Use of a prognostic gene expression profile test for T1 cutaneous melanoma: Will it help or harm patients?

The Use of Gene Expression Profiling and Biomarkers in Melanoma Diagnosis and Predicting Recurrence: Implications for Surveillance and Treatment

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.

Advances in melanoma: epidemiology, diagnosis, and prognosis

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.

Breslow thickness 2.0: Why gene expression profiling is a step toward better patient selection for sentinel lymph node biopsies

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.

Using a Clinicopathologic and Gene Expression (CP-GEP) Model to Identify Stage I-II Melanoma Patients at Risk of Disease Relapse

Background: The current standard of care for patients without sentinel node (SN) metastasis (i.e., stage I−II melanoma) is watchful waiting, while >40% of patients with stage IB−IIC will eventually present with disease recurrence or die as a result of melanoma. With the prospect of adjuvant therapeutic options for patients with a negative SN, we assessed the performance of a clinicopathologic and gene expression (CP-GEP) model, a model originally developed to predict SN metastasis, to identify patients with stage I−II melanoma at risk of disease relapse. Methods: This study included patients with cutaneous melanoma ≥18 years of age with a negative SN between October 2006 and December 2017 at the Sahlgrenska University Hospital (Sweden) and Erasmus MC Cancer Institute (The Netherlands). According to the CP-GEP model, which can be applied to the primary melanoma tissue, the patients were stratified into high or low risk of recurrence. The primary aim was to assess the 5-year recurrence-free survival (RFS) of low- and high-risk CP-GEP. A secondary aim was to compare the CP-GEP model with the EORTC nomogram, a model based on clinicopathological variables only. Results: In total, 535 patients (stage I−II) were included. CP-GEP stratification among these patients resulted in a 5-year RFS of 92.9% (95% confidence interval (CI): 86.4−96.4) in CP-GEP low-risk patients (n = 122) versus 80.7% (95%CI: 76.3−84.3) in CP-GEP high-risk patients (n = 413; hazard ratio 2.93 (95%CI: 1.41−6.09), p < 0.004). According to the EORTC nomogram, 25% of the patients were classified as having a ‘low risk’ of recurrence (96.8% 5-year RFS (95%CI 91.6−98.8), n = 130), 49% as ‘intermediate risk’ (88.4% 5-year RFS (95%CI 83.6−91.8), n = 261), and 26% as ‘high risk’ (61.1% 5-year RFS (95%CI 51.9−69.1), n = 137). Conclusion: In these two independent European cohorts, the CP-GEP model was able to stratify patients with stage I−II melanoma into two groups differentiated by RFS.

A novel melanoma prediction model for imbalanced data using optimized SqueezeNet by bald eagle search optimization

Skin lesion classification plays a crucial role in diagnosing various gene and related local medical cases in the field of dermoscopy. In this paper, a new model for the classification of skin lesions as either normal or melanoma is presented. The proposed melanoma prediction model was evaluated on a large publicly available dataset called ISIC 2020. The main challenge of this dataset is severe class imbalance. This paper proposes an approach to overcome this problem using a random over-sampling method followed by data augmentation. Moreover, a new hybrid version of a convolutional neural network architecture and bald eagle search (BES) optimization is proposed. The BES algorithm is used to find the optimal values of the hyperparameters of a SqueezeNet architecture. The proposed melanoma skin cancer prediction model obtained an overall accuracy of 98.37%, specificity of 96.47%, sensitivity of 100%, f-score of 98.40%, and area under the curve of 99%. The experimental results showed the robustness and efficiency of the proposed model compared with VGG19, GoogleNet, and ResNet50. Additionally, the results showed that the proposed model was very competitive compared with the state of the art.

Evaluation of a Gene Expression Profiling Assay in Primary Cutaneous Melanoma

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.

Performance of Gene Expression Profile Tests for Prognosis in Patients With Localized Cutaneous Melanoma: A Systematic Review and Meta-analysis

Importance

The performance of prognostic gene expression profile (GEP) tests for cutaneous melanoma is poorly characterized.

Objective

To systematically assess the performance of commercially available GEP tests in patients with American Joint Committee on Cancer (AJCC) stage I or stage II disease.

Data Sources

For this systematic review and meta-analysis, comprehensive searches of PubMed/MEDLINE, Embase, and Web of Science were conducted on December 12, 2019, for English-language studies of humans without date restrictions.

Study Selection

Two reviewers identified GEP external validation studies of patients with localized melanoma. After exclusion criteria were applied, 7 studies (8%; 5 assessing DecisionDx-Melanoma and 2 assessing MelaGenix) were included.

Data Extraction and Synthesis

Data were extracted using an adaptation of the Checklist for Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modeling Studies (CHARMS-PF). When feasible, meta-analysis using random-effects models was performed. Risk of bias and level of evidence were assessed with the Quality in Prognosis Studies tool and an adaptation of Grading of Recommendations Assessment, Development, and Evaluation.

