Gene Expression Profile Testing in Melanoma: A Review and Discussion of Three Impactful Studies

Introduction

J Clin Aesthet Dermatol. 2023;16(12 Suppl 1):S3.

by Laura Ferris, MD, PhD

Dr. Ferris is a Professor of Dermatology at the University of Pittsburgh School of Medicine in Pittsburgh, Pennsylvania.

Over the past several years we have seen several advances in melanoma therapy, including new therapeutic targets, studies showing the benefits of neoadjuvant therapy, and the approval of two therapies for the treatment of patients with stage IIB/C disease in the adjuvant setting. These advances have had a meaningful impact as deaths from cutaneous melanoma have decreased over the past several years primarily due to therapeutic advances.1,2 The changing melanoma therapeutic landscape gives us an opportunity to rethink how we identify those patients who will benefit most from these therapies and, conversely, which patients may benefit from more conservative therapeutic and surveillance approaches. While conventional staging using clinical pathologic features, such as tumor thickness, ulceration, and sentinel lymph node status, can provide important prognostic information, conventional staging alone has some limitations. Most patients in the United States are diagnosed with earlier melanoma, especially Stage I disease.3 Further, most patients who undergo sentinel lymph node biopsy will have a negative sentinel node.4 Both factors are good prognostic indicators. However, we also know that the majority of melanoma deaths paradoxically occur in patients initially diagnosed with early stage disease (stage I/II) and in those who have a negative sentinel lymph node biopsy.3,4 Additionally, patients with stage II disease were traditionally considered a lower risk population. However, this population (those with stage IIB/C disease) is now eligible for adjuvant therapy, highlighting the risk to a sentinel node negative population.1,2 Additionally, patient age is not part of the AJCC staging system but has important prognostic implications as older patients have lower melanoma-specific survival but are also less likely to have a positive sentinel lymph node biopsy.5 These factors highlight the need for additional prognostic features to better stratify patients’ risk of melanoma recurrence or death to help guide decisions about surveillance or therapy. The use of gene expression profiling (GEP) can help to provide additional information to allow for a more personalized risk assessment. GEP is used in several other tumors to help risk stratify patients including uveal melanoma and breast cancer. Several studies have show that GEP testing in melanoma with the 31-GEP test (DecisionDx®-Melanoma; Castle Biosciences, Inc., Friendswood, Texas) is an independent predictor of melanoma-specific, recurrence-free, and overall survival as well as sentinel node positivity among patients referred for sentinel lymph node biopsy. The 31-GEP test classifies patients as having low (class 1) or high (class 2) risk of distant metastasis. Within each class patients are further stratified into class 1A (lowest risk), class 1B or 2A (intermediate risk), or class 2B (highest risk). Several recent studies have further investigated the prognostic significance of this test. One study evaluated the prognostic significance of these results in predicting melanoma-specific and overall survival in a large cohort of patients in the SEER registry and compared outcomes of patients who were tested to those who did not have GEP testing performed.6 Two additional studies showed that 31-GEP testing can help to identify patients who are at higher risk of distant recurrence and may benefit most from routine radiographic imaging to identify metastatic disease at an early stage.7,8 Real-world studies can provide valuable outcomes data that can be helpful in determining how patients’ care may be guided by GEP testing.

References

  1. Long GV et al. Pembrolizumab versus placebo as adjuvant therapy in resected stage IIB or IIC melanoma (KEYNOTE-716): distant metastasis-free survival results of a multicentre, double-blind, randomised, phase 3 trial. Lancet Oncol. 2022 Nov;23(11):1378-1388.
  2. Kirkwood JM et al. Adjuvant nivolumab in resected stage IIB/C melanoma: primary results from the randomized, phase 3 CheckMate 76K trial. Nat Med. 2023 Oct 16.
  3. Landow SM et al. Mortality burden and prognosis of thin melanomas overall and by subcategory of thickness, SEER registry data, 1992-2013. J Am Acad Dermatol. 2017 Feb;76(2):258-263.
  4. Morton DL et al. Sentinel-node biopsy or nodal observation in melanoma. N Engl J Med. 2006 Sep 28;355(13):1307-17.
  5. Balch CM et al. Age as a predictor of sentinel node metastasis among patients with localized melanoma: an inverse correlation of melanoma mortality and incidence of sentinel node metastasis among young and old patients. Ann Surg Oncol. 2014 Apr;21(4):1075-81.
  6. Bailey C, Martin B, Petkov V, et al. 31-Gene Expression Profile Testing in Cutaneous Melanoma and Survival Outcomes in a Population-Based Analysis: A SEER Collaboration. JCO Precis Oncol. 2023;7:e2300044.
  7. Williams A, Hamilton O, Likar C, et al. The Benefit of Positron Emission Tomography/Computed Tomography in Stage I and Stage II Melanomas With High-Risk Decisiondx-Melanoma Scores. The American Surgeon. 2022. 88(7):1446–1451. 
  8. Dhillon et al. Routine imaging guided by a 31‑gene expression profile assay results in earlier detection of melanoma with decreased metastatic tumor burden compared to patients without surveillance imaging studies. Arch Dermatol Res. 2023 Oct;315(8):
    2303.
     

