Evidence map›Paper›PMID 39068564›Full record

ArticleAsian Pacific journal of cancer prevention : APJCP2024

To Establish a Nomogram Prediction of Prostate Cancer Based on Pyroptosis-Related Genes that Affect the Immune Microenvironment.

Chundong Ji, Sandeep Shrestha, Farra Aidah Jumuddin

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Article in Asian Pacific journal of cancer prevention : APJCP, 2024. 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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3 · Its place in the literature

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2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Chundong JiDepartment of Histology and Pathology, Faculty of Medicine, Lincoln University College, Malaysia.ORCID 0000-0002-6858-7413
Sandeep ShresthaDepartment of Histology and Pathology, Faculty of Medicine, Lincoln University College, Malaysia.
Farra Aidah JumuddinDepartment of Histology and Pathology, Faculty of Medicine, Lincoln University College, Malaysia.ORCID 0000-0002-3817-7050

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundProstate cancer is the most common tumor in men worldwide with a poor prognosis. In recent years, studies have revealed that pyroptosis can affect the tumor immune microenvironment. However, the relationship between the immune microenvironment regulated by pyroptosis-related genes and the prognosis of prostate cancer is still unclear.

methodsThirty-three cell death-associated genes were selected from a literature review. The "DESeq2" R package was used to identify differentially expressed cell death-associated genes between normal prostate tissue (GTEx) and prostate cancer tissue (TCGA) samples. Biological functional enrichment analysis of differentially expressed cell death genes was performed using R statistical software packages, such as "clusterProfiler," "org.Hs.eg.db," "enrichplot," "ggplot2," and "GOplot." Univariate Cox and LASSO Cox regression analyses were conducted to identify prognostic genes associated with the immune microenvironment using the "survival" package. Finally, a predictive model was established based on Gleason score, T stage, and cell death-associated genes.odel was established based on Gleason score, T stage, and cell death-associated genes.

resultsSeventeen differentially expressed genes related to pyroptosis were screened out. Based on these differentially expressed genes, biological function enrichment analysis showed that they were related to pyroptosis of prostate cells. Based on univariate Cox and (LASSO) Cox regression analysis, four pyroptosis-related genes (CASP3, PLCG1, GSDMB, GPX4) were determined to be related to the prognosis of prostate cancer, and the immune correlation analysis of the four pyroptosis-related genes was performed. The expression of CASP3, PLCG1 and GSDMB was positively correlated with the proportion of immune cells, and the expression of GPX4 was negatively correlated with the proportion of immune cells. A predictive nomogram was established by combining Gleason score, T and pyroptosis genes. The nomogram was accompanied by a calibration curve and used to predict 1 -, 2 -, and 5-year survival in PAAD patients.

conclusionCell death-associated genes (CASP3, PLCG1, GSDMB, GPX4) play crucial roles in modulating the immune microenvironment and can be used to predict the prognosis of prostate cancer.

Indexed as

Biomarkers, TumorNomogramsProstatic NeoplasmsPyroptosisTumor MicroenvironmentGene Expression Regulation, NeoplasticHumansMalePrognosisBiomarkers, TumorImmune microenvironmentprognostic modelProstate CancerPyroptosis

Identifiers

PMID39068564
PMCPMC11480613

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