Evidence map›Paper›PMID 41522514›Full record

ArticlePeerJ2026

Analysis of molecular subtypes and prognostic signature of senescence-associated secretory phenotype in pancreatic cancer.

Yuewen Kuang, Mingkun Jia, Yuming Zhu, Zhiyong Xiang

Abstract read
In one paragraph

Article in PeerJ, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Yuewen KuangHepatobiliary and Pancreatic Surgery, The Third Affiliated Hospital of Chongqing Medical University (Fangda Hospital), Chongqing, China.
Mingkun JiaHepatobiliary and Pancreatic Surgery, The Third Affiliated Hospital of Chongqing Medical University (Fangda Hospital), Chongqing, China.
Yuming ZhuHepatobiliary and Pancreatic Surgery, The Third Affiliated Hospital of Chongqing Medical University (Fangda Hospital), Chongqing, China.
Zhiyong XiangHepatobiliary and Pancreatic Surgery, The Third Affiliated Hospital of Chongqing Medical University (Fangda Hospital), Chongqing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Pancreatic cancer (PC) exhibits an extremely poor prognosis due to its high heterogeneity. The senescence-associated secretory phenotype (SASP), a distinct secretory profile displayed by senescent cells, has been increasingly studied. However, the role of SASP in PC prognosis and treatment remains unclear. Methods: Transcriptomic sequencing data from PC patients were analyzed using consensus clustering based on SASP genes. A prognostic signature was subsequently constructed Results: Consensus clustering based on SASP genes identified two SASP-associated clusters (SASPclusters), with cluster B demonstrating significantly worse prognosis than cluster A. Thirty-three SASP genes showed significant associations with PC prognosis, and a 7-gene SASP-based prognostic signature was established. High-risk patients exhibited significantly higher mutation rates. Distinct immune cell infiltration patterns, immune functions, checkpoint expression levels, and chemosensitivity profiles were observed between risk groups. Besides, we found that ANGPTL4 could promote PC cell proliferation, migration, and invasion. Conclusion: Molecular subtyping and risk stratification based on SASP genes effectively predict PC prognosis and reveal heterogeneity in mutational burden, immune microenvironment, and therapeutic sensitivity. These computational findings deepen our understanding of potential role of SASP in PC and provide a theoretical foundation for personalized treatment strategies.

Indexed as

Pancreatic NeoplasmsSenescence-Associated Secretory PhenotypeAngiopoietin-Like Protein 4Biomarkers, TumorCell ProliferationCellular SenescenceGene Expression ProfilingGene Expression Regulation, NeoplasticHumansMutationPhenotypePrognosisTumor MicroenvironmentAngiopoietin-Like Protein 4ANGPTL4 protein, humanBiomarkers, TumorPancreatic cancerSenescence-associated secretory phenotypeTumor microenvironment

Identifiers

PMID41522514
PMCPMC12786131

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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.