Main Outcomes and Measures

Proportion of patients with or without melanoma recurrence correctly classified by the GEP test as being at high or low risk.

Results

In the 7 included studies, a total of 1450 study participants contributed data (age and sex unknown). The performance of both GEP tests varied by AJCC stage. Of patients tested with DecisionDx-Melanoma, 623 had stage I disease (6 true-positive [TP], 15 false-negative, 61 false-positive, and 541 true-negative [TN] results) and 212 had stage II disease (59 TP, 13 FN, 78 FP, and 62 TN results). Among patients with recurrence, DecisionDx-Melanoma correctly classified 29% with stage I disease and 82% with stage II disease. Among patients without recurrence, the test correctly classified 90% with stage I disease and 44% with stage II disease. Of patients tested with MelaGenix, 88 had stage I disease (7 TP, 15 FN, 15 FP, and 51 TN results) and 245 had stage II disease (59 TP, 19 FN, 95 FP, and 72 TN results). Among patients with recurrence, MelaGenix correctly classified 32% with stage I disease and 76% with stage II disease. Among patients without recurrence, the test correctly classified 77% with stage I disease and 43% with stage II disease.

Conclusions and Relevance

The prognostic ability of GEP tests among patients with localized melanoma varied by AJCC stage and appeared to be poor at correctly identifying recurrence in patients with stage I disease, suggesting limited potential for clinical utility in these patients.

Prognostic Gene Expression Profiling in Cutaneous Melanoma: Identifying the Knowledge Gaps and Assessing the Clinical Benefit

Importance

Use of prognostic gene expression profile (GEP) testing in cutaneous melanoma (CM) is rising despite a lack of endorsement as standard of care.

Objective

To develop guidelines within the national Melanoma Prevention Working Group (MPWG) on integration of GEP testing into the management of patients with CM, including (1) review of published data using GEP tests, (2) definition of acceptable performance criteria, (3) current recommendations for use of GEP testing in clinical practice, and (4) considerations for future studies.

Evidence Review

The MPWG members and other international melanoma specialists participated in 2 online surveys and then convened a summit meeting. Published data and meeting abstracts from 2015 to 2019 were reviewed.

Findings

The MPWG members are optimistic about the future use of prognostic GEP testing to improve risk stratification and enhance clinical decision-making but acknowledge that current utility is limited by test performance in patients with stage I disease. Published studies of GEP testing have not evaluated results in the context of all relevant clinicopathologic factors or as predictors of regional nodal metastasis to replace sentinel lymph node biopsy (SLNB). The performance of GEP tests has generally been reported for small groups of patients representing particular tumor stages or in aggregate form, such that stage-specific performance cannot be ascertained, and without survival outcomes compared with data from the American Joint Committee on Cancer 8th edition melanoma staging system international database. There are significant challenges to performing clinical trials incorporating GEP testing with SLNB and adjuvant therapy. The MPWG members favor conducting retrospective studies that evaluate multiple GEP testing platforms on fully annotated archived samples before embarking on costly prospective studies and recommend avoiding routine use of GEP testing to direct patient management until prospective studies support their clinical utility.

Conclusions and Relevance

More evidence is needed to support using GEP testing to inform recommendations regarding SLNB, intensity of follow-up or imaging surveillance, and postoperative adjuvant therapy. The MPWG recommends further research to assess the validity and clinical applicability of existing and emerging GEP tests. Decisions on performing GEP testing and patient management based on these results should only be made in the context of discussion of testing limitations with the patient or within a multidisciplinary group.

The role of integrins in melanoma: a review

Integrins are the major family of cell adhesion receptors in humans and essential for a wide range of normal physiology, including formation and maintenance of tissue structure integrity, cell migration, proliferation, and differentiation. Integrins also play a prominent role in tumor growth and metastasis. Translational research has tried to define the contribution of integrins to the phenotypic aggressiveness of melanoma because such knowledge is clinically useful. For example, differential expression of integrins in primary cutaneous melanoma can be used to distinguish indolent from aggressive, prometastatic melanoma. Recent studies have shown that gene expression-based testing of patient-derived melanoma tissue is feasible, and molecular tests may fully replace interventional surgical methods such as sentinel lymph node biopsies in the future. Because of their central role in mediating invasion and metastasis, integrins are likely to be useful biomarkers. Integrins are also attractive candidate targets for interventional therapy. This article focuses on the role of integrins in melanoma and highlights recent advances in the field of translational research.

