Department of Thoracic/Head and Neck Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences, Houston, TX, USA.
Sci Rep. 2019 Mar 20;9(1):4819. doi: 10.1038/s41598-019-41301-2.
Lung cancer is the foremost cause of cancer related deaths in the U.S. It is a heterogeneous disease composed of genetically and phenotypically distinct tumor cells surrounded by heterotypic cells and extracellular matrix dynamically interacting with the tumor cells. Research in lung cancer is often restricted to patient-derived tumor specimens, in vitro cell cultures and limited animal models, which fail to capture the cellular or microenvironment heterogeneity of the tumor. Therefore, our knowledge is primarily focused on cancer-cell autonomous aberrations. For a fundamental understanding of lung cancer progression and an exploration of therapeutic options, we focused our efforts to develop an Ex Vivo Tumor platform to culture tumors in 3D matrices, which retains tumor cell heterogeneity arising due to in vivo selection pressure and environmental influences and recapitulate responses of tumor cells to external manipulations. To establish this model, implanted syngeneic murine tumors from a mutant KRAS/p53 model were harvested to yield multicellular tumor aggregates followed by culture in 3D extracellular matrices. Using this system, we identified Src signaling as an important driver of invasion and metastasis in lung cancer and demonstrate that EVTs are a robust experimental tool bridging the gap between conventional in vitro and in vivo models.
肺癌是美国癌症相关死亡的首要原因。它是一种异质性疾病,由遗传和表型上不同的肿瘤细胞组成,这些肿瘤细胞被异质细胞和细胞外基质包围,它们与肿瘤细胞动态相互作用。肺癌的研究通常局限于患者来源的肿瘤标本、体外细胞培养和有限的动物模型,这些模型无法捕捉肿瘤的细胞或微环境异质性。因此,我们的知识主要集中在肿瘤细胞自主性异常上。为了深入了解肺癌的进展并探索治疗方案,我们致力于开发一种体外肿瘤平台,以 3D 基质培养肿瘤,该平台保留了由于体内选择压力和环境影响而产生的肿瘤细胞异质性,并重现了肿瘤细胞对外部操作的反应。为了建立这个模型,我们从一个突变 KRAS/p53 模型的同种异体小鼠肿瘤中取出植入的肿瘤,产生多细胞肿瘤聚集体,然后在 3D 细胞外基质中培养。使用这个系统,我们发现Src 信号是肺癌侵袭和转移的重要驱动因素,并证明 EVTs 是一个强大的实验工具,可以弥合传统的体外和体内模型之间的差距。