Enhanced metastatic risk assessment in cutaneous squamous cell carcinoma with the 40-gene expression profile test

Lay abstract Cutaneous squamous cell carcinoma is a common skin cancer, with approximately 2 million cases diagnosed each year in the USA. Because substantial numbers of patients experience metastasis, which can result in death, accurate metastatic risk assessment is important. Clinicians use clinicopathologic factors to determine risk for disease progression. However, traditional methods miss pinpointing many patients who experience metastasis and sometimes categorize patients as at risk who do not develop metastasis, indicating that additional tools are needed. A molecular test, the 40-gene expression profile (40-GEP), was developed to predict metastatic risk based on the biology of the tumor. This study demonstrates that the 40-GEP, either as an independent tool or together with traditional methods, accurately identifies patients' risk of metastasis. Using the 40-GEP could improve patient management to improve patient outcomes. Aim: To clinically validate the 40-gene expression profile (40-GEP) test for cutaneous squamous cell carcinoma patients and evaluate coupling the test with individual clinicopathologic risk factor-based assessment methods. Patients & methods: In a 33-site study, primary tumors with known patient outcomes were assessed under clinical testing conditions (n = 420). The 40-GEP results were integrated with clinicopathologic risk factors. Kaplan-Meier and Cox regression analyses were performed for metastasis. Results: The 40-GEP test demonstrated significant prognostic value. Risk classification was improved via integration of 40-GEP results with clinicopathologic risk factor-based assessment, with metastasis rates near the general cutaneous squamous cell carcinoma population for Class 1 and >= 50% for Class 2B. Conclusion: Combining molecular profiling with clinicopathologic risk factor assessment enhances stratification of cutaneous squamous cell carcinoma patients and may inform decision-making for risk-appropriate management strategies.