Integrated network toxicology and bioinformatics reveal PFAS-driven prognostic biomarkers and molecular mechanisms in breast cancer: insights from transcriptome analysis and molecular docking.

IF 2.8 4区 医学 Q3 ENDOCRINOLOGY & METABOLISM
Yingqiang Fu, Yiyang Liu, Ziqi Sui
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Abstract

Background: Per- and polyfluoroalkyl substances (PFAS), pervasive environmental contaminants, are increasingly linked to breast cancer, yet their molecular mechanisms remain unclear. This study integrates network toxicology and bioinformatics to elucidate PFAS-associated pathways and prognostic biomarkers in breast cancer.

Methods: Using the TCGA-BRCA dataset, we identified differentially expressed genes (DEGs) between normal and breast cancer tissues. We cross-referenced these genes with PFAS-related genes from the Comparative Toxicogenomics Database (CTD) to identify common targets. Enrichment analysis, network construction, and survival analysis were performed to elucidate the biological mechanisms and prognostic value. The CIBERSORT algorithm assessed immune cell infiltration, and molecular docking evaluated interactions between PFAS compounds and key genes.

Results: We identified 141 common DEGs, significantly enriched in pathways related to cytokine activity, growth factor activity, and chemokine receptor binding. A PFAS-toxicity target-breast cancer network illustrated potential mechanistic pathways. Six key prognostic genes (MRPL13, LEF1, ATP7B, IFNG, SFRP1, DNMT3B) were identified, forming a risk model that stratified patients with significant differences in survival. Higher risk scores were associated with advanced stages, specific histological types, and hormone receptor statuses. Immune cell infiltration analysis revealed distinct profiles between high and low-risk groups, with high-risk patients exhibiting elevated activated T cells and macrophages. Molecular docking showed strong interactions between PFAS compounds (PFOS and PFDE) and DNMT3B, suggesting potential gene function disruptions.

Conclusion: PFAS exposure is linked to altered gene expression, immune cell infiltration, and potential disruptions in key genes, contributing to breast cancer development and progression. These findings provide insights into potential therapeutic targets and underline the importance of addressing environmental factors in breast cancer management.

综合网络毒理学和生物信息学揭示pfas驱动的乳腺癌预后生物标志物和分子机制:来自转录组分析和分子对接的见解。
背景:全氟烷基和多氟烷基物质(PFAS)是普遍存在的环境污染物,与乳腺癌的关系越来越密切,但其分子机制尚不清楚。本研究结合网络毒理学和生物信息学来阐明乳腺癌中pfas相关通路和预后生物标志物。方法:利用TCGA-BRCA数据集,我们鉴定了正常和乳腺癌组织之间的差异表达基因(DEGs)。我们将这些基因与比较毒物基因组学数据库(CTD)中的pfas相关基因进行交叉比对,以确定共同的靶点。通过富集分析、网络构建和生存分析来阐明生物学机制和预后价值。CIBERSORT算法评估免疫细胞浸润,分子对接评估PFAS化合物与关键基因之间的相互作用。结果:我们鉴定了141个常见的deg,显著富集与细胞因子活性、生长因子活性和趋化因子受体结合相关的途径。pfas -毒性靶点-乳腺癌网络阐明了潜在的机制途径。鉴定出6个关键预后基因(MRPL13、LEF1、ATP7B、IFNG、SFRP1、DNMT3B),形成风险模型,对生存差异显著的患者进行分层。较高的风险评分与晚期、特定的组织学类型和激素受体状态有关。免疫细胞浸润分析揭示了高风险和低风险组之间的不同特征,高风险患者表现出活化的T细胞和巨噬细胞升高。分子对接显示,PFAS化合物(PFOS和PFDE)与DNMT3B之间存在强烈的相互作用,提示可能存在基因功能破坏。结论:PFAS暴露与基因表达改变、免疫细胞浸润和关键基因的潜在破坏有关,有助于乳腺癌的发生和进展。这些发现为潜在的治疗靶点提供了见解,并强调了在乳腺癌管理中解决环境因素的重要性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Discover. Oncology
Discover. Oncology Medicine-Endocrinology, Diabetes and Metabolism
CiteScore
2.40
自引率
9.10%
发文量
122
审稿时长
5 weeks
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