SKIN May 2022 Volume 6 Issue 3 (c) 2022 THE AUTHORS. Published by the National Society for Cutaneous Medicine. 189 CLINICAL MANAGEMENT RECOMMENDATIONS Integrating Genomic Testing for Melanoma Into Your Practice Nicholas Brownstone, MD1, Danny Zakria, MD, MBA2, McKenzie A. Dirr, BA, BS3, Yenn Lu, BA4, Darrell S. Rigel, MD, MS5 1 National Society for Cutaneous Medicine, New York, NY 2 Department of Surgery, Vanderbilt University Medical Center, Nashville, TN 3 Medical University of South Carolina, Charleston, SC 4 University of Missouri, Kansas City, Kansas City, MO 5 Department of Dermatology, Mount Sinai Icahn School of Medicine, New York, NY Melanoma is the most dangerous form of skin cancer and mortality is dependent upon stage of diagnosis. Patients with a stage I melanoma will have a 97% 5-year survival rate versus a patient with a stage IV lesion will only have a 15% survival rate. Therefore, early detection is critical as management is heavily affected by prognosis. Given this relationship, accurate assessment of prognosis is critical for effectively managing melanoma. Traditionally, tumor depth and other clinical and histological factors have been used to help predict the likelihood of metastasis and have ultimately been used as a proxy for survival1,2. While the American Joint Committee on Cancer’s (AJCC) clinicopathological factors are effective at accurately assessing tumor stage, the majority of deaths still occur in early stage disease3. Excluding stage IV patients, 80% of patients present with Stage I disease yet 41% of deaths still occur in this population. This is due to the fact that while the overall survival percentage is higher for thin melanomas, the absolute number of mortalities is greatest for thin tumors4. Furthermore, one study found pathological diagnostic discordance between thin invasive melanomas and melanoma in situ (MMIS) when reviewed by an expert dermatopathologist5. In addition, the factors that have been traditionally used for prognosis, including tumor thickness and ulceration status, are somewhat subjective. For all of these reasons, it has been suggested that adding molecular information to the AJCC melanoma staging system could contribute to improved prognostic accuracy in melanoma patients6. Recent advances in genomic technology have also led to earlier detection of melanoma and in some cases allowed the clinician to avoid an invasive biopsy altogether7 8. This clinical management guideline manuscript reviews how gene expression profiling (GEP) can be used to improve the diagnosis and prognosis of melanoma and will offer guidance on effective integration into clinical practice using patient vignettes. INTRODUCTION Using Genomics to Assess Prognosis SKIN May 2022 Volume 6 Issue 3 (c) 2022 THE AUTHORS. Published by the National Society for Cutaneous Medicine. 190 The 31-GEP test is a Clinical Laboratory Improvement Amendments (CLIA) approved test that uses formalin-fixed, paraffin- embedded tissue that requires no extra processing on behalf of the dermatologist or dermatopathologist. It identifies a genomic profile using a validated algorithm that identifies the likelihood of developing melanoma tumor recurrence or metastasis within 5 years. The test uses 28 genes and 3 control genes that are involved in many cellular processes associated with tumor progression and metastasis and assesses the net activity of the interplay between these genes9. The 31-GEP test was developed with the goal of assessing the risk of melanoma recurrence independent from clinicopathologic factors. Patients are risk stratified into Class 1A meaning low risk of melanoma recurrence, 1B/2A for moderate risk or Class 2B indicating a high risk of melanoma recurrence. Approximately 85% of patients fall within Class 1A (lowest risk category) or Class 2B (highest risk category). Through a more accurate assessment of prognosis, 31-GEP can help guide management in the clinical setting. A patient with a low-risk result can be considered for lower frequency clinical follow up. A patient with a higher-risk result can be considered for closer monitoring and more aggressive intervention such as adjuvant therapy or advanced imaging. The 31-GEP test has been validated in over 2,900 patients across 20 peer reviewed publications including validation/performance studies, prospective studies and clinical impact studies10, 11,12. Physicians, nurse practitioners and physician assistants have been shown to use the results from this test to make more risk appropriate changes in their clinical management13,11. The 31-GEP test can also guide decision making regarding sentinel lymph node biopsy (SLNB) in melanoma