Guidance of Sentinel Lymph Node Biopsy Decisions In Patients With T1–T2 Melanoma Using Gene Expression Profiling

Vetto, John T.; Hsueh, Eddy C.; Gastman, Brian; Dillon, Larry D; Monzon, Federico A.; Cook, Robert W.; Keller, Jennifer; Huang, Xin; Fleming, Andrew; Hewgley, Preston; Gerami, Pedram; Leachman, Sancy A.; Wayne, Jeffrey D.; Berger, Adam C.; Fleming, Martin D.

doi:10.2217/fon-2018-0912

Cited by 60 publications

(56 citation statements)

References 40 publications

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“…Similarly, two recent prospective studies (consisting primarily of AJCC stage I/II patients) found GEP class to be the strongest predictor of both local recurrence and distant metastasis [8,9]. Finally, in a study of 1421 prospectively tested T1/T2 tumor stage patients – most undergoing SLNB – from 26 centers, GEP class was a significant predictor of SLNB-positivity [10]. The 31-GEP test is now covered by Centers for Medicare and Medicaid Services for patients over age 65 with T1a (with adverse features), T1b and T2 tumors.…”

Section: Prognostic Gep Tests For Melanomamentioning

confidence: 93%

Prognostic Gene Expression Profiling in Melanoma: Necessary Steps to Incorporate into Clinical Practice

et al. 2019

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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.

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Section: Prognostic Gep Tests For Melanomamentioning

confidence: 93%

Prognostic Gene Expression Profiling in Melanoma: Necessary Steps to Incorporate into Clinical Practice

et al. 2019

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“…As Cam_121 was developed and tested on the same dataset, there are chances of overfitting. Therefore, we further tested the signatures’ prognostic power in an externally acquired independent validation dataset from the Leeds Melanoma Cohort (n=677) (15). This confirmed that Cam_121 was associated with melanoma-specific survival (MSS) in both univariate (HR=1.49 (95% CI 1.27-1.74), p=5×10 −7 ) and multivariate Cox regression models (HR=1.7 (95% CI), p=0.001, Figure 2).…”

Section: Resultsmentioning

confidence: 99%

“…Building on these data, Gerami et al first reported a prognostic gene expression profile (GEP) test utilising the 31-gene panel (28 discriminating and 3 control genes) for use in patients with CM (Decision-Dx Melanoma™) (12). The test measures the expression of individual genes from formalin-fixed paraffin-embedded (FFPE) primary melanomas to provide a binary classification of low (class 1) or high (class 2) risk for developing metastases within 5 years of diagnosis (with A and B subclasses to further stratify risk) (13-15). A further recent unsupervised clustering analyses based on 677 primary melanoma transcriptomes embedded within a population-controlled cohort study from the Leeds Melanoma Cohort (LMC) identified a six-class 150-gene prognostic signature (herein reference to as LMC_150) (16).…”

Section: Introductionmentioning

confidence: 99%

Tumour gene expression signature in primary melanoma predicts long-term outcomes: A prospective multicentre study

Garg

Couturier

Nsengimana

et al. 2020

Preprint

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PurposePredicting outcomes after resection of primary melanoma remains crude, primarily based on tumour thickness. We explored gene expression signatures for their ability to better predict outcomes.MethodsDifferential expression analysis of 194 primary melanomas resected from patients who either developed distant metastasis (n=89) or did not (n=105) was performed. We identified 121 metastasis-associated genes that were included in our prognostic signature, “Cam_121”. Several machine learning classification models were trained using nested leave- one-out cross validation (LOOCV) to test the signature’s capacity to predict metastases, as well as regression models to predict survival. The prognostic accuracy was externally validated in two independent datasets.ResultsCam_121 performed significantly better in predicting distant metastases than any of the models trained with the clinical covariates alone (pAccuracy=4.92×10−3), as well as those trained with two published prognostic signatures. Cam_121 expression score was strongly associated with progression-free survival (HR=1.7, p=3.44×10−6), overall survival (HR=1.73, p=7.71×10−6) and melanoma-specific survival (HR=1.59, p=0.02). Cam_121 expression score also negatively correlated with measures of immune cell infiltration (ρ=−0.73, p<2.2×10−16), with a higher score representing reduced tumour lymphocytic infiltration and a higher absolute 5-year risk of death in stage II melanoma.ConclusionsThe Cam_121 primary melanoma gene expression signature outperformed currently available alternatives in predicting the risk of distant recurrence. The signature confirmed (using unbiased approaches) the central prognostic importance of immune cell infiltration in long-term patient outcomes and could be used to identify stage II melanoma patients at highest risk of metastases and poor survival who might benefit most from adjuvant therapies.Translational relevancePredicting outcomes after resection of primary melanoma is currently based on traditional histopathological staging, however survival outcomes within these disease stages varies markedly. Since adjuvant systemic therapies are now being used routinely, accurate prognostic information is needed to better risk stratify patients and avoid unnecessary use of high cost, potentially harmful drugs, as well as to inform future adjuvant strategies. The Cam_121 gene expression signature appears to have this capability and warrants evaluation in prospective clinical trials.

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“…Currently, the NCCN does not recommend SLNB in patients whose risk for a positive finding is <5% (T1a and below); however, they do recommend offering SLNB in the appropriate clinical setting when the risk is 5%-10% (T1b lesions). 5,6 , 7…”

Section: Introductionmentioning

confidence: 99%

“…The 31-GEP seeks to identify those T1 and T2 tumors with genetic signatures that are likely to behave in either low-risk or high-risk manners with regard to recurrence, distant metastasis, and mortality. 6,8-11 This test stratified patients into 4 groups: Class 1A (considered low risk of metastasis or recurrence), Classes 1B and 2A (intermediate risk), and Class 2B (high risk). When these groups are further broken down by patient age, it becomes apparent that patients >55 years of age whose tumors are Class 1A have <5% incidence of SLNB positivity.…”

Section: Introductionmentioning

confidence: 99%

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

Scott

Dale

Conforti

et al. 2020

The American Surgeon

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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.

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Guidance of Sentinel Lymph Node Biopsy Decisions In Patients With T1–T2 Melanoma Using Gene Expression Profiling

Cited by 60 publications

References 40 publications

Prognostic Gene Expression Profiling in Melanoma: Necessary Steps to Incorporate into Clinical Practice

Prognostic Gene Expression Profiling in Melanoma: Necessary Steps to Incorporate into Clinical Practice

Tumour gene expression signature in primary melanoma predicts long-term outcomes: A prospective multicentre study

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

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