Evidence map›Paper›PMID 37782328›Full record

ArticleJournal of cancer research and clinical oncology2023

Identification of a potential prognostic model combining pyroptosis-related gene with immune microenvironment for pancreatic ductal adenocarcinoma.

Haoran Xie, Jingxian Xu, Qiuyan Zhao

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Article in Journal of cancer research and clinical oncology, 2023. 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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1 · What the graph read from it

What it found

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

3 authors at 3 institutions in 1 country.

Haoran Xie *Hepatobiliary Pancreatic Center, Beijing Tsinghua Changgung Hospital, School of Clinical Medicine, Tsinghua University, Beijing, China.
Jingxian Xu *Department of Gastroenterology, Peking University Third Hospital, Beijing, China.
Qiuyan ZhaoDepartment of Gastroenterology, Henan Provincial People's Hospital, People's Hospital of Zhengzhou University, Zhengzhou, Henan, China. zhaosjtu@163.com.
Beijing Tsinghua Chang Gung Hospital · CNPeking University Third Hospital · CNZhengzhou University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPancreatic ductal adenocarcinoma (PDAC) is a fatal tumor with grave prognosis. Pyroptosis, a programmed cell death, is involved in tumorigenesis. However, a few studies have elucidated the functions of pyroptosis in PDAC.

methodsThe mRNA expression profiles were downloaded from the TCGA and GEO databases. Univariate and LASSO Cox regression analyses were used to screen out differentially expressed genes (DEGs) and construct the pyroptosis-related genes (PRGs) risk model. The efficiency of model was examined by Kaplan-Meier curve, ROC curve, and nomogram. Univariate and multivariate Cox regression analyses were utilized to assess whether the risk model could be used as an independent prognostic factor. The biological function was analyzed by GO, KEGG, and GSEA enrichment analysis. qRT-PCR and immunohistochemical staining detected gene expression.

resultsTotally 9 PRGs with differential expression were identified between normal and PDAC tissues. Then, according to PRGs, we filtered out three key DEGs and constructed the prognostic risk model. Kaplan-Meier curve, ROC curve, and nomogram indicated that the prognostic risk model had high survival prediction efficiency. Meanwhile, the risk model had also shown to be an independent prognostic factor. Further functional enrichment analysis showed that cell adhesion, PI3K-AKT signaling pathway, and dysregulated immune status may be associated with PDAC development. External validation of the model was carried out in the GEO cohort, and the results were similar to that in the TCGA cohort. Finally, the expression of three genes was verified by qRT-PCR and immunohistochemical staining.

conclusionThe prognostic risk model established in this study can give a good prediction of the prognosis of PDAC patients, which might provide insights into clinical treatments and prognostic prediction of PDAC.

Indexed as

Carcinoma, Pancreatic DuctalPancreatic NeoplasmsHumansPhosphatidylinositol 3-KinasesPrognosisPyroptosisTumor MicroenvironmentPhosphatidylinositol 3-KinasesImmune infiltrationPancreatic ductal adenocarcinomaPrognosisPyroptosisRisk model

Identifiers

PMID37782328
PMCPMC11797131
OpenAlexW4387241660

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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.