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Vol.48 No.4 contents | Japanese/English |
 | Full Text of PDF (1209K) Article in Japanese |
- Review Article -
Microarray Analysis for Detection of Metastasis and Evaluation of Prognosis in Lung Cancers
Kentaro Inamura1, Yuichi Ishikawa11Department of Pathology, The Cancer Institute, Japanese Foundation for Cancer Research (JFCR), Japan
Objective. Since the commencement of human genome projects, molecular analysis of human tissues has become much easier. Now we can monitor expression of most genes simultaneously and comprehensively using microarray technologies. It is well known that cancers develop from accumulations of multiple gene abnormalities and signal pathway alterations, and therefore we must systematically analyze many genes to elucidate the genesis and progression of tumors. Result. In this review article, we describe some results of comprehensive analysis of gene expression that are useful for classification of heterogeneous lung tumors and help to understand their biological natures. We introduced a new clustering technique, called non-negative matrix factorization (NMF) to subclassify squamous cell carcinoma of the lung. We also analyzed neuroendocrine tumors and found a group with very good prognosis, independent of small-cell or large-cell neuroendocrine carcinoma histologies. Further, we described recent studies on metastatic potentials of lung cancer, including our own results on metastatic signature analysis of heterogeneous lung adenocarcinomas as well as some other models of prediction of prognosis or metastasis using small numbers of genes.
key words: Lung cancer, Microarray, Expression profiling, Classification, Microdissection
Received: February 19, 2008
Accepted: June 12, 2008
JJLC 48 (4): 247-253, 2008