 

Commentary: The Benefit of Positron Emission Tomography/Computed Tomography in Stage I and Stage II Melanomas with High-Risk DecisionDx-Melanoma Scores

J Clin Aesthet Dermatol. 2023;16(12 Suppl 1):S4–S5.

by Mary Garland-Kledzik, MD

Dr. Garland-Kledzik is with the Department of Surgery, Division of Surgical Oncology, West Virginia University, Morgantown, West Virginia.

Disclosures: Dr. Garland-Kledzik reports no disclosures relevant to the content of this article.

Melanoma care has changed dramatically over the past decade between immunotherapy and two large randomized, controlled surgical trials: the German Dermatologic Cooperative Oncology Group—Selective Lymphadenectomy Trial (DeCOG-SLT) and the Multicenter Selective Lymphadenectomy Trial II (MSLT-II).1,2 The adoption of these treatment paradigms has resulted in significant improvement in disease-free survival, overall survival, and reduction in morbidity. Despite this success, about half of metastatic patients still recur and about 40 percent of recurrences are in Stage I and II patients. Given these findings, there is concern that the current American Joint Committee on Cancer (AJCC) TNM pathologic staging is not adequately identifying patients who are at high risk of recurrence. Consequently, alternative factors need to be evaluated to see if they can better prognosticate these patients. Recent literature has shown that the tumor microenvironment as well as somatic mutations may result in differing outcomes and can even affect response to cytotoxic chemotherapies and/or immunotherapy.3

Castle Biosciences (Friendswood, Texas) developed DecisionDx®-Melanoma (DDx-M), a 31-gene expression profile, to measure genes associated with prognosis that are not seen through histology alone. Studies using this test support its ability to predict melanoma specific survival (MSS) and disease-free survival (DFS) for melanomas >0.3mm in Breslow Depth by stratifying them into Class 1A, 1B, 2A, and 2B with Class 2 patients having a higher risk of recurrence.4 Based on this risk, our institution began increasing screening in Stage I and II melanoma patients with a Class 2 DDx-M result. We excluded Stage III patients as they were already on increased screening with full body imaging. We staged them with a 18FDG-PET-CT and brain MRI yearly for three years and did physical exams every three months rather than our standard frequency of every six months. 

After several years of this change in practice, we reviewed our data to ensure that we were in fact using resources wisely. We reviewed 297 patients who had DDx-M from 2014 to 2021. Sixty-six of these patients were Class 2 DDx-M and Stage I or II. Two hundred and nineteen were Class 1. Within three years of follow-up, 8 of the 66 patients (12.1%) had metastases detected during screening 18FDG-PET-CT. None were found on brain MRI. Of note, 13 patients were found to have a concerning lesion on screening 18FDG-PET-CT (19.7%). Four had benign findings and one was lost to follow-up. Two other patients on screening protocol presented to the ER outside of our protocol with symptomatic brain metastases. Finally, one other patient was having screening imaging for a second malignancy and was found to have metastases. This shows that the rate of recurrence is higher than 12 percent and that screening imaging was helpful in detecting earlier recurrence. All of the recurrences in patients with confirmed metastases were Stage II. Two were Stage IIA, one Stage IIB, and five Stage IIC. We conclude from our review that increased screening with full body imaging is recommended for Class 2 DDx-M patients, particularly those who are Stage II.5

Interestingly, our review came at about the same time as the Keynote-716 study showing that adjuvant immunotherapy reduces recurrence over observation in Stage IIB and IIC.6 Approximately half of our patients on this increased screening protocol fall into that category (51.5%). When excluding Stage IIB and IIC patients, 2 of 32 (6.3%) patients in the study had a recurrence caught by increased screening. If you focus on the Stage IIA and Class 2 patients, 2 of 15 (13.3%) had a recurrence. Our study supports that gene expression profiling is a useful adjunct to AJCC staging. In a medical system where resource utilization is important, screening this most at-risk group will catch early recurrence in about 1 in 8. 

