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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...

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Detalles Bibliográficos
Autores principales: Lee, Ju-Seog, Kim, Ji Hoon, Park, Yun-Yong, Mills, Gordon B.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Korean Cancer Association 2011
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.
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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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