Skip to Main content Skip to Navigation
Journal articles

Gene network analysis leads to functional validation of pathways linked to cancer cell growth and survival.

Abstract : Hepatocellular carcinoma (HCC) represents one of the most frequently diagnosed human cancers; however, there are currently few treatment alternatives to surgical resection. In this study we performed bioinformatic analysis of previously published transcriptomic data in order to characterize liver specific networks, including biological functions, signaling pathways and transcription factors, potentially dysregulated in HCC. By incorporating specific signaling inhibitors into real-time proliferation assays using HepG2 cells, we then validated these in silico results. We found that G protein subunits Gi/G0, protein kinase C, Mek1/2, and Erk1/2 (P42/44), JAK1, PPARA and NFκB p65 subunit were the major signaling molecules required for survival and proliferation of human HCC cell lines. We also found that these pathways regulate the expression of key hepatic transcription factors involved in cell differentiation, such as CEBPA, EGR1, FOXM1 and PPARs. By combining bioinformatic and functional analyses, major signaling pathways related to tumorigenicity in HCC are revealed, thereby elucidating potential targets for drug therapies.
Document type :
Journal articles
Complete list of metadatas

Cited literature [50 references]  Display  Hide  Download

https://www.hal.inserm.fr/inserm-00813081
Contributor : Evelyne Vericel <>
Submitted on : Monday, April 15, 2013 - 8:50:52 AM
Last modification on : Thursday, October 1, 2020 - 1:28:02 PM
Long-term archiving on: : Tuesday, July 16, 2013 - 4:04:45 AM

File

berger.pdf
Files produced by the author(s)

Identifiers

Collections

Citation

Emmanuelle Berger, Nathalie Vega, Hubert Vidal, Alain Geloen. Gene network analysis leads to functional validation of pathways linked to cancer cell growth and survival.. Biotechnology Journal, Wiley-VCH Verlag, 2012, 7 (11), pp.1395-404. ⟨10.1002/biot.201200188⟩. ⟨inserm-00813081⟩

Share

Metrics

Record views

509

Files downloads

880