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Multi-OMICs and Genome Editing Perspectives on Liver Cancer Signaling Networks
The advent of the human genome sequence and the resulting ~20,000 genes provide a crucial framework for a transition from traditional biology to an integrative “OMICs” arena (Lander et al., 2001; Venter et al., 2001; Kitano, 2002). This brings in a revolution for cancer research, which now enters a...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi Publishing Corporation
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4923561/ https://www.ncbi.nlm.nih.gov/pubmed/27403431 http://dx.doi.org/10.1155/2016/6186281 |
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author | Lin, Shengda Yin, Yi A. Jiang, Xiaoqian Sahni, Nidhi Yi, Song |
author_facet | Lin, Shengda Yin, Yi A. Jiang, Xiaoqian Sahni, Nidhi Yi, Song |
author_sort | Lin, Shengda |
collection | PubMed |
description | The advent of the human genome sequence and the resulting ~20,000 genes provide a crucial framework for a transition from traditional biology to an integrative “OMICs” arena (Lander et al., 2001; Venter et al., 2001; Kitano, 2002). This brings in a revolution for cancer research, which now enters a big data era. In the past decade, with the facilitation by next-generation sequencing, there have been a huge number of large-scale sequencing efforts, such as The Cancer Genome Atlas (TCGA), the HapMap, and the 1000 genomes project. As a result, a deluge of genomic information becomes available from patients stricken by a variety of cancer types. The list of cancer-associated genes is ever expanding. New discoveries are made on how frequent and highly penetrant mutations, such as those in the telomerase reverse transcriptase (TERT) and TP53, function in cancer initiation, progression, and metastasis. Most genes with relatively frequent but weakly penetrant cancer mutations still remain to be characterized. In addition, genes that harbor rare but highly penetrant cancer-associated mutations continue to emerge. Here, we review recent advances related to cancer genomics, proteomics, and systems biology and suggest new perspectives in targeted therapy and precision medicine. |
format | Online Article Text |
id | pubmed-4923561 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Hindawi Publishing Corporation |
record_format | MEDLINE/PubMed |
spelling | pubmed-49235612016-07-11 Multi-OMICs and Genome Editing Perspectives on Liver Cancer Signaling Networks Lin, Shengda Yin, Yi A. Jiang, Xiaoqian Sahni, Nidhi Yi, Song Biomed Res Int Review Article The advent of the human genome sequence and the resulting ~20,000 genes provide a crucial framework for a transition from traditional biology to an integrative “OMICs” arena (Lander et al., 2001; Venter et al., 2001; Kitano, 2002). This brings in a revolution for cancer research, which now enters a big data era. In the past decade, with the facilitation by next-generation sequencing, there have been a huge number of large-scale sequencing efforts, such as The Cancer Genome Atlas (TCGA), the HapMap, and the 1000 genomes project. As a result, a deluge of genomic information becomes available from patients stricken by a variety of cancer types. The list of cancer-associated genes is ever expanding. New discoveries are made on how frequent and highly penetrant mutations, such as those in the telomerase reverse transcriptase (TERT) and TP53, function in cancer initiation, progression, and metastasis. Most genes with relatively frequent but weakly penetrant cancer mutations still remain to be characterized. In addition, genes that harbor rare but highly penetrant cancer-associated mutations continue to emerge. Here, we review recent advances related to cancer genomics, proteomics, and systems biology and suggest new perspectives in targeted therapy and precision medicine. Hindawi Publishing Corporation 2016 2016-06-14 /pmc/articles/PMC4923561/ /pubmed/27403431 http://dx.doi.org/10.1155/2016/6186281 Text en Copyright © 2016 Shengda Lin et al. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Review Article Lin, Shengda Yin, Yi A. Jiang, Xiaoqian Sahni, Nidhi Yi, Song Multi-OMICs and Genome Editing Perspectives on Liver Cancer Signaling Networks |
title | Multi-OMICs and Genome Editing Perspectives on Liver Cancer Signaling Networks |
title_full | Multi-OMICs and Genome Editing Perspectives on Liver Cancer Signaling Networks |
title_fullStr | Multi-OMICs and Genome Editing Perspectives on Liver Cancer Signaling Networks |
title_full_unstemmed | Multi-OMICs and Genome Editing Perspectives on Liver Cancer Signaling Networks |
title_short | Multi-OMICs and Genome Editing Perspectives on Liver Cancer Signaling Networks |
title_sort | multi-omics and genome editing perspectives on liver cancer signaling networks |
topic | Review Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4923561/ https://www.ncbi.nlm.nih.gov/pubmed/27403431 http://dx.doi.org/10.1155/2016/6186281 |
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