Evidence map›Paper›PMID 39960565›Full record

ArticleDiscover oncology2025

Identification of exosome-related genes associated with prognosis and immune infiltration features in pancreatic cancer.

Jie Wang, Ming Qing, Jie Gui, Pingyong Zhong, Hao Hua

Abstract read
In one paragraph

Article in Discover oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Jie Wang *Department of Hepatobiliary Surgery, Southwest Hospital, Third Military Medical University (Army Medical University), Chongqing, China.
Ming Qing *Department of Hepatobiliary Surgery, The First People's Hospital of Neijiang, Sichuan, China.
Jie GuiDepartment of Hepatobiliary Surgery, The First Affiliated Hospital of Chongqing Medical University, No. 1, Youyi Road, Yuan Jiagang, Yuzhong District, Chongqing, 400016, People's Republic of China.
Pingyong ZhongDepartment of Hepatobiliary Surgery, The First People's Hospital of Neijiang, Sichuan, China.
Hao HuaDepartment of Hepatobiliary Surgery, The First Affiliated Hospital of Chongqing Medical University, No. 1, Youyi Road, Yuan Jiagang, Yuzhong District, Chongqing, 400016, People's Republic of China. 529065285@qq.com.

Funding

the National Nature Science Foundation of China 82403622
6 · The paper itself

Abstract

backgroundThis study is designed to explore the prognostic significance of exosome-related genes (ERGs) and their impact on the the tumor microenvironment (TME) of pancreatic cancer.

methodsTranscriptomic data alongside clinical details of patients with PC were retrieved from both The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) repository. A collection of 121 exosome-associated genes were obtained from the ExoBCD database. For constructing a risk scoring model, the absolute shrinkage and selection operator (LASSO) regression method was employed. Gene set enrichment and variance analyses were facilitated by the clusterProfiler and GSVA R software tools. Additionally, CIBERSORT was used to estimate immune cell infiltration levels. Lastly, the TIDE algorithm was leveraged to evaluate the connection between gene expression and drug sensitivity. A series of experiments were used to verify the role of DLGAP5 in PC.

resultsTwo unique molecular clusters were uncovered, and our analysis revealed a connection between ERG dysregulation across multiple layers and patient demographic, histopathological attributes, prognosis, as well as immune cell infiltration patterns within the TME. An ERG_score was developed for forecasting overall survival and its predictive capacity was confirmed in PC cases. A precise nomogram was established to enhance the clinical utility of the ERG_score. Patients in the low-risk group exhibited higher immune and ESTIMATE scores than that in the high-risk group, displaying an improved overall survival (OS). The ERG_score was associated with cancer stem cell (CSC) index and drug sensitivity. Crucial evaluations of ERGs illuminated the significance of DLGAP5, emphasizing its expression in PC and its contributory role in tumor growth stimulation.

conclusionsOur investigation reveals a correlation between the exosome-related risk assessment signature and the survival outcome as well as immune cell infiltration in patients with PC. This finding potentially paves the way for enhanced therapeutic strategies for PC.

Indexed as

ExosomePancreatic cancerPrognosisRisk signatureThe tumor microenvironment

Identifiers

PMID39960565
PMCPMC11832983

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