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潜在调控网络的紧急动力学将前列腺癌中的上皮-间质转化与雄激素受体依赖性耐药联系起来。

Emergent dynamics of underlying regulatory network links EMT and androgen receptor-dependent resistance in prostate cancer.

作者信息

Jindal Rashi, Nanda Abheepsa, Pillai Maalavika, Ware Kathryn E, Singh Divyoj, Sehgal Manas, Armstrong Andrew J, Somarelli Jason A, Jolly Mohit Kumar

机构信息

Center for BioSystems Science and Engineering, Indian Institute of Science, Bangalore 560012, India.

Undergraduate Programme, Indian Institute of Science, Bangalore 560012, India.

出版信息

Comput Struct Biotechnol J. 2023 Feb 8;21:1498-1509. doi: 10.1016/j.csbj.2023.01.031. eCollection 2023.

Abstract

Advanced prostate cancer patients initially respond to hormone therapy, be it in the form of androgen deprivation therapy or second-generation hormone therapies, such as abiraterone acetate or enzalutamide. However, most men with prostate cancer eventually develop hormone therapy resistance. This resistance can arise through multiple mechanisms, such as through genetic mutations, epigenetic mechanisms, or through non-genetic pathways, such as lineage plasticity along epithelial-mesenchymal or neuroendocrine-like axes. These mechanisms of hormone therapy resistance often co-exist within a single patient's tumor and can overlap within a single cell. There exists a growing need to better understand how phenotypic heterogeneity and plasticity results from emergent dynamics of the regulatory networks governing androgen independence. Here, we investigated the dynamics of a regulatory network connecting the drivers of androgen receptor (AR) splice variant-mediated androgen independence and those of epithelial-mesenchymal transition. Model simulations for this network revealed four possible phenotypes: epithelial-sensitive (ES), epithelial-resistant (ER), mesenchymal-resistant (MR) and mesenchymal-sensitive (MS), with the latter phenotype occurring rarely. We observed that well-coordinated "teams" of regulators working antagonistically within the network enable these phenotypes. These model predictions are supported by multiple transcriptomic datasets both at single-cell and bulk levels, including in vitro EMT induction models and clinical samples. Further, our simulations reveal spontaneous stochastic switching between the ES and MR states. Addition of the immune checkpoint molecule, PD-L1, to the network was able to capture the interactions between AR, PD-L1, and the mesenchymal marker SNAIL, which was also confirmed through quantitative experiments. This systems-level understanding of the driver of androgen independence and EMT could aid in understanding non-genetic transitions and progression of such cancers and help in identifying novel therapeutic strategies or targets.

摘要

晚期前列腺癌患者最初会对激素疗法产生反应,无论是雄激素剥夺疗法还是第二代激素疗法,如醋酸阿比特龙或恩杂鲁胺。然而,大多数前列腺癌患者最终会产生激素疗法耐药性。这种耐药性可通过多种机制产生,如基因突变、表观遗传机制,或通过非遗传途径,如沿上皮-间质或神经内分泌样轴的谱系可塑性。这些激素疗法耐药机制通常在单个患者的肿瘤中共存,并且可能在单个细胞内重叠。越来越需要更好地了解雄激素独立性调控网络的涌现动力学如何导致表型异质性和可塑性。在这里,我们研究了一个调控网络的动力学,该网络连接雄激素受体(AR)剪接变体介导的雄激素独立性驱动因子和上皮-间质转化驱动因子。该网络的模型模拟揭示了四种可能的表型:上皮敏感(ES)、上皮耐药(ER)、间质耐药(MR)和间质敏感(MS),后一种表型很少出现。我们观察到,在网络中协同工作的调节因子“团队”能够实现这些表型。这些模型预测得到了单细胞和整体水平的多个转录组数据集的支持,包括体外EMT诱导模型和临床样本。此外,我们的模拟揭示了ES和MR状态之间的自发随机转换。将免疫检查点分子PD-L1添加到网络中能够捕捉AR、PD-L1和间质标志物SNAIL之间的相互作用,这也通过定量实验得到了证实。这种对雄激素独立性和EMT驱动因子的系统层面理解有助于理解此类癌症的非遗传转变和进展,并有助于识别新的治疗策略或靶点。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/228b/9957767/c55f77cf7997/ga1.jpg

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