Identification of patients at risk of metastasis using a prognostic 31-gene expression profile in subpopulations of melanoma patients with favorable outcomes by standard criteria

Long-term outcomes and patterns of recurrence in patients with thin melanoma and a negative sentinel lymph node biopsy: a single-center experience

The majority of patients diagnosed with melanoma have thin melanomas (≤1 mm). Data on the rate and pattern of recurrence after a negative sentinel lymph node biopsy (SLNB) are sparse. We retrospectively searched our institutional database and retrieved the records of patients with thin melanomas who underwent an SLNB with negative results. We analyzed patterns of recurrence, time to recurrence, and mode of diagnosis. Thirteen of the 198 patients with thin melanomas and negative SLNB results had tumor recurrence (6.5%): two local in transit (15.4%), three regional (21.3%), and eight distant (61.5%). Distant recurrences tended to occur later than local or regional ones [median disease-free survival = 50 months (95% confidence interval: 36.1-63.9) vs. 34 and 15 months (95% confidence interval: 5.4-24.6), P  = 0.005, respectively]. The percentage of patients with tumor thickness ≥0.8 mm was higher among those who sustained recurrence (84.6 vs. 64.9% for no recurrence, P  = 0.04). The majority of patients with recurrence were not being followed up when diagnosed (69%), and they are presented because of clinical symptoms. Patients with recurrence had lower survival compared with those without recurrence (median: 118 months vs. ongoing survival, P  < 0.001, respectively). Melanoma recurrence in patients with thin melanomas and negative SLNBs is rare, tends to be distant, and negatively affects prognosis. Recurrence tends to occur in patients with melanoma thickness ≥0.8 mm. Further studies are needed to identify patients with high recurrence risk and determine optimal follow-up protocols.

Society of Surgical Oncology Consensus Statement: Assessing the Evidence for and Utility of Gene Expression Profiling of Primary Cutaneous Melanoma

INTRODUCTION

Gene expression profiling (GEP) of primary cutaneous melanoma aims to offer prognostic and predictive information to guide clinical care. Despite limited evidence of clinical utility, these tests are increasingly incorporated into clinical care.

METHODS

A panel of melanoma experts from the Society of Surgical Oncology convened to develop recommendations regarding the use of GEP to guide management of patients with melanoma. The use of currently available GEP tests were evaluated in three clinical scenarios: (1) the utility in patient selection for sentinel lymph node biopsy; (2) the utility to guide surveillance; and (3) the utility to inform adjuvant therapy. As a basis for these recommendations, the panel performed a systematic review of the literature, including articles published from January 2012 until August 2023.

RESULTS

After review of 137 articles, 50 met the inclusion criteria. These articles included evidence related to three available GEP tests: 31-GEP, CP-GEP, and 11-GEP. The consensus recommendations were finalized using a modified Delphi process. The panel found that current evidence often fails to account for known clinicopathologic risk factors and lacks high-level data. The panel recognizes that the study of GEP tests is still evolving. The integration of GEP into routine clinical practice for predicting sentinel lymph node status and patient prognosis in melanoma is therefore not currently recommended.

CONCLUSION

At present, GEP should be considered primarily an investigational tool, ideally used in the context of clinical trials or specialized research settings.

Circulating tumor DNA-based assessment of molecular residual disease in non-metastatic melanoma

In patients with resected non-metastatic melanoma, the liquid biopsy for the assessment of molecular residual disease (MRD) by circulating tumour DNA (ctDNA) represents a promising tool to stratify the risk and to monitor tumour evolution. However, its validation requires the demonstration of analytical validity, clinical validity and utility. Indeed, the development of sensitive and specific assays can optimize prognostication and eventually help clinicians to modulate adjuvant treatments, in order to improve clinical outcomes. Data about ctDNA-guided prognosis stratification is emerging, but clinical trials assessing ctDNA-guided therapeutic decisions are still ongoing. This review aims to depict the role of ctDNA-based MRD assessment in patients with non-metastatic melanoma and to provide a roadmap to face challenges for its introduction into clinical practice.

Reporting tumor genomic test results to SEER registries via linkages

BACKGROUND

Precision medicine has become a mainstay of cancer care in recent years. The National Cancer Institute (NCI) Surveillance, Epidemiology, and End Results (SEER) Program has been an authoritative source of cancer statistics and data since 1973. However, tumor genomic information has not been adequately captured in the cancer surveillance data, which impedes population-based research on molecular subtypes. To address this, the SEER Program has developed and implemented a centralized process to link SEER registries' tumor cases with genomic test results that are provided by molecular laboratories to the registries.

METHODS

Data linkages were carried out following operating procedures for centralized linkages established by the SEER Program. The linkages used Match*Pro, a probabilistic linkage software, and were facilitated by the registries' trusted third party (an honest broker). The SEER registries provide to NCI limited datasets that undergo preliminary evaluation prior to their release to the research community.

RESULTS

Recently conducted genomic linkages included OncotypeDX Breast Recurrence Score, OncotypeDX Breast Ductal Carcinoma in Situ, OncotypeDX Genomic Prostate Score, Decipher Prostate Genomic Classifier, DecisionDX Uveal Melanoma, DecisionDX Preferentially Expressed Antigen in Melanoma, DecisionDX Melanoma, and germline tests results in Georgia and California SEER registries.

CONCLUSIONS

The linkages of cancer cases from SEER registries with genomic test results obtained from molecular laboratories offer an effective approach for data collection in cancer surveillance. By providing de-identified data to the research community, the NCI's SEER Program enables scientists to investigate numerous research inquiries.

Management of melanoma: can we use gene expression profiling to help guide treatment and surveillance?

Although the incidence of cutaneous melanoma (CM) has been increasing annually, the mortality rate has been decreasing, likely due to better prevention, earlier detection, improved surveillance, and the development of new therapies. Current clinical management guidelines by the National Comprehensive Cancer Network (NCCN) are based on patient risk assignment using staging criteria established by the American Joint Committee on Cancer (AJCC). However, some patients with localized disease (stage I-II), generally considered to have a good prognosis, will develop metastatic disease and die, whereas some patients with later stage disease (stage III-IV) will be cured by surgery, adjuvant therapy, and/or systemic therapy. These results emphasize the importance of identifying patients whose risk may be over or underestimated with standard staging. Gene expression profile (GEP) tests are noninvasive molecular tests that assess the expression levels of a panel of validated genes, providing information about tumor prognosis, including the risk of recurrence, metastasis, and cancer-specific death. GEP tests can provide prognostic information beyond standard staging that may aid clinicians and patients in treatment and surveillance management decisions. This review describes how combining clinicopathologic staging with a robust assessment of tumor biology may provide information that will allow more refined intervention and long-term management.