Gene expression profiling is an interesting concept that has been used in other cancers, including breast cancer. Oncotype DX® (Exact Sciences Corporation, Madison, Wisconsin), a similar gene test for breast cancer, has been used to predict recurrence and utility of chemotherapy.7 There is not currently data to support adjusting systemic therapy recommendations based on gene expression profiling. While we used DDx-M in this trial to screen high-risk patients, next steps in our evolving treatment paradigm should include studying the utility of immunotherapy in Class 1 versus 2 patients at higher stages.

Our understanding of cancer prognosis is constantly improving. Our study shows that DDx-M can be an important prognostic tool and can be valuable for surveillance, especially in those not receiving adjuvant systemic therapy. We recommend increased screening with whole-body imaging yearly in patients with a Class 2 DecisionDx-Melanoma score, particularly in Stage II patients.  From these studies, we propose to consider expanding the use of this test to other clinical stages to see if the test can help provide prognostic information to guide treatment. 

References

  1. Leiter U, Stadler R, Mauch C, et al. Final Analysis of DeCOG-SLT Trial: No Survival Benefit for Complete Lymph Node Dissection in Patients With Melanoma With Positive Sentinel Node. J Clin Oncol. 2019 Nov 10;37(32):3000-3008.
  2. Faries MB, Thompson JF, Cochran AJ, et al. Completion Dissection or Observation for Sentinel-Node Metastasis in Melanoma. N Engl J Med. 2017 Jun 8;376(23):2211-2222.
  3. Gopalakrishnan V, Helmink BA, Spencer CN, Reuben A, Wargo JA. The Influence of the Gut Microbiome on Cancer, Immunity, and Cancer Immunotherapy. Cancer Cell. 2018 Apr 9;33(4):570-580.  
  4. Greenhaw BN, Covington KR, Kurley SJ, et al. Molecular risk prediction in cutaneous melanoma: A meta-analysis of the 31-gene expression profile prognostic test in 1,479 patients. J Am Acad Dermatol. 2020 Sep;83(3):745-753. 
  5. Williams A, Hamilton O, Likar C, et al. The Benefit of Positron Emission Tomography/Computed Tomography in Stage I and Stage II Melanomas With High-Risk Decisiondx-Melanoma Scores. The American Surgeon. 2022;88(7):1446–1451. 
  6. Luke JJ, Rutkowski P, Queirolo P, et al. Pembrolizumab versus placebo as adjuvant therapy in completely resected stage IIB or IIC melanoma (KEYNOTE-716): a randomised, double-blind, phase 3 trial. Lancet. 2022 Apr 30;399(10336):1718-1729.
  7. Sparano JA, Gray RJ, Makower DF, et al. Adjuvant Chemotherapy Guided by a 21-Gene Expression Assay in Breast Cancer. N Engl J Med. 2018 Jul 12;379(2):111-121.  

 

Commentary: Routine Imaging based on Gene Expression Profiling, a New Paradigm for the Era of Immunotherapy

J Clin Aesthet Dermatol. 2023;16(12 Suppl 1):S6–S8.

by Jeffrey D. Wayne, MD

Dr. Wayne is with the Division of Surgical Oncology, Northwestern University Feinberg School of Medicine in Chicago, Illinois.

Disclosures: Dr. Wayne has served as a speaker and investigator for Castle Biosciences, Inc. 

Melanoma remains a significant public health problem, with over 97,000 estimated new cases in the United States in 2023 and almost 8,000 deaths.1 Traditional follow-up for a patient with melanoma relies upon physical examination with variable imaging recommendations.2 Widely accepted guidelines, such as the National Comprehensive Cancer Network (NCCN) guidelines, base follow-up recommendations on pathologic AJCC stage, after surgical management, in particular sentinel lymph node biopsy. Routine imaging to screen for asymptomatic recurrence or metastatic disease is not generally recommended.3 Furthermore, until recently, intensive follow-up strategies were felt to be unjustified in the absence of effective systemic therapies for inoperable metastatic disease. More recently, gene expression profile testing has offered an individualized risk of recurrence. A 31-gene expression profile (31-GEP) test was introduced in 2013 and yields a continuous probability score between zero and one that stratifies the risk of melanoma disease recurrence. The score is assigned to four categories: low risk of recurrence (Class 1A; 0–0.41 and Class 1B; 0.42–0.49), and high risk of recurrence (Class 2A; 0.50–0.58 and Class 2B; 0.59–1).4-7 The 31-GEP Class has been demonstrated to be an independent predictor of recurrence, including nodal recurrence and distant metastasis-free survival (DMFS) in meta-analyses and multiple prospective and retrospective studies.6,8

