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Background <p>Breast cancer metastasis remains a major clinical challenge due to its complex molecular mechanisms, highlighting the need to identify key regulatory factors.</p> Methods <p>Multiple breast cancer metastasis datasets were integrated to comprehensively identify metastasis-related genes. Differential expression analysis, weighted gene co-expression network analysis (WGCNA), and five machine learning algorithms were employed to screen for key candidate genes. Immune cell infiltration was assessed using the CIBERSORT algorithm, and miRNA expression profiles associated with lymph node metastasis were analyzed to construct potential regulatory networks. The biological functions of target genes were further verified through in vitro functional experiments.</p> Results <p>PAICS was identified as a metastasis-associated gene and was associated with patient survival in TCGA-BRCA. Its expression correlated with the infiltration of multiple immune cell subsets. Four metastasis-related miRNAs were involved in potential regulatory networks. Functional assays demonstrated that PAICS knockdown suppressed migration and invasion while increasing E-cadherin and decreasing N-cadherin and Vimentin expression.</p> Conclusions <p>PAICS acts as a biomarker that promotes breast cancer metastasis by modulating epithelial–mesenchymal transition and the immune microenvironment, offering potential for clinical translation.</p>

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Integrative multi-omics analysis identifies PAICS as a key regulator of epithelial-mesenchymal transition in breast cancer metastasis

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年4月14日

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  • Jian Guo,
  • Lichao Cen,
  • Xinye Qian,
  • Shengban You

摘要

Background

Breast cancer metastasis remains a major clinical challenge due to its complex molecular mechanisms, highlighting the need to identify key regulatory factors.

Methods

Multiple breast cancer metastasis datasets were integrated to comprehensively identify metastasis-related genes. Differential expression analysis, weighted gene co-expression network analysis (WGCNA), and five machine learning algorithms were employed to screen for key candidate genes. Immune cell infiltration was assessed using the CIBERSORT algorithm, and miRNA expression profiles associated with lymph node metastasis were analyzed to construct potential regulatory networks. The biological functions of target genes were further verified through in vitro functional experiments.

Results

PAICS was identified as a metastasis-associated gene and was associated with patient survival in TCGA-BRCA. Its expression correlated with the infiltration of multiple immune cell subsets. Four metastasis-related miRNAs were involved in potential regulatory networks. Functional assays demonstrated that PAICS knockdown suppressed migration and invasion while increasing E-cadherin and decreasing N-cadherin and Vimentin expression.

Conclusions

PAICS acts as a biomarker that promotes breast cancer metastasis by modulating epithelial–mesenchymal transition and the immune microenvironment, offering potential for clinical translation.