Literature DB >> 12524204

Classifying human cancer by analysis of gene expression.

Garret M Hampton1, Henry F Frierson.   

Abstract

With the development and application of DNA microarrays, the expression of almost all human genes can now be systematically examined in human malignancies. This can lead to the identification of candidate molecular targets for therapeutic intervention and biomarkers for early detection of these diseases. However, perhaps the most exciting result to come from this research has been the demonstration that patterns of gene expression can distinguish between tumors of different anatomical origin, and define new subgroups of cancer with similar histological appearance, but distinct molecular profiles. Some of these new molecular subclasses of tumor appear to correlate with clinical behavior. If substantiated in larger studies, this might form a basis for stratifying patients so that they receive optimal therapeutic treatment and follow-up.

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Year:  2003        PMID: 12524204     DOI: 10.1016/s1471-4914(02)00006-0

Source DB:  PubMed          Journal:  Trends Mol Med        ISSN: 1471-4914            Impact factor:   11.951


  3 in total

1.  Template-driven gene selection procedure.

Authors:  N Knowlton; I Dozmorov; K D Kyker; R Saban; C Cadwell; M B Centola; R E Hurst
Journal:  Syst Biol (Stevenage)       Date:  2006-01

2.  Functional network construction in Arabidopsis using rule-based machine learning on large-scale data sets.

Authors:  George W Bassel; Enrico Glaab; Julietta Marquez; Michael J Holdsworth; Jaume Bacardit
Journal:  Plant Cell       Date:  2011-09-06       Impact factor: 11.277

3.  Molecular signature of clinical severity in recovering patients with severe acute respiratory syndrome coronavirus (SARS-CoV).

Authors:  Yun-Shien Lee; Chun-Houh Chen; Angel Chao; En-Shih Chen; Min-Li Wei; Lung-Kun Chen; Kuender D Yang; Meng-Chih Lin; Yi-Hsi Wang; Jien-Wei Liu; Hock-Liew Eng; Ping-Cherng Chiang; Ting-Shu Wu; Kuo-Chein Tsao; Chung-Guei Huang; Yin-Jing Tien; Tzu-Hao Wang; Hsing-Shih Wang; Ying-Shiung Lee
Journal:  BMC Genomics       Date:  2005-09-21       Impact factor: 3.969

  3 in total

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