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Systems Biology Approaches to Decoding the Genome of Liver Cancer
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 du...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Korean Cancer Association
2011
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3253861/ https://www.ncbi.nlm.nih.gov/pubmed/22247704 http://dx.doi.org/10.4143/crt.2011.43.4.205 |
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author | Lee, Ju-Seog Kim, Ji Hoon Park, Yun-Yong Mills, Gordon B. |
author_facet | Lee, Ju-Seog Kim, Ji Hoon Park, Yun-Yong Mills, Gordon B. |
author_sort | Lee, Ju-Seog |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-3253861 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2011 |
publisher | Korean Cancer Association |
record_format | MEDLINE/PubMed |
spelling | pubmed-32538612012-01-13 Systems Biology Approaches to Decoding the Genome of Liver Cancer Lee, Ju-Seog Kim, Ji Hoon Park, Yun-Yong Mills, Gordon B. Cancer Res Treat Review Article 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. Korean Cancer Association 2011-12 2011-12-27 /pmc/articles/PMC3253861/ /pubmed/22247704 http://dx.doi.org/10.4143/crt.2011.43.4.205 Text en Copyright © 2011 by the Korean Cancer Association http://creativecommons.org/licenses/by-nc/3.0 This is an Open-Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Review Article Lee, Ju-Seog Kim, Ji Hoon Park, Yun-Yong Mills, Gordon B. Systems Biology Approaches to Decoding the Genome of Liver Cancer |
title | Systems Biology Approaches to Decoding the Genome of Liver Cancer |
title_full | Systems Biology Approaches to Decoding the Genome of Liver Cancer |
title_fullStr | Systems Biology Approaches to Decoding the Genome of Liver Cancer |
title_full_unstemmed | Systems Biology Approaches to Decoding the Genome of Liver Cancer |
title_short | Systems Biology Approaches to Decoding the Genome of Liver Cancer |
title_sort | systems biology approaches to decoding the genome of liver cancer |
topic | Review Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3253861/ https://www.ncbi.nlm.nih.gov/pubmed/22247704 http://dx.doi.org/10.4143/crt.2011.43.4.205 |
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