Evidence map›Paper›PMID 42404264›Full record

ArticleJID innovations : skin science from molecules to population health2026

High-throughput, multiplex immunofluorescence for the computer-automated immunophenotyping of Mycosis Fungoides.

Patrick McMullan, Marc R Benoit, Nathan Gasek, Sydney Riddick, Joseph Masison, Katalin Ferenczi, David Rowe, Gillian Weston

Abstract read
In one paragraph

Article in JID innovations : skin science from molecules to population health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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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

8 authors.

Patrick McMullanDepartment of Dermatology, University of Connecticut School of Medicine, Farmington, Connecticut, USA.
Marc R BenoitDepartment of Neuroscience, University of Connecticut School of Medicine, Farmington, Connecticut, USA.
Nathan GasekDepartment of Dermatology, University of Connecticut School of Medicine, Farmington, Connecticut, USA.
Sydney RiddickDepartment of Dermatology, University of Connecticut School of Medicine, Farmington, Connecticut, USA.
Joseph MasisonDepartment of Dermatology, University of Connecticut School of Medicine, Farmington, Connecticut, USA.
Katalin FerencziDepartment of Dermatology, University of Connecticut School of Medicine, Farmington, Connecticut, USA.
David RoweDepartment of Reconstructive Sciences, Center for Regenerative Medicine and Skeletal Development, University of Connecticut School of Dental Medicine, Farmington, Connecticut, USA.
Gillian WestonDepartment of Dermatology, University of Connecticut School of Medicine, Farmington, Connecticut, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The diagnosis of mycosis fungoides is difficult and often delayed, exacerbated by the limitation of conventional immunohistochemistry to analyze only 1 antigen per tissue section, often necessitating repeat biopsies and extensive workups. We sought to validate a high-throughput multiplex immunofluorescence method, coupled with computer-automated image analysis, to generate comprehensive immunophenotyping data from a single formalin-fixed, paraffin-embedded biopsy. We applied an 11-biomarker multiplex immunofluorescence panel across 18 archived skin specimens (9 mycosis fungoides/TCR clonality positive and 9 control/TCR clonality negative). Initial validation confirmed that multiplex immunofluorescence antigen expression and spatial localization were concordant with those of sequential immunohistochemistry-stained sections. Whole-slide image stacks were analyzed using both computer-assisted and computer-automated pipelines. Both methods successfully delineated immunophenotypic differences. Mycosis fungoides specimens showed a significant expansion of hematopoietic cells, atypical T-lymphocytes, and proliferative T-lymphocytes when compared with controls. Our results validate the potential of multiplex immunofluorescence to obtain comprehensive, high-dimensional diagnostic information from a single tissue section. Integration with computer-automated analysis offers a scalable, high-throughput platform that can significantly aid in the timely and accurate diagnosis of cutaneous lymphomas.

Indexed as

ImmunohistochemistryImmunophenotypingMultiplex immunofluorescenceMycosis fungoides

Identifiers

PMID42404264
PMCPMC13330524

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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.