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在接受传统化疗后,对巨噬细胞靶向疗法联合免疫检查点抑制剂的治疗反应进行量化。

Quantifying treatment response to a macrophage-targeted therapy in combination with immune checkpoint inhibitors after exposure to conventional chemotherapy.

作者信息

Bess Shelby N, Smart Gaven K, Muldoon Timothy J

机构信息

Department of Biomedical Engineering, University of Arkansas, Fayetteville, AR, United States.

出版信息

Front Immunol. 2025 Apr 28;16:1565953. doi: 10.3389/fimmu.2025.1565953. eCollection 2025.

DOI:10.3389/fimmu.2025.1565953
PMID:40356923
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12066502/
Abstract

BACKGROUND

Conventional chemotherapeutic agents, such as 5-fluorouracil (5-FU), can exert anti-tumor effects through immunogenic cell death (ICD) induction. Researchers have found hallmarks that quantify ICD (such as the translocation of HMGB1 and calreticulin). Although chemotherapeutic agents can induce ICD, they increase the expression of immune checkpoints, limiting their effectiveness. Studies have emphasized the importance of investigating the heterogeneous responses of cells co-localized in a solid tumor (macrophages, tumor cells, etc.) to ICD induction. However, these studies were performed , which limits the collection of information on cell-cell interactions due to model complexity.

METHODS

In this study, we used a multicellular spheroid model in conjunction with single spheroid imaging to understand the structural and metabolic changes of a simulated solid tumor model. In addition to using the spheroid model, conventional 2D co-culture monolayers were used to quantify ICD hallmarks and changes in macrophage functional behavior while correlating immune responses after exposure to the combinatory regimen of immune checkpoint inhibitors and an ICD inducer.

RESULTS

Results indicate that the combination of two immune checkpoint inhibitors in addition to a chemotherapy agent reduced spheroid growth (~46%) and reduced M2 macrophage expression and cellular proliferation while modulating cellular metabolism, ICD hallmarks, and phagocytic function.

CONCLUSIONS

Overall, this study not only quantified microregional metabolic and structural changes in a simulated spheroid model but also quantified changes in ICD hallmarks and macrophage functional behavior. It was also found that correlations between spheroid structure and ICD hallmarks through immunofluorescence markers could exist after exposure to the combinatory regimen of immune checkpoint inhibitors and an ICD inducer.

摘要

背景

传统化疗药物,如5-氟尿嘧啶(5-FU),可通过诱导免疫原性细胞死亡(ICD)发挥抗肿瘤作用。研究人员已发现可量化ICD的特征(如高迁移率族蛋白B1(HMGB1)和钙网蛋白的易位)。尽管化疗药物可诱导ICD,但它们会增加免疫检查点的表达,从而限制了其有效性。研究强调了调查实体瘤中共定位的细胞(巨噬细胞、肿瘤细胞等)对ICD诱导的异质性反应的重要性。然而,这些研究的开展方式限制了因模型复杂性而获取的细胞间相互作用信息。

方法

在本研究中,我们使用多细胞球体模型结合单球体成像来了解模拟实体瘤模型的结构和代谢变化。除使用球体模型外,还采用传统的二维共培养单层来量化ICD特征以及巨噬细胞功能行为的变化,同时关联暴露于免疫检查点抑制剂和ICD诱导剂联合方案后的免疫反应。

结果

结果表明,除化疗药物外,两种免疫检查点抑制剂的联合使用可减少球体生长(约46%),降低M2巨噬细胞表达和细胞增殖,同时调节细胞代谢、ICD特征和吞噬功能。

结论

总体而言,本研究不仅量化了模拟球体模型中的微区域代谢和结构变化,还量化了ICD特征和巨噬细胞功能行为的变化。还发现,在暴露于免疫检查点抑制剂和ICD诱导剂联合方案后,通过免疫荧光标记可能存在球体结构与ICD特征之间的相关性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5c41/12066502/b7fa3101c6da/fimmu-16-1565953-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5c41/12066502/3c1a29d968f7/fimmu-16-1565953-g001.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5c41/12066502/7ab62d272200/fimmu-16-1565953-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5c41/12066502/002df978a1fb/fimmu-16-1565953-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5c41/12066502/6d0b8137d69d/fimmu-16-1565953-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5c41/12066502/63e9b4db88aa/fimmu-16-1565953-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5c41/12066502/0a83d3d97a6c/fimmu-16-1565953-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5c41/12066502/b7fa3101c6da/fimmu-16-1565953-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5c41/12066502/3c1a29d968f7/fimmu-16-1565953-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5c41/12066502/9c36546d01fa/fimmu-16-1565953-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5c41/12066502/d06fc89ab1ba/fimmu-16-1565953-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5c41/12066502/3b3f21e70af7/fimmu-16-1565953-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5c41/12066502/8f808518d5e7/fimmu-16-1565953-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5c41/12066502/1ee954099af8/fimmu-16-1565953-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5c41/12066502/a4440fe77cd9/fimmu-16-1565953-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5c41/12066502/7ab62d272200/fimmu-16-1565953-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5c41/12066502/002df978a1fb/fimmu-16-1565953-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5c41/12066502/6d0b8137d69d/fimmu-16-1565953-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5c41/12066502/63e9b4db88aa/fimmu-16-1565953-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5c41/12066502/0a83d3d97a6c/fimmu-16-1565953-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5c41/12066502/b7fa3101c6da/fimmu-16-1565953-g013.jpg

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