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迈向更完善的人类癌症模型。

Toward improved models of human cancer.

作者信息

Ayuso Jose M, Park Keon-Young, Virumbrales-Muñoz María, Beebe David J

机构信息

Department of Surgery, University of California San Francisco, San Francisco, California 94143, USA.

出版信息

APL Bioeng. 2021 Jan 21;5(1):010902. doi: 10.1063/5.0026857. eCollection 2021 Mar.

Abstract

Cancer is a leading cause of death across the world and continues to increase in incidence. Despite years of research, multiple tumors (e.g., glioblastoma, pancreatic cancer) still have limited treatment options in the clinic. Additionally, the attrition rate and cost of drug development have continued to increase. This trend is partly explained by the poor predictive power of traditional tools and animal models. Moreover, multiple studies have highlighted that cell culture in traditional Petri dishes commonly fail to predict drug sensitivity. Conversely, animal models present differences in tumor biology compared with human pathologies, explaining why promising therapies tested in animal models often fail when tested in humans. The surging complexity of patient management with the advent of cancer vaccines, immunotherapy, and precision medicine demands more robust and patient-specific tools to better inform our understanding and treatment of human cancer. Advances in stem cell biology, microfluidics, and cell culture have led to the development of sophisticated bioengineered microscale organotypic models (BMOMs) that could fill this gap. In this Perspective, we discuss the advantages and limitations of patient-specific BMOMs to improve our understanding of cancer and how these tools can help to confer insight into predicting patient response to therapy.

摘要

癌症是全球主要的死亡原因之一,其发病率持续上升。尽管经过多年研究,但多种肿瘤(如胶质母细胞瘤、胰腺癌)在临床上的治疗选择仍然有限。此外,药物研发的损耗率和成本也持续增加。这种趋势部分是由于传统工具和动物模型的预测能力较差。此外,多项研究强调,传统培养皿中的细胞培养通常无法预测药物敏感性。相反,与人类病理学相比,动物模型在肿瘤生物学方面存在差异,这解释了为什么在动物模型中测试有前景的疗法在人体测试时往往会失败。随着癌症疫苗、免疫疗法和精准医学的出现,患者管理的复杂性激增,需要更强大且针对患者的工具,以更好地指导我们对人类癌症的理解和治疗。干细胞生物学、微流体技术和细胞培养的进展促使了复杂的生物工程微尺度器官型模型(BMOMs)的发展,这些模型可以填补这一空白。在这篇观点文章中,我们讨论了针对患者的BMOMs的优势和局限性,以增进我们对癌症的理解,以及这些工具如何有助于深入了解预测患者对治疗的反应。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d178/7822630/44783ad6c118/ABPID9-000005-010902_1-g001.jpg

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