The Impact of Next-Generation Sequencing on Interobserver Agreement and Diagnostic Accuracy of Deep Penetrating Melanocytic Neoplasms

12/23/2025

The Impact of Next-Generation Sequencing on Interobserver Agreement and Diagnostic Accuracy of Deep Penetrating Melanocytic Neoplasms

Journal of Cutaneous Pathology

Authors Julia Edwin Jeyakumar, Afua Konadu Addo, Haya Mary Beydoun, Shantel Olivares, Armita Bahrami, Thiagarajah Balamurugan, Raymond L. Barnhill, Willeke A. M. Blokx, Klaus J. Busam, Lorenzo Cerroni, Martin Cook, Arnaud de La Fouchardière, Lyn M. Duncan, David E. Elder, Peter Ferguson, Gerardo Ferrara, Iva Johansson, Jennifer S. Ko, Ji Eun Kwon, Gilles Landman, Cecilia Lezcano, Lori Lowe, Daniela Massi, Jane Messina, Daniela Mihic-Probst, Douglas C. Parker, Margaret Redpath, Michael R. Sargen, Richard A. Scolyer, Christopher R. Shea, Michael Tetzlaff, Carlos Torres-Cabala, Victor Tron, Xiaowei Xu, Iwei Yeh, Sook Jung Yun, Artur Zembowicz, Pedram Gerami

ABSTRACT

Background: Next-generation sequencing (NGS) is becoming more commonly used for diagnosis in dermatopathology. It’scritical to appraise its efficacy and limitations. Distinguishing benign deep penetrating nevi (DPN) from deep penetrating like-melanoma (DPN-M) is a challenging diagnostic scenario even for experienced dermatopathologists.

Methods: We sent a two-phase survey (pre-and postgenomics) to 32 experienced dermatopathologists to evaluate 39 diagnosti-cally challenging cases from the DPN/WNT-activated family of melanocytic neoplasms.

Results: With NGS data, interobserver agreement improved from 0.41 to 0.51 (p < 0.0001) in distinguishing DPN-M from nonme-lanoma cases. Overall diagnostic accuracy improved, mostly driven by a 16% increase in accurate diagnosis of DPN-M. However,in two cases, the inclusion of genomics shifted the majority vote from a correct to an incorrect diagnosis. A total of 218 diagnosticchanges occurred between Survey 1 and 2. Among the changes, 132 votes moved toward the correct diagnosis while 86 movedtoward an incorrect diagnosis. The shift in voting which resulted in improved diagnostic accuracy was statistically significant(p = 0.0001).

Conclusions: NGS has the potential to improve interobserver agreement and diagnostic accuracy. We provide guidance on theutilization of bioinformatic data to maximize its benefits and improve diagnostic accuracy and interobserver agreement.

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