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Integrating the 40-Gene Expression Profile (40-GEP) Test Improves Metastatic Risk-Stratification Within Clinically
Ashley Wysong1, Ally-Khan Somani2,3, Sherrif F Ibrahim4
1Department of Dermatology, University of Nebraska Medical Center, Omaha, NE, USA.
Dermatology and Therapy
|February 29, 2024
Summary
The 40-gene expression profile (40-GEP) test accurately stratifies metastatic risk for cutaneous squamous cell carcinoma (cSCC). Integrating 40-GEP improves prediction accuracy, enabling personalized patient management.
Area of Science:
- Oncology
- Genomics
- Biomarkers
Background:
- Cutaneous squamous cell carcinoma (cSCC) risk stratification is crucial for patient management.
- The 40-gene expression profile (40-GEP) test is a validated tool for assessing metastasis risk in cSCC.
- High-risk clinicopathologic features necessitate accurate risk stratification.
Purpose of the Study:
- To evaluate the 40-GEP test's risk stratification performance in a large cSCC cohort.
- To assess 40-GEP performance in specific subgroups, including NCCN high/very-high risk and early-stage tumors.
- To determine if 40-GEP improves risk prediction accuracy compared to existing systems.
Main Methods:
- Multicenter study involving 897 patients with cSCC.
- Kaplan-Meier analysis to assess 40-GEP Class 1, 2A, and 2B risk profiles.
- Nested Cox regression models to compare clinicopathologic systems with and without 40-GEP integration.
Main Results:
- 40-GEP Class 1, 2A, and 2B groups showed significantly different metastatic risk profiles (p < 0.0001).
- Integration of 40-GEP significantly improved the accuracy of predicting metastatic events across various risk classification systems (p < 0.0001).
- Improved predictive accuracy was observed when combining 40-GEP with NCCN and AJCC staging systems.
Conclusions:
- The 40-GEP test provides accurate and independent stratification of metastatic risk in cSCC.
- Integrating 40-GEP enhances the predictive accuracy of existing risk classification systems.
- The 40-GEP test facilitates more personalized and risk-aligned patient management decisions by incorporating tumor biology.

