Evidence map›Paper›PMID 38446321›Full record

ArticleBiochemical genetics2025

Immunogenic Cell Death-related Signature Evaluates the Tumor Microenvironment and Predicts the Prognosis in Diffuse Large B-Cell Lymphoma.

Shengqiang Huang, Wenbin Liu, Qiuling Zhao, Ting Chen, Ruyi Huang, Liangliang Dong, Zilin Nian, Lin Yang

Abstract read
PubMed Publisher
In one paragraph

Article in Biochemical genetics, 2025. 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
0.3field-weighted citation impact, top 41% of its field
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 citations in OpenAlex.

  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

8 authors at 2 institutions in 1 country.

Shengqiang HuangClinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, No.420, Fuma Road, Fuzhou, Fujian, China.
Wenbin LiuClinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, No.420, Fuma Road, Fuzhou, Fujian, China.
Qiuling ZhaoClinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, No.420, Fuma Road, Fuzhou, Fujian, China.
Ting ChenClinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, No.420, Fuma Road, Fuzhou, Fujian, China.
Ruyi HuangClinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, No.420, Fuma Road, Fuzhou, Fujian, China.
Liangliang DongClinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, No.420, Fuma Road, Fuzhou, Fujian, China.
Zilin NianClinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, No.420, Fuma Road, Fuzhou, Fujian, China.
Lin YangClinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, No.420, Fuma Road, Fuzhou, Fujian, China. LinYang@fjzlhospital.com.
Fujian Provincial Cancer Hospital · CNFujian Medical University · CN

Funding

Fujian Provincial Health Technology Project 2022CXA027Joint Funds for the Innovation of Science and Technology, Fujian Province 2019Y9040Natural Science Foundation of Fujian Province 2020J011117
6 · The paper itself

Abstract

Current literatures suggest a growing body of evidence highlighting the pivotal role of Immunogenic Cell Death (ICD) in multiple tumor types. Nevertheless, the potential and mechanisms of ICD in diffuse large B-cell lymphoma (DLBCL) remain inadequately studied. To address this gap, our current study aims to examine the impact of ICD on DLBCL and identify a corresponding gene signature in DLBC. Using the expression profiles of ICD-associated genes, the gene expression omnibus (GEO) samples were segregated into ICD-high and ICD-low subtypes utilizing non-negative matrix factorization clustering. Next, univariate and LASSO Cox regression analyses were employed to establish the ICD-related gene signature. Subsequently, the CIBERSORT tool, ssGSEA, and ESTIMATE algorithm were utilized to examine the association between the signature and tumor immune microenvironment of DLBC. Finally, the oncoPredict algorithm was implemented to evaluate the drug sensitivity prediction of DLBCL patients. These findings suggest that the immune microenvironment of the ICD-high group with a poor prognosis was significantly suppressed. An 8-gene ICD-related signature was identified and validated to prognosticate and evaluate the tumor immune microenvironment in DLBCL. Similarly, the high-risk group exhibited a worse prognosis compared to the low-risk group, and the immune function was considerably suppressed. Moreover, the results of oncoPredict algorithm indicated that patients in the high-risk group exhibited higher sensitivity to Cisplatin, Cytarabine, Epirubicin, Oxaliplatin, and Vincristine with low IC50. In conclusion, the present study provides novel insights into the role of ICD in DLBCL by identifying a new biomarker for the disease and may have implications for the development of immune-targeted therapies for the tumor.

Indexed as

Biomarkers, TumorImmunogenic Cell DeathLymphoma, Large B-Cell, DiffuseTumor MicroenvironmentGene Expression ProfilingGene Expression Regulation, NeoplasticHumansMalePrognosisTranscriptomeBiomarkers, TumorChemotherapyImmunogenic cell deathLymphomaPrognostic signatureTumor immune microenvironment

Identifiers

PMID38446321
OpenAlexW4392507583

What OpenQuestion holds

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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.