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Sun J, Karasaki KM, Farma JM. The Use of Gene Expression Profiling and Biomarkers in Melanoma Diagnosis and Predicting Recurrence: Implications for Surveillance and Treatment. Cancers (Basel) 2024; 16:583. [PMID: 38339333 PMCID: PMC10854922 DOI: 10.3390/cancers16030583] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2023] [Revised: 01/22/2024] [Accepted: 01/26/2024] [Indexed: 02/12/2024] Open
Abstract
Cutaneous melanoma is becoming more prevalent in the United States and has the highest mortality among cutaneous malignancies. The majority of melanomas are diagnosed at an early stage and, as such, survival is generally favorable. However, there remains prognostic uncertainty among subsets of early- and intermediate-stage melanoma patients, some of whom go on to develop advanced disease while others remain disease-free. Melanoma gene expression profiling (GEP) has evolved with the notion to help bridge this gap and identify higher- or lower-risk patients to better tailor treatment and surveillance protocols. These tests seek to prognosticate melanomas independently of established AJCC 8 cancer staging and clinicopathologic features (sex, age, primary tumor location, thickness, ulceration, mitotic rate, lymphovascular invasion, microsatellites, and/or SLNB status). While there is a significant opportunity to improve the accuracy of melanoma prognostication and diagnosis, it is equally important to understand the current landscape of molecular profiling for melanoma treatment. Society guidelines currently do not recommend molecular testing outside of clinical trials for melanoma clinical decision making, citing insufficient high-quality evidence guiding indications for the testing and interpretation of results. The goal of this chapter is to review the available literature for GEP testing for melanoma diagnosis and prognostication and understand their place in current treatment paradigms.
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Affiliation(s)
- James Sun
- Department of Surgical Oncology, Fox Chase Cancer Center, Philadelphia, PA 19002, USA;
| | | | - Jeffrey M. Farma
- Department of Surgical Oncology, Fox Chase Cancer Center, Philadelphia, PA 19002, USA;
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Waseh S, Lee JB. Advances in melanoma: epidemiology, diagnosis, and prognosis. Front Med (Lausanne) 2023; 10:1268479. [PMID: 38076247 PMCID: PMC10703395 DOI: 10.3389/fmed.2023.1268479] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2023] [Accepted: 10/13/2023] [Indexed: 06/30/2024] Open
Abstract
Unraveling the multidimensional complexities of melanoma has required concerted efforts by dedicated community of researchers and clinicians battling against this deadly form of skin cancer. Remarkable advances have been made in the realm of epidemiology, classification, diagnosis, and therapy of melanoma. The treatment of advanced melanomas has entered the golden era as targeted personalized therapies have emerged that have significantly altered the mortality rate. A paradigm shift in the approach to melanoma classification, diagnosis, prognosis, and staging is underway, fueled by discoveries of genetic alterations in melanocytic neoplasms. A morphologic clinicopathologic classification of melanoma is expected to be replaced by a more precise molecular based one. As validated, convenient, and cost-effective molecular-based tests emerge, molecular diagnostics will play a greater role in the clinical and histologic diagnosis of melanoma. Artificial intelligence augmented clinical and histologic diagnosis of melanoma is expected to make the process more streamlined and efficient. A more accurate model of prognosis and staging of melanoma is emerging based on molecular understanding melanoma. This contribution summarizes the recent advances in melanoma epidemiology, classification, diagnosis, and prognosis.
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Affiliation(s)
- Shayan Waseh
- Department of Dermatology, Temple University Hospital, Philadelphia, PA, United States
| | - Jason B. Lee
- Department of Dermatology, Thomas Jefferson University, Philadelphia, PA, United States
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Sadurní MB, Meves A. Breslow thickness 2.0: Why gene expression profiling is a step toward better patient selection for sentinel lymph node biopsies. Mod Pathol 2022; 35:1509-1514. [PMID: 35654998 PMCID: PMC9162102 DOI: 10.1038/s41379-022-01101-y] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2021] [Revised: 04/23/2022] [Accepted: 05/05/2022] [Indexed: 12/20/2022]
Abstract
Risk-stratification of cutaneous melanoma is important. Patients want to know what to expect after diagnosis, and physicians need to decide on a treatment plan. Historically, melanoma that had spread beyond the skin and regional lymph nodes was largely incurable, and the only approach to preventing a bad outcome was surgery. Through the seminal work of Alexander Breslow and Donald Morton, a system was devised to carefully escalate surgery based on primary tumor thickness and sentinel lymph node status. Today, we know that prophylactic lymph node dissections do not improve survival, but we continue to appreciate the prognostic implications of a positive sentinel node and the benefits of removing nodal metastases, which facilitates locoregional disease control. However, the question arises whether we can better select patients for sentinel lymph node biopsies (SLNB) as, currently, 85% of these procedures are negative and non-therapeutic. Here, we argue that gene expression profiling (GEP) of the diagnostic biopsy is a valuable step toward better patient selection when combined with reliable clinicopathologic (CP) information such as patient age and Breslow thickness. Recently, a CP-GEP-based classifier of nodal metastasis risk, the Merlin Assay, has become commercially available. While CP-GEP is still being validated in prospective studies, preliminary data suggest that it is an independent predictor of nodal metastasis, outperforming clinicopathological variables. The hunt is on for Breslow thickness 2.0.
