Multicentre evaluation the early prognostic performance of a genetic signature in a multicentre prospectively evaluated cohort.

Gene expression profile class and node status stratified tumors into significantly different 5-year survival groups by Kaplan-Meier method and both were independent predictors of recurrence in multivariate analysis.

Multicenter prospective study in T1-T2 tumors showed combining GEP with Breslow thickness and age can provide a more precise determination of SLN positivity risk.

MyPath Melanoma guides dermatologists in treatment decisions leading to a 72% reduction in re-excisions when the GEP result is benign

DecisionDx-Melanoma test results influenced 85% of clinicians’ decisions regarding the SLNB surgical procedure. Use of the test results could help avoid unnecessary procedures in low-risk patients whose tumor biology indicates they could safely forgo the procedure.

A quantitative, multiplexed biomarker imaging approach termed TissueCypher™ that applies systems biology to anatomic pathology.

Expert panel of 6 key opinion leaders in dermatology consensus panel unanimously approved eleven usage guidelines and consensus supporting statements for the appropriate use of GEP testing

Examined the prognostic value of the 31-gene expression profile (31-GEP) test for the risk of recurrence in stage I CM patients according to 31-GEP class.

Discovery of reduced RFS for patients with thin tumors and Class 2B biology and cumulative validation cohort for DecisionDx-Melanoma. DecisionDx-Melanoma was the strongest independent predictor of RFS, DMFS and MSS.

TissueCypher has been shown to risk-stratify Barrett’s esophagus patients in five clinical validation studies. Given that clinical validation, this study was conducted in conjunction with Geisinger Medical Center to assess the impact of TissueCypher on clinicians’ management decisions.

The 40-GEP identified patients most likely to benefit from ART (Class 2B) and those that can consider deferring treatment (Class 1).

Treatment decisions for patients with cutaneous squamous cell carcinoma (cSCC) are traditionally based upon clinicopathologic risk factors and staging systems. Due to the accuracy limitations of these resources in predicting poor outcomes, there is a clinically significant need for more accurate methods of risk assessment. T