A 35-Gene Expression Profile Test for use in Suspicious Pigmented Lesions Impacts Clinical Management Decisions of Dermatopathologists and Dermatologists
Main Article Content
Keywords
35-GEP, melanoma, management, clinical utility, diagnostic test
Abstract
Purpose: Histopathological examination is sufficient for diagnosis of many melanocytic neoplasms, however, diagnostic discordance is common between dermatopathologists. A timely and confident diagnosis is optimal, especially in cases where both benign and malignant melanocytic neoplasms are considered in the differential diagnosis as treatment plans diverge significantly.
A 35-gene expression profile (GEP) test that classifies melanocytic lesions into categories (benign, intermediate-risk and malignant), has reported accuracy metrics of 99.1% sensitivity, 94.3% specificity, 93.6% positive predictive value and 99.2% negative predictive value in a validation cohort of 503 samples. The clinical utility of the 35-GEP is described.
Methods: Dermatopathologists (n=6) and dermatologists (n=14) were queried regarding diagnostic challenges and patient management strategies in 60 difficult-to-diagnose melanocytic neoplasms. Participants reviewed each lesion twice, once without the 35-GEP result and once with. Responses were evaluated for consistent trends in the utilization of the 35-GEP test result.
Results: Dermatopathologists utilized the 35-GEP result to refine their diagnoses by increasing overall lesion diagnostic concordance and confidence, while reducing additional work up requests. Dermatologists utilized the 35-GEP result to gauge overall prognosis and case difficulty. Alterations in office visit frequency, biopsies, and referrals to specialists were also influenced by the 35-GEP result and treatment plan modifications also matched the appropriate directionality of the 35-GEP result.
Conclusions: The diagnosis of challenging melanocytic neoplasms and subsequent clinical management decisions are influenced by 35-GEP results in a manner that agrees with the test result. The utility of the test provides the opportunity to improve patient care.
References
2. Farmer ER, Gonin R, Hanna MP. Discordance in the histopathologic diagnosis of melanoma and melanocytic nevi between expert pathologists. Hum Pathol. 1996;27(6):528-531. doi:10.1016/s0046-8177(96)90157-4
3. Shoo BA, Sagebiel RW, Kashani-Sabet M. Discordance in the histopathologic diagnosis of melanoma at a melanoma referral center. J Am Acad Dermatol. 2010;62(5):751-756. doi:10.1016/j.jaad.2009.09.043
4. Glazer A, Cockerell C. Histopathologic discordance in melanoma can have substantial impacts on patient care. SKIN J Cutan Med. 2019;3(2):85. doi:10.25251/skin.3.2.41
5. Patrawala S, Maley A, Greskovich C, et al. Discordance of histopathologic parameters in cutaneous melanoma: Clinical implications. J Am Acad Dermatol. 2016;74(1):75-80. doi:10.1016/j.jaad.2015.09.008
6. National Cancer Institute, National Institutes of Health. Melanoma of the Skin - Cancer Stat Facts. SEER. Published 2020. Accessed October 24, 2019. https://seer.cancer.gov/statfacts/html/melan.html
7. Siegel RL, Miller KD, Jemal A. Cancer statistics, 2018. CA Cancer J Clin. Published online January 4, 2018. doi:10.3322/caac.21442
8. Gonzalez ML, Young ED, Bush J, et al. Histopathologic features of melanoma in difficult-to-diagnose lesions: A case-control study. J Am Acad Dermatol. 2017;77(3):543-548.e1. doi:10.1016/j.jaad.2017.03.017
9. Andea AA. Updates on molecular diagnostic assays in melanocytic pathology. Diagn Histopathol. 2020;26(3):135-142. doi:10.1016/j.mpdhp.2019.12.005
10. Lee JJ, Lian CG. Molecular Testing for Cutaneous Melanoma: An Update and Review. Arch Pathol Lab Med. 2019;143(7):811-820. doi:10.5858/arpa.2018-0038-RA