patients. As per the National Comprehensive Cancer Center (NCCN) guidelines, if the risk of SLNB positivity is less than 5%, SLNB should not be recommended to patients, but if the risk is calculated to be greater than 10% then it should be discussed and offered to the patient. Unfortunately the SLNB false negative rate is significant, with some studies estimating it be as high as 17%14. Moreover, the SLNB procedure itself has morbidity including poor wound healing, infection and lymphedema. Multiple studies have shown that the 31-GEP test is able identify lower SLNB positivity rates for Class 1A patients and higher positivity rates for Class 2B patients15,16,17. Vetto et. al. demonstrated that for patients 55 years or older, the 31-GEP test can identify a population with a low risk (<5%) of SLNB positivity and a high risk (>10%) of SLNB positivity18. When the test is applied to a T1- T2 SLNB eligible melanoma, a discussion regarding the potential avoidance of a SLNB procedure in a class 1A patient (< 5% risk of positivity) is possible. Conversely, the procedure could be offered to Class 2B patients (> 10% risk of positivity). This management approach has the potential to result in an increase in the yield of SLNB procedures, an avoidance of unnecessary surgical procedures in low-risk patients and a reduction in healthcare costs. Importantly, this test is also covered by Medicare. Example 1 A 66-year-old female presents to your office for further management after a biopsy performed by a local family medicine physician. Results of the biopsy show 31-GEP Test Clinical Examples SKIN May 2022 Volume 6 Issue 3 (c) 2022 THE AUTHORS. Published by the National Society for Cutaneous Medicine. 191 melanoma with Breslow thickness of 0.6 mm. There is no ulceration or mitoses present. The patient has no history of melanoma but does a have a history of a previously treated basal cell carcinoma and actinic keratosis. The patient asks you about her prognosis and if she needs any further treatment. To help guide this decision, you order the 31-GEP test on this patient’s biopsy specimen. The result of this test is a class 2B which indicates she is at high risk for recurrence and metastasis. Based on this information you decide to alter your normal management regimen usually employed for a lesion of this thickness. You counsel the patient on the importance of being followed more frequently than you had originally planned and you also refer her to clinical oncology to evaluate the need for advanced imaging and adjuvant therapy. This example highlights a patient with traditionally low risk clinical tumor characteristics who has a high-risk tumor genetic profile and might therefore benefit from a more rigorous management regimen. Example 2 A 30-year-old Female patient presents to your office after her husband had noticed a changing pigmented lesion on her back. The patient has no past medical history and no history of skin cancer but did frequently use tanning beds throughout her college years. After taking a biopsy of the lesion, the report comes back a few days later with a 0.7 mm Breslow thickness melanoma extending to the base of the specimen. Since the actual Breslow thickness is unknown, you decide to order the 31-GEP test to help guide further management. The test shows a Class 1A result. Given this low-risk result, you can counsel the patient that she does not require more intensive monitoring and does not need any further imaging or adjuvant therapy. In this scenario, the 31-GEP test helps guide management by demonstrating that the patient was at a low risk for metastasis or recurrence, even though the true Breslow thickness could not be determined. Example 3 A 68-year-old Female patient returns to your office after having a biopsy proven melanoma detected in clinic the previous week. The patient’s melanoma has a Breslow thickness of 1.1 mm, a mitotic rate of 1/mm2, positive ulceration but no other high-risk features. As per AJCC staging criteria alone, this patient would qualify as stage T2b which would predict her likelihood of SLNB positivity to be >10%. Given that alone, you would discuss and offer the procedure to this patient. However, you decide to apply the 31-GEP test to the patient’s already processed biopsy specimen. You receive a report which indicates the patient has a Class 1A result. Based on this new information, the predicted SLNB positivity rate is 2.9% and you can now confidently have an informed discussion with the patient on the low yield of the procedure. Example 4 A 63-year-old Male patient returns to your office after having a biopsy proven melanoma from his recent office visit. The patient’s melanoma has a Breslow thickness of 0.7 mm and has no other high-risk features. As per the traditional staging criteria, this patient would qualify as stage T1a which would predict his SLNB positivity to be less than 5%. Therefore, you would not typically discuss and offer the procedure to this patient. However, you decide to apply the 31-GEP test to the patient’s already processed biopsy specimen. You receive a report which indicates the patient has a SKIN May 2022 Volume 6 Issue 3 (c) 2022 THE AUTHORS. Published by the National Society for Cutaneous Medicine. 