Flow cytometric assessment of T-cell receptor β-chain constant region 1/2 skewing as a surrogate marker for clonality in human T-cell leukaemia virus type-1-infected cells.

Authors

Koji Jimbo, Aileen G Rowan, Momoko Usui, Kako Suzuki, Makoto Yamagishi, Junya Makiyama, Lucy B M Cook, Yoshihisa Yamano, Kaoru Uchimaru, Yasuhito Nannya, Shigeo Fuji

Published in

British journal of haematology. Oct 16, 2026. Epub Oct 16, 2026.

Abstract

Estimating T-cell clonality within human T-cell leukaemia virus type 1 (HTLV-1)-infected cell populations may aid risk assessment and diagnosis of adult T-cell leukaemia/lymphoma (ATL). However, direct assessment of HTLV-1 integration-site clonality requires genetic analyses that are costly and labour-intensive. We developed a simple flow cytometric surrogate assay by combining the HTLV-1 analysis system by flow cytometry (HAS-Flow) method, which efficiently identifies HTLV-1-infected cells, with T-cell receptor β-chain constant region (TRBC1/2) staining. We analysed 53 HTLV-1-infected individuals, including asymptomatic carriers (n = 25), patients with HTLV-1-associated myelopathy (n = 4) and patients with ATL (n = 24). TRBC1/2 skewing was quantified using the dominant TRBC ratio. The dominant TRBC ratio was significantly higher in ATL than in non-ATL cases and effectively discriminated ATL from non-ATL cases (Area under the receiver operating characteristic curve [AUC], 0.913; 95% confidence interval, 0.803-1.000; p < 0.0001). It correlated with established markers of disease progression, including abnormal lymphocyte burden, proviral load and soluble interleukin-2 receptor levels, as well as clonality assessed by two independent HTLV-1 integration-site-based methods (viral integration site and RAISING-CLOVA). These findings indicate that assessment of TRBC1/2 skewing in HTLV-1-infected cells (HAS-TRBC method) is a simple, cost-effective surrogate for estimating T-cell clonality within HTLV-1-infected cell populations, with potential clinical utility.

PMID:
42885517
Bibliographic data and abstract were imported from PubMed on 16 Oct 2026.

Read full publication at:
Please sign in to see all details.

Stats

1-terrible, 9-excellent. How would you rate this publication? Sign in in to submit your rating.

Post a comment

You need to be signed in to post comments. You can sign in here.

Comments

There are no comments yet.