The role of acrylamide exposure in prostate cancer progression: An integrated analysis based on network toxicology and experimental validation

OBJECTIVE: Acrylamide (AA), a widespread environmental and food-borne pollutant, has been classified as a probable human carcinogen. However, its specific role and underlying mechanisms in the progression of prostate cancer (PCa) remain poorly elucidated. This study aims to comprehensively investigate the effect of AA on PCa progression and its molecular mechanisms. METHODS: Differentially expressed AA-related genes (DEARGs) were identified by intersecting data from the Comparative Toxicogenomics Database (CTD) and The Cancer Genome Atlas (TCGA) database. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analyses were performed to reveal biological functions of DEARGs. A prognostic signature was constructed using Lasso regression analysis. The expression and cellular localization of the key genes were analyzed using single-cell RNA sequencing (scRNA-seq) data. Additionally, the effects of glycidamide (GA) on PCa cells malignant phenotypes and tumor growth in vivo were experimentally validated. RESULTS: We identified a total of 165 DEARGs significantly associated with PCa. Functional analysis revealed they mainly enriched in PI3K-Akt and cAMP signaling pathway. The prognostic model constructed from the six DEARGs (CYP11A1, TUBB3, ALB, ESPL1, FOXN4, ISYNA1) demonstrated satisfactory predictive accuracy for biochemical recurrence-free survival (BCRFS) in PCa patients. scRNA-seq analysis delineated the specific expression of six target genes within the tumor microenvironment. It was found that expression of CYP11A1 was downregulated, while expressions of TUBB3, ALB, ESPL1, FOXN4 and ISYNA1 were upregulated after treatment with GA. In vitro and in vivo experiments confirmed that GA significantly enhanced proliferation, migration, invasion of PCa cells and tumor growth. RNA‑sequencing and functional rescue assays further revealed that the MAPK pathway may be a key mechanism by which GA promoted proliferation, invasion, and metastasis of PCa cells. CONCLUSION: This study successfully identified and validated an AA-related prognostic model to effectively predict BCRFS of PCa. The oncogenic effects of GA are primarily mediated by the activation of specific MAPK signaling pathways, elucidating a key mechanistic basis for its toxicity in PCa.

Authors

Institutions

Publication Details

Journal
Ecotoxicology and Environmental Safety
Published
2026-06-26
DOI
https://doi.org/10.1016/j.ecoenv.2026.120441
Primary Topic
Potato Plant Research
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The role of acrylamide exposure in prostate cancer progression: An integrated analysis based on network toxicology and experimental validation

J P Chen, Wen‐Cai Zheng, Zhi‐Bin Ke, Qing‐Shui Zheng et al.
Ecotoxicology and Environmental Safety
Potato Plant Research
article

The role of acrylamide exposure in prostate cancer progression: An integrated analysis based on network toxicology and experimental validation

J P Chen, Wen‐Cai Zheng, Zhi‐Bin Ke, Qing‐Shui Zheng, Ning Xu, Bin Lin, Ting-Ting Lin, Zi-Heng YAN, Xue-Yi Xue, Meng-Xin Liu, Yong Wei
article en

Abstract

OBJECTIVE: Acrylamide (AA), a widespread environmental and food-borne pollutant, has been classified as a probable human carcinogen. However, its specific role and underlying mechanisms in the progression of prostate cancer (PCa) remain poorly elucidated. This study aims to comprehensively investigate the effect of AA on PCa progression and its molecular mechanisms. METHODS: Differentially expressed AA-related genes (DEARGs) were identified by intersecting data from the Comparative Toxicogenomics Database (CTD) and The Cancer Genome Atlas (TCGA) database. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analyses were performed to reveal biological functions of DEARGs. A prognostic signature was constructed using Lasso regression analysis. The expression and cellular localization of the key genes were analyzed using single-cell RNA sequencing (scRNA-seq) data. Additionally, the effects of glycidamide (GA) on PCa cells malignant phenotypes and tumor growth in vivo were experimentally validated. RESULTS: We identified a total of 165 DEARGs significantly associated with PCa. Functional analysis revealed they mainly enriched in PI3K-Akt and cAMP signaling pathway. The prognostic model constructed from the six DEARGs (CYP11A1, TUBB3, ALB, ESPL1, FOXN4, ISYNA1) demonstrated satisfactory predictive accuracy for biochemical recurrence-free survival (BCRFS) in PCa patients. scRNA-seq analysis delineated the specific expression of six target genes within the tumor microenvironment. It was found that expression of CYP11A1 was downregulated, while expressions of TUBB3, ALB, ESPL1, FOXN4 and ISYNA1 were upregulated after treatment with GA. In vitro and in vivo experiments confirmed that GA significantly enhanced proliferation, migration, invasion of PCa cells and tumor growth. RNA‑sequencing and functional rescue assays further revealed that the MAPK pathway may be a key mechanism by which GA promoted proliferation, invasion, and metastasis of PCa cells. CONCLUSION: This study successfully identified and validated an AA-related prognostic model to effectively predict BCRFS of PCa. The oncogenic effects of GA are primarily mediated by the activation of specific MAPK signaling pathways, elucidating a key mechanistic basis for its toxicity in PCa.

Ecotoxicology and Environmental SafetyVol. 321
Fujian Medical University (CN), First Affiliated Hospital of Fujian Medical University (CN)
Natural Science Foundation of Fujian Province
Good health and well-being
Openalex Percentile: Top 9%
Potato Plant Research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.