Evidence map›Paper›PMID 42060374›Full record

ArticleAnalytical cellular pathology (Amsterdam)2026

The Role of Chemokine-Related Genes in Diffuse Large B-Cell Lymphoma Prognosis and Tumor Microenvironment Characteristics.

Anna Su, Yunfei Zhao, Zongze Gu, Laxin Sabitjan, Gulimire Adili, Xun Li, Weiling Yu

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Analytical cellular pathology (Amsterdam), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

7 authors.

Anna SuDepartment of Oncology, The Fourth Clinical Medical College of Xinjiang Medical University, Urumqi, Xinjiang, China, xjmu.edu.cn.ORCID https://orcid.org/0009-0007-4828-0602
Yunfei ZhaoDepartment of Oncology, The Fourth Clinical Medical College of Xinjiang Medical University, Urumqi, Xinjiang, China, xjmu.edu.cn.ORCID https://orcid.org/0009-0000-7161-2192
Zongze GuDepartment of Oncology, The Fourth Clinical Medical College of Xinjiang Medical University, Urumqi, Xinjiang, China, xjmu.edu.cn.ORCID https://orcid.org/0009-0004-8386-6762
Laxin SabitjanDepartment of Oncology, The Fourth Clinical Medical College of Xinjiang Medical University, Urumqi, Xinjiang, China, xjmu.edu.cn.ORCID https://orcid.org/0009-0004-9425-0664
Gulimire AdiliDepartment of Oncology, The Fourth Clinical Medical College of Xinjiang Medical University, Urumqi, Xinjiang, China, xjmu.edu.cn.ORCID https://orcid.org/0009-0003-4993-6635
Xun LiDepartment of Oncology, The Fourth Clinical Medical College of Xinjiang Medical University, Urumqi, Xinjiang, China, xjmu.edu.cn.ORCID https://orcid.org/0000-0002-2118-0261
Weiling YuHaikou People's Hospital, Haikou, Hainan, China.ORCID https://orcid.org/0009-0007-4930-686X

Funding

Natural Science Foundation of Xinjiang Uygur Autonomous Region 2023D01C135Xinjiang Uygur Autonomous Region Graduate Student Research and Innovation Program XJ2025G162Xinjiang Uygur Autonomous Region "Tianchi Talent" Talent Introduction Program
6 · The paper itself

Abstract

backgroundDiffuse large B-cell lymphoma (DLBCL) is a malignant neoplasm characterized by intermediate to high aggressiveness and heterogeneity. Chemokines and their receptors are involved in various antitumor and protumor immune processes in vivo and influence patient prognosis and treatment response. Therefore, investigating the potential associations between chemotactic cytokine-related genes (CCRGs) and prognosis, as well as the immune microenvironment in DLBCL holds significant importance.

methodsDifferentially expressed and prognosis-related CCRGs in DLBCL were extracted from the GEO database. A prognostic risk model was constructed using Lasso-Cox regression analysis, followed by internal and external cohort validation to assess the model's predictive independence. This risk model was then applied to immunological analysis, enrichment analysis, and drug prediction analysis. Single-cell sequencing was employed to investigate the correlation between genes in the prognostic model and immune cell types.

resultsWe identified 23 prognosis-related CCRGs and revealed two CCRG-associated subtypes exhibiting distinct immune processes. Subsequently, a six-gene prognostic model was established using LASSO-Cox regression analysis. Univariate and multivariate prognostic analyses demonstrated that the risk model serves as an independent prognostic factor, and both the CCRG prognostic model and signature genes showed a significant correlation with the tumor immune microenvironment (TIME).

conclusionThe CCRG risk model proposed in this study can accurately and stably predict the prognosis of DLBCL patients and is closely associated with the TIME, providing new targets and theoretical support for DLBCL patients.

Indexed as

ChemokinesLymphoma, Large B-Cell, DiffuseTumor MicroenvironmentBiomarkers, TumorFemaleGene Expression Regulation, NeoplasticHumansPrognosisBiomarkers, TumorChemokineschemokines and receptorsdiffuse large B-cell lymphomaimmune checkpointsprognostic biomarkerstumor immune microenvironment

Identifiers

PMID42060374
PMCPMC13131906

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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.