Supplementary Figures 1-5 from Oncogene-Mediated Human Lung Epithelial Cell Transformation Produces Adenocarcinoma Phenotypes In Vivo
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posted on 2023-03-30, 20:50 authored by Ken Sasai, Taiko Sukezane, Emmy Yanagita, Harumi Nakagawa, Azusa Hotta, Tomoo Itoh, Tsuyoshi AkagiSupplementary Figures 1-5 from Oncogene-Mediated Human Lung Epithelial Cell Transformation Produces Adenocarcinoma Phenotypes In Vivo
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ARTICLE ABSTRACT
It has been challenging to engineer lung adenocarcinoma models via oncogene-mediated transformation of primary cultured normal human cells. Although viral oncoprotein-mediated malignant transformation has been reported, xenografts derived from such transformed cells generally represent poorly differentiated cancers. Here, we demonstrate that the combined expression of multiple cellular factors induces malignant transformation in normal human lung epithelial cells. Although a combination of four genetic alterations, including hTERT overexpression, inactivation of the pRB and p53 pathways, and KRAS activation, is insufficient for normal human small airway epithelial cells to be fully transformed, expression of one additional oncogene induces malignant transformation. Notably, we have succeeded in reproducing human lung adenocarcinoma phenotypes in the flanks of nude mice by introducing an active form of PIK3CA, CYCLIN-D1, or a dominant-negative form of LKB1 in combination with the four genetic alterations above. Besides differentiated lung cancer, poorly differentiated cancer models can also be engineered by employing c-MYC as one of the genetic elements, indicating that histologic features and degree of differentiation of xenografts are controllable to some extent by changing the combination of genetic elements introduced. This is the first study reporting malignant transformation of normal lung epithelial cells in the absence of viral oncoproteins. We propose that our model system would be useful to identify the minimal and most crucial set of changes required for lung tumorigenesis, and that it would provide a broadly applicable approach for discovering attractive therapeutic targets. Cancer Res; 71(7); 2541–9. ©2011 AACR.Usage metrics
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