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<p>The occurrence and advancement of skin cutaneous melanoma (SKCM) is closely associated with tumor microenvironment (TME). Evaluating the condition of immune cell infiltration is pivotal to the comprehension regarding the features of TME in SKCM. Baicalin has been demonstrated to have anti-tumor effects by regulating the TME in tumors. However, its pharmacological potential in melanoma still needs to be elucidated. In this study, through unsupervised clustering analysis and network pharmacology, 32 potential baicalin targets have been identified. The prognostic model effectively stratifies patients, and an individualized clinical prediction model can be developed from it. Single-cell analysis demonstrated the expression of prognostic targets was associated with TME and mainly accumulated in mono/macro subset. Finally, in vitro experiments demonstrated that baicalin significantly reduced the viability, proliferation, and migration capabilities of melanoma cells. Additionally, baicalin promoted pro-inflammatory polarization of macrophages under co-culture with melanoma cells and baicalin exerted relatively high biological safety. In conclusion, this study demonstrates that baicalin inhibits melanoma by modulating the TME and establishes a prognostic model with predictive potential. These findings expand the therapeutic potential of baicalin and provide novel insights for melanoma treatment strategies.</p>

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Exploring medicinal mechanism of baicalin in tumor microenvironment of melanoma via bioinformatic and in vitro study

  • 期刊论文

  • 发表日期：

    2025年12月26日

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  • Zuohao Liu,
  • Bingrong Dang,
  • Xingsheng Wang,
  • Yuhan Liu,
  • Chunming Wang,
  • Changjun Lin

摘要

The occurrence and advancement of skin cutaneous melanoma (SKCM) is closely associated with tumor microenvironment (TME). Evaluating the condition of immune cell infiltration is pivotal to the comprehension regarding the features of TME in SKCM. Baicalin has been demonstrated to have anti-tumor effects by regulating the TME in tumors. However, its pharmacological potential in melanoma still needs to be elucidated. In this study, through unsupervised clustering analysis and network pharmacology, 32 potential baicalin targets have been identified. The prognostic model effectively stratifies patients, and an individualized clinical prediction model can be developed from it. Single-cell analysis demonstrated the expression of prognostic targets was associated with TME and mainly accumulated in mono/macro subset. Finally, in vitro experiments demonstrated that baicalin significantly reduced the viability, proliferation, and migration capabilities of melanoma cells. Additionally, baicalin promoted pro-inflammatory polarization of macrophages under co-culture with melanoma cells and baicalin exerted relatively high biological safety. In conclusion, this study demonstrates that baicalin inhibits melanoma by modulating the TME and establishes a prognostic model with predictive potential. These findings expand the therapeutic potential of baicalin and provide novel insights for melanoma treatment strategies.