The 31-Gene Expression Profile Test Outperforms AJCC in Stratifying Risk of Recurrence in Patients with Stage I Cutaneous Melanoma

BACKGROUND

Patients with stage I cutaneous melanoma (CM) are considered at low risk for metastasis or melanoma specific death; however, because the majority of patients are diagnosed with stage I disease, they represent the largest number of melanoma deaths annually. The 31-gene expression profile (31-GEP) test has been prospectively validated to provide prognostic information independent of staging, classifying patients as low (Class 1A), intermediate (Class 1B/2A), or high (Class 2B) risk of poor outcomes.

METHODS

Patients enrolled in previous studies of the 31-GEP were combined and evaluated for recurrence-free (RFS) and melanoma-specific survival (MSS) (n = 1261, "combined"). A second large, unselected real-world cohort (n = 5651) comprising clinically tested patients diagnosed 2013-2018 who were linked to outcomes data from the NCI Surveillance, Epidemiology, and End Results (SEER) Program registries was evaluated for MSS.

RESULTS

Combined cohort Class 1A patients had significantly higher RFS than Class 1B/2A or Class 2B patients (97.3%, 88.6%, 77.3%, p < 0.001)-better risk stratification than AJCC8 stage IA (97.5%) versus IB (89.3%). The SEER cohort showed better MSS stratification by the 31-GEP (Class 1A = 98.0%, Class 1B/2A = 97.5%, Class 2B = 92.3%; p < 0.001) than by AJCC8 staging (stage IA = 97.6%, stage IB = 97.9%; p < 0.001).

CONCLUSIONS

The 31-GEP test significantly improved patient risk stratification, independent of AJCC8 staging in patients with stage I CM. The 31-GEP provided greater separation between high- (Class 2B) and low-risk (Class 1A) groups than seen between AJCC stage IA and IB. These data support integrating the 31-GEP into clinical decision making for more risk-aligned management plans.

Relationship of Histopathologic Parameters and Gene Expression Profiling in Malignant Melanoma

BACKGROUND

Histopathologic characteristics (HC) are a mainstay in melanoma prognosis; gene expression profiling (GEP) has emerged as a potential additional independent value.

OBJECTIVE

To elucidate HC predictive of groups obtained via GEP of malignant melanoma.

METHODS

A retrospective study analyzing HC of 265 melanomas submitted for GEP over the course of 8 years. GEP was conducted as a part of regular clinicopathologic workup through Castle Biosciences Decision Dx®.

RESULTS

Of the 265 cases, the major HC found to have an association with reported gene expression profiles were melanoma histology subtype, depth of invasion, and presence of ulcer.

LIMITATIONS

This study is limited by its cross-sectional nature. Causation and long-term related outcomes of the use of GEP versus American Joint Committee on Cancer histopathologic staging cannot be ascertained by this design.

CONCLUSIONS

An association, but no definitive prediction, exists between histopathologic categories of depth of invasion, melanoma subtype, and presence or absence of ulcer and gene expression profiles. GEP adds valuable data to the evaluation of malignant melanomas that cannot be definitively predicted by conventional models. The findings add to needed groundwork for comparison of traditional markers and molecular genotyping and begins to build a robust predictive model for better outcomes in patients with malignant melanoma.

Society for Immunotherapy of Cancer (SITC) clinical practice guideline on immunotherapy for the treatment of melanoma, version 3.0

Since the first approval for immune checkpoint inhibitors (ICIs) for the treatment of cutaneous melanoma more than a decade ago, immunotherapy has completely transformed the treatment landscape of this chemotherapy-resistant disease. Combination regimens including ICIs directed against programmed cell death protein 1 (PD-1) with anti-cytotoxic T lymphocyte antigen-4 (CTLA-4) agents or, more recently, anti-lymphocyte-activation gene 3 (LAG-3) agents, have gained regulatory approvals for the treatment of metastatic cutaneous melanoma, with long-term follow-up data suggesting the possibility of cure for some patients with advanced disease. In the resectable setting, adjuvant ICIs prolong recurrence-free survival, and neoadjuvant strategies are an active area of investigation. Other immunotherapy strategies, such as oncolytic virotherapy for injectable cutaneous melanoma and bispecific T-cell engager therapy for HLA-A*02:01 genotype-positive uveal melanoma, are also available to patients. Despite the remarkable efficacy of these regimens for many patients with cutaneous melanoma, traditional immunotherapy biomarkers (ie, programmed death-ligand 1 expression, tumor mutational burden, T-cell infiltrate and/or microsatellite stability) have failed to reliably predict response. Furthermore, ICIs are associated with unique toxicity profiles, particularly for the highly active combination of anti-PD-1 plus anti-CTLA-4 agents. The Society for Immunotherapy of Cancer (SITC) convened a panel of experts to develop this clinical practice guideline on immunotherapy for the treatment of melanoma, including rare subtypes of the disease (eg, uveal, mucosal), with the goal of improving patient care by providing guidance to the oncology community. Drawing from published data and clinical experience, the Expert Panel developed evidence- and consensus-based recommendations for healthcare professionals using immunotherapy to treat melanoma, with topics including therapy selection in the advanced and perioperative settings, intratumoral immunotherapy, when to use immunotherapy for patients with BRAFV600-mutated disease, management of patients with brain metastases, evaluation of treatment response, special patient populations, patient education, quality of life, and survivorship, among others.

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

Patients with early-stage disease typically have a good prognosis, but still have a risk of recurrence, even with negative sentinel lymph node biopsy (SLNB). This study explores the utility of routine imaging to detect metastases in patients with negative SLNB but high-risk 31 gene expression profile (31-GEP) scores. We retrospectively identified melanoma patients with negative SLNBs. Patients with high-risk GEP results were placed in the experimental group and patients without GEP testing were placed in the control group. Among both cohorts, recurrent melanoma groups were identified. The tumor burden at the time of recurrence and the time to recurrence were compared between experimental group patients with routine imaging and control group patients without imaging schedules. We identified 327 control patients and 307 experimental patients, of which 14.1% versus 20.5% had melanoma recurrence, respectively. 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. However, melanoma recurrence was detected earlier (25.50 months versus 35.35 months) in the experimental group at a lower overall tumor burden (73.10 mm versus 27.60 mm). A higher percentage of experimental patients started immunotherapy when offered (76.3% and 67.9%). 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.

Modern Approach to Melanoma Adjuvant Treatment with Anti-PD1 Immune Check Point Inhibitors or BRAF/MEK Targeted Therapy: Multicenter Real-World Report

BACKGROUND

The landscape of melanoma management changed as randomized trials have launched adjuvant treatment.

MATERIALS AND METHODS

An analysis of data on 248 consecutive melanoma stage III and IV patients given adjuvant therapy in eight centers (February 2019 to January 2021) was conducted.