Technological advances for the detection of melanoma: Advances in molecular techniques

The growth of molecular technologies analyzing skin cells and inherited genetic variations has the potential to address current gaps in both diagnostic accuracy and prognostication in patients with melanoma or in individuals who are at risk for developing melanoma. In the second article in this continuing medical education series, novel molecular technologies are reviewed. These have been developed as adjunct tools for melanoma management and include the Pigmented Lesion Assay, myPath Melanoma, and DecisionDx-Melanoma tests, and genetic testing in patients with a strong familial melanoma history. These tests are commercially available and marketed as ancillary tools for clinical decision-making, diagnosis, and prognosis. We review fundamental principles behind each test, discuss peer-reviewed literature assessing their performance, and highlight the utility and limitations of each assay. The goal of this article is to provide a comprehensive, evidence-based foundation for clinicians regarding the management of patients with difficult pigmented lesions.

Model Combining Tumor Molecular and Clinicopathologic Risk Factors Predicts Sentinel Lymph Node Metastasis in Primary Cutaneous Melanoma

PURPOSE

More than 80% of patients who undergo sentinel lymph node (SLN) biopsy have no nodal metastasis. Here we describe a model that combines clinicopathologic and molecular variables to identify patients with thin and intermediate thickness melanomas who may forgo the SLN biopsy procedure due to their low risk of nodal metastasis.

PATIENTS AND METHODS

Genes with functional roles in melanoma metastasis were discovered by analysis of next generation sequencing data and case control studies. We then used PCR to quantify gene expression in diagnostic biopsy tissue across a prospectively designed archival cohort of 754 consecutive thin and intermediate thickness primary cutaneous melanomas. Outcome of interest was SLN biopsy metastasis within 90 days of melanoma diagnosis. A penalized maximum likelihood estimation algorithm was used to train logistic regression models in a repeated cross validation scheme to predict the presence of SLN metastasis from molecular, clinical and histologic variables.

RESULTS

Expression of genes with roles in epithelial-to-mesenchymal transition (glia derived nexin, growth differentiation factor 15, integrin β3, interleukin 8, lysyl oxidase homolog 4, TGFβ receptor type 1 and tissue-type plasminogen activator) and melanosome function (melanoma antigen recognized by T cells 1) were associated with SLN metastasis. The predictive ability of a model that only considered clinicopathologic or gene expression variables was outperformed by a model which included molecular variables in combination with the clinicopathologic predictors Breslow thickness and patient age; AUC, 0.82; 95% CI, 0.78-0.86; SLN biopsy reduction rate of 42% at a negative predictive value of 96%.

CONCLUSION

A combined model including clinicopathologic and gene expression variables improved the identification of melanoma patients who may forgo the SLN biopsy procedure due to their low risk of nodal metastasis.

Melanoma pathology reporting and staging

The pathological diagnosis of melanoma can be challenging. The provision of an appropriate biopsy and pertinent history can assist in establishing an accurate diagnosis and reliable estimate of prognosis. In their reports, pathologists should document both the criteria on which the diagnosis was based as well as important prognostic parameters. For melanoma, such prognostic parameters include tumor thickness, ulceration, mitotic rate, lymphovascular invasion, neurotropism, and tumor-infiltrating lymphocytes. Disease staging is important for risk stratifying melanoma patients into prognostic groups and patient management recommendations are often stage based. The 8th edition American Joint Committee on Cancer (AJCC) Melanoma Staging System was implemented in 2018 and several important changes were made. Tumor thickness and ulceration remain the key T category criteria. T1b melanomas were redefined as either ulcerated melanomas <1.0 mm thick or nonulcerated melanomas 0.8-1.0 mm thick. Although mitotic rate was removed as a T category criterion in the 8th edition, it remains a very important prognostic factor and should continue to be documented in primary melanoma pathology reports. It was also recommended in the 8th edition that tumor thickness be recorded to the nearest 0.1 mm (rather than the nearest 0.01 mm). In the future, incorporation of additional prognostic parameters beyond those utilized in the current version of the staging system into (web based) prognostic models/clinical tools will likely facilitate more personalized prognostic estimates. Evaluation of molecular markers of prognosis is an active area of current research; however, additional data are needed before it would be appropriate to recommend use of such tests in routine clinical practice.

Prognostic gene expression profiling in melanoma: necessary steps to incorporate into clinical practice

Prognostic gene expression profiling (GEP) tests for cutaneous melanoma (CM) are not recommended in current guidelines outside of a clinical trial. However, their use is becoming more prevalent and some practitioners are using GEP tests to guide patient management. Thus, there is an urgent need to bridge this gap between test usage and clinical guideline recommendations by obtaining high-quality evidence to guide us toward best practice use of GEP testing in CM patients. We focus here on the opportunities and uncertainties associated with prognostic GEP testing in CM, review how GEP testing was incorporated into clinical care guidelines for uveal melanoma and breast cancer and discuss the role of clinical trials to determine best use in patients with CM.