Concurrently immunotherapies and targeted therapies have revolutionized the treatment of patients with melanoma. Specifically, immunotherapies such as anti-programmed cell death ligand 1(anti-PD-1) immune checkpoint inhibitor (ICI) and anti-cytotoxic T lymphocyte antigen-2 (anti-CTLA-4) ICI, as well as targeted antitumor treatments, including B-Raf proto-oncogene (BRAF) and mitogen-activated protein-kinase-kinase (MEK) inhibitors, are now standard of care for patients with Stage III and IV disease.9,10 Long-term follow up from numerous clinical trials support the effectiveness of these newer therapies in improving progression-free survival (PFS) and overall survival (OS).9-11 Importantly, many trials involving these novel agents suggest greater efficacy when administered to patients with an initial lower tumor burden.12-16 Recent studies have suggested that routine imaging can detect early relapse when there is a lower tumor burden.17-19

Thus, Dhillon et al. sought to determine if routine imaging led to detection of metastatic disease in a cohort of patients who were sentinel node negative, but who had high risk GEP scores.20 This was a retrospective review of patients at three academic medical centers. Three-hundred and seven patients were identified who were sentinel node negative but who underwent GEP testing in the post-operative period. This was the experimental group. The control group consisted of 327 patients, from the same time period, who were similarly sentinel node negative, but who did not undergo GEP testing. In the control group, follow up was in concordance with NCCN recommendations, with no cross-sectional imaging for asymptomatic patients with Stage IA-IIA tumors. Patients with Stage IIB and IIC tumors typically underwent routine radiographic follow up (most commonly a CT scan of the chest, abdomen and pelvis and an MRI of the brain) at least once a year. Patients in the study group underwent routine radiographic follow up every 6 to 12 months. There were two primary endpoints to this study. The first was overall survival, and the second was tumor burden at the time of diagnosis. To calculate the tumor burden, the authors totaled all measurable sites of disease (in mm) on all available imaging studies when that first recurrence was noted. Time to progression was measured from date of diagnosis of the primary melanoma to the date of first visceral or lymphatic metastasis. 

A total of 307 patients with Stage I or II clinical disease and a GEP Class 2A/B result were included in the experimental group. In comparison, 327 stage I or II patients without GEP testing were included in the control group. There were 63 recurrences in the experimental group versus 46 in the control group, which was statistically significant (20.5% versus 14.1%, p=0.031). Among the 63 recurrences in the experimental group, 38 patients followed a routine imaging protocol, while 25 did not, so they were excluded from the primary endpoint analysis for tumor burden. None of the patients in the control group followed an imaging protocol.

Of the patients with recurrent melanoma, those in the experimental group were older (65.75 versus 59.20), had higher Breslow depths (3.72 mm versus 3.31 mm), and had advanced tumor staging (89.5% versus 71.4% of patients presenting clinical stage ≥II) compared to the control group at primary diagnosis. None of these differences were statistically significant. However, melanoma recurrence was detected earlier (25.50 months versus 35.35 months, p=0.004) in the experimental group at a lower overall tumor burden (73.10 mm versus 27.60 mm, p=0.027). A higher percentage of experimental patients started immunotherapy when offered (76.3% and 67.9%). At the time of the last follow-up, 76.3 percent (29/38) of the patients with melanoma recurrence in the experimental group were alive with an average follow-up time of 45.63 months, compared to 50.0 percent (14/28) of recurrent melanoma patients in the control group with an average follow-up time of 63.32 months. The difference in overall survival was statistically significant, with a chi-square p-value of 0.027. 

Limitations to this trial include its retrospective nature, as well as the small numbers of evaluable patients in both the experimental and control groups. In addition, there was a difference in average follow-up times between the control and experimental groups, with an average follow-up of 63.32 months and 45.63 months, respectively. Given that the follow-up time was longer in the control group, this may have led to more deaths being reported.