RESULTS

The analyzed cohort comprised 147 melanoma patients given anti-PD1 (33% nivolumab, 26% pembrolizumab), and 101 (41%) were given dabrafenib plus trametinib (DT). The 2-year overall survival (OS), relapse-free survival (RFS), and distant-metastases-free survival (DMFS) rates were 86.7%, 61.4%, and 70.2%, respectively. The disease stage affected only the RFS rate; for stage IV, it was 52.2% (95% CI: 33.4-81.5%) vs. 62.5% (95% CI: 52.3-74.8%) for IIIA-D, p = 0.0033. The type of lymph node surgery before adjuvant therapy did not influence the outcomes. Completion of lymph node dissection cessation after positive SLNB did not affect the results in terms of RFS or OS. Treatment-related adverse events (TRAE) were associated with longer 24-month RFS, with a rate of 68.7% (55.5-84.9%) for TRAE vs. 56.6% (45.8-70%) without TRAE, p = 0.0031. For TRAE of grade ≥ 3, a significant decline in OS to 60.6% (26.9-100%; p = 0.004) was observed.

CONCLUSIONS

Melanoma adjuvant therapy with anti-PD1 or DT outside clinical trials appears to be effective and comparable with the results of registration studies. Our data support a de-escalating surgery approach in melanoma treatment.

Topographical and Chronological Analysis of Thin Cutaneous Melanoma's Progressions: A Multicentric Study

A great portion of cutaneous melanoma's diagnoses nowadays is attributed to thin tumors with up to 1 mm in Breslow thickness (hereafter thin CMs), which occasionally metastasize. The objective of this study was to identify thin CM's metastatic patterns from a topographical and chronological standpoint. A total of 204 cases of metastatic thin CMs from five specialized centers were included in the study, and corresponding data were collected (clinical, epidemiological, histopathological information of primary tumor and the number, anatomical site, and time intervals of their progressions). First progressions occurred locally, in regional lymph nodes, and in a distant site in 24%, 15% and 61% of cases, respectively, with a median time to first progression of 3.10 years (IQR: 1.09-5.24). The median elapsed time between the first and second progression and between the second and third progression was 0.82 (IQR: 0.34-1.97) and 0.49 (IQR: 0.21-2.30) years, respectively, while the median survival time was about 4 years since first progression. Furthermore, the sequences of locations and time intervals of the progressions were associated with the clinicopathological and demographic features of the primary tumors along with the features of the preceding progressions. In conclusion, the findings of this study describe the natural history of thin CMs, thus highlighting the necessity to identify subgroups of thin CMs at a higher risk for metastasis and contributing to the optimization of the management and follow-up of thin CM patients.

Adjuvant therapy for stage II melanoma: the need for further studies

Immunotherapy with checkpoint inhibitors has revolutionised the outcomes for melanoma patients. In the metastatic setting, patients treated with nivolumab and ipilimumab have an expected 5-year survival of> 50%. For patients with resected high-risk stage III disease, adjuvant pembrolizumab, nivolumab or dabrafenib and trametinib are associated with a significant improvement in both relapse-free survival (RFS) and distant metastasis-free survival (DMFS). More recently neoadjuvant immunotherapy has shown very promising outcomes in patients with clinically detectable nodal disease and is likely to become a new standard of care. For stage IIB/C disease, two pivotal adjuvant trials of pembrolizumab and nivolumab have also reported a significant improvement in both RFS and DMFS. However, the absolute benefit is low and there are concerns about the risk of severe toxicities as well as long-term morbidity from endocrine toxicity. Ongoing registration phase III trials are currently evaluating newer immunotherapy combinations and the role of BRAF/MEK-directed targeted therapy for stage II melanoma. However, our ability to personalise therapy based on molecular risk stratification has lagged behind the development of novel immune therapies. There is a critical need to evaluate the use of tissue and blood-based biomarkers, to better select patients that will recur and avoid unnecessary treatment for the majority of patients cured by surgery alone.

Cutaneous melanoma

Cutaneous melanoma is a malignancy arising from melanocytes of the skin. Incidence rates are rising, particularly in White populations. Cutaneous melanoma is typically driven by exposure to ultraviolet radiation from natural sunlight and indoor tanning, although there are several subtypes that are not related to ultraviolet radiation exposure. Primary melanomas are often darkly pigmented, but can be amelanotic, with diagnosis based on a combination of clinical and histopathological findings. Primary melanoma is treated with wide excision, with margins determined by tumour thickness. Further treatment depends on the disease stage (following histopathological examination and, where appropriate, sentinel lymph node biopsy) and can include surgery, checkpoint immunotherapy, targeted therapy, or radiotherapy. Systemic drug therapies are recommended as an adjunct to surgery in patients with resectable locoregional metastases and are the mainstay of treatment in advanced melanoma. Management of advanced melanoma is complex, particularly in those with cerebral metastasis. Multidisciplinary care is essential. Systemic drug therapies, particularly immune checkpoint inhibitors, have substantially increased melanoma survival following a series of landmark approvals from 2011 onward.

Identifying the Transcriptional Drivers of Metastasis Embedded within Localized Melanoma

In melanoma, predicting which tumors will ultimately metastasize guides treatment decisions. Transcriptional signatures of primary tumors have been utilized to predict metastasis, but which among these are driver or passenger events remains unclear. We used data from the adjuvant AVAST-M trial to identify a predictive gene signature in localized tumors that ultimately metastasized. Using a zebrafish model of primary melanoma, we interrogated the top genes from the AVAST-M signature in vivo. This identified GRAMD1B, a cholesterol transfer protein, as a bona fide metastasis suppressor, with a majority of knockout animals rapidly developing metastasis. Mechanistically, excess free cholesterol or its metabolite 27-hydroxycholesterol promotes invasiveness via activation of an AP-1 program, which is associated with increased metastasis in humans. Our data demonstrate that the transcriptional seeds of metastasis are embedded within localized tumors, suggesting that early targeting of these programs can be used to prevent metastatic relapse.

SIGNIFICANCE

We analyzed human melanoma transcriptomics data to identify a gene signature predictive of metastasis. To rapidly test clinical signatures, we built a genetic metastasis platform in adult zebrafish and identified GRAMD1B as a suppressor of melanoma metastasis. GRAMD1B-associated cholesterol overload activates an AP-1 program to promote melanoma invasion. This article is highlighted in the In This Issue feature, p. 1.

