Go to The Journal of Clinical Investigation
  • About
  • Editors
  • Consulting Editors
  • For authors
  • Publication ethics
  • Transfers
  • Advertising
  • Job board
  • Contact
  • Current issue
  • Past issues
  • By specialty
    • COVID-19
    • Cardiology
    • Immunology
    • Metabolism
    • Nephrology
    • Oncology
    • Pulmonology
    • All ...
  • Videos
  • Collections
    • Resource and Technical Advances
    • Clinical Medicine
    • Reviews
    • Editorials
    • Perspectives
    • Top read articles
  • JCI This Month
    • Current issue
    • Past issues

  • Current issue
  • Past issues
  • Specialties
  • In-Press Preview
  • Editorials
  • Viewpoint
  • Top read articles
  • About
  • Editors
  • Consulting Editors
  • For authors
  • Publication ethics
  • Transfers
  • Advertising
  • Job board
  • Contact

Usage Information

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.
View: Text | PDF
Research Article Genetics Oncology

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

  • Text
  • PDF
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

×

Usage data is cumulative from December 2022 through December 2023.

Usage JCI PMC
Text version 854 366
PDF 64 77
Figure 188 1
Supplemental data 85 32
Citation downloads 23 0
Totals 1,214 476
Total Views 1,690
(Click and drag on plot area to zoom in. Click legend items above to toggle)

Usage information is collected from two different sources: this site (JCI) and Pubmed Central (PMC). JCI information (compiled daily) shows human readership based on methods we employ to screen out robotic usage. PMC information (aggregated monthly) is also similarly screened of robotic usage.

Various methods are used to distinguish robotic usage. For example, Google automatically scans articles to add to its search index and identifies itself as robotic; other services might not clearly identify themselves as robotic, or they are new or unknown as robotic. Because this activity can be misinterpreted as human readership, data may be re-processed periodically to reflect an improved understanding of robotic activity. Because of these factors, readers should consider usage information illustrative but subject to change.

Advertisement

Copyright © 2023 American Society for Clinical Investigation
ISSN 2379-3708

Sign up for email alerts