This study suggests that patients who received routine imaging after high-risk GEP test scores had an earlier recurrence diagnosis with lower tumor burden, leading to better clinical outcomes. This represents a paradigm shift in the intensity of follow up for patients with melanoma, specifically for patients felt to have relatively early (Stage I-II) disease. Identifying which sentinel node negative patients who may actually be at high risk for recurrent disease (GEP class 2A/2B), should help clinicians tailor follow up for each individual patient. There is at least one prospective trial ongoing which seeks to confirm this result and add to the evidence supporting the use of GEP in the management of patients with melanoma.

References

  1. Siegel, RL, Miller, KD, Wagle, NS, Jemal, A. Cancer statistics, 2023. CA Cancer J Clin. 2023; 73(1):17–48.
  2. Deschner, B, Wayne, JD. Follow-up of the melanoma patient. J Surg Oncol. 2019; 119: 262–268. 
  3. National Comprehensive Cancer Network. Melanoma (Version2.2023). https://www.nccn.org/professionals/physician_gls/pdf/cutaneous_melanoma.pdf. Accessed October 1, 2023. 
  4. Gerami P et al. Development of a prognostic genetic signature to predict the metastatic risk associated with cutaneous melanoma. Clin Cancer Res. 2015;21(1):175–183. 
  5. Gerami P et al. Gene expression profiling for molecular staging of cutaneous melanoma in patients undergoing sentinel lymph node biopsy. J Am Acad Dermatol. 2015;72(5):780–5.e3. 
  6. Zager JS et al. Performance of a prognostic 31-gene expression profile in an independent cohort of 523 cutaneous melanoma patients. BMC Cancer. 2018;18(1):130. 
  7. Whitman ED et al. Integrating 31-gene expression profiling with clinicopathologic features to optimize cutaneous melanoma sentinel lymph node metastasis prediction. JCO Precis Oncol. 2021.
  8. Jarell A et al. The 31-gene expression profle stratifes recurrence and metastasis risk in patients with cutaneous melanomax. Future Oncol. 2021;17(36):5023–5031. 
  9. Namikawa K, Yamazaki N. Targeted Therapy and Immunotherapy for Melanoma in Japan. Curr Treat Options Oncol. 2019;20(1):7. 
  10. Weiss SA, Wolchok JD, Sznol M. Immunotherapy of melanoma: facts and hopes. Clin Cancer Res. 2019; 25(17):5191–5201. 
  11. Lugowska I, Teterycz P, Rutkowski P. Immunotherapy of melanoma. Contemp Oncol (Pozn). 2018;22(1a):61–67.
  12. Poklepovic AS, Carvajal RD. Prognostic value of low tumor burden in patients with melanoma. Oncology (Williston Park). 2018;32(9):e90–e96.
  13. Ribas A et al. Association of pembrolizumab with tumor response and survival among patients with advanced melanoma. JAMA. 2016;315(15):1600–1609. 
  14. Huang AC et al. T-cell invigoration to tumour burden ratio associated with anti-PD-1 response. Nature. 2017;545(7652):60–65. 
  15. Meckbach D et al. Survival according to BRAF-V600 tumor mutations–an analysis o 437 patients with primary melanoma. PLoS ONE. 2014;9(1):e86194.
  16. Long GV et al. Dabrafenib plus trametinib versus dabrafenib monotherapy in patients with metastatic BRAF V600E/K-mutant melanoma: long-term survival and safety analysis of a phase 3 study. Ann Oncol. 2017;28(7):1631–1639.
  17. Podlipnik S et al. Cost-efectiveness analysis of imaging strategy for an intensive follow-up of patients with American Joint Committee on Cancer stage IIB, IIC and III malignant melanoma. Br J Dermatol. 2019;180(5):1190–1197. 
  18. Park TS et al. Routine computer tomography imaging for the detection of recurrences in high-risk melanoma patients. Ann Surg Oncol. 24(4):947–951
  19. Livingstone E et al. Prospective evaluation of follow-up in melanoma patients in Germany: results of a multicentre and longitudinal study. Eur J Cancer. 2015;51(5):653–667. 
  20. Dhillon S, Duarte-Bateman D, Fowler G, et al. Routine imaging guided by a 31-gene expression profile assay results in earlier detection of melanoma with decreased metastatic tumor burden compared to patients without surveillance imaging studies. Arch Dermatol Res. 2023 Oct;315(8):2295-2302. Epub 2023 Mar 28. Erratum in: Arch Dermatol Res. 2023 Apr 12.  