Tissue Biomarkers Predicting Lymph Node Status in Cutaneous Melanoma

Cutaneous melanoma is a severe neoplasm that shows early invasiveness of the lymph nodes draining the primary site, with increased risk of distant metastases and recurrence. The tissue biomarker identification could be a new frontier to predict the risk of early lymph node invasiveness, especially in cases considered by current guidelines to be at low risk of lymph node involvement and not requiring evaluation of the sentinel lymph node (SLN). For this reason, we present a narrative review of the literature, seeking to provide an overview of current tissue biomarkers, particularly vascular endothelium growth factors (VEGF), Tetraspanin CD9, lymphatic vessel endothelial hyaluronan receptor-1 (LYVE-1), D2-40, and gene expression profile test (31-GEP). Among these, 31-GEP seems to be able to provide a distinction between low or high risk for positive SLN classes. VEGF receptor-3 and CD9 expression may be independent predictors of positive SLN. Lastly, LYVE-1 and D2-40 allow an easier assessment of lymph vascular invasion, which can be considered a good predictor of SLN status. In conclusion, biomarkers to assess the lymph node status of cutaneous melanoma patients may play an important role in those cases where the clinician is in doubt whether or not to perform SLN biopsy.

Optimizing treatment approaches for patients with cutaneous melanoma by integrating clinical and pathologic features with the 31-gene expression profile test

BACKGROUND

Many patients with low-stage cutaneous melanoma will experience tumor recurrence, metastasis, or death, and many higher staged patients will not.

OBJECTIVE

To develop an algorithm by integrating the 31-gene expression profile test with clinicopathologic data for an optimized, personalized risk of recurrence (integrated 31 risk of recurrence [i31-ROR]) or death and use i31-ROR in conjunction with a previously validated algorithm for precise sentinel lymph node positivity risk estimates (i31-SLNB) for optimized treatment plan decisions.

METHODS

Cox regression models for ROR were developed (n = 1581) and independently validated (n = 523) on a cohort with stage I-III melanoma. Using National Comprehensive Cancer Network cut points, i31-ROR performance was evaluated using the midpoint survival rates between patients with stage IIA and stage IIB disease as a risk threshold.

RESULTS

Patients with a low-risk i31-ROR result had significantly higher 5-year recurrence-free survival (91% vs 45%, P < .001), distant metastasis-free survival (95% vs 53%, P < .001), and melanoma-specific survival (98% vs 73%, P < .001) than patients with a high-risk i31-ROR result. A combined i31-SLNB/ROR analysis identified 44% of patients who could forego sentinel lymph node biopsy while maintaining high survival rates (>98%) or were restratified as being at a higher or lower risk of recurrence or death.

LIMITATIONS

Multicenter, retrospective study.

CONCLUSION

Integrating clinicopathologic features with the 31-GEP optimizes patient risk stratification compared to clinicopathologic features alone.

Sentinel Lymph Node Gene Expression Signature Predicts Recurrence-Free Survival in Cutaneous Melanoma

We sought to develop a sentinel lymph node gene expression signature score predictive of disease recurrence in patients with cutaneous melanoma. Gene expression profiling was performed on SLN biopsies using U133A 2.0 Affymetrix gene chips. The top 25 genes associated with recurrence-free survival (RFS) were selected and a penalized regression function was used to select 12 genes with a non-zero coefficient. A proportional hazards regression model was used to evaluate the association between clinical covariates, gene signature score, and RFS. Among the 45 patients evaluated, 23 (51%) had a positive SLN. Twenty-one (46.7%) patients developed disease recurrence. For the top 25 differentially expressed genes (DEG), 12 non-zero penalized coefficients were estimated (CLGN, C1QTNF3, ADORA3, ARHGAP8, DCTN1, ASPSCR1, CHRFAM7A, ZNF223, PDE6G, CXCL3, HEXIM1, HLA-DRB). This 12-gene signature score was significantly associated with RFS (p < 0.0001) and produced a bootstrap C index of 0.888. In univariate analysis, Breslow thickness, presence of primary tumor ulceration, SLN positivity were each significantly associated with RFS. After simultaneously adjusting for these prognostic factors in relation to the gene signature, the 12-gene score remained a significant independent predictor for RFS (p < 0.0001). This SLN 12-gene signature risk score is associated with melanoma recurrence regardless of SLN status and may be used as a prognostic factor for RFS.

Expanded evidence that the 31-gene expression profile test provides clinical utility for melanoma management in a multicenter study

OBJECTIVE

National Comprehensive Cancer Network (NCCN) guidelines for cutaneous melanoma (CM) recommend physicians consider increased surveillance for patients who typically have lower melanoma survival rates (stages IIB-IV as determined by the American Joint Committee on Cancer (AJCC), 8th edition). However, up to 15% of patients identified as having a low recurrence risk (stages I-IIA) experience disease recurrence, and some patients identified as having a high recurrence risk will not experience any recurrence. The 31-gene expression profile test (31-GEP) stratifies patient recurrence risk into low (Class 1) and high (Class 2) and has demonstrated risk-appropriate impact on disease management and clinical decisions.

METHODS

Five-year plans for lab work, frequency of clinical visits, and imaging pre- and post-31-GEP test results were assessed for a cohort of 509 stage I-III patients following an interim subset analysis of 247 patients.

RESULTS

After receiving 31-GEP results, 50.6% of patients had a change in management plans in at least one of the following categories-clinical visits, lab work, or surveillance imaging. The changes aligned with the risk predicted by the 31-GEP for 76.1% of patients with a Class 1 result and 78.7% of patients with a Class 2 result. A Class 1 31-GEP result was associated with changes toward low-intensity management recommendations, while a Class 2 result was associated with changes toward high-intensity management recommendations.

CONCLUSION

The 31-GEP can stratify patient recurrence risk in patients with CM, and clinicians understand and apply the prognostic ability of the 31-GEP test to alter patient management in risk-appropriate directions.

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.

Development and validation of a nomogram incorporating gene expression profiling and clinical factors for accurate prediction of metastasis in patients with cutaneous melanoma following Mohs micrographic surgery

BACKGROUND

There is a need to improve prognostic accuracy for patients with cutaneous melanoma. A 31-gene expression profile (31-GEP) test uses the molecular biology of primary tumors to identify individual patient metastatic risk.

OBJECTIVE

Develop a nomogram incorporating 31-GEP with relevant clinical factors to improve prognostic accuracy.

METHODS

In an IRB-approved study, 1124 patients from 9 Mohs micrographic surgery centers were prospectively enrolled, treated with Mohs micrographic surgery, and underwent 31-GEP testing. Data from 684 of those patients with at least 1-year follow-up or a metastatic event were included in nomogram development to predict metastatic risk.

RESULTS

Logistic regression modeling of 31-GEP results and T stage provided the simplest nomogram with the lowest Bayesian information criteria score. Validation in an archival cohort (n = 901) demonstrated a significant linear correlation between observed and nomogram-predicted risk of metastasis. The resulting nomogram more accurately predicts the risk for cutaneous melanoma metastasis than T stage or 31-GEP alone.

