Xu Chunlong, Wu Sen, Schook Lawrence B, Schachtschneider Kyle M
State Key Laboratory of Agrobiotechnology, College of Biological Sciences, China Agricultural University, Beijing, China.
Department of Radiology, University of Illinois at Chicago, Chicago, IL, United States.
Front Oncol. 2019 Feb 25;9:105. doi: 10.3389/fonc.2019.00105. eCollection 2019.
The global incidence of cancer is rapidly rising, and despite an improved understanding of cancer molecular biology, immune landscapes, and advancements in cytotoxic, biologic, and immunologic anti-cancer therapeutics, cancer remains a leading cause of death worldwide. Cancer is caused by the accumulation of a series of gene mutations called driver mutations that confer selective growth advantages to tumor cells. As cancer therapies move toward personalized medicine, predictive modeling of the role driver mutations play in tumorigenesis and therapeutic susceptibility will become essential. The development of next-generation sequencing technology has made the evaluation of mutated genes possible in clinical practice, allowing for identification of driver mutations underlying cancer development in individual patients. This, combined with recent advances in gene editing technologies such as CRISPR-Cas9 enables development of personalized tumor models for prediction of treatment responses for mutational profiles observed clinically. Pigs represent an ideal animal model for development of personalized tumor models due to their similar size, anatomy, physiology, metabolism, immunity, and genetics compared to humans. Such models would support new initiatives in precision medicine, provide approaches to create disease site tumor models with designated spatial and temporal clinical outcomes, and create standardized tumor models analogous to human tumors to enable therapeutic studies. In this review, we discuss the process of utilizing genomic sequencing approaches, gene editing technologies, and transgenic porcine cancer models to develop clinically relevant, personalized large animal cancer models for use in co-clinical trials, ultimately improving treatment stratification and translation of novel therapeutic approaches to clinical practice.
全球癌症发病率正在迅速上升，尽管对癌症分子生物学、免疫格局的理解有所提高，并且细胞毒性、生物和免疫抗癌治疗也取得了进展，但癌症仍然是全球主要的死亡原因。癌症是由一系列称为驱动突变的基因突变积累引起的，这些突变赋予肿瘤细胞选择性生长优势。随着癌症治疗向个性化医学发展，预测驱动突变在肿瘤发生和治疗敏感性中所起作用的建模将变得至关重要。下一代测序技术的发展使临床实践中对突变基因的评估成为可能，从而能够识别个体患者癌症发展背后的驱动突变。这与CRISPR-Cas9等基因编辑技术的最新进展相结合，使得能够开发个性化肿瘤模型，以预测临床观察到的突变谱的治疗反应。与人类相比，猪由于其相似的大小、解剖结构、生理、代谢、免疫和遗传学，是开发个性化肿瘤模型的理想动物模型。此类模型将支持精准医学的新举措，提供创建具有指定时空临床结果的疾病部位肿瘤模型的方法，并创建类似于人类肿瘤的标准化肿瘤模型以进行治疗研究。在这篇综述中，我们讨论了利用基因组测序方法、基因编辑技术和转基因猪癌症模型来开发临床上相关的、个性化的大型动物癌症模型以用于联合临床试验的过程，最终改善治疗分层并将新的治疗方法转化为临床实践。
