逐步编辑的人类黑色素瘤模型揭示了突变对肿瘤和微环境的影响。
Stepwise-edited, human melanoma models reveal mutations' effect on tumor and microenvironment.
机构信息
Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02115, USA.
出版信息
Science. 2022 Apr 29;376(6592):eabi8175. doi: 10.1126/science.abi8175.
Establishing causal relationships between genetic alterations of human cancers and specific phenotypes of malignancy remains a challenge. We sequentially introduced mutations into healthy human melanocytes in up to five genes spanning six commonly disrupted melanoma pathways, forming nine genetically distinct cellular models of melanoma. We connected mutant melanocyte genotypes to malignant cell expression programs in vitro and in vivo, replicative immortality, malignancy, rapid tumor growth, pigmentation, metastasis, and histopathology. Mutations in malignant cells also affected tumor microenvironment composition and cell states. Our melanoma models shared genotype-associated expression programs with patient melanomas, and a deep learning model showed that these models partially recapitulated genotype-associated histopathological features as well. Thus, a progressive series of genome-edited human cancer models can causally connect genotypes carrying multiple mutations to phenotype.
在人类癌症的遗传改变与特定的恶性表型之间建立因果关系仍然是一个挑战。我们依次在多达五个跨越六个常见的黑色素瘤通路的基因中引入突变,形成了九个具有不同遗传特征的黑色素瘤细胞模型。我们将突变体黑素细胞的基因型与体外和体内的恶性细胞表达程序、复制性永生、恶性、快速肿瘤生长、色素沉着、转移和组织病理学联系起来。恶性细胞中的突变也影响了肿瘤微环境的组成和细胞状态。我们的黑色素瘤模型与患者黑色素瘤共享与基因型相关的表达程序,深度学习模型表明,这些模型部分再现了与基因型相关的组织病理学特征。因此,一系列经过逐步基因组编辑的人类癌症模型可以将携带多种突变的基因型与表型联系起来。
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