Tumor Purity in Preclinical Mouse Tumor Models

临床前小鼠肿瘤模型中的肿瘤纯度

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作者:Wubin Qian ,Xiaobo Chen ,Yanghui Sheng ,Likun Zhang ,Jingjing Wang ,Zhenzhen Song ,Qi-Xiang Li ,Sheng Guo

Abstract

Tumor biology is determined not only by immortal cancer cells but also by the tumor microenvironment consisting of noncancerous cells and extracellular matrix, together they dictate the pathogenesis and response to treatments. Tumor purity is the proportion of cancer cells in a tumor. It is a fundamental property of cancer and is associated with many clinical features and outcomes. Here we report the first systematic study of tumor purity in patient-derived xenograft (PDX) and syngeneic tumor models using next-generation sequencing data from >9,000 tumors. We found that tumor purity in PDX models is cancer specific and mimics patient tumors, with variation in stromal content and immune infiltration influenced by immune systems of host mice. After the initial engraftment, human stroma in a PDX tumor is quickly replaced by mouse stroma, and tumor purity then stays stable in subsequent transplantations and increases only slightly by passage. Similarly, in syngeneic mouse cancer cell line models, tumor purity also turns out to be an intrinsic property with model and cancer specificities. Computational and pathology analysis confirmed the impact on tumor purity by the diverse stromal and immune profiles. Our study deepens the understanding of mouse tumor models, which will enable their better and novel uses in developing cancer therapeutics, especially ones targeting tumor microenvironment. Significance: PDX models are an ideal experimental system to study tumor purity because of its distinct separation of human tumor cells and mouse stromal and immune cells. This study provides a comprehensive view of tumor purity in 27 cancers in PDX models. It also investigates tumor purity in 19 syngeneic models based on unambiguously identified somatic mutations. It will facilitate tumor microenvironment research and drug development in mouse tumor models.

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