Overview
The 31-GEP is a molecular test used to predict cutaneous melanomas as high or low risk based on the tumor’s genetic profile. Using 28 prognostic genes and three control genes, as well as a training cohort of 164 melanoma cases in predictive modeling, melanomas are characterized as Class 1 or Class 2, with Class 1 given a favorable prognosis and Class 2 posing a poor outlook in terms of 5-year recurrence-free survival, distant metastasis-free survival, and melanoma-specific survival.
Literature Review of Clinical Validity
The first 31-GEP study is a detailed account of its inception and a validation of its prognostic accuracy. Gerami et al. utilized previously published genomic data comparing primary vs. metastatic melanoma to select genes that varied considerably and consistently between the two tumor types [7]. This literature-derived genetic profile was applied to the 164-sample training cohort with known outcomes. Using machine learning on this training cohort to classify new samples, the 31-GEP test was then validated in an independent retrospective cohort of 104 archived samples from multiple institutions. A Kaplan–Meier analysis of the two classes identified by the 31-GEP test demonstrated, with significance, a 66% difference in disease-free survival rates. Following validation, the study compared the 31-GEP test to other prognostic indicators, including Breslow thickness, ulceration, mitotic rate, and age. A multivariate analysis found that the 31-GEP classifications were independent predictors of metastatic risk (hazard ratio [HR] 9.55, confidence interval [CI] 2.3–39.5, p = 0.002).
The next study compared the 31-GEP test to the sentinel lymph node biopsy (SLNB), by retrospectively evaluating 217 samples from numerous cancer centers [8]. The investigators found that the positive predictive value of the SLNB was similar to the molecular test (55% and 50% with 95% CI of 42–68 and 42–59, respectively). More importantly, the negative predictive value of the 31-GEP test surpassed the SLNB (82% and 67% with 95% CI of 59–74 and 71–89, respectively). The strength of the 31-GEP test’s negative predictive value is particularly noteworthy, as many patients who die from metastatic melanoma are initially SLNB negative [9]. This fact was reflected in the study findings, as the combination of SLNB and 31-GEP testing led to significantly improved prognostication when compared with either modality alone [8].
Ferris et al. further refined the role of the 31-GEP test in prognostication by evaluating its validity and utility for stage I and II cutaneous melanoma, a subset known to account for the majority of melanoma deaths [9, 10]. Using 205 specimens from multiple centers, a head-to-head comparison of the 31-GEP test vs. the AJCC Individualized Melanoma Patient Outcome Prediction Tool was performed [10]. In regard to all three outcomes of recurrence, distant metastasis, and death, the genetic test was ultimately more sensitive, while the AJCC calculator was more specific.
This study complemented previous articles that found combining molecular testing with traditional clinical markers yielded improved prediction of risk than either tool alone [8]. Ferris et al. determined the sensitivity of the AJCC prediction tool combined with the 31-GEP test to be at least 88% for recurrence, 85% for distant metastasis, and 82% for death [10]. This represented a minimum increase of 4% and a maximum increase of 54% in sensitivity from either test alone. As expected, specificity declined when combining the two tools; however, this was at most a 22% decline in specificity in contrast to the 54% increase in sensitivity.
The investigators also considered circumstances when the AJCC calculator and the genetic test did not agree, such that tumors would be classified as Class 1/AJCC high risk and Class 2/AJCC low risk. Of the 43 cases with contrary classifications, the number of study outcomes (recurrence, distant metastasis, or death) in the Class 1/AJCC high risk was 38%, whereas in the Class 2/AJCC low risk was 46%. While these findings hint at the increased sensitivity of the 31-GEP test as described above, the small sample size and the use of 124 previously analyzed specimens preclude definitive conclusions from being drawn.
The next assessment of the 31-GEP test was the first prospective evaluation of its prognostic capability. Hsueh et al. evaluated 322 patients from 11 different medical centers in a 1.5-year interim analysis of a 5-year study [11]. In comparison to a positive SLNB and the presence of ulceration, the Class 2 designation was more sensitive for recurrence (40%, 60%, and 80% respectively, and p < 0.0001 for all), distant metastasis (50%, 75%, and 83%, and p < 0.001, < 0.0001, and < 0.0001, respectively), and death (9%, 45%, and 73%, and p = 1, 0.04, and 0.0001, respectively) predictions. Furthermore, a multivariate analysis indicated that Class 2 designations were associated with a significant 7.15 HR for recurrence risk. Analysis of the HR for Class 2 in regard to distant metastasis or overall survival was not significant; however, these two outcomes were limited in number, which may have caused difficulties when assessing for significance. Importantly, ulceration was not associated with a significant HR.
