Evidence map›Paper›PMID 42688584›Full record

ArticleeGastroenterology2026

Plasma cell-CD8+ T cell co-enrichment distinguishes immunotherapy-responsive hepatocellular carcinoma subtypes.

Aryan Neupane, Anuradha Budhu, Farid Rashidi Mehrabadi, Aiwu He, Lipika Goyal, Robin Kate Kelley, Tim F Greten, Xin Wei Wang

Abstract read
In one paragraph

Article in eGastroenterology, 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
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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

8 authors.

Aryan NeupaneLiver Cancer Program, National Cancer Institute, Center for Cancer Research, Bethesda, Maryland, USA.
Anuradha BudhuLiver Cancer Program, National Cancer Institute, Center for Cancer Research, Bethesda, Maryland, USA.ORCID https://orcid.org/0000-0001-7724-751X
Farid Rashidi MehrabadiLaboratory of Human Carcinogenesis, National Cancer Institute, Center for Cancer Research, Bethesda, Maryland, USA.
Aiwu HeDepartment of Medicine, Columbia University Irving Medical Center, New York City, New York, USA.
Lipika GoyalDepartment of Medical Oncology, Stanford University, Stanford, California, USA.
Robin Kate KelleyDepartment of Medicine (Hematology/Oncology), UCSF Helen Diller Family Comprehensive Cancer Center, San Francisco, California, USA.
Tim F GretenLiver Cancer Program, National Cancer Institute, Center for Cancer Research, Bethesda, Maryland, USA.
Xin Wei WangLiver Cancer Program, National Cancer Institute, Center for Cancer Research, Bethesda, Maryland, USA.

Funding

Liver Cancer ProgramZIABC011870 · NCI · DIVISION OF BASIC SCIENCES - NCI · PI WANG, XIN WEI · 2019 to 2025
$10.1M
Molecular signatures for liver cancer diagnosis and treatment stratificationZ01BC010313 · NCI · DIVISION OF BASIC SCIENCES - NCI · PI WANG, XIN WEI · 1999 to 2008
$1.8M
The role of cancer stem cells in liver cancer heterogeneity and subtypesZ01BC010876 · NCI · DIVISION OF BASIC SCIENCES - NCI · PI WANG, XIN · 2008 to 2008
$490k
The identification of human hepatocellular carcinoma metastasis genesZ01BC010877 · NCI · DIVISION OF BASIC SCIENCES - NCI · PI WANG, XIN · 2008 to 2008
$327k
Intramural NIH HHS Z01 BC010313Intramural NIH HHS Z01 BC010876Intramural NIH HHS Z01 BC010877Intramural NIH HHS ZIA BC011870NCI NIH HHS HHSN261201800001C
6 · The paper itself

Abstract

Background: Hepatocellular carcinoma (HCC) is characterised by significant racial disparities in incidence and outcomes, yet whether these reflect distinct tumour biology or differential distribution of molecular subtypes among immunotherapy patients remains unclear. Methods: We characterised molecular heterogeneity among 46 patients with HCC of differing background population from the NCI-CLARITY cohort receiving immune checkpoint inhibitor therapy, using transcriptomic and genomic profiling, with validation across multiple independent cohorts. Results: Differential expression analysis comparing African American versus non-African American patients identified 126 genes, of which 55 demonstrated tumour-specific expression across independent validation cohorts with paired tumour-normal samples. Consensus clustering revealed two molecular subtypes with no significant race association, indicating these clusters capture tumour-intrinsic biology rather than ancestry. The genomic landscape showed minimal differences between subtypes. A prognostic signature derived from these expression profiles demonstrated significant risk stratification in the NCI-CLARITY cohort and TCGA-LIHC, but not in Asian cohorts, suggesting population-specific applicability. Immune deconvolution revealed that the two subtypes represent distinct immune microenvironments: one subtype exhibited markedly elevated plasma cell infiltration with strong plasma cell-CD8+T cell correlation suggesting coordinated adaptive immunity, along with elevated tertiary lymphoid structure signatures. The other subtype showed regulatory T cell-macrophage correlation and enrichment for immune-excluded phenotypes. The immune-enriched subtype trended towards higher immunotherapy response rates. Conclusions: Molecular heterogeneity in HCC reveals distinct tumour-immune ecosystems that transcend racial classification. Tumour immune heterogeneity in HCC reflects distinct molecular patterns, with immune hot tumours characterised by elevated tertiary lymphoid structure signatures and enriched plasma cell and CD8+T cells. These patterns may serve as prognostic biomarkers for immunotherapy patient stratification and demonstrate the value of diverse cohort representation in identifying clinically relevant therapeutic targets.

Indexed as

Gastrointestinal CancerImmunityInflammationLiver DiseasesLiver Neoplasms

Identifiers

PMID42688584
PMCPMC13536050

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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.