Systems Biology Approaches to Decoding the Genome of Liver Cancer.
- Author:
Ju Seog LEE
1
;
Ji Hoon KIM
;
Yun Yong PARK
;
Gordon B MILLS
Author Information
1. Department of Systems Biology, MD Anderson Cancer Center, The University of Texas, Houston, TX, USA. jlee@mdanderson.org
- Publication Type:Review
- Keywords:
Oligonucleotide array sequence analysis;
Gene expression profiling;
Hepatocellular carcinoma;
Genomics;
Systems biology;
Proteomics
- MeSH:
Biomarkers;
Breast;
Breast Neoplasms;
Carcinoma, Hepatocellular;
Child;
Clinical Protocols;
Epidermal Growth Factor;
Epigenomics;
Estrogens;
Gene Expression Profiling;
Genome;
Genomics;
Humans;
Precision Medicine;
Liver;
Liver Neoplasms;
Oligonucleotide Array Sequence Analysis;
Prognosis;
Proteomics;
Systems Biology
- From:Cancer Research and Treatment
2011;43(4):205-211
- CountryRepublic of Korea
- Language:English
-
Abstract:
Molecular classification of cancers has been significantly improved patient outcomes through the implementation of treatment protocols tailored to the abnormalities present in each patient's cancer cells. Breast cancer represents the poster child with marked improvements in outcome occurring due to the implementation of targeted therapies for estrogen receptor or human epidermal growth factor receptor-2 positive breast cancers. Important subtypes with characteristic molecular features as potential therapeutic targets are likely to exist for all tumor lineages including hepatocellular carcinoma (HCC) but have yet to be discovered and validated as targets. Because each tumor accumulates hundreds or thousands of genomic and epigenetic alterations of critical genes, it is challenging to identify and validate candidate tumor aberrations as therapeutic targets or biomarkers that predict prognosis or response to therapy. Therefore, there is an urgent need to devise new experimental and analytical strategies to overcome this problem. Systems biology approaches integrating multiple data sets and technologies analyzing patient tissues holds great promise for the identification of novel therapeutic targets and linked predictive biomarkers allowing implementation of personalized medicine for HCC patients.