Zager et al. reaffirmed previous findings by increasing the size of the retrospective cohort analyzed [12]. Five hundred and twenty-three previously unreported cutaneous melanomas from 16 facilities were evaluated using the 31-GEP test to determine the risk of recurrence and distant metastasis. As determined previously, Class 1 vs. Class 2 had significantly different levels of risk, with Class 2 associated with a worse prognosis regardless of tumor stage. Notably, this study subdivided Class 1 and Class 2 designations into A and B subclasses, such that Class 1A has the best prognosis, Class 2B has the worst prognosis, and Classes 1B/2A have intermediate prognoses. Similar to Gerami et al. [7], this study demonstrated high accuracy metrics for both classifications and found combining 31-GEP testing with SLNB increased prognostic accuracy more than either alone.
A recent study directly evaluated the utility of the 31-GEP test to identify high-risk lesions amongst tumors traditionally categorized as low risk. Melanomas usually considered to be low risk included: thin tumors ≤ 1 mm (T1), stage I–IIA disease, and those with negative SLNB. Gastman et al. assessed 690 cutaneous melanomas from a pooled cohort that excluded samples previously used for test development [13]. Comparison of tumors with a negative SLNB paired with a Class 1A vs. Class 2B designation found that melanomas with the higher risk molecular classification were associated with a significantly worse prognosis, despite the lesions’ traditionally low-risk profile. These results were echoed in the evaluations of molecular categorizations for other cutaneous melanomas that met the standard criteria of low risk. Furthermore, for lesions classified as thin or stage I–IIA, a multivariate analysis accounting for thickness, ulceration, and mitotic rate found that the 31-GEP Class 2B was a significant predictor of recurrence-free survival.
Finally, Greenhaw et al. retrospectively assessed a registry of 256 patients with cutaneous melanoma who, either at the time of diagnosis or first follow-up visit, received the 31-GEP test as part of their clinical care [14]. This study demonstrated a 99% negative predictive value for a Class 1 designation. The sensitivity of the molecular test was also substantial, with 77% of melanomas that recurred accurately called Class 2.
Literature Review of Analytic Validity and Clinical Utility
The primary focus of this review is to objectively assess the clinical validity of the 31-GEP test. However, adoption of a molecular test into clinical practice requires additional considerations, such as the analytic validity and clinical utility of the test. The available literature addressing the analytic validity and clinical utility of the 31-GEP test is briefly summarized here.
Cook et al. evaluated the analytical validity, or test reliability, of the 31-GEP test through multiple inter-assay, inter-instrument, and inter-operator studies [15]. One hundred and sixty-eight melanoma samples tested on 2 consecutive days yielded an inter-assay concordance score of 99%. Inter-instrument validity was assessed by comparing probability scores generated by two models of the same machine and two entirely different machines. The total sample size of 43 was associated with a 95% concordance rate between instruments. Finally, inter-operator concordance was evaluated using 298 melanoma samples and generated a concordance value of 100%.
Clinical utility studies, necessary to demonstrate if and how testing impacts patient management decisions by physicians, have also been performed for the 31-GEP assay [16,17,18,19,20,21]. Changes to patient management for physician visits, imaging, laboratory workup, referrals, and SLNB guidance with 31-GEP testing have been assessed by the following study designs: prospective testing of 31-GEP impact on physician recommendations (247 patients, stage I–II at consent) [16] and retrospective chart reviews with prospective testing of cases (156 and 91 patients, stage I–III) [17, 18]. These clinical impact studies reported patient management changes in approximately half of the patients tested with the 31-GEP test. Of these patients, follow-up, surveillance, and interdisciplinary care were generally reduced in intensity or frequency after a Class 1 result and increased with a Class 2 result. The majority of patients who had their management influenced by the 31-GEP test result were stage I–II. While patient outcomes were not assessed as part of these utility studies, the importance and contribution of appropriate clinical follow-up and surveillance for detection of distant disease and its impact on survival has been detailed elsewhere [22]. Intended-use decision studies using hypothetical clinical vignettes and survey responses have demonstrated physicians and nurse practitioners are willing to use the 31-GEP test and re-evaluate management accordingly, particularly in patients with melanomas at least 0.5 mm thick [19,20,21].
The financial impact of the molecular test is also a significant factor to consider prior to implementation into clinical practice. Unfortunately, the current data evaluating the economic ramifications of the GEP-31 test are limited; however, incorporation of the molecular test within projected cost-of-care models suggests that the assay may result in a 31% net reduction in expenditure for those with T1/T2 disease by impacting surveillance and SLNB management [23]. Additional studies are needed to fully assess the economic impact of 31-GEP testing.