LIMITATIONS

The patient population is representative of Mohs micrographic surgery centers. Sentinel lymph node biopsy was not performed for most patients and could not be used in the nomogram.

CONCLUSIONS

Integration of 31-GEP and T stage can gain clinically useful prognostic information from data obtained noninvasively.

Expert Consensus on the Use of Prognostic Gene Expression Profiling Tests for the Management of Cutaneous Melanoma: Consensus from the Skin Cancer Prevention Working Group

BACKGROUND

Prognostic assessment of cutaneous melanoma relies on historical, clinicopathological, and phenotypic risk factors according to American Joint Committee on Cancer(AJCC) and National Comprehensive Cancer Network (NCCN) guidelines but may not account for a patient's individual additional genetic risk factors.

OBJECTIVE

To review the available literature regarding commercially available gene expression profile (GEP) tests and their use in the management of cutaneous melanoma.

METHODS

A literature search was conducted for original, English-language studies or meta-analyses published between 2010 and 2021 on commercially available GEP tests in cutaneous melanoma prognosis, clinical decision-making regarding sentinel lymph node biopsy, and real-world efficacy. After the literature review, the Skin Cancer Prevention Working Group, an expert panel of dermatologists with specialized training in melanoma and non-melanoma skin cancer diagnosis and management, utilized a modified Delphi technique to develop consensus statements regarding prognostic gene expression profile tests. Statements were only adopted with a supermajority vote of > 80%.

RESULTS

The initial search identified 1064 studies/meta-analyses that met the search criteria. Of these, we included 21 original articles and meta-analyses that studied the 31-GEP test (DecisionDx-Melanoma; Castle Biosciences, Inc.), five original articles that studied the 11-GEP test (Melagenix; NeraCare GmbH), and four original articles that studied the 8-GEP test with clinicopathological factors (Merlin; 8-GEP + CP; SkylineDx B.V.) in this review. Six statements received supermajority approval and were adopted by the panel.

CONCLUSION

GEP tests provide additional, reproducible information for dermatologists to consider within the larger framework of the eighth edition of the AJCC and NCCN cutaneous melanoma guidelines when counseling regarding prognosis and when considering a sentinel lymph node biopsy.

Follow-up of primary melanoma patients with high risk of recurrence: recommendations based on evidence and consensus

In spite of the good prognosis of patients with early-stage melanoma, there is a substantial proportion of them that develop local or distant relapses. With the introduction of targeted and immune therapies for advanced melanoma, including at the adjuvant setting, early detection of recurrent melanoma and/or second primary lesions is crucial to improve clinical outcomes. However, there is a lack of universal guidelines regarding both frequency of surveillance visits and diagnostic imaging and/or laboratory evaluations. In this article, a multidisciplinary expert panel recommends, after careful review of relevant data in the field, a consensus- and experience-based follow-up strategy for melanoma patients, taking into account prognostic factors and biomarkers and the high-risk periods and patterns of recurrence in each (sub) stage of the disease. Apart from the surveillance intensity, healthcare professionals should focus on patients' education to perform regular self-examinations of the skin and palpation of lymph nodes.

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

Simple Summary

Many people with skin cancer will have their cancer come back. The 31-gene expression profile (31-GEP) test can help predict if a cancer has a low (Class 1) or high (Class 2) chance of returning. This study looked at 86 patients with early skin cancer to see how well the 31-GEP test predicted if their cancer would return. None of the patients with a Class 1 GEP result had their cancer return within 3 years, but one-fourth of patients with a Class 2 result did. This study showed that the 31-GEP test can help predict if a patient’s skin cancer will return. Accurate risk prediction can help doctors make better treatment plans for patients with skin cancer.

Abstract

Background: Fifteen to forty percent of patients with localized cutaneous melanoma (CM) (stages I–II) will experience disease relapse. The 31-gene expression profile (31-GEP) uses gene expression data from the primary tumor in conjunction with clinicopathologic features to refine patient prognosis. The study’s objective was to evaluate 31-GEP risk stratification for disease-free survival (DFS) in a previously published cohort with longer follow-up. Methods: Patients with stage IB–II CM (n = 86) were prospectively tested with the 31-GEP. Follow-up time increased from 2.2 to 3.9 years. Patient outcomes were compared using Kaplan-Meier and Cox regression analysis. Results: A Class 2B result was a significant predictor of 3-year DFS (hazard ratio (HR) 8.4, p = 0.008) in univariate analysis. The 31-GEP significantly stratified patients by risk of relapse (p = 0.005). A Class 2B result was associated with a lower 3-year DFS (75.0%) than a Class 1A result (100%). The 31-GEP had a high sensitivity (77.8%) and negative predictive value (95.0%). Conclusions: The 31-GEP is a significant predictor of disease relapse in patients with stage IB–II melanoma and accurately stratified patients by risk of relapse.

Role of Biomarkers in the Integrated Management of Melanoma

Melanoma, which is an aggressive skin cancer, is currently the fifth and seventh most common cancer in men and women, respectively. The American Cancer Society reported that approximately 106,110 new cases of melanoma were diagnosed in the United States in 2021, with 7,180 people dying from the disease. This information could facilitate the early detection of possible metastatic lesions and the development of novel therapeutic techniques for melanoma. Additionally, early detection of malignant melanoma remains an objective of melanoma research. Recently, melanoma treatment has substantially improved, given the availability of targeted treatments and immunotherapy. These developments have highlighted the significance of identifying biomarkers for prognosis and predicting therapy response. Biomarkers included tissue protein expression, circulating DNA detection, and genetic alterations in cancer cells. Improved diagnostic and prognostic biomarkers are becoming increasingly relevant in melanoma treatment, with the development of newer and more targeted treatments. Here, the author discusses the aspects of biomarkers in the real-time management of patients with melanoma.

Impact of Next-generation Sequencing on Interobserver Agreement and Diagnosis of Spitzoid Neoplasms

Atypical Spitzoid melanocytic tumors are diagnostically challenging. Many studies have suggested various genomic markers to improve classification and prognostication. We aimed to assess whether next-generation sequencing studies using the Tempus xO assay assessing mutations in 1711 cancer-related genes and performing whole transcriptome mRNA sequencing for structural alterations could improve diagnostic agreement and accuracy in assessing neoplasms with Spitzoid histologic features. Twenty expert pathologists were asked to review 70 consultation level cases with Spitzoid features, once with limited clinical information and again with additional genomic information. There was an improvement in overall agreement with additional genomic information. Most significantly, there was increase in agreement of the diagnosis of conventional melanoma from moderate (κ=0.470, SE=0.0105) to substantial (κ=0.645, SE=0.0143) as measured by an average Cohen κ. Clinical follow-up was available in all 70 cases which substantiated that the improved agreement was clinically significant. Among 3 patients with distant metastatic disease, there was a highly significant increase in diagnostic recognition of the cases as conventional melanoma with genomics (P<0.005). In one case, none of 20 pathologists recognized a tumor with BRAF and TERT promoter mutations associated with fatal outcome as a conventional melanoma when only limited clinical information was provided, whereas 60% of pathologists correctly diagnosed this case when genomic information was also available. There was also a significant improvement in agreement of which lesions should be classified in the Spitz category/WHO Pathway from an average Cohen κ of 0.360 (SE=0.00921) to 0.607 (SE=0.0232) with genomics.

