RT Journal Article
A1 Sol Efroni
AD The Mina and Everard Goodman Life Science Faculty, Bar Ilan University, Ramat Gan, Israel
A1 Daoud Meerzaman
AD Laboratory of Population Genetics, National Institutes of Health, Bethesda, MD 20892, USA
A1 Carl F. Schaefer
AD National Cancer Institute Center for Biomedical Informatics, National Institutes of Health, Rockville, MD 20852, USA
A1 Sharon Greenblum
AD National Cancer Institute Center for Biomedical Informatics, National Institutes of Health, Rockville, MD 20852, USA
A1 Myung Soo-Lyu
AD Laboratory of Population Genetics, National Institutes of Health, Bethesda, MD 20892, USA
A1 Ying Hu
AD Laboratory of Population Genetics, National Institutes of Health, Bethesda, MD 20892, USA
A1 Constance Cultraro
AD Laboratory of Population Genetics, National Institutes of Health, Bethesda, MD 20892, USA
A1 Eran Meshorer
AD Department of Genetics, The Hebrew University of Jerusalem, Jerusalem 91904, Israel
A1 Kenneth H. Buetow
AD Laboratory of Population Genetics, National Institutes of Health, Bethesda, MD 20892, USA
AD National Cancer Institute Center for Biomedical Informatics, National Institutes of Health, Rockville, MD 20852, USA
AD Complex Adaptive Systems and School of Life Sciences, Arizona State University, USA

PB iet
T1 Systems analysis utilising pathway interactions identifies sonic hedgehog pathway as a primary biomarker and oncogenic target in hepatocellular carcinoma
JN IET Systems Biology
VO 7
IS 6
SP 243
OP 251
AB The development and progression of cancer is associated with disruption of biological networks. Historically studies have identified sets of signature genes involved in events ultimately leading to the development of cancer. Identification of such sets does not indicate which biologic processes are oncogenic drivers and makes it difficult to identify key networks to target for interventions. Using a comprehensive, integrated computational approach, the authors identify the sonic hedgehog (SHH) pathway as the gene network that most significantly distinguishes tumour and tumour-adjacent samples in human hepatocellular carcinoma (HCC). The analysis reveals that the SHH pathway is commonly activated in the tumour samples and its activity most significantly differentiates tumour from the non-tumour samples. The authors experimentally validate these in silico findings in the same biologic material using Western blot analysis. This analysis reveals that the expression levels of SHH, phosphorylated cyclin B1, and CDK7 levels are much higher in most tumour tissues as compared to normal tissue. It is also shown that siRNA-mediated silencing of SHH gene expression resulted in a significant reduction of cell proliferation in a liver cancer cell line, SNU449 indicating that SHH plays a major role in promoting cell proliferation in liver cancer. The SHH pathway is a key network underpinning HCC aetiology which may guide the development of interventions for this most common form of human liver cancer.
K1 biologic processes
K1 cell proliferation
K1 pathway interactions
K1 liver cancer cell line
K1 biomedical informatics
K1 primary biomarker
K1 phosphorylated cyclin B1
K1 SHH pathway
K1 sonic hedgehog pathway
K1 cancer development
K1 CDK7 levels
K1 cancer progression
K1 gene network
K1 oncogenic target
K1 network underpinning HCC aetiology
K1 human liver cancer
K1 integrated computational approach
K1 in silico findings
K1 biological networks
K1 SHH gene expression
K1 Western blot analysis
K1 oncogenic drivers
K1 siRNA-mediated silencing
K1 human hepatocellular carcinoma
K1 systems analysis
K1 tumour-adjacent samples
DO https://doi.org/10.1049/iet-syb.2010.0078
UL https://digital-library.theiet.org/;jsessionid=b1f9e6pb7rp7e.x-iet-live-01content/journals/10.1049/iet-syb.2010.0078
LA English
SN 1751-8849
YR 2013
OL EN