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Affiliation(s)
- Mariana B. Sadurní
- grid.66875.3a0000 0004 0459 167XDepartment of Dermatology, Mayo Clinic, 200 First Street SW, Rochester, MN 55905 USA
| | - Alexander Meves
- Department of Dermatology, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA.
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Garg M, Couturier DL, Nsengimana J, Fonseca NA, Wongchenko M, Yan Y, Lauss M, Jönsson GB, Newton-Bishop J, Parkinson C, Middleton MR, Bishop DT, McDonald S, Stefanos N, Tadross J, Vergara IA, Lo S, Newell F, Wilmott JS, Thompson JF, Long GV, Scolyer RA, Corrie P, Adams DJ, Brazma A, Rabbie R. Tumour gene expression signature in primary melanoma predicts long-term outcomes. Nat Commun 2021; 12:1137. [PMID: 33602918 PMCID: PMC7893180 DOI: 10.1038/s41467-021-21207-2] [Citation(s) in RCA: 31] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2020] [Accepted: 01/15/2021] [Indexed: 02/08/2023] Open
Abstract
Adjuvant systemic therapies are now routinely used following resection of stage III melanoma, however accurate prognostic information is needed to better stratify patients. We use differential expression analyses of primary tumours from 204 RNA-sequenced melanomas within a large adjuvant trial, identifying a 121 metastasis-associated gene signature. This signature strongly associated with progression-free (HR = 1.63, p = 5.24 × 10-5) and overall survival (HR = 1.61, p = 1.67 × 10-4), was validated in 175 regional lymph nodes metastasis as well as two externally ascertained datasets. The machine learning classification models trained using the signature genes performed significantly better in predicting metastases than models trained with clinical covariates (pAUROC = 7.03 × 10-4), or published prognostic signatures (pAUROC < 0.05). The signature score negatively correlated with measures of immune cell infiltration (ρ = -0.75, p < 2.2 × 10-16), with a higher score representing reduced lymphocyte infiltration and a higher 5-year risk of death in stage II melanoma. Our expression signature identifies melanoma patients at higher risk of metastases and warrants further evaluation in adjuvant clinical trials.
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Affiliation(s)
- Manik Garg
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Hinxton, Cambridgeshire, UK
| | - Dominique-Laurent Couturier
- Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, UK
| | - Jérémie Nsengimana
- University of Leeds School of Medicine, Leeds, United Kingdom
- Biostatistics Research Group, Population Health Sciences Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, UK
| | - Nuno A Fonseca
- CIBIO/InBIO-Centro de Investigação em Biodiversidade e Recursos Genéticos, Universidade do Porto, Rua Padre Armando Quintas, 4485-601, Vairão, Portugal
| | - Matthew Wongchenko
- Oncology Biomarker Development, Genentech Inc., 1 DNA Way, South San Francisco, CA, 94080, USA
| | - Yibing Yan
- Oncology Biomarker Development, Genentech Inc., 1 DNA Way, South San Francisco, CA, 94080, USA
| | - Martin Lauss
- Lund University Cancer Center, Lund University, Lund, Sweden
| | - Göran B Jönsson
- Lund University Cancer Center, Lund University, Lund, Sweden
| | | | - Christine Parkinson
- Cambridge Cancer Centre, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - Mark R Middleton
- Oxford NIHR Biomedical Research Centre and Department of Oncology, University of Oxford, Oxford, UK
| | | | - Sarah McDonald
- Department of Pathology, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - Nikki Stefanos
- Department of Pathology, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - John Tadross
- Department of Pathology, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - Ismael A Vergara
- Melanoma Institute Australia, The University of Sydney, North Sydney, NSW, Australia
- Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia
| | - Serigne Lo
- Melanoma Institute Australia, The University of Sydney, North Sydney, NSW, Australia
- Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia
- Institute for Research and Medical Consultations (IRMC), Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia
| | - Felicity Newell
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - James S Wilmott
- Melanoma Institute Australia, The University of Sydney, North Sydney, NSW, Australia
- Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia
| | - John F Thompson
- Melanoma Institute Australia, The University of Sydney, North Sydney, NSW, Australia
- Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia
- Discipline of Surgery, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia
| | - Georgina V Long
- Melanoma Institute Australia, The University of Sydney, North Sydney, NSW, Australia
- Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia
- Royal North Shore and Mater Hospitals, Sydney, Australia
| | - Richard A Scolyer
- Melanoma Institute Australia, The University of Sydney, North Sydney, NSW, Australia
- Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia
- Tissue Pathology and Diagnostic Oncology, Royal Prince Alfred Hospital and New South Wales Health Pathology, Sydney, NSW, Australia
| | - Pippa Corrie
- Cambridge Cancer Centre, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - David J Adams
- Experimental Cancer Genetics, The Wellcome Sanger Institute, Hinxton, Cambridgeshire, UK
| | - Alvis Brazma
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Hinxton, Cambridgeshire, UK
| | - Roy Rabbie
- Cambridge Cancer Centre, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK.