Bioinformatic and Machine Learning Applications in Melanoma Risk Assessment and Prognosis: A Literature Review

Over 100,000 people are diagnosed with cutaneous melanoma each year in the United States. Despite recent advancements in metastatic melanoma treatment, such as immunotherapy, there are still over 7000 melanoma-related deaths each year. Melanoma is a highly heterogenous disease, and many underlying genetic drivers have been identified since the introduction of next-generation sequencing. Despite clinical staging guidelines, the prognosis of metastatic melanoma is variable and difficult to predict. Bioinformatic and machine learning analyses relying on genetic, clinical, and histopathologic inputs have been increasingly used to risk stratify melanoma patients with high accuracy. This literature review summarizes the key genetic drivers of melanoma and recent applications of bioinformatic and machine learning models in the risk stratification of melanoma patients. A robustly validated risk stratification tool can potentially guide the physician management of melanoma patients and ultimately improve patient outcomes.

Sentinel lymph node biopsy in melanoma: beyond histologic factors

Sentinel lymph node (SLN) biopsy should be performed with the technical expertise required to correctly identify the sentinel node, in the context of understanding both the likelihood of positivity in a given patient and the prognostic significance of a positive or negative result. National Comprehensive Cancer Network guidelines recommend SLN biopsy for all cutaneous melanoma patients with primary tumor thickness greater than 1 mm and in select patients with thickness between 0.8 and 1 mm, yet admit a lack of consistent clarity in its utility for prognosis and therapeutic value in tumors < 1 mm and leave the decision for undergoing the procedure up to the patient and treating physician. Recent studies have evaluated specific patient populations, tumor histopathologic characteristics, and gene expression profiling and their use in predicting SLN positivity. These data have given insight into improving the physician's ability to potentially predict SLN positivity, shedding light on if and when omission of SLN biopsy in specific patients based on clinicopathological characteristics might be appropriate. This review provides discussion and insight into these recent advancements.

Molecular Biomarkers for Melanoma Screening, Diagnosis and Prognosis: Current State and Future Prospects

Despite significant progress in the development of treatment options, melanoma remains a leading cause of death due to skin cancer. Advances in our understanding of the genetic, transcriptomic, and morphologic spectrum of benign and malignant melanocytic neoplasia have enabled the field to propose biomarkers with potential diagnostic, prognostic, and predictive value. While these proposed biomarkers have the potential to improve clinical decision making at multiple critical intervention points, most remain unvalidated. Clinical validation of even the most commonly assessed biomarkers will require substantial resources, including limited clinical specimens. It is therefore important to consider the properties that constitute a relevant and clinically-useful biomarker-based test prior to engaging in large validation studies. In this review article we adapt an established framework for determining minimally-useful biomarker test characteristics, and apply this framework to a discussion of currently used and proposed biomarkers designed to aid melanoma detection, staging, prognosis, and choice of treatment.

Long-Term Outcomes in a Multicenter, Prospective Cohort Evaluating the Prognostic 31-Gene Expression Profile for Cutaneous Melanoma

PURPOSE

Current guidelines for postoperative management of patients with stage I-IIA cutaneous melanoma (CM) do not recommend routine cross-sectional imaging, yet many of these patients develop metastases. Methods that complement American Joint Committee on Cancer (AJCC) staging are needed to improve identification and treatment of these patients. A 31-gene expression profile (31-GEP) test predicts metastatic risk as low (class 1) or high (class 2). Prospective analysis of CM outcomes was performed to test the hypotheses that the 31-GEP provides prognostic value for patients with stage I-III CM, and that patients with stage I-IIA melanoma and class 2 31-GEP results have metastatic risk similar to patients for whom surveillance is recommended.

MATERIALS AND METHODS

Two multicenter registry studies, INTEGRATE (ClinicalTrials.gov identifier:NCT02355574) and EXPAND (ClinicalTrials.gov identifier:NCT02355587), were initiated under institutional review board approval, and 323 patients with stage I-III CM and median follow-up time of 3.2 years met inclusion criteria. Primary end points were 3-year recurrence-free survival (RFS), distant metastasis-free survival (DMFS), and overall survival (OS).

RESULTS

The 31-GEP was significant for RFS, DMFS, and OS in a univariate analysis and was a significant, independent predictor of RFS, DMFS, and OS in a multivariable analysis. GEP class 2 results were significantly associated with lower 3-year RFS, DMFS, and OS in all patients and those with stage I-IIA disease. Patients with stage I-IIA CM and a class 2 result had recurrence, distant metastasis, and death rates similar to patients with stage IIB-III CM. Combining 31-GEP results and AJCC staging enhanced sensitivity over each approach alone.

CONCLUSION

These data provide a rationale for using the 31-GEP along with AJCC staging, and suggest that patients with stage I-IIA CM and a class 2 31-GEP signature may be candidates for more intense follow-up.

Utility of a 31-gene expression profile for predicting outcomes in patients with primary cutaneous melanoma referred for sentinel node biopsy

BACKGROUND

A 31-gene genetic expression profile (31-GEP; Class 1 = low risk, Class 2 = high risk) developed to predict outcome in cutaneous melanoma (CM) has been validated by retrospective, industry-sponsored, or small series.

METHODS

Tumor features, sentinel node biopsy (SNB) results, and outcomes were extracted from a prospective database of 383 C M patients who underwent SNB and had a 31-GEP run on their primary tumor. Groups were compared by uni- and multi-variable analysis. Relapse-free and distant metastasis-free survival (RFS, DMFS) were estimated by Kaplan-Meier method.

RESULTS

Breslow thickness, T stage, and SNB positivity were significantly higher in Class 2 patients. Recurrence rates were higher for Class 2 vs Class 1 patients and highest in patients who were Class 2 and SNB positive. GEP class was predictive of RFS and DMFS and independently predicted relapse in AJCC "low risk" (stages IA-IIA) patients.

CONCLUSIONS

31-GEP adds prognostic information in CM patents undergoing SNB.

Scutellarin Suppresses RPMI7951 Melanoma Cell Proliferation by Targeting TOPK

BACKGROUND

T-LAK cell-Originated Protein Kinase (TOPK) belongs to the serine/threonine protein kinase family. It is highly expressed in RPMI7951 melanoma cells. Scutellarin (SCU) is an active ingredient extracted from Erigeron breviscapus (Vant.) Hand.-Mazz. Its main physiological functions are related to its anti-inflammatory and antitumour activities.

