Evidence map›Paper›PMID 42174674›Full record

ArticleBiomarker research2026

Single-cell transcriptomic mapping of immune heterogeneity across angioimmunoblastic T-cell lymphoma subtypes.

Huimin Liu, Yang Tong, Meijuan Wu, Zhuoxin Zhang, Yao Yao, Zhanqi Li, Yin Shi, Zhen Yu, Gang An, Lugui Qiu and 4 more

Abstract readLetter
In one paragraph

Article in Biomarker research, 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

14 authors.

Huimin Liu *State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, 300020, China.
Yang Tong *State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, 300020, China.
Meijuan Wu *Zhejiang Cancer Hospital, Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, Zhejiang, 310022, China.
Zhuoxin ZhangState Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, 300020, China.
Yao YaoState Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, 300020, China.
Zhanqi LiState Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, 300020, China.
Yin ShiState Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, 300020, China.
Zhen YuState Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, 300020, China.
Gang AnState Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, 300020, China.
Lugui QiuState Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, 300020, China.
Yang YangThe Province and Ministry Co-Sponsored Collaborative Innovation Center for Medical Epigenetics, State Key Laboratory of Experimental Hematology, Tianjin Key Laboratory of Inflammatory Biology, Department of Bioinformatics, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, 300070, China. yy@tmu.edu.cn.
Haiyan YangZhejiang Cancer Hospital, Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, Zhejiang, 310022, China. yanghy@zjcc.org.cn.
Dehui ZouState Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, 300020, China. zoudehui@ihcams.ac.cn.
Jiapei YuanState Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, 300020, China. yuanjiapei@ihcams.ac.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Relapse and treatment resistance remain critical obstacles in the clinical management of angioimmunoblastic T-cell lymphoma (AITL), limiting the success of current therapeutic strategies. Therefore, a comprehensive characterization of the tumor microenvironment (TME) in AITL is essential to enhance treatment efficacy. This study analyzed samples from 68 patients with AITL, stratified into three molecular subtypes based on immunoglobulin (IG) gene rearrangement and flow cytometry results. Utilizing single-cell RNA sequencing, the TME was profiled across subtypes A, B, and C, sampling multiple disease sites including the bone marrow, lymph nodes, and peripheral blood. Our findings revealed subtype-specific variations in cellular composition and transcriptional programs within the TME. Unlike other subtypes, subtype C was associated with a pronounced immunosuppressive environment at diagnosis and relapse. Additionally, it exhibited an enhanced response to Epstein-Barr virus infection, consistent with upregulated CD70 expression at relapse. Through the analysis of cellular communication networks, CD70, programmed cell death 1 (PDCD1), and inducible T cell costimulator (ICOS) were identified as promising immunotherapeutic targets in AITL. Finally, we delineated distinct cellular proportions and gene expression signatures characteristic of each subtype, providing a foundation for the development of tailored therapeutic interventions for patients with AITL.

Indexed as

Angioimmunoblastic T-cell lymphomaLongitudinal profilingSpatial heterogeneityTumor microenvironment

Identifiers

PMID42174674
PMCPMC13198054

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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.