Evidence map›Paper›PMID 42524412›Full record

ArticleJournal of Cancer2026

A digital polymerase chain reaction method targeting non-recombined T-cell receptor sequences aids in diagnosing primary cutaneous T-cell lymphomas.

Chien-Chin Chen, Cheng-Lin Wu, Bo-Jiun Tzeng, Pin-Jun Chen, Wan-Li Chen, Sern Yan Lim, Yi-Ling Chen, Yi-Lin Chen, Chung-Liang Ho, Tsunglin Liu

Abstract read
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Article in Journal of Cancer, 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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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

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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

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4 · The record

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5 · Who and what money

Authors and funding

10 authors.

Chien-Chin ChenDepartment of Biotechnology and Bioindustry Sciences, College of Bioscience and Biotechnology, National Cheng Kung University, Tainan, Taiwan.
Cheng-Lin WuDepartment of Pathology, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan, Taiwan.
Bo-Jiun TzengInstitute of Molecular Medicine, College of Medicine, National Cheng Kung University, Tainan, Taiwan.
Pin-Jun ChenInstitute of Molecular Medicine, College of Medicine, National Cheng Kung University, Tainan, Taiwan.
Wan-Li ChenMolecular Medicine Core Laboratory, Research Center of Clinical Medicine, National Cheng Kung University Hospital, Tainan, Taiwan.
Sern Yan LimDepartment of Biotechnology and Bioindustry Sciences, College of Bioscience and Biotechnology, National Cheng Kung University, Tainan, Taiwan.
Yi-Ling ChenMedical Laboratory Science and Biotechnology, College of Medicine, National Cheng Kung University, Tainan, Taiwan.
Yi-Lin ChenDepartment of Pathology, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan, Taiwan.
Chung-Liang HoDepartment of Pathology, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan, Taiwan.
Tsunglin LiuDepartment of Biotechnology and Bioindustry Sciences, College of Bioscience and Biotechnology, National Cheng Kung University, Tainan, Taiwan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Diagnosing primary cutaneous T-cell lymphoma (PCTCL) relies on the comprehensive evaluation of clinical presentation, histopathology, immune profile, and molecular testing. Regarding molecular testing, the BIOMED-2 assay is most commonly used for detecting monoclonality of T-cell receptor (TCR) genes. However, its sensitivity is not ideal for PCTCLs, and a supplementary test is required. We recently found that the ratios of non-recombined TCR sequences J2-2P and J2-3 of the Methods: Formalin-fixed paraffin-embedded tissue samples of clinicopathologically proven PCTCL cases with a negative BIOMED-2 clonality result were retrospectively retrieved, and the clinicopathological characteristics were collected. After RNA extraction and quality checking, dPCR was performed on PCTCL specimens and control samples to quantify the J2-2P and J2-3 sequences. Results: We collected 35 skin biopsy samples from patients with early-stage PCTCL and 11 inflammatory dermatoses as controls. Ratios of the J2-2P to J2-3 concentration in controls ranged from 0.03 to 0.55% (mean ± standard deviation: 0.21 ± 0.17%). In contrast, 25 of the 35 (71.42%) PCTCL specimens exhibited J2-2P/J2-3 ratios exceeding the defined upper limit of the control group. Conclusion: Our dPCR assay on the non-recombined

Indexed as

BIOMED-2cutaneous T-cell lymphomadigital PCRT-cell receptor

Identifiers

PMID42524412
PMCPMC13410567

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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.