 

Commentary: 31-Gene Expression Profile Testing in Cutaneous Melanoma and Survival Outcomes in a Population-Based Analysis: A SEER Collaboration

J Clin Aesthet Dermatol. 2023;16(12 Suppl 1):S9–S11.

by Peter A. Prieto, MD, MPH

Dr. Prieto is with the Division of Surgical Oncology, Department of Surgery at the Wilmot Cancer Center, University of Rochester Medical Center in Rochester, New York. 

Disclosures: Dr. Prieto is a consultant and on the speaker’s bureau for Castle Biosciences, Inc.

Cutaneous melanoma (CM) is the fifth most common malignancy in the United States and the deadliest form of skin cancer.1  However, CM prognosis varies widely, with the lowest-risk patients having almost 100-percent five-year survival rates, while those with the highest risk have only 32 percent five-year survival rates.1,2 Clinicians must accurately assess a patient’s individual risk of poor outcomes to recommend the best treatment and surveillance management plan for that patient. Additionally, melanoma patients and survivors report high levels of anxiety and fear of cancer progression.3,4 Thus, tools that can accurately predict risk of recurrence, metastasis, and cancer-specific mortality can help clinicians make risk-appropriate management decisions with their patients and have the potential to ease patient fears about the uncertainty of their disease.5,6

The 31-gene expression profile (31-GEP) test assesses tumor gene expression to provide prognostic information about risk of sentinel lymph node biopsy (SLNB) positivity, tumor recurrence, metastasis, or death by stratifying risk into low (Class 1A), intermediate (Class 1B/2A), or high (Class 2B) categories.7,8  The test has been prospectively and retrospectively validated in numerous studies, most recently among patients included in the National Cancer Institute (NCI) Surveillance, Epidemiology and End Results (SEER) database, which covers over one-third of the United States population.9–12  The SEER collaboration study provides the largest population of patients assessed by the 31-GEP to date.9

In the SEER collaboration study, 31-GEP test results for patients tested from 2016 to 2018 were linked to patient data included in SEER registries, and a de-identified set of data including 4,687 patients with stage I–III CM was analyzed.9  Differences in melanoma-specific survival (MSS) and overall survival (OS) between 31-GEP risk stratification groups were assessed by Kaplan-Meier analysis, log-rank test, and Cox proportional hazards.  Multivariable analyses for risk stratification included 31-GEP class, age, Breslow thickness, ulceration, and lymph node status. Additionally, 31-GEP-tested patients were propensity score-matched to a group of untested patients to assess survival differences between tested and untested patients. In this analysis, 31-GEP-tested and untested patients were propensity score-matched by age, sex, race, socioeconomic status, year of diagnosis, follow-up time, T-stage, mitotic rate, nodal assessment, nodal positivity, and tumor location.  

Patients with low-risk 31-GEP results had higher three-year MSS and OS rates than those with intermediate- or high-risk results (MSS=99.7% vs. 97.1% vs. 89.6%, p<0.001 and OS=96.6% vs. 90.2% vs. 79.4%, p<0.001).  Multivariable Cox regression analysis identified the 31-GEP test result as the greatest predictor of melanoma-specific mortality (Class 2B HR=7.00 and Class 1B/2A HR=4.86). Other significant predictors were a positive lymph node (HR=2.64) and Breslow thickness (HR=1.16).  The 31-GEP result was also the strongest predictor of overall mortality (Class 2B HR=2.39 and Class 1B/2A HR=2.22); additional predictors of overall mortality included ulceration (HR=1.45; 95%), unknown LN status (HR=1.45), Breslow thickness (HR=1.14), and age (HR=1.08). Finally, of particular interest, patients tested with the 31-GEP had 29-percent lower melanoma-specific mortality and 17-percent lower overall mortality than matched patients who were untested.