- Experimental Cancer Genetics, The Wellcome Sanger Institute, Hinxton, Cambridgeshire, UK.
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Kangas-Dick AW, Greenbaum A, Gall V, Groisberg R, Mehnert J, Chen C, Moore DF, Berger AC, Koshenkov V. Evaluation of a Gene Expression Profiling Assay in Primary Cutaneous Melanoma. Ann Surg Oncol 2021; 28:4582-4589. [PMID: 33486642 DOI: 10.1245/s10434-020-09563-7] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2020] [Accepted: 12/17/2020] [Indexed: 11/18/2022]
Abstract
BACKGROUND A significant proportion of deaths from cutaneous melanoma occur among patients with an initial diagnosis of stage 1 or 2 disease. The Decision-Dx Melanoma (DDM) 31-gene assay attempts to stratify these patients by risk of recurrence. This study aimed to evaluate this assay in a large single-institution series. METHODS A retrospective chart review of all patients who underwent surgery for melanoma at a large academic cancer center with DDM results was performed. Patient demographics, tumor pathologic characteristics, sentinel node status, gene expression profile (GEP) class, and recurrence-free survival (RFS) were reviewed. The primary outcomes were recurrence of melanoma and distant metastatic recurrence. RESULTS Data from 361 patients were analyzed. The median follow-up period was 15 months. Sentinel node biopsy was performed for 75.9% (n = 274) of the patients, 53 (19.4%) of whom tested positive. Overall, 13.6% (n = 49) of the patients had recurrence, and 8% (n = 29) had distant metastatic recurrence. The 3- and 5-year RFS rates were respectively 85% and 75% for the class 1A group, 74% and 47% for the class 1B/class 2A group, and 54% and 45% for the class 2B group. Increased Breslow thickness, ulceration, mitoses, sentinel node biopsy positivity, and GEP class 2B status were significantly associated with RFS and distant metastasis-free survival (DMFS) in the univariate analysis (all p < 0.05). In the multivariate analysis, only Breslow thickness and ulceration were associated with RFS (p < 0.003), and only Breslow thickness was associated with DMFS (p < 0.001). CONCLUSION Genetic profiling of cutaneous melanoma can assist in predicting recurrence and help determine the need for close surveillance. However, traditional pathologic factors remain the strongest independent predictors of recurrence risk.
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Affiliation(s)
- Aaron W Kangas-Dick
- Division of Surgical Oncology, Rutgers Cancer Institute of New Jersey (CINJ), New Brunswick, NJ, USA. .,Department of Surgery, Maimonides Medical Center, Brooklyn, NY, USA.
| | - Alissa Greenbaum
- Division of Surgical Oncology, Rutgers Cancer Institute of New Jersey (CINJ), New Brunswick, NJ, USA
| | - Victor Gall
- Division of Surgical Oncology, Rutgers Cancer Institute of New Jersey (CINJ), New Brunswick, NJ, USA
| | - Roman Groisberg
- Division of Medical Oncology, Rutgers Cancer Institute of New Jersey, New Brunswick, NJ, USA
| | - Janice Mehnert
- Division of Medical Oncology, Rutgers Cancer Institute of New Jersey, New Brunswick, NJ, USA
| | - Chunxia Chen
- Division of Biometrics, Rutgers Cancer Institute of New Jersey, New Brunswick, NJ, USA
| | - Dirk F Moore
- Division of Biometrics, Rutgers Cancer Institute of New Jersey, New Brunswick, NJ, USA.,Department of Biostatistics and Epidemiology, Rutgers School of Public Health, Piscataway, NJ, USA
| | - Adam C Berger
- Division of Surgical Oncology, Rutgers Cancer Institute of New Jersey (CINJ), New Brunswick, NJ, USA
| | - Vadim Koshenkov
- Division of Surgical Oncology, Rutgers Cancer Institute of New Jersey (CINJ), New Brunswick, NJ, USA
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Kangas-Dick A, Berger AC, Koshenkov V. ASO Author Reflections: Gene Expression Profiling for Melanoma: Is it Ready for Prime Time? Ann Surg Oncol 2021; 28:4590-4591. [PMID: 33479864 DOI: 10.1245/s10434-021-09599-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2021] [Accepted: 01/05/2021] [Indexed: 11/18/2022]
Affiliation(s)
- Aaron Kangas-Dick
- Division of Surgical Oncology, Rutgers Cancer Institute of New Jersey, New Brunswick, NJ, USA. .,Department of Surgery, Maimonides Medical Center, Brooklyn, NY, USA.
| | - Adam C Berger
- Division of Surgical Oncology, Rutgers Cancer Institute of New Jersey, New Brunswick, NJ, USA
| | - Vadim Koshenkov
- Division of Surgical Oncology, Rutgers Cancer Institute of New Jersey, New Brunswick, NJ, USA
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