This video is Part 2 of a 4-part expert series designed to strengthen clinician confidence in the use of the 31-gene expression profiling (31-GEP) test for prognostic assessment in cutaneous melanoma. Across the series, David Cotter, MD, PhD, addresses common questions and hesitations around molecular prognostic testing to support more consistent and effective integration of 31-GEP into routine dermatologic practice.
Expert consensus statement
Integration of 31-GEP testing with traditional staging methods can accurately inform the decision to recommend sentinel lymph node biopsy (SLNB).
This consensus statement comes from the expert panel publication “31-Gene expression profiling for cutaneous melanoma: an expert consensus panel” and serves as the foundation for this discussion.
SLNB as a critical, but imperfect, decision point
SLNB remains a key step in melanoma staging, but decision-making is not always straightforward in borderline cases. Dr Cotter highlights scenarios frequently encountered in practice, where estimated risk falls near clinical thresholds and management varies.
For example:
Although a ≥10% risk often supports proceeding with SLNB, these estimates are population-based. In practice, patient-specific factors, such as comorbidities or surgical candidacy, introduce additional nuance, contributing to variability in care.
The “gray zone” in current guidelines
Current guidance generally avoids SLNB in patients with less than a 5% likelihood of nodal positivity. However, this threshold reflects an inherent limitation in the available tools.
Among melanomas <1 mm:
In effect, these values offset one another. Clinically, this means that when SLNB is deferred in this population, a small proportion of patients with occult metastatic melanoma may not be identified at diagnosis. This tradeoff highlights a gap in precision when relying on population-level risk estimates alone.
Refining risk stratification with 31-GEP
31-GEP testing offers a more individualized approach to risk assessment, particularly in intermediate-risk groups such as T1B melanomas. By incorporating tumor biology, it helps refine which patients may benefit from SLNB.
Data discussed in this segment demonstrate that:
These findings suggest that integrating 31-GEP into clinical workflows can improve patient selection and reduce uncertainty in borderline cases.
Moving beyond static measures: the role of tumor biology
Traditional staging relies on histopathologic features such as Breslow depth and ulceration; these factors are important, but inherently limited to a single timepoint.
31-GEP evaluates gene expression patterns to better characterize tumor behavior. This approach allows clinicians to move beyond population-based estimates and incorporate individualized biologic risk into decision-making.
As Dr Cotter describes, the combination of clinicopathologic staging and 31-GEP results supports a more comprehensive and patient-specific framework for care.
Key takeaways