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由细胞外基质结构决定的肿瘤免疫逃逸和清除的不同进化模式。

Distinct evolutionary patterns of tumour-immune escape and elimination determined by extracellular matrix architectures.

作者信息

Fan Yijia, George Jason T

机构信息

Department of Biomedical Engineering, Texas A&M University College Station, TX, USA.

Translational Medical Sciences, Texas A&M University Health Science Center, Houston, TX, USA.

出版信息

J R Soc Interface. 2025 Jul;22(228):20250116. doi: 10.1098/rsif.2025.0116. Epub 2025 Jul 9.

Abstract

Cancer progression remains a significant clinical challenge. Phenotypic adaptation by tumour cells results in disease heterogeneity, which drives treatment resistance and immune escape. T-cell immunotherapy, while effective at treating some cancer subtypes, can also fail due to limits on tumour immunogenicity or T-cell recognition. For example, one potential contributor to immune escape involves the density and alignment of the extracellular matrix (ECM) surrounding tumours, also known as tumour-associated collagen signature (TACS). However, the specific mechanisms by which aligned fibres contribute to decreased patient survival rates have not yet been decoupled. Here, we developed EVO-ACT (EVOlutionary agent-based cancer T-cell interaction), a two-dimensional agent-based modelling framework designed to investigate how different TACS architectures impact tumour evolution and dynamic interactions with CD8[Formula: see text] T cells. Our results highlight that TACS-driven modulation of T-cell dynamics, combined with phenotypic adaptation, such as epithelial-to-mesenchymal transition, underlies differences in tumour immunogenicity and the application of our model can successfully recapitulate clinically observed breast cancer survival trends.

摘要

癌症进展仍然是一个重大的临床挑战。肿瘤细胞的表型适应导致疾病异质性,进而引发治疗抵抗和免疫逃逸。T细胞免疫疗法虽然在治疗某些癌症亚型方面有效,但也可能因肿瘤免疫原性或T细胞识别的限制而失败。例如,免疫逃逸的一个潜在因素涉及肿瘤周围细胞外基质(ECM)的密度和排列,也称为肿瘤相关胶原特征(TACS)。然而,排列的纤维导致患者生存率降低的具体机制尚未得到解析。在此,我们开发了EVO-ACT(基于进化因子的癌症T细胞相互作用),这是一个二维基于因子的建模框架,旨在研究不同的TACS结构如何影响肿瘤进化以及与CD8[公式:见正文]T细胞的动态相互作用。我们的结果表明,TACS驱动的T细胞动力学调节,与表型适应(如上皮-间质转化)相结合,是肿瘤免疫原性差异的基础,并且我们模型的应用能够成功重现临床观察到的乳腺癌生存趋势。

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