Potential Molecular Links Between Triclosan Exposure and Prostate Cancer: An Integrative Computational Analysis
- 1School of Pharmaceutical Sciences, Changchun University of Chinese Medicine, Changchun 130117, China
Abstract
Triclosan (TCS) is a widely used antimicrobial and endocrine-disrupting chemical whose potential relevance to prostate cancer (PCa) biology remains insufficiently understood. We integrated multi-omics and computational analyses to identify candidate targets that overlap between predicted TCS-related molecular targets and PCa-related transcriptomic alterations. Cross-database target mapping, differential expression, and network analyses were combined with machine learning, molecular docking, molecular dynamics simulations, Mendelian randomization, and single-cell transcriptomic profiling. Pathway analyses highlighted oxidative stress and metabolic dysregulation as key processes shared between predicted TCS-related targets and PCa-associated transcriptomic alterations. Machine learning prioritized five candidate genes—FERMT2, F5, PRKCA, ABCC4, and ACOX2—with discriminative value for PCa classification in the analyzed cohorts. Docking and molecular dynamics simulations supported plausible binding compatibility of TCS to ABCC4 and ACOX2. Mendelian randomization suggested that genetically predicted ABCC4 expression may be associated with PCa risk. Single-cell analysis further showed cell-type-specific expression of candidate genes in tumor-enriched epithelial populations. These findings provide an integrative framework for generating mechanistic hypotheses on how TCS-related molecular targets may be associated with PCa biology.
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BibTeX
@article{you2026potential,
title = {{Potential Molecular Links Between Triclosan Exposure and Prostate Cancer: An Integrative Computational Analysis}},
author = {Hongyang You and Yunlu Zou and Jiatong Liu and Yinghao Xiao and Jixin Li and Jiahui Xu and Wei Xu},
journal = {International Journal of Molecular Sciences},
year = {2026},
month = oct,
doi = {10.3390/ijms27209143},
url = {https://www.mdpi.com/1422-0067/27/20/9143},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Potential Molecular Links Between Triclosan Exposure and Prostate Cancer: An Integrative Computational Analysis
AU - Hongyang You
AU - Yunlu Zou
AU - Jiatong Liu
AU - Yinghao Xiao
AU - Jixin Li
AU - Jiahui Xu
AU - Wei Xu
PY - 2026
DA - 2026/10/15
JO - International Journal of Molecular Sciences
DO - 10.3390/ijms27209143
UR - https://www.mdpi.com/1422-0067/27/20/9143
AB - Triclosan (TCS) is a widely used antimicrobial and endocrine-disrupting chemical whose potential relevance to prostate cancer (PCa) biology remains insufficiently understood. We integrated multi-omics and computational analyses to identify candidate targets that overlap between predicted TCS-related molecular targets and PCa-related transcriptomic alterations. Cross-database target mapping, differential expression, and network analyses were combined with machine learning, molecular docking, molecular dynamics simulations, Mendelian randomization, and single-cell transcriptomic profiling. Pathway analyses highlighted oxidative stress and metabolic dysregulation as key processes shared between predicted TCS-related targets and PCa-associated transcriptomic alterations. Machine learning prioritized five candidate genes—FERMT2, F5, PRKCA, ABCC4, and ACOX2—with discriminative value for PCa classification in the analyzed cohorts. Docking and molecular dynamics simulations supported plausible binding compatibility of TCS to ABCC4 and ACOX2. Mendelian randomization suggested that genetically predicted ABCC4 expression may be associated with PCa risk. Single-cell analysis further showed cell-type-specific expression of candidate genes in tumor-enriched epithelial populations. These findings provide an integrative framework for generating mechanistic hypotheses on how TCS-related molecular targets may be associated with PCa biology.
SN - 1422-0067
ER -