Evidence map›Paper›PMID 42279412›Full record

ReviewCancers2026

Current Clinical Utility of Gene Expression Panels in Primary Cutaneous Melanoma.

Taylor L Garza, Jae Hwan Choi, Michelle McGee, Edmond Box, Timothy Nywening, Andreas Karachristos, Abraham Schwarzberg, Mayer Fishman, Richard Jacobson

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Cancers, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Taylor L GarzaDepartment of Surgery, University of South Florida, Tampa, FL 33606, USA.ORCID 0009-0002-7549-5231
Jae Hwan ChoiDepartment of Surgery, University of South Florida, Tampa, FL 33606, USA.ORCID 0000-0003-4975-5140
Michelle McGeeDepartment of Surgery, University of South Florida, Tampa, FL 33606, USA.
Edmond BoxDepartment of Surgery, University of South Florida, Tampa, FL 33606, USA.ORCID 0000-0002-7316-8539
Timothy NyweningDepartment of Surgery, University of South Florida, Tampa, FL 33606, USA.
Andreas KarachristosDepartment of Surgery, University of South Florida, Tampa, FL 33606, USA.
Abraham SchwarzbergCancer Institute, Tampa General Hospital, Tampa, FL 33606, USA.
Mayer FishmanCancer Institute, Tampa General Hospital, Tampa, FL 33606, USA.
Richard JacobsonDepartment of Surgery, University of South Florida, Tampa, FL 33606, USA.ORCID 0000-0002-3432-5378

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Roughly 100,000 new cases of melanoma are diagnosed yearly in the United States, the majority of which are early-stage disease with excellent prognosis. However, a subset of patients harbors clinically occult aggressive biology that can go undetected on standard clinicopathologic analyses. Gene expression profiling (GEP) assays have emerged as molecular adjuncts to risk stratification, aiming to improve sentinel lymph node biopsy (SLNB) decision-making and surveillance planning. Two commercial tests are widely available: the 31-gene expression profile (31-GEP, DecisionDx-Melanoma, Castle Biosciences) and the clinicopathologic gene expression profile (CP-GEP, Merlin, SkylineDx). This review summarizes the current evidence for each assay regarding their performance and utility, with a focus on potentially actionable use cases, limitations, and the practical context in which these tools are most valuable.

Indexed as

gene expression panelmelanomasentinel lymph node biopsy

Identifiers

PMID42279412
PMCPMC13256794

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.