Integrating the 40-Gene Expression Profile (40-GEP) Test Improves Metastatic Risk-Stratification Within Clinically Relevant Subgroups of High-Risk Cutaneous Squamous Cell Carcinoma (cSCC) Patients

Abstract

Introduction: The validated 40-gene expression profile (40-GEP) test independently stratifies risk of regional or distant metastasis for cutaneous squamous cell carcinoma (cSCC) tumors with high-risk clinicopathologic features. This study evaluated the stratification of risk by the 40-GEP test in a large cohort of tumors with one or more high-risk factors and in clinically relevant subgroups, including tumors within National Comprehensive Cancer Network (NCCN) high- and very-high-risk groups, lower-stage BWH T1 and T2a tumors, and patients > 65 years old.

Methods: This multicenter (n = 58) performance study of the 40-GEP included 897 patients. Kaplan-Meier analyses were performed to assess risk stratification profiles for 40-GEP Class 1 (low), Class 2A (higher) and Class 2B (highest) risk groups, while nested Cox regression models were used to compare risk prediction of clinicopathologic risk classification systems versus risk classification systems in combination with 40-GEP.

Results: Patients classified as 40-GEP Class 1, Class 2A, or Class 2B had significantly different metastatic risk profiles (p < 0.0001). Integrating 40-GEP results into models with individual clinicopathologic risk factors or risk classification systems (Brigham and Women's Hospital, American Joint Committee on Cancer Staging Manual, 8th Edition) and NCCN demonstrated significant improvement in accuracy for prediction of metastatic events (ANOVA for model deviance, p < 0.0001 for all models).

Conclusion: The 40-GEP test demonstrates accurate, independent, clinically actionable stratification of metastatic risk and improves predictive accuracy when integrated into risk classification systems. The improved accuracy of risk assessment when including tumor biology via the 40-GEP test ensures more risk-aligned, personalized patient management decisions.