Microarray Analysis of Gene Expression of Cancer to Guide the Use of Chemotherapeutics
The beauty of microarray analysis of gene expression (MAGE) is that it can be used to discover some genes that were previously thought to be unrelated to a physiologic or pathologic event. During the period from 1999 to 2007, applications of MAGE in cancer investigation have shifted from molecular p...
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Format: | Article |
Language: | English |
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Elsevier
2007-09-01
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Series: | Taiwanese Journal of Obstetrics & Gynecology |
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Online Access: | http://www.sciencedirect.com/science/article/pii/S1028455908600248 |
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author | Tzu-Hao Wang Angel Chao |
author_facet | Tzu-Hao Wang Angel Chao |
author_sort | Tzu-Hao Wang |
collection | DOAJ |
description | The beauty of microarray analysis of gene expression (MAGE) is that it can be used to discover some genes that were previously thought to be unrelated to a physiologic or pathologic event. During the period from 1999 to 2007, applications of MAGE in cancer investigation have shifted from molecular profiling, identifying previously undiscovered cancer types, predicting outcomes of cancer patients, revealing metastasis signatures of solid tumors, to guiding the use of therapeutics. The roles of cancer genomic signatures have evolved through three phases. In the first phase, genomic signatures were described in stored cancer specimens and dubbed as molecular portraits of cancer. When gene expression profiles were carefully correlated with sufficient clinical information of cancer patients, new subgroups of cancers with distinct outcomes were revealed. In studies of the second phase, validation of cancer signatures was emphasized and commonly performed with independent groups of cancer specimens or independent data set. In the third phase, cancer genomic signatures have been further expanded beyond depicting the molecular portrait of cancer to predicting patient outcomes and guiding the use of cancer therapeutics. Cancer genomic signatures have become an essential part of a new generation of cancer clinical trials. It is advocated that, in future clinical trials of cancer therapy, the cancer specimens of each participant should be tested for currently available predictor genomic signatures, so that the most effective treatment with the least adverse effects for each patient can be identified. Then, participants can be triaged to an appropriate study group. |
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format | Article |
id | doaj.art-2671ad8cec444e46a4e59b09def95a25 |
institution | Directory Open Access Journal |
issn | 1028-4559 |
language | English |
last_indexed | 2024-12-12T19:41:37Z |
publishDate | 2007-09-01 |
publisher | Elsevier |
record_format | Article |
series | Taiwanese Journal of Obstetrics & Gynecology |
spelling | doaj.art-2671ad8cec444e46a4e59b09def95a252022-12-22T00:14:12ZengElsevierTaiwanese Journal of Obstetrics & Gynecology1028-45592007-09-0146322222910.1016/S1028-4559(08)60024-8Microarray Analysis of Gene Expression of Cancer to Guide the Use of ChemotherapeuticsTzu-Hao Wang0Angel Chao1Department of Obstetrics and Gynecology, Lin-Kou Medical Center, Chang Gung Memorial Hospital, Chang Gung University, Tao-Yuan, TaiwanDepartment of Obstetrics and Gynecology, Lin-Kou Medical Center, Chang Gung Memorial Hospital, Chang Gung University, Tao-Yuan, TaiwanThe beauty of microarray analysis of gene expression (MAGE) is that it can be used to discover some genes that were previously thought to be unrelated to a physiologic or pathologic event. During the period from 1999 to 2007, applications of MAGE in cancer investigation have shifted from molecular profiling, identifying previously undiscovered cancer types, predicting outcomes of cancer patients, revealing metastasis signatures of solid tumors, to guiding the use of therapeutics. The roles of cancer genomic signatures have evolved through three phases. In the first phase, genomic signatures were described in stored cancer specimens and dubbed as molecular portraits of cancer. When gene expression profiles were carefully correlated with sufficient clinical information of cancer patients, new subgroups of cancers with distinct outcomes were revealed. In studies of the second phase, validation of cancer signatures was emphasized and commonly performed with independent groups of cancer specimens or independent data set. In the third phase, cancer genomic signatures have been further expanded beyond depicting the molecular portrait of cancer to predicting patient outcomes and guiding the use of cancer therapeutics. Cancer genomic signatures have become an essential part of a new generation of cancer clinical trials. It is advocated that, in future clinical trials of cancer therapy, the cancer specimens of each participant should be tested for currently available predictor genomic signatures, so that the most effective treatment with the least adverse effects for each patient can be identified. Then, participants can be triaged to an appropriate study group.http://www.sciencedirect.com/science/article/pii/S1028455908600248cancer therapeuticsclinical applicationgene expressiongenomic signaturesmicroarrays |
spellingShingle | Tzu-Hao Wang Angel Chao Microarray Analysis of Gene Expression of Cancer to Guide the Use of Chemotherapeutics Taiwanese Journal of Obstetrics & Gynecology cancer therapeutics clinical application gene expression genomic signatures microarrays |
title | Microarray Analysis of Gene Expression of Cancer to Guide the Use of Chemotherapeutics |
title_full | Microarray Analysis of Gene Expression of Cancer to Guide the Use of Chemotherapeutics |
title_fullStr | Microarray Analysis of Gene Expression of Cancer to Guide the Use of Chemotherapeutics |
title_full_unstemmed | Microarray Analysis of Gene Expression of Cancer to Guide the Use of Chemotherapeutics |
title_short | Microarray Analysis of Gene Expression of Cancer to Guide the Use of Chemotherapeutics |
title_sort | microarray analysis of gene expression of cancer to guide the use of chemotherapeutics |
topic | cancer therapeutics clinical application gene expression genomic signatures microarrays |
url | http://www.sciencedirect.com/science/article/pii/S1028455908600248 |
work_keys_str_mv | AT tzuhaowang microarrayanalysisofgeneexpressionofcancertoguidetheuseofchemotherapeutics AT angelchao microarrayanalysisofgeneexpressionofcancertoguidetheuseofchemotherapeutics |