Journal of clinical oncology : official journal of the American Society of Clinical Oncology
October 15, 2026 · via Europe PMC
Expert Histopathologic Evaluation and Molecular Analyses for Ambiguous Cutaneous Melanocytic Tumors.
Ebbelaar CF, Lensing AWA, Breimer GE, +8 more, Blokx WAM
AI summary — for doctors, generated from the abstract only
Expert pathology review plus molecular testing resolved nearly all ambiguous melanocytic tumors, and the diagnoses held up in follow-up.
What was studied
Prospective cohort of 994 patients with ambiguous primary cutaneous melanocytic tumors at a Dutch referral center (2018-2021), assessed by expert review and, if inconclusive, sequencing, SNP array and RNA sequencing.
Key findings
- A diagnosis was reached in 966 (97.2%): 417 by expert review alone and 549 after molecular analyses
- 608 nonmelanoma cases had no melanoma-related events over a median 5.4 years
- Among 358 melanoma diagnoses, 20 had events (cumulative incidence 5.7%)
- No events occurred in 28 borderline cases
Clinical relevance
Dermatologists and pathologists facing equivocal lesions may find reassurance about stepwise expert and molecular referral.
Who should care
Limitations
Single referral center with limited follow-up, and very few borderline cases limit conclusions on those.
Referral for expert and molecular assessment may help when histology is uncertain.
This is an AI-generated summary of the published abstract, not a clinical recommendation. It may not reflect the full text or subsequent updates — verify against the original source before acting on it.
Abstract
PURPOSE
A subset of cutaneous melanocytic tumors has ambiguous histopathologic features that preclude reliable classification as benign or malignant. We evaluated the diagnostic yield and long-term clinical validity of expert histopathologic evaluation and, when inconclusive, additional molecular analyses in patients with ambiguous primary cutaneous melanocytic tumors.
METHODS
In this prospective cohort study, consecutive patients with primary cutaneous melanocytic tumors deemed ambiguous by referring pathologists were evaluated at a tertiary dermatopathology referral center in the Netherlands from September 2018 through December 2021. Tumors underwent expert histopathologic evaluation, with next-generation sequencing, single-nucleotide polymorphism array, and targeted RNA sequencing when inconclusive. Tumors were classified as nonmelanoma, melanoma, or borderline melanoma. Clinical validity was assessed by melanoma-related events during follow-up.
RESULTS
Among 258,562 patients with excised melanocytic tumors nationwide, 2,685 (1.0%) had ambiguous tumors. We included 994 patients and reached a diagnosis in 966 (97.2%): 417 (42.0%) after expert histopathologic evaluation alone and 549 (55.2%) after additional molecular analyses. Among 608 patients (61.2%) with a nonmelanoma diagnosis, no melanoma-related events occurred during median follow-up of 5.4 years (incidence, 0.0%; 95% CI, 0.0 to 0.6). Among 358 patients (36.0%) with a melanoma diagnosis, 33 of 186 (17.7%) had a positive sentinel node biopsy, and 20 developed melanoma-related events during median follow-up of 5.0 years (cumulative incidence, 5.7%; 95% CI, 3.3 to 8.1). No events occurred in 28 patients (2.8%) with a borderline melanoma diagnosis.
CONCLUSION
Expert histopathologic evaluation combined with molecular analyses provided a definitive diagnosis in nearly all patients with ambiguous primary cutaneous melanocytic tumors. Long-term follow-up supported the clinical validity of this stepwise diagnostic approach.
DOI
10.1200/JCO-26-00432
PMID
42879715
Research metadata (titles, abstracts, authors, publication dates) is sourced from Europe PMC, which aggregates content from PubMed/MEDLINE, PubMed Central, and other providers under the U.S. National Library of Medicine (NLM/NCBI). NLM does not claim copyright on abstracts; the original journal publishers or authors may hold rights to the full articles. AI-generated summaries are derived only from the abstract, never the full text, and are always labeled as AI-generated.
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