Evidence map›Paper›PMID 41080575›Full record

ArticleFrontiers in immunology2025

Dendritic cell-related gene signature in pancreatic cancer stratifies patient subtypes and implicates a KCTD14-TNF signaling axis.

Yuxin Liang, Yuheng Gu, Zilong Zhang, Deyuan Zhong, Hongtao Yan, Yuhao Su, Yahui Chen, Fei Wang, Zhengwei Leng, Xiaolun Huang

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in immunology, 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
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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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

10 authors.

Yuxin Liang *Liver Transplantation Center and HBP Surgery, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China.
Yuheng Gu *Clinical Medical College, Southwest Medical University, Luzhou, China.
Zilong Zhang *Hepatic Surgery Center, Clinical Medical Research Center of Hepatic Surgery at Hubei Province, Hubei Key Laboratory of Hepato-Pancreatic-Biliary Diseases, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
Deyuan ZhongLiver Transplantation Center and HBP Surgery, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China.
Hongtao YanLiver Transplantation Center and HBP Surgery, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China.
Yuhao SuLiver Transplantation Center and HBP Surgery, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China.
Yahui ChenLiver Transplantation Center and HBP Surgery, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China.
Fei WangCenter for Natural Products Research, Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, China.
Zhengwei LengLiver Transplantation Center and HBP Surgery, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China.
Xiaolun HuangLiver Transplantation Center and HBP Surgery, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Pancreatic cancer (PC) is characterized by a profoundly immunosuppressive tumor microenvironment and poor prognosis. Dendritic cells (DCs) are pivotal for antigen presentation and T-cell activation, yet their prognostic and mechanistic roles in PC remain incompletely defined. Methods: This study performed weighted gene co-expression network analysis (WGCNA) on transcriptomic data from The Cancer Genome Atlas (TCGA) and two Gene Expression Omnibus cohorts (GSE62165, GSE85916) to identify DC-related gene modules. Consensus clustering based on these modules stratified patients into two immune phenotypes. A four-gene DC-related risk score (DCRS) was constructed using LASSO-Cox regression and validated in independent cohorts. Single-cell RNA sequencing data from 25 PC samples (GSE242230) were analyzed through cell clustering analysis, cell-cell communication analysis, and pathway-specific analysis. Functional assays following Results: WGCNA identified 130 overlapping DC-related genes enriched in immune pathways. Two DC-related patient clusters exhibited distinct overall survival (OS) (P < 0.05). The DCRS robustly stratified patients into high- and low-risk groups in both TCGA training and validation sets. DCRS demonstrated good predictive potential for OS and there is a significant difference in OS between the two groups of patients ( Conclusion: We identified a novel DC-related gene signature that stratifies PC patients by prognosis and highlights KCTD14 as a novel immunomodulatory oncogene acting through the TNF-TNFR1 axis. Our findings provide a foundation for integrating DCRS into clinical risk assessment and for pursuing KCTD14/TNFR1-targeted therapies to overcome DC-mediated immune suppression in pancreatic cancer.

Indexed as

Dendritic CellsPancreatic NeoplasmsTranscriptomeTumor Necrosis Factor-alphaBiomarkers, TumorCell Line, TumorFemaleGene Expression ProfilingGene Expression Regulation, NeoplasticGene Regulatory NetworksHumansPrognosisSignal TransductionTumor MicroenvironmentBiomarkers, TumorTNF protein, humanTumor Necrosis Factor-alphadendritic cellsKctd14pancreatic ductal adenocarcinomaprognosissignatureTNF signaling

Identifiers

PMID41080575
PMCPMC12507779

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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.