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Long-Term Outcomes in a Multicenter, Prospective Cohort Evaluating the Prognostic 31-Gene Expression Profile for
Eddy C Hsueh1, James R DeBloom2, Jonathan H Lee3
1Department of Surgery, St Louis University, St Louis, MO.
JCO Precision Oncology
|May 26, 2021
Summary
A 31-gene expression profile (31-GEP) test identifies high-risk cutaneous melanoma (CM) patients. Class 2 results indicate a metastatic risk similar to higher stage disease, suggesting intensified follow-up for stage I-IIA CM.
Area of Science:
- Oncology
- Dermatology
- Molecular Diagnostics
Background:
- Current guidelines for stage I-IIA cutaneous melanoma (CM) lack methods to identify patients at high risk for metastasis.
- Improved risk stratification is needed to complement the American Joint Committee on Cancer (AJCC) staging system.
Purpose of the Study:
- To evaluate the prognostic value of a 31-gene expression profile (31-GEP) test in patients with stage I-III CM.
- To determine if stage I-IIA CM patients with a high-risk 31-GEP signature (class 2) have a metastatic risk comparable to higher-stage CM patients.
Main Methods:
- Prospective analysis of 323 patients with stage I-III CM from two multicenter registry studies (INTEGRATE and EXPAND).
- Assessment of 3-year recurrence-free survival (RFS), distant metastasis-free survival (DMFS), and overall survival (OS).
- Univariate and multivariable analyses of the 31-GEP's predictive performance.
Main Results:
- The 31-GEP was a significant independent predictor of RFS, DMFS, and OS across all stages.
- Stage I-IIA CM patients with a class 2 31-GEP result exhibited recurrence, metastasis, and death rates similar to stage IIB-III CM patients.
- Combining 31-GEP results with AJCC staging improved sensitivity for risk prediction compared to either method alone.
Conclusions:
- The 31-GEP test provides significant prognostic value for CM patients.
- Stage I-IIA CM patients with a class 2 31-GEP signature may benefit from more intensive surveillance strategies.
- Integrating 31-GEP with AJCC staging enhances the identification of high-risk patients.

