Tumor-derived ARHGAP35 mutations enhance the Gα 13 -Rho signaling axis in human endometrial cancer.
Hiroshi YagiIchiro OnoyamaKazuo AsanomaMinoru KawakamiShoji MaenoharaKeisuke KodamaYumiko MatsumuraNorio HamadaEmiko HoriKazuhisa HachisugaMasafumi YasunagaTatsuhiro OhgamiKaoru OkugawaHideaki YahataKiyoko KatoPublished in: Cancer gene therapy (2022)
Dysregulated G protein-coupled receptor signaling is involved in the formation and progression of human cancers. The heterotrimeric G protein Gα 13 is highly expressed in various cancers and regulates diverse cancer-related transcriptional networks and cellular functions by activating Rho. Herein, we demonstrate that increased expression of Gα 13 promotes cell proliferation through activation of Rho and the transcription factor AP-1 in human endometrial cancer. Of interest, the RhoGTPase activating protein (RhoGAP), ARHGAP35 is frequently mutated in human endometrial cancers. Among the 509 endometrial cancer samples in The Cancer Genome Atlas database, 108 harbor 152 mutations at 126 different positions within ARHGAP35, representing a somatic mutation frequency of 20.2%. We evaluated the effect of 124 tumor-derived ARHGAP35 mutations on Gα 13 -mediated Rho and AP-1 activation. The RhoGAP activity of ARHGAP35 was impaired by 55 of 124 tumor-derived mutations, comprised of 23 nonsense, 15 frame-shift, 15 missense mutations, and two in-frame deletions. Considering that ARHGAP35 is mutated in >2% of all tumors, it ranks among the top 30 most significantly mutated genes in human cancer. Our data suggest potential roles of ARHGAP35 as an oncogenic driver gene, providing novel therapeutic opportunities for endometrial cancer.
Keyphrases
- endometrial cancer
- endothelial cells
- transcription factor
- induced pluripotent stem cells
- genome wide
- emergency department
- pluripotent stem cells
- signaling pathway
- squamous cell carcinoma
- gene expression
- risk assessment
- protein kinase
- oxidative stress
- papillary thyroid
- climate change
- long non coding rna
- small molecule
- copy number
- single cell
- machine learning
- childhood cancer
- lymph node metastasis
- protein protein