論文

査読有り
2016年11月

Inhibition of Glutaminolysis Inhibits Cell Growth via Down-regulating Mtorc1 Signaling in Lung Squamous Cell Carcinoma

ANTICANCER RESEARCH
  • Xulu Ye
  • ,
  • Qiliang Zhou
  • ,
  • Yoshifumi Matsumoto
  • ,
  • Masato Moriyama
  • ,
  • Shun Kageyama
  • ,
  • Masaaki Komatsu
  • ,
  • Seijiro Satoh
  • ,
  • Masanori Tsuchida
  • ,
  • Yasuo Saijo

36
11
開始ページ
6021
終了ページ
6029
記述言語
英語
掲載種別
研究論文(学術雑誌)
DOI
10.21873/anticanres.11191
出版者・発行元
INT INST ANTICANCER RESEARCH

Background/Aim: Inhibition of glutaminolysis has been reported as a promising therapeutic strategy to target several solid carcinomas. We aimed to investigate the effects of glutaminolysis on cell proliferation in lung squamous cell carcinoma cell lines and to explore the potential of targeting glutaminolysis as an anticancer strategy. Materials and Methods: Glutamine (Gln) dependence was assessed in six lung squamous cell carcinoma cell lines. Cell proliferation, mammalian target of rapamycin complex 1 (mTORC1) activity and the induction of autophagy were assessed after inhibition of glutaminolysis via Gln depletion or glutaminase (GLS) inhibition. Results: Five of six lung squamous cell carcinoma cell lines exhibited glutamine- dependence. The extent of dependence was correlated with the mRNA levels of GLS1/GLS2. Inhibition of glutaminolysis inhibited cell proliferation by down-regulating of mTORC1 signaling and inducing autophagy in Gln-dependent lung squamous cell carcinoma cell lines. Conclusion: Targeting glutaminolysis may represent a potential therapeutic strategy for the treatment of Gln-dependent lung squamous cell carcinomas.

リンク情報
DOI
https://doi.org/10.21873/anticanres.11191
PubMed
https://www.ncbi.nlm.nih.gov/pubmed/27793929
Web of Science
https://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=JSTA_CEL&SrcApp=J_Gate_JST&DestLinkType=FullRecord&KeyUT=WOS:000388486700050&DestApp=WOS_CPL
ID情報
  • DOI : 10.21873/anticanres.11191
  • ISSN : 0250-7005
  • eISSN : 1791-7530
  • PubMed ID : 27793929
  • Web of Science ID : WOS:000388486700050

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