Evidence map›Paper›PMID 41113120›Full record

ArticleJHEP reports : innovation in hepatology2025

Landscape of T-cell exhaustion heterogeneity and HBV integration in virus-related HCC revealed by whole-exome, transcriptome, and single-cell sequencing.

Soon Kyu Lee, Jinyeong Lim, Joo Yeon Jhun, Jeonghyeon Moon, Hye Seon Kim, Jong Young Choi, Ho Joong Choi, Young Kyoung You, Ji Won Han, Pil Soo Sung and 5 more

Abstract read
In one paragraph

Article in JHEP reports : innovation in hepatology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Review
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  5. Review
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

15 authors.

Soon Kyu LeeDivision of Gastroenterology and Hepatology, Department of Internal Medicine, Incheon St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea.
Jinyeong LimDepartment of Health Sciences and Technology, Samsung Advanced Institute for Health Science and Technology, Sungkyunkwan University, Seoul, Republic of Korea.
Joo Yeon JhunDepartment of Pathology, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea.
Jeonghyeon MoonDepartments of Neurology and Immunobiology, Yale School of Medicine, New Haven 06511, CT, USA.
Hye Seon KimThe Catholic University Liver Research Center, Collage of Medicine, The Catholic University of Korea, Seoul, Republic of Korea.
Jong Young ChoiThe Catholic University Liver Research Center, Collage of Medicine, The Catholic University of Korea, Seoul, Republic of Korea.
Ho Joong ChoiDepartment of Surgery, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea.
Young Kyoung YouDepartment of Surgery, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea.
Ji Won HanThe Catholic University Liver Research Center, Collage of Medicine, The Catholic University of Korea, Seoul, Republic of Korea.
Pil Soo SungThe Catholic University Liver Research Center, Collage of Medicine, The Catholic University of Korea, Seoul, Republic of Korea.
Kwon Yong TakThe Catholic University Liver Research Center, Collage of Medicine, The Catholic University of Korea, Seoul, Republic of Korea.
Seung Kew YoonThe Catholic University Liver Research Center, Collage of Medicine, The Catholic University of Korea, Seoul, Republic of Korea.
Woong-Yang ParkDepartment of Health Sciences and Technology, Samsung Advanced Institute for Health Science and Technology, Sungkyunkwan University, Seoul, Republic of Korea.
Mi-La ChoDepartment of Pathology, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea.
Jeong Won JangThe Catholic University Liver Research Center, Collage of Medicine, The Catholic University of Korea, Seoul, Republic of Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background & Aims: To enhance our understanding of the tumor immune microenvironment (TIME) in hepatocellular carcinoma (HCC), we investigated the heterogeneity of T-cell exhaustion and its association with HBV integrations and direct oncogenic potential in HCC. Methods: We conducted a multi-omics analysis, including single-cell RNA sequencing, whole-exome sequencing, whole-transcriptome sequencing, and next-generation sequencing (NGS)-based HBV integration analysis, in eight patients with virus-related HCC. For validation, bulk RNA sequencing and NGS-based HBV integration analysis were performed in an independent cohort (n = 106). Results: Based on the expression scores of exhaustion markers in effector CD8 Conclusions: Our study revealed the heterogeneity in T-cell exhaustion in the TIME of HCC, along with differences in HBV integrations and molecular subtypes. These findings provide insight into the intricate relationship between high exhaustion, proliferation subtype, increased HBV integrations, and enhanced HBV-induced oncogenic potential in virus-related HCC. Impact and implications: This study provides a comprehensive immune landscape of T-cell exhaustion using multi-omics analysis, offering critical insights into T cell heterogeneity in virus-related HCC. It establishes a strong association between higher HBV integration, enhanced oncogenic potential, T-cell exhaustion, and proliferation subtypes in HCC. Our results also establish a basis for personalized therapies tailored to the immune-exhaustion status within the TIME of each patient with HCC.

Indexed as

HBV integrationHepatocellular carcinomaSingle-cell RNA sequencingT cellWhole-exome sequencingWhole-transcriptome sequencing

Identifiers

PMID41113120
PMCPMC12529496

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LicenceCC BY-NC-ND
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Registered trials

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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.