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UBTD1 induces cellular senescence through an UBTD1-Mdm2/p53 positive feedback loop.

The Journal of pathology | 2015

The tumour suppressor p53 plays an important role in tumourigenesis. Besides inducing apoptosis, it regulates cellular senescence, which constitutes an important barrier to tumourigenesis. The mechanism of regulation of cellular senescence by p53 and its downstream pathway are poorly understood. Here, we report that the ubiquitin domain-containing 1 (UBTD1) gene, a new downstream target of p53, induces cellular senescence and acts as a novel tumour suppressor by a mechanism that depends on p53. Expression of UBTD1 increased upon cellular senescence induced by serial passageing of cultures, as well as by exposure to DNA-damageing drugs that induce premature senescence. Over-expression of UBTD1 induces senescence in human fibroblasts and cancer cells and attenuation of the transformed phenotype in cancer cells. UBTD1 is down-regulated in gastric and colorectal cancer tissues, and its lower expression correlates with a more aggressive phenotype and worse prognosis. Multivariate analysis revealed that UBTD1 expression was an independent prognostic factor for gastric cancer patients. Furthermore, UBTD1 increased the stability of p53 protein, by promoting the degradation of Mdm2 protein. Importantly, UBTD1 and p53 function mutually depend on each other in regulating cellular senescence and proliferation. Thus, our data suggest that, upon DNA damage, p53 induction by UBTD1 creates a positive feedback mechanism to further increase p53 expression. Our results establish UBTD1 as a regulator of cellular senescence that mediates p53 function, and provide insights into the mechanism of Mdm2 inhibition that impacts p53 dynamics during cellular senescence and tumourigenesis.

Pubmed ID: 25382750 RIS Download

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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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