not only confirmed the gene number variation in BRAF, CDKN2A and PTEN, but also revealed gain in MYC. These results added valuable information in the diagnosis of melanoma. This case demonstrated the usefulness of molecular analysis as the ancillary tools in assisting the diagnosis of childhood melanoma. Int J Clin Pediatr. 2014;3(1):22-28 doi: http://dx.doi.org/ 10.14740 / ijcp148e
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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 | 0.001 | 0.004 |
| 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".