192 Class 2B result. Based on this new information, the predicted SLNB positivity rate is 15.1% and you can now confidently have an informed discussion about the procedure’s benefits. The 2-GEP test uses a noninvasive adhesive patch to sample a suspicious skin lesion to help classify pigmented lesions as melanoma or non-melanoma when dealing with clinically difficult cases19. This pigmented lesion assay analyzes two genes, LINC (long intergenic non-protein coding RNA 518) and PRAME (preferentially expressed antigen in melanoma). These two genes were chosen due to the fact that these were the best performing gene pairs, of an original 17 gene discriminatory set, when separating melanoma from non- melanoma lesions with high levels of accuracy19. LINC is a part of a cluster of regulatory RNA molecules involved in melanoma proliferation and PRAME promotes tumor progression by interfering with retinoic acid receptor (RAR) signaling. The negative predictive value of the 2-GEP test was found to be greater than 99% in the real-world TRUST study. After analyzing over 5,000 patients, the 2-GEP test reduced biopsies by approximately 85%20. The test has been well validated with 14 peer- reviewed manuscripts demonstrating analytical validation, clinical validation and clinical utility. Clinicians have been shown to follow the test guidance in over 98% of cases21,22. Brouha et. al. demonstrated a close correlation between the genomic atypia and advanced histopathological atypia of melanoma, further validating the utility of the 2-GEP test as a non-invasive method to detect melanoma8. A 54-year-old male is being evaluated for a chief complaint of a “suspicious lesion”. The patient has no personal history but does a have a family history of melanoma. He shows you a sharply demarcated, irregularly-shaped, 6 mm pigmented lesion on his left distal forearm which he thinks has been growing. However, clinical and dermoscopic exam reveals a mostly homogenous pigment pattern consistent with neighboring, smaller lesions. Given these equivocal findings, you decide to apply the 2-GEP test to evaluate the lesion for genomic atypia to help guide your decision to perform a biopsy. After applying the non-invasive skin patch and sending the specimen for analysis, you receive a report that LINC and PRAME were both detected. Given this additional information, you decide to perform a biopsy which resulted in a histopathological diagnosis of a 0.5mm, stage pT1a melanoma. The patient had a subsequent surgical excision with appropriate margins and has no signs of recurrence at his 6 month follow up and subsequent visits. Melanoma is a life-threatening neoplasm where early detection along with appropriately timed intervention has the ability to significantly improve outcomes. However, practice gaps still exist for the diagnosis and treatment of melanoma given the challenges in defining high-risk subsets of lower-risk patients who may die from this cancer. Furthermore, decisions to biopsy suspicious lesions are heavily dependent upon subjective visual exams. Integrating the non-invasive 31-GEP and 2-GEP tests into clinical practice for assessing melanoma Using Genomics to Assess Diagnosis 2-GEP Test Clinical Example Conclusion SKIN May 2022 Volume 6 Issue 3 (c) 2022 THE AUTHORS. Published by the National Society for Cutaneous Medicine. 193 diagnosis and prognosis has been shown to enhance accuracy. For these reasons, gene expression profiling technology is becoming an important adjunct in clinical practice to the standard of care for melanoma management. Conflict of Interest Disclosures: DSR serves as a consultant for Castle Biosciences and DermTech Funding: None Corresponding Author: Nicholas Brownstone, MD Melanoma Fellow National Society for Cutaneous Medicine New York NY Email: nicholas@fred.health References: 1. Mossbacher U, Knollmayer S, Binder M, Steiner A, Wolff K, Pehamberger H. Increased nuclear volume in metastasizing “thick” melanomas. J Invest Dermatol. 1996;106(3):437-440. doi:10.1111/1523- 1747.ep12343580 2. Breslow A. Thickness, cross-sectional areas and depth of invasion in the prognosis of cutaneous melanoma. Ann Surg. 1970;172(5):902-908. 