METHODS

The relationship between SCU and TOPK was assessed by molecular docking, an in vitro binding assay and an in vitro kinase assay. The effect of SCU on RPMI7951 cells was detected by MTS and soft agar assays. TOPK knockdown was induced by lentiviral infection. The TOPK downstream signalling pathway was detected by western blot and immunohistochemical analyses in vitro and in vivo.

RESULTS

SCU was found to directly bind with TOPK and inhibit TOPK activity in vitro. SCU inhibited the proliferation and colony formation of RPMI7951 cells in a dose-dependent manner. Silencing TOPK decreased the sensitivity of colon cancer cells to SCU. SCU inhibited the phosphorylation levels of Extracellular Regulated protein Kinases 1/2 (ERK1/2) and histone H3 in a time- and dose-dependent manner in RPMI7951 cells. In addition, SCU inhibited the growth of xenograft tumours of RPMI7951 cells and decreased the phosphorylation levels of extracellular regulated protein kinases 1/2 and histone H3 in vivo.

CONCLUSION

The results showed that SCU exerts promising antitumour effects on human RPMI7951 cells by inhibiting the activity of TOPK.

Tumour gene expression signature in primary melanoma predicts long-term outcomes

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.

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.

Integrating the melanoma 31-gene expression profile test with surgical oncology practice within national guideline and staging recommendations

Aim: Define changes in clinical management resulting from the use of the prognostic 31-gene expression profile (31-GEP) test for cutaneous melanoma in a surgical oncology practice. Patients & methods: Management plans for 112 consecutively tested patients with stage I-III melanoma were evaluated for duration and number of clinical visits, blood work and imaging. Results: 31-GEP high-risk (class 2; n = 46) patients received increased management compared with low-risk (class 1; n = 66) patients. Test results were most closely associated with follow-up and imaging. Of class 1 patients, 65% received surveillance intensity within guidelines for stage I-IIA patients; 98% of class 2 patients received surveillance intensity equal to stage IIB-IV patients. Conclusion: We suggest clinical follow-up and metastatic screening be adjusted according to 31-GEP test results.

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.

Gene co-expression and histone modification signatures are associated with melanoma progression, epithelial-to-mesenchymal transition, and metastasis

BACKGROUND

We have previously developed a murine cellular system that models the transformation from melanocytes to metastatic melanoma cells. This model was established by cycles of anchorage impediment of melanocytes and consists of four cell lines: differentiated melanocytes (melan-a), pre-malignant melanocytes (4C), malignant (4C11-), and metastasis-prone (4C11+) melanoma cells. Here, we searched for transcriptional and epigenetic signatures associated with melanoma progression and metastasis by performing a gene co-expression analysis of transcriptome data and a mass-spectrometry-based profiling of histone modifications in this model.

RESULTS

Eighteen modules of co-expressed genes were identified, and some of them were associated with melanoma progression, epithelial-to-mesenchymal transition (EMT), and metastasis. The genes in these modules participate in biological processes like focal adhesion, cell migration, extracellular matrix organization, endocytosis, cell cycle, DNA repair, protein ubiquitination, and autophagy. Modules and hub signatures related to EMT and metastasis (turquoise, green yellow, and yellow) were significantly enriched in genes associated to patient survival in two independent melanoma cohorts (TCGA and Leeds), suggesting they could be sources of novel prognostic biomarkers. Clusters of histone modifications were also linked to melanoma progression, EMT, and metastasis. Reduced levels of H4K5ac and H4K8ac marks were seen in the pre-malignant and tumorigenic cell lines, whereas the methylation patterns of H3K4, H3K56, and H4K20 were related to EMT. Moreover, the metastatic 4C11+ cell line showed higher H3K9me2 and H3K36me3 methylation, lower H3K18me1, H3K23me1, H3K79me2, and H3K36me2 marks and, in agreement, downregulation of the H3K36me2 methyltransferase Nsd1.

CONCLUSIONS

We uncovered transcriptional and histone modification signatures that may be molecular events driving melanoma progression and metastasis, which can aid in the identification of novel prognostic genes and drug targets for treating the disease.

Integration of a 31-Gene Expression Profile Into Clinical Decision-Making in the Treatment of Cutaneous Melanoma

BACKGROUND

The practice of utilizing gene expression profile (GEP) for the evaluation and treatment of cutaneous melanomas has been found to predict the risk of sentinel-node metastasis and recurrence. Information obtained from this assay has been used to determine clinical decision-making, including serving as an indication for sentinel lymph node biopsy and also for the intensity of screening measures.

METHODS

Herein we present our early experience in utilizing 31-GEP in intermediate melanomas and its effect on clinical management. A retrospective review was conducted of patients who had undergone treatment for melanoma whose tumors had been subjected to 31-GEP. Additionally, patient characteristics, attributes of the original tumor biopsied, findings on final pathology, and procedures performed were evaluated.

RESULTS

31-GEP stratified patients into 4 groups; groups 1A and 1B are considered low risk of metastasis or recurrence, while 2A and 2B are considered high risk. Over the study period, 31-GEP was conducted on 26 cutaneous melanoma patients. Testing and treatment data are available for 23 of these patients. Eleven patients were found to be low risk (9 as 1A, 2 as 1B), 12 were found to be high risk (4 as 2A, 8 as 2B). Decision-making was altered such that sentinel lymph node biopsy was omitted in 2 cases in which the patients were found to be low risk with age >65 years.

DISCUSSION

In 8 cases of node-negative disease in genetically high-risk patients, surveillance measures were augmented with positron emission tomography/computed tomography. Utilization of 31-GEP is ongoing at our institution.

Risk prediction in cutaneous melanoma patients from their clinico-pathological features: superiority of clinical data over gene expression data

Risk assessment in cutaneous melanoma (CM) patients is one of the major challenges in the effective treatment of CM patients. Traditionally, clinico-pathological features such as Breslow thickness, American Joint Committee on Cancer (AJCC) tumor staging, etc. are utilized for this purpose. However, due to advancements in technology, most of the upcoming risk prediction methods are gene-expression profile (GEP) based. In this study, we have tried to develop new GEP and clinico-pathological features-based biomarkers and assessed their prognostic strength in contrast to existing prognostic methods. We developed risk prediction models using the expression of the genes associated with different cancer-related pathways and got a maximum hazard ratio (HR) of 2.52 with p-value ~10-8 for the apoptotic pathway. Another model, based on combination of apoptotic and notch pathway genes boosted the HR to 2.57. Next, we developed models based on individual clinical features and got a maximum HR of 2.45 with p-value ~10-6 for Breslow thickness. We also developed models using the best features of clinical as well as gene-expression data and obtained a maximum HR of 3.19 with p-value ~10-9. Finally, we developed a new ensemble method using clinical variables only and got a maximum HR of 6.40 with p-value ~10-15. Based on this method, a web-based service and an android application named 'CMcrpred' is available at (https://webs.iiitd.edu.in/raghava/cmcrpred/) and Google Play Store respectively to facilitate scientific community. This study reveals that our new ensemble method based on only clinico-pathological features overperforms methods based on GEP based profiles as well as currently used AJCC staging. It also highlights the need to explore the full potential of clinical variables for prognostication of cancer patients.

