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Mutational landscape in genetically engineered, carcinogen-induced, and radiation-induced mouse sarcoma
Chang-Lung Lee, … , Kouros Owzar, David G. Kirsch
Chang-Lung Lee, … , Kouros Owzar, David G. Kirsch
Published May 21, 2019
Citation Information: JCI Insight. 2019;4(13):e128698. https://doi.org/10.1172/jci.insight.128698.
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Research Article Genetics Oncology

Mutational landscape in genetically engineered, carcinogen-induced, and radiation-induced mouse sarcoma

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Abstract

Cancer development is influenced by hereditary mutations, somatic mutations due to random errors in DNA replication, or external factors. It remains unclear how distinct cell-intrinsic and -extrinsic factors affect oncogenesis within the same tissue type. We investigated murine soft-tissue sarcomas generated by oncogenic alterations (KrasG12D activation and p53 deletion), carcinogens (3-methylcholanthrene [MCA] or ionizing radiation), and both factors in a potentially novel model (MCA plus p53 deletion). Whole-exome sequencing demonstrated distinct mutational signatures in individual sarcoma cohorts. MCA-induced sarcomas exhibited high mutational burden and predominantly G-to-T transversions, while radiation-induced sarcomas exhibited low mutational burden and a distinct genetic signature characterized by C-to-T transitions. The insertion-deletion/substitution ratio and number of gene copy number variations were high for radiation-induced sarcomas. MCA-induced tumors generated on a p53-deficient background showed the highest genomic instability. MCA-induced sarcomas harbored mutations in putative cancer driver genes that regulate MAPK signaling (Kras and Nf1) and the Hippo pathway (Fat1 and Fat4). In contrast, radiation-induced sarcomas and KrasG12D p53–/– sarcomas did not harbor recurrent oncogenic mutations; rather, they exhibited amplifications of specific oncogenes: Kras and Myc in KrasG12D p53–/– sarcomas and Met and Yap1 for radiation-induced sarcomas. These results reveal that different initiating events drive oncogenesis through distinct mechanisms.

Authors

Chang-Lung Lee, Yvonne M. Mowery, Andrea R. Daniel, Dadong Zhang, Alexander B. Sibley, Joe R. Delaney, Amy J. Wisdom, Xiaodi Qin, Xi Wang, Isibel Caraballo, Jeremy Gresham, Lixia Luo, David Van Mater, Kouros Owzar, David G. Kirsch

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Figure 3

The relationship between somatic mutations and CNVs among sarcomas generated by discrete tumor-initiating events.

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The relationship between somatic mutations and CNVs among sarcomas gener...
(A) The number of genes affected by mutations versus the number of genes affected by CNVs within each sarcoma sample. (B) The ratio of the number of genes affected by mutations to the number of genes affected by CNVs. In panels A and B, the dashed line indicates equal numbers of mutations and CNVs. (C) The number of COSMIC genes affected by nonsynonymous mutations per tumor. (D) The number of COSMIC genes affected by CNVs per tumor. In C and D, horizontal lines indicate median values for each cohort. All panels illustrate the data for n = 37 tumors.

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