The greatest strength of this study is the large, population-based, real-world cohort of patients included in the SEER data set. In almost 5,000 patients, the 31-GEP was confirmed as a significant predictor of melanoma-specific mortality and overall mortality, independent of factors incorporated into American Joint Committee on Cancer (AJCC) version 8 staging. To be effective in the clinic, a prognostic test must accurately stratify patient risk levels so that clinicians can feel confident in using the results to guide management decisions. Previous studies have shown that clinicians use 31-GEP test results to guide SLNB decisions in 50 to 85 percent of patients.5,10,13 In a prospective study evaluating use of SLNB, only patient preference had a greater influence on whether a biopsy was performed than 31-GEP results, and use of 31-GEP resulted in an approximately one-third SLNB reduction rate.5

Although this is the first study to find a survival benefit associated with the use of 31-GEP testing for CM, other studies have demonstrated that clinicians use 31-GEP results to guide treatment and surveillance management decisions with patients, and studies have shown appropriate treatment management leads to better patient outcomes.5,10,13  Importantly, a second study by Dhillon et al found that using the 31-GEP to guide imaging surveillance in patients with CM was associated with identifying recurrence earlier and at lower tumor burden, resulting in better survival outcomes.14,15  Accurate risk assessment allows clinicians and patients to make appropriate treatment and clinical management decisions based on a personalized risk assessment, leading to improved patient outcomes and longer survival.

As additional treatment options are developed for patients with CM, it becomes even more important to use tools that provide accurate risk stratification for patients.  New adjuvant therapies have greatly extended survival for patients with CM; however, they are not without risks, as up to 65 to 80 percent of patients receiving immunotherapy treatment will experience an adverse event, some of which are permanent and life-threatening.16 Additionally, the costs of newer therapeutics and more advanced imaging are high, burdening patients, their families, and the healthcare system.17,18 Thus, there is a critical need for accurate prognostic tools that can provide truly personalized risk assessments, such as the 31-GEP test, to be incorporated into clinical care for patients with CM. The 31-GEP can guide risk-aligned management plans and its use has now been directly associated with improved patient outcomes that allow clinicians to provide better care for their patients with this impactful skin cancer.

References

  1. Melanoma of the Skin – Cancer Stat Facts. SEER. Accessed September 7, 2023. https://seer.cancer.gov/statfacts/html/melan.html
  2. Miller KD, Nogueira L, Devasia T, et al. Cancer treatment and survivorship statistics, 2022. CA Cancer J Clin. Published online June 23, 2022. 
  3. Rogiers A, Leys C, De Cremer J, et al. Health-related quality of life, emotional burden, and neurocognitive function in the first generation of metastatic melanoma survivors treated with pembrolizumab: a longitudinal pilot study. Support Care Cancer. 2020;28(7):3267-3278.
  4. Bell KJL, Mehta Y, Turner RM, et al. Fear of new or recurrent melanoma after treatment for localised melanoma. Psycho-Oncology. 2017;26(11):1784-1791. 
  5. Yamamoto M, Sickle-Santanello B, Beard T, et al. The 31-gene expression profile test informs sentinel lymph node biopsy decisions in patients with cutaneous melanoma: results of a prospective, multicenter study. Curr Med Res Opin. 2023;39(3):417-423. 
  6. Ahmed K, Siegel JJ, Morgan-Linnell SK, LiPira K. Attitudes of patients with cutaneous melanoma toward prognostic testing using the 31-gene expression profile test. Cancer Medicine. Published online August 2022.
  7. Gerami P, Cook RW, Russell MC, et al. Gene expression profiling for molecular staging of cutaneous melanoma in patients undergoing sentinel lymph node biopsy. J Am Acad Dermatol. 2015;72(5):780-785.e3. 
  8. 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. 2015;21(1):175-183. 
  9. Bailey CN, Martin BJ, Petkov VI, et al. 31-Gene Expression Profile Testing in Cutaneous Melanoma and Survival Outcomes in a Population-Based Analysis: A SEER Collaboration. JCO Precis Oncol. 2023;7:e2300044.
  10. 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 Cutaneous Med. 2018;2(2):111-121. 
  11. Hsueh EC, DeBloom JR, Lee JH, et al. Long-Term Outcomes in a Multicenter, Prospective Cohort Evaluating the Prognostic 31-Gene Expression Profile for Cutaneous Melanoma. JCO Precision Oncology. 2021;5(5):589-601.
  12. Podlipnik S, Boada A, López-Estebaranz JL, et al. Using a 31-Gene Expression Profile Test to Stratify Patients with Stage I–II Cutaneous Melanoma According to Recurrence Risk: Update to a Prospective, Multicenter Study. Cancers. 2022;14(4):1060. 
  13. Berger AC, Davidson RS, Poitras JK, et al. Clinical impact of a 31-gene expression profile test for cutaneous melanoma in 156 prospectively and consecutively tested patients. Curr Med Res Opin. 2016;32(9):1599-1604. 
  14. Dhillon S, Duarte-Bateman D, Fowler G, et al. Routine imaging guided by a 31-gene expression profile assay results in earlier detection of melanoma with decreased metastatic tumor burden compared to patients without surveillance imaging studies. Arch Dermatol Res. 2023;315(8):2295-2302.
  15. Freeman M, Laks S. Surveillance imaging for metastasis in high-risk melanoma: importance in individualized patient care and survivorship. Melanoma Manag. 2019;6(1).
  16. Kennedy LB, Salama AKS. A Review of Immune-Mediated Adverse Events in Melanoma. Oncol Ther. 2019;7(2):101-120. 
  17.  Kao SYZ, Ekwueme DU, Holman DM, Rim SH, Thomas CC, Saraiya M. Economic burden of skin cancer treatment in the USA: an analysis of the Medical Expenditure Panel Survey Data, 2012-2018. Cancer Causes Control. 2023;34(3):205-212. 
  18. Gogebakan KC, Mukherjee K, Berry EG, Sonmez K, Leachman SA, Etzioni R. Impact of novel systemic therapies on the first-year costs of care for melanoma among Medicare beneficiaries. Cancer. 2021;127(16):2926-2933.  

