Evidence map›Paper›PMID 40029433›Full record

ArticleCancer immunology, immunotherapy : CII2025

Identification of intratumoral microbiome-driven immune modulation and therapeutic implications in diffuse large B-cell lymphoma.

Zheng Yijia, Xiaoyu Li, Lina Ma, Siying Wang, Hong Du, Yun Wu, Jing Yu, Yunxia Xiang, Daiqin Xiong, Huiting Shan and 4 more

Abstract read
In one paragraph

Article in Cancer immunology, immunotherapy : CII, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Review
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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.

Zheng Yijia *School of Pharmacy, Xinjiang Medical University, Urumqi, 830011, China.
Xiaoyu Li *School of Pharmacy, Xinjiang Medical University, Urumqi, 830011, China.
Lina Ma *School of Pharmacy, Xinjiang Medical University, Urumqi, 830011, China.
Siying WangSchool of Pharmacy, Xinjiang Medical University, Urumqi, 830011, China.
Hong DuSchool of Pharmacy, Xinjiang Medical University, Urumqi, 830011, China.
Yun WuDepartment of General Medicine, The First Affiliated Hospital of the Xinjiang Medical University, Urumqi, 830011, China.
Jing YuSchool of Pharmacy, Xinjiang Medical University, Urumqi, 830011, China.
Yunxia XiangDepartment of Pharmacy, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, 830011, China.
Daiqin XiongDepartment of Pharmacy, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, 830011, China.
Huiting ShanDepartment of Pharmacy, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, 830011, China.
Yubo WangDepartment of Pharmacy, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, 830011, China.
Zhi WangDepartment of Pharmacy, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, 830011, China.
Jianping HaoDepartment of Haematology, The First Affiliated Hospital of the Xinjiang Medical University, Urumqi, 830011, China.
Jie WangDepartment of Pharmacy, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, 830011, China. JieW629@163.com.

Funding

Xinjiang Uygur Autonomous Region Distinguished Young Scientists Fund Project 2022D01E72Xinjiang Uygur Autonomous Region Youth Science and Technology Top Talent Project-Youth Science and Technology Innova-tion Talent Training Program 2022TSYCCX0027
6 · The paper itself

Abstract

objectiveDiffuse large B-cell lymphoma (DLBCL) is the most common subtype of non-Hodgkin lymphoma, with significant clinical heterogeneity. Recent studies suggest that the intratumoral microbiome may influence the tumor microenvironment, affecting patient prognosis and therapeutic responses. This study aims to identify microbiome-related subtypes in DLBCL and assess their impact on prognosis, immune infiltration, and therapeutic sensitivity.

methodsTranscriptomic and microbiome data from 48 DLBCL patients were obtained from public databases. Consensus clustering was used to classify patients into distinct microbiome-related subtypes. Functional enrichment analysis, immune infiltration assessments, and single-cell RNA sequencing were performed to explore the biological characteristics of these subtypes. Drug sensitivity predictions were made using the OncoPredict tool. Hub genes' expression and biological function were validated and inferred in cell lines and independent cohorts of DLBCL.

resultsTwo distinct microbiome-related subtypes were identified. Patients in Cluster 1 exhibited significantly better overall survival (P < 0.05), with higher immune infiltration of regulatory T cells and M0 macrophages compared to Cluster 2, which was associated with poorer outcomes. Functional enrichment analysis revealed that genes in Cluster 1 were involved in immune regulatory pathways, including cytokine-cytokine receptor interactions and chemokine signaling, suggesting enhanced anti-tumor immune responses. In contrast, genes in Cluster 2 were enriched in immunosuppressive pathways, contributing to a less favorable prognosis. Single-cell RNA sequencing analysis revealed significant heterogeneity in immune cell populations within the tumor microenvironment. B cells exhibited the most notable heterogeneity, as indicated by stemness and differentiation potential scoring. Intercellular communication analysis demonstrated that B cells played a key role in immune cell interactions, with significant differences observed in MIF signaling between B-cell subgroups. Pseudo-time analysis further revealed distinct differentiation trajectories of B cells, highlighting their potential heterogeneity across different immune environments. Metabolic pathway analysis showed significant differences in the average expression levels of metabolic pathways among B-cell subgroups, suggesting functional specialization. Furthermore, interaction analysis between core genes involved in B-cell differentiation and microbiome-driven differentially expressed genes identified nine common genes (GSTM5, LURAP1, LINC02802, MAB21L3, C2CD4D, MMEL1, TSPAN2, and CITED4), which were found to play critical roles in B-cell differentiation and were influenced by the intratumoral microbiome. DLBCL cell lines and clinical cohorts validated that MMEL1 and CITED4 with important biologically function in DLBCL cell survival and subtype classification.

conclusionsThis study demonstrates the prognostic significance of the intratumoral microbiome in DLBCL, identifying distinct microbiome-related subtypes that impact immune infiltration, metabolic activity, and therapeutic responses. The findings provide insights into the immune heterogeneity within the tumor microenvironment, focusing on B cells and their differentiation dynamics. These results lay the foundation for microbiome-based prognostic biomarkers and personalized treatment approaches, ultimately aiming to enhance patient outcomes in DLBCL.

Indexed as

Lymphoma, Large B-Cell, DiffuseMicrobiotaFemaleHumansMalePrognosisTranscriptomeTumor MicroenvironmentDiffuse large B-cell lymphomaImmune infiltrationIntratumoral microbiomePersonalized medicineTumor microenvironment

Identifiers

PMID40029433
PMCPMC11876501

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

None linked

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.