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Norway

PMID:23597566  

The pivotal role of IKKα in the development of spontaneous lung squamous cell carcinomas.

Zuoxiang Xiao | Qun Jiang | Jami Willette-Brown | Sichuan Xi | Feng Zhu | Sandra Burkett | Timothy Back | Na-Young Song | Mahesh Datla | Zhonghe Sun | Romina Goldszmid | Fanching Lin | Travis Cohoon | Kristen Pike | Xiaolin Wu | David S Schrump | Kwok-Kin Wong | Howard A Young | Giorgio Trinchieri | Robert H Wiltrout | Yinling Hu
Cancer cell | 2013

Here, we report that kinase-dead IKKα knockin mice develop spontaneous lung squamous cell carcinomas (SCCs) associated with IKKα downregulation and marked pulmonary inflammation. IKKα reduction upregulated the expression of p63, Trim29, and keratin 5 (K5), which serve as diagnostic markers for human lung SCCs. IKKα(low)K5(+)p63(hi) cell expansion and SCC formation were accompanied by inflammation-associated deregulation of oncogenes, tumor suppressors, and stem cell regulators. Reintroducing transgenic K5.IKKα, depleting macrophages, and reconstituting irradiated mutant animals with wild-type bone marrow (BM) prevented SCC development, suggesting that BM-derived IKKα mutant macrophages promote the transition of IKKα(low)K5(+)p63(hi) cells to tumor cells. This mouse model resembles human lung SCCs, sheds light on the mechanisms underlying lung malignancy development, and identifies targets for therapy of lung SCCs.

Pubmed ID: 23597566

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Associated grants

  • Agency: Intramural NIH HHS, United States
    Id: ZIA BC011212
  • Agency: NCI NIH HHS, United States
    Id: R01 CA122794
  • Agency: NCI NIH HHS, United States
    Id: P01 CA154303
  • Agency: NCI NIH HHS, United States
    Id: R01 CA140594
  • Agency: Intramural NIH HHS, United States
    Id: ZIA BC011391
  • Agency: Intramural NIH HHS, United States
    Id: ZIA BC011212-04
  • Agency: Intramural NIH HHS, United States
    Id: ZIA BC011391-01
  • Agency: NCI NIH HHS, United States
    Id: R01 CA166480

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Gene Expression Omnibus (GEO) (tool)

RRID:SCR_007303

Functional genomics data repository supporting MIAME-compliant data submissions. Includes microarray-based experiments measuring the abundance of mRNA, genomic DNA, and protein molecules, as well as non-array-based technologies such as serial analysis of gene expression (SAGE) and mass spectrometry proteomic technology. Array- and sequence-based data are accepted. Collection of curated gene expression DataSets, as well as original Series and Platform records. The database can be searched using keywords, organism, DataSet type and authors. DataSet records contain additional resources including cluster tools and differential expression queries.

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