 

Closing

by Laura Ferris, MD, PhD

J Clin Aesthet Dermatol. 2023;16(12 Suppl 1):S12.

Disclosures: Dr. Ferris has served as an investigator for Castle Biosciences, Inc. 

The studies discussed by Drs. Garland-Kledzik, Wayne, and Prieto have several interesting findings. (1) In the SEER registry, in patients rigorously matched for multiple prognostic factors, 31-GEP testing was associated with better melanoma-specific and overall survival. (2) Among patients with early stage (I or II) melanoma who have a class 2 GEP who were followed with 18FDG-PET-CT, 12.1 percent had a scan-detected recurrence within three years, with additional patients presenting with incidentally noted or symptomatic recurrences, bringing the total recurrence rate in this population to over 16 percent. (3) Patients with stage I or II, class 2 melanoma followed with a routine imaging protocol (usually CT scan of chest, abdomen, and pelvis every three months and brain MRI every six months) were more likely than stage I or II melanoma patients without GEP testing who did not undergo surveillance to be diagnosed with recurrence earlier and with a lower tumor volume. Interestingly, among patients with recurrence, more patients were alive at the time of last follow up among those who underwent routine surveillance based on GEP testing than among those with recurrence who did not undergo GEP testing or routine radiographic surveillance.

Taken together, the findings in these studies suggest that imaging guided by 31-GEP score may help to identify tumor progression earlier. This may lead to earlier treatment, which may have an associated mortality benefit. While routine surveillance of all patients could theoretically have the same benefit, this would come at a great cost given the sheer number of patients diagnosed with stage I and II melanoma annually. Much like sentinel lymph node biopsy, radiographic imaging is not without risk including exposure to contrast medium and radiation exposure. Earlier identification of metastatic disease may be advantageous, as several studies have shown better outcomes in patients with lower tumor burden.1

As treatment options for patients with melanoma increase, so do the associated cost to the healthcare system. Both cost and impact on access to care make surveillance for all patients with earlier stage disease impractical. Identifying a higher risk population using GEP can be helpful in excluding about 75 percent of patients who are at lower risk of recurrence. Better stratification of risk will also be helpful as immunotherapy becomes an option for patients with earlier stage melanoma based on the recent approvals of pembrolizumab and now nivolumab for stage IIB and IIC melanoma in the adjuvant setting. Both drugs can improve survival but at a high financial cost and risk of immune-related toxicities. 

In summary, GEP has been shown to provide important, independent prognostic information with patients with melanoma. This may help us to target those patients at highest risk of recurrence, particularly those who may be missed by our current staging system, for more intense surveillance and treatment. Data such as that presented in these three studies help to form the foundation of our understanding of how GEP can guide patient care and inform future studies.

References

  1. Annovazzi A, Ferraresi V, Rea S, Russillo M, Renna D, Carpano S, Sciuto R. Prognostic value of total metabolic tumour volume and therapy-response assessment by [18F]FDG PET/CT in patients with metastatic melanoma treated with BRAF/MEK inhibitors. Eur Radiol. 2022 May;32(5):3398-3407.  
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