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Utility of TERT Promoter Mutations for Cutaneous Primary Melanoma Diagnosis

Thomas, Nancy E., MD, PhD*,†; Edmiston, Sharon N., BS*,†; Tsai, Yihsuan S., PhD; Parker, Joel S., PhD†,‡; Googe, Paul B., MD*,§; Busam, Klaus J., MD; Scott, Glynis A., MD‖,**; Zedek, Daniel C., MD*,§; Parrish, Eloise A., MS; Hao, Honglin*; Slater, Nathaniel A., MD*; Pearlstein, Michelle V., MD*; Frank, Jill S., MS†,††; Kuan, Pei Fen, PhD‡‡; Ollila, David W., MD†,††; Conway, Kathleen, PhD*,†,§§

The American Journal of Dermatopathology: April 2019 - Volume 41 - Issue 4 - p 264–272
doi: 10.1097/DAD.0000000000001259
Original Study

Abstract: Telomerase reverse transcriptase (TERT) promoter mutations are commonly found in malignant melanomas but rare in melanocytic nevi. To assess its potential diagnostic utility for the distinction of melanoma from nevus, we determined the TERT promoter mutation status of 86 primary melanomas, 72 melanocytic nevi, and 40 diagnostically problematic melanocytic proliferations. Of the 86 melanomas, 67 (77.9%) were TERT-positive, defined as harboring a hotspot TERT promoter mutation at positions -124C>T, -124_125CC>TT, -138_139CC>TT, or -146C>T. Of the 72 nevi, only 1 (1.4%) was TERT-positive. Of the 40 diagnostically uncertain melanocytic proliferations, 2 (5.0%) were TERT-positive. TERT positivity as a test for melanoma versus nevus had an accuracy of 87.3% [95% confidence interval (CI), 81.1–92.1], a sensitivity of 77.9% (95% CI, 68.9–85.4), a specificity of 98.6% (95% CI, 95.8–100), a positive predictive value of 98.5% (95% CI, 95.6–100), and a negative predictive value of 78.9% (95% CI, 72.6–85.4). Our results indicate that hotspot TERT promoter mutation status may be a useful ancillary parameter for the diagnosis of melanoma. In particular, the high specificity of these mutations for melanoma indicates the presence of a TERT promoter mutation in a melanocytic neoplasm associated with diagnostic controversy, or uncertainty should increase concern for a melanoma.

*Department of Dermatology, School of Medicine, University of North Carolina, Chapel Hill, NC;

Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC;

Departments of Genetics, and

§Pathology and Laboratory Medicine, School of Medicine, University of North Carolina, Chapel Hill, NC;

Department of Pathology, Memorial Sloan-Kettering Cancer Center, Manhattan, NY

Departments of Dermatology, and

**Pathology and Laboratory Medicine, University of Rochester School of Medicine, Rochester, NY;

††Department of Surgery, School of Medicine, University of North Carolina, Chapel Hill, NC;

‡‡Department of Applied Mathematics and Statistics, State University of New York, Stony Brook, NY; and

§§Department of Epidemiology, School of Public Health, University of North Carolina, Chapel Hill, NC.

Correspondence: Nancy E. Thomas, MD, PhD, Department of Dermatology, University of North Carolina, 2159 Genomic Science Building, CB#7287, Chapel Hill, NC 27599 (e-mail:

This work was funded by the National Cancer Institute grants R21CA134368, R33CA160138, R03CA199487 to K. Conway and N.E. Thomas, P01CA206980 to M. Berwick and N.E. Thomas, and P30CA016086 to H.S. Earp. This work was also supported by the Lineberger Comprehensive Cancer Center Bioinformatics Core.

The authors declare no conflicts of interest.

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