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<p>Triple-negative breast cancer (TNBC) presents a major clinical challenge owing to its immunosuppressive tumor microenvironment, target scarcity, and poor therapeutic response. Recently, the combination therapy of immune checkpoint blockade and CCL19 has shown significant efficacy in TNBC. To systematically unravel the synergistic mechanisms between CCL19 and anti-PD-1, we developed a mathematical model by integrating cellular and molecular scales to capture essential tumor-immune interactions and predict the dynamics of tumor evolution under various therapies. In this study, we proposed three quantitative indicators: (1) the tumor relative volume index (TRVI), (2) the therapeutic efficacy discrepancy index (TEDI), and (3) the immune heterogeneity treatment response index (IHTRI). Our model validated that the immunostimulatory effect of CCL19 in synergizing with anti-PD-1, and revealed that this synergy is highly modulated by individual baseline immune heterogeneity. Notably, our analysis identified (CTLs × CCL19)/PD-L1 as a novel dynamic biomarker combination with significant predictive (AUC = 0.86) and prognostic value (log-rank <i>p</i>= 0.019). Finally, virtual clinical trials revealed that administering anti-PD-1 therapy prior to CCL19 injection draws more significant clinical benefits in TNBC. Collectively, this study provides a theoretical foundation for elucidating the synergistic mechanism between CCL19-mediated immunostimulation and anti-PD-1 therapy.</p>

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Multiscale modeling reveals synergy between CCL19 and PD-1 blockade in reshaping the TNBC microenvironment

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年4月16日

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  • Chunjie Gao,
  • Chenghang Li,
  • Lei Du,
  • Jing Liu,
  • Jinzhi Lei,
  • Lei Wang

摘要

Triple-negative breast cancer (TNBC) presents a major clinical challenge owing to its immunosuppressive tumor microenvironment, target scarcity, and poor therapeutic response. Recently, the combination therapy of immune checkpoint blockade and CCL19 has shown significant efficacy in TNBC. To systematically unravel the synergistic mechanisms between CCL19 and anti-PD-1, we developed a mathematical model by integrating cellular and molecular scales to capture essential tumor-immune interactions and predict the dynamics of tumor evolution under various therapies. In this study, we proposed three quantitative indicators: (1) the tumor relative volume index (TRVI), (2) the therapeutic efficacy discrepancy index (TEDI), and (3) the immune heterogeneity treatment response index (IHTRI). Our model validated that the immunostimulatory effect of CCL19 in synergizing with anti-PD-1, and revealed that this synergy is highly modulated by individual baseline immune heterogeneity. Notably, our analysis identified (CTLs × CCL19)/PD-L1 as a novel dynamic biomarker combination with significant predictive (AUC = 0.86) and prognostic value (log-rank p= 0.019). Finally, virtual clinical trials revealed that administering anti-PD-1 therapy prior to CCL19 injection draws more significant clinical benefits in TNBC. Collectively, this study provides a theoretical foundation for elucidating the synergistic mechanism between CCL19-mediated immunostimulation and anti-PD-1 therapy.