High glucose induced c-Met activation promotes aggressive phenotype and regulates expression of glucose metabolism genes in HCC cells

Hande Topel, Ezgi Bağırsakçı, Yeliz Yılmaz, Ayşim Güneş, Gülsün Bağcı, Dehan Çömez, Erkan Kahraman, Peyda Korhan, Neşe Atabey*

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

Abstract

Hepatocellular carcinoma (HCC) is strongly associated with metabolic dysregulations/deregulations and hyperglycemia is a common metabolic disturbance in metabolic diseases. Hyperglycemia is defined to promote epithelial to mesenchymal transition (EMT) of cancer cells in various cancers but its molecular contribution to HCC progression and aggressiveness is relatively unclear. In this study, we analyzed the molecular mechanisms behind the hyperglycemia-induced EMT in HCC cell lines. Here, we report that high glucose promotes EMT through activating c-Met receptor tyrosine kinase via promoting its ligand-independent homodimerization. c-Met activation is critical for high glucose induced acquisition of mesenchymal phenotype, survival under high glucose stress and reprogramming of cellular metabolism by modulating glucose metabolism gene expression to promote aggressiveness in HCC cells. The crucial role of c-Met in high glucose induced EMT and aggressiveness may be the potential link between metabolic syndrome-related hepatocarcinogenesis and/or HCC progression. Considering c-Met inhibition in hyperglycemic patients would be an important complementary strategy for therapy that favors sensitization of HCC cells to therapeutics.

Original languageEnglish
Article number11376
JournalScientific Reports
Volume11
Issue number1
Number of pages15
ISSN2045-2322
DOIs
Publication statusPublished - 31. May 2021
Externally publishedYes

Bibliographical note

Funding Information:
We thank Prof. Dr. Mehmet Ozturk for providing HCC cells, Izmir Biomedicine and Genome Center for establishment of required technical and instrumental infrastructure for this study, Prof. Dr. Jan-Wilhelm Kornfeld and Dr. Matteo Oliverio for their support in Seahorse experiments and Dr. Yasemin Öztemur Islakoğlu for her kind contribution to bioinformatic data analysis. This research was funded by “Scientific and Technological Research Council of Turkey (TUBITAK)” with the grant number of “114S359”.

Publisher Copyright:
© 2021, The Author(s).

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