Carcinomas with Occult Metastasis Potential: Diagnosis/Prognosis Accuracy Improvement by Means of Force Spectroscopy

Accurate diagnosis of cancer stage is inevitable for the following prognosis in patients struggling with these lesions to promote their health and survival rate. Previous studies on survival rate statistics show, in some cases, failure in cancer stage surveys in which metastasis or recurrence of the disease was not accurately prognosed. Morphology study of cancer cells advances the understanding about cancer behavior and its progression, in which, in our previous study on invasive cancer cells, fewer formations of cytoskeleton components compared to their counterparts was observed. Here it is shown that carcinomas with an occult propensity of metastasis depict a number of poorly differentiated cells with decreased amounts of cytoskeleton components in a near-well differentiated population. Force spectroscopy in conjunction with fluorescence microscopy of lung cancer, liver hepatoma, and melanoma provides a general view of these cells' architecture, leading to the conclusion that the scarce abnormal-shaped cells with low formation of structural filaments convey the high risk of metastatic potential of the tumor. The results demonstrate that force spectroscopy complements conventional diagnostic approaches by an accurate cytoskeleton assessment and can improve the following prognosis in epithelial cancers with occult metastasis risk.

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.

Molecular risk prediction in cutaneous melanoma: A meta-analysis of the 31-gene expression profile prognostic test in 1,479 patients

BACKGROUND

Multiple studies have reported on the accuracy of the prognostic 31-gene expression profile test for cutaneous melanoma. Consistency of the test results across studies has not been systematically evaluated.

OBJECTIVE

To assess the robustness of the prognostic value of the 31-gene expression profile.

METHODS

Raw data were obtained from studies identified from systematic review. A meta-analysis was performed to determine overall effect of the 31-gene expression profile. Clinical outcome metrics for the 31-gene expression profile were compared with American Joint Committee on Cancer staging.

RESULTS

Three studies met inclusion criteria; data from a novel cohort of 211 patients were included (n = 1,479). Five-year recurrence-free and distant metastasis-free survival rates were 91.4% and 94.1% for Class 1A patients and 43.6% and 55.5% for Class 2B patients (P < .0001). Meta-analysis results showed that Class 2 was significantly associated with recurrence (hazard ratio 2.90; P < .0001) and distant metastasis (hazard ratio 2.75; P < .0001). The 31-gene expression profile identified American Joint Committee on Cancer stage I to III patient subsets with high likelihood for recurrence and distant metastasis. Sensitivity was 76% (95% confidence interval 71%-80%) and 76% (95% confidence interval 70%-82%) for each end point, respectively. When 31-gene expression profile and sentinel lymph node biopsy results were considered together, sensitivity and negative predictive value for distant metastasis-free survival were both improved.

CONCLUSION

The 31-gene expression profile test consistently and accurately identifies melanoma patients at increased risk of metastasis, is independent of other clinicopathologic covariates, and augments current risk stratification by reclassifying patients for heightened surveillance who were previously designated as being at low risk.

Considering adjuvant therapy for stage II melanoma

Melanoma is among the few cancers that demonstrate an increasing incidence over time. Simultaneously, this trend has been marked by an epidemiologic shift to earlier stage at diagnosis. Before 2011, treatment options were limited for patients with metastatic disease, and the median overall survival was less than 1 year. Since then, the field of melanoma therapeutics has undergone major changes. The use of anti–CTLA‐4 and anti‐PD1 immune checkpoint inhibitors and combination BRAF/MEK inhibitors for patients with BRAF V600 mutations has significantly extended survival and allowed some patients to remain in durable disease remission off therapy. It has now been confirmed that these classes of agents have a benefit for patients with stage III melanoma after surgical resection, and anti‐PD1 and BRAF/MEK inhibitors are standards of care in this setting. Some patients with stage II disease (lymph node‐negative; American Joint Committee on Cancer stage IIB and IIC) have worse melanoma‐specific survival relative to some patients with stage III disease. Given these results, expanding the population of patients who are considered for adjuvant therapy to include those with stage II melanoma has become a priority, and randomized phase 3 clinical trials are underway. Moving into the future, the validation of patient risk‐stratification and treatment‐benefit prediction models will be important to improve the number needed to treat and limit exposure to toxicity in the large population of patients with early stage melanoma.

Adjuvant therapy has improved outcomes in patients with stage III melanoma and is being explored in those with stage II melanoma. Stage III data as well as risk‐stratification tools and clinical considerations for the lymph node‐negative population are reviewed.

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.

Level of Evidence Review for a Gene Expression Profile Test for Cutaneous Melanoma

BACKGROUND

The advent of molecular medicine may allow for individualized cancer prognostication, which should enable better clinical management and, hopefully, improve patient outcomes. A 31-gene expression profile (31-GEP) test is currently available for patients diagnosed with cutaneous melanoma; this test helps inform patients' individual treatment plans, especially when combined with traditional biomarkers.

OBJECTIVE

The objective of this study was to review the current literature and establish the level of evidence for a cutaneous melanoma 31-GEP test.

METHODS

A review of seven development and validation studies for the 31-GEP test was conducted. The respective strengths and weaknesses of each study were applied to the level of evidence criteria from major organizations that publish guidelines for melanoma management: American Joint Committee on Cancer, National Comprehensive Cancer Network, and American Academy of Dermatology.

RESULTS

Evaluating each study led to classifying the 31-GEP test as level I/II, I-IIIB, and IIA according to American Joint Committee on Cancer, National Comprehensive Cancer Network, and American Academy of Dermatology criteria, respectively. This stands in contrast to the official unrated status conferred by the American Joint Committee on Cancer and National Comprehensive Cancer Network and the II/IIIC rating designated by the American Academy of Dermatology.

CONCLUSIONS

Differences between the authors' findings and official published ratings may be attributed to chronological issues, as many of the studies were not yet published when the aforementioned organizations conducted their reviews. There was also difficulty in applying the National Comprehensive Cancer Network criteria to this prognostic test, as their guidelines were intended for evaluation of predictive markers. Nevertheless, based upon the most current data available, integration of the 31-GEP test into clinical practice may be warranted in certain clinical situations.