11. Miedema J, Andea AA. Through the looking glass and what you find there: making sense of comparative genomic hybridization and fluorescence in situ hybridization for melanoma diagnosis. Mod Pathol. Published online February 17, 2020. doi:10.1038/s41379-020-0490-7
12. Rimm DL. What brown cannot do for you. Nat Biotechnol. 2006;24(8):914-916. doi:10.1038/nbt0806-914
13. Reimann JDR, Salim S, Velazquez EF, et al. Comparison of melanoma gene expression score with histopathology, fluorescence in situ hybridization, and SNP array for the classification of melanocytic neoplasms. Mod Pathol Off J U S Can Acad Pathol Inc. 2018;31(11):1733-1743. doi:10.1038/s41379-018-0087-6
14. Clarke LE, Flake DD, Busam K, et al. An independent validation of a gene expression signature to differentiate malignant melanoma from benign melanocytic nevi. Cancer. 2017;123(4):617-628. doi:10.1002/cncr.30385
15. Clarke LE, Warf MB, Flake DD, et al. Clinical validation of a gene expression signature that differentiates benign nevi from malignant melanoma. J Cutan Pathol. 2015;42(4):244-252. doi:10.1111/cup.12475
16. Clarke LE, Pimentel JD, Zalaznick H, Wang L, Busam KJ. Gene expression signature as an ancillary method in the diagnosis of desmoplastic melanoma. Hum Pathol. 2017;70:113-120. doi:10.1016/j.humpath.2017.10.005
17. Ko JS, Matharoo-Ball B, Billings SD, et al. Diagnostic Distinction of Malignant Melanoma and Benign Nevi by a Gene Expression Signature and Correlation to Clinical Outcomes. Cancer Epidemiol Biomarkers Prev. 2017;26(7):1107-1113. doi:10.1158/1055-9965.EPI-16-0958
18. Ko JS, Clarke LE, Minca EC, Brown K, Flake DD, Billings SD. Correlation of melanoma gene expression score with clinical outcomes on a series of melanocytic lesions. Hum Pathol. 2019;86:213-221. doi:10.1016/j.humpath.2018.12.001
19. Cockerell CJ, Tschen J, Evans B, et al. The influence of a gene expression signature on the diagnosis and recommended treatment of melanocytic tumors by dermatopathologists: Medicine (Baltimore). 2016;95(40):e4887. doi:10.1097/MD.0000000000004887
20. Cockerell C, Tschen J, Billings SD, et al. The influence of a gene-expression signature on the treatment of diagnostically challenging melanocytic lesions. Pers Med. 2017;14(2):123-130. doi:10.2217/pme-2016-0097
21. Estrada SI, Shackelton JB, Cleaver NJ, et al. Development and validation of a diagnostic 35-gene expression profile test for ambiguous or difficult-to-diagnose suspicious pigmented skin lesions. SKIN J Cutan Med. 2020;Submitted.
22. Kristiansen G. Markers of clinical utility in the differential diagnosis and prognosis of prostate cancer. Mod Pathol. 2018;31(S1):S143-155. doi:10.1038/modpathol.2017.168
23. Alford AV, Brito JM, Yadav KK, Yadav SS, Tewari AK, Renzulli J. The Use of Biomarkers in Prostate Cancer Screening and Treatment. Rev Urol. 2017;19(4):221-234. doi:10.3909/riu0772
24. Chapman CJ, Healey GF, Murray A, et al. EarlyCDT®-Lung test: improved clinical utility through additional autoantibody assays. Tumor Biol. 2012;33(5):1319-1326. doi:10.1007/s13277-012-0379-2
25. Alexander EK, Schorr M, Klopper J, et al. Multicenter clinical experience with the Afirma gene expression classifier. J Clin Endocrinol Metab. 2014;99(1):119-125. doi:10.1210/jc.2013-2482
26. Piepkorn MW, Longton GM, Reisch LM, et al. Assessment of Second-Opinion Strategies for Diagnoses of Cutaneous Melanocytic Lesions. JAMA Netw Open. 2019;2(10):e1912597. doi:10.1001/jamanetworkopen.2019.12597
27. Ensslin CJ, Hibler BP, Lee EH, Nehal KS, Busam KJ, Rossi AM. Atypical Melanocytic Proliferations: A Review of the Literature. Dermatol Surg Off Publ Am Soc Dermatol Surg Al. 2018;44(2):159-174. doi:10.1097/DSS.0000000000001367