3. Morton DL, Thompson JF, Cochran AJ, et al. Final Trial Report of Sentinel-Node Biopsy versus Nodal Observation in Melanoma. N Engl J Med. 2014;370(7):599-609. doi:10.1056/NEJMoa1310460 4. More people die from thin melanomas than thick melanomas. Accessed December 13, 2021. https://www.mdedge.com/internalmedicine/artic le/87682/melanoma/more-people-die-thin- melanomas-thick-melanomas 5. Santillan AA, Messina JL, Marzban SS, Crespo G, Sondak VK, Zager JS. Pathology review of thin melanoma and melanoma in situ in a multidisciplinary melanoma clinic: impact on treatment decisions. J Clin Oncol Off J Am Soc Clin Oncol. 2010;28(3):481-486. doi:10.1200/JCO.2009.24.7734 6. Ferguson PM, Gershenwald JE, Scolyer RA. Staging of Cutaneous Melanoma: Is There Room for Further Improvement? JAMA Netw Open. 2018;1(1):e180086. doi:10.1001/jamanetworkopen.2018.0086 7. Puglisi R, Bellenghi M, Pontecorvi G, Pallante G, Carè A, Mattia G. Biomarkers for Diagnosis, Prognosis and Response to Immunotherapy in Melanoma. Cancers. 2021;13(12):2875. doi:10.3390/cancers13122875 8. Brouha B, Ferris L, Skelsey M, et al. Genomic Atypia to Enrich Melanoma Positivity in Biopsied Lesions: Gene Expression and Pathology Findings From a Large U.S. Registry Study. SKIN J Cutan Med. 2021;5(1):13-18. doi:10.25251/skin.5.1.3 9. Gerami P, Cook RW, Wilkinson J, et al. Development of a prognostic genetic signature to predict the metastatic risk associated with cutaneous melanoma. Clin Cancer Res Off J Am Assoc Cancer Res. 2015;21(1):175-183. doi:10.1158/1078-0432.CCR-13-3316 10. Gastman BR, Zager JS, Messina JL, et al. Performance of a 31-gene expression profile test in cutaneous melanomas of the head and neck. Head Neck. 2019;41(4):871-879. doi:10.1002/hed.25473 11. Mirsky R, Prado G, Svoboda R, Glazer A, Rigel D. Management Decisions Made by Physician Assistants and Nurse Practitioners in Cutaneous Malignant Melanoma Patients: Impact of a 31-Gene Expression Profile Test. J Drugs Dermatol JDD. 2018;17(11):1220-1223. 12. Keller J, Schwartz TL, Lizalek JM, et al. Prospective validation of the prognostic 31- gene expression profiling test in primary cutaneous melanoma. Cancer Med. 2019;8(5):2205-2212. doi:10.1002/cam4.2128 13. Dillon LD, Gadzia JE, Davidson RS, et al. Prospective, Multicenter Clinical Impact Evaluation of a 31-Gene Expression Profile Test for Management of Melanoma Patients. SKIN J Cutan Med. 2018;2(2):111-121. doi:10.25251/skin.2.2.3 14. Durham AB, Schwartz JL, Lowe L, et al. The natural history of thin melanoma and the utility of sentinel lymph node biopsy. J Surg Oncol. 2017;116(8):1185-1192. doi:10.1002/jso.24765 15. Schuitevoerder D, Heath M, Cook RW, et al. Impact of Gene Expression Profiling on Decision-Making in Clinically Node Negative Melanoma Patients after Surgical Staging. J Drugs Dermatol JDD. 2018;17(2):196-199. 16. Hsueh EC, DeBloom JR, Lee J, et al. Interim analysis of survival in a prospective, multi- center registry cohort of cutaneous melanoma tested with a prognostic 31-gene expression profile test. J Hematol OncolJ Hematol Oncol. 2017;10(1):152. doi:10.1186/s13045-017-0520- 1 SKIN May 2022 Volume 6 Issue 3 (c) 2022 THE AUTHORS. Published by the National Society for Cutaneous Medicine. 194 17. Vetto JT, Hsueh EC, Gastman BR, et al. Guidance of sentinel lymph node biopsy decisions in patients with T1-T2 melanoma using gene expression profiling. Future Oncol Lond Engl. 2019;15(11):1207-1217. doi:10.2217/fon-2018-0912 18. Vetto JT, Hsueh EC, Gastman BR, et al. Guidance of sentinel lymph node biopsy decisions in patients with T1-T2 melanoma using gene expression profiling. Future Oncol Lond Engl. 2019;15(11):1207-1217. doi:10.2217/fon-2018-0912 19. Gerami P, Yao Z, Polsky D, et al. Development and validation of a noninvasive 2-gene molecular assay for cutaneous melanoma. J Am Acad Dermatol. 2017;76(1):114-120.e2. doi:10.1016/j.jaad.2016.07.038 20. Skelsey M, Brouha B, Rock J, et al. Non- Invasive Detection of Genomic Atypia Increases Real-World NPV and PPV of the Melanoma Diagnostic Pathway and Reduces Biopsy Burden. SKIN J Cutan Med. 2021;5(5):512-523. doi:10.25251/skin.5.5.9 21. Ferris LK, Rigel DS, Siegel DM, et al. Impact on clinical practice of a non-invasive gene expression melanoma rule-out test: 12-month follow-up of negative test results and utility data from a large US registry study. Dermatol Online J. 2019;25(5):13030/qt61w6h7mn. 22. Elmore JG, Barnhill RL, Elder DE, et al. Pathologists’ diagnosis of invasive melanoma and melanocytic proliferations: observer accuracy and reproducibility study. BMJ. 2017;357:j2813. doi:10.1136/bmj.j2813