OBJECTIVE To study the gene expression profiles of human endometrial cancers at various differentia0ted grade levels and to identify the genes related to differentiation of the endometrial cancers. METHODS cDNA microa...OBJECTIVE To study the gene expression profiles of human endometrial cancers at various differentia0ted grade levels and to identify the genes related to differentiation of the endometrial cancers. METHODS cDNA microarray technology was used to analyze the differentially-expressed genes among different differentiated grades of 32 cases of endometrial cancer. Hierarchical cluster analysis （HCA） for the gene expression profiles of the cases was employed. RESULTS The tissue samples were grouped based on the various differentiated tumor grades with 33 differentiation-related genes identified out （P〈0.001）. Based on the results from the HCA, the conformity rate was 91% among the 33 differentially-expressed genes, and the analysis of pathological classification.CONCLUSION Genes related to the differentiation of endometrial cancer can be identified by using gene chips to analyze the expression profiles of endometrial cancers at various differentiated grades; HCA of the gene expression profiles can be helpful for distinguishing high-risk endometrial cancers before surgery.展开更多
基金This work was supported by a grant from theNational Natural Science Foundation of China(No.30371481)the Natural Science Founda-tion of Shanghai(No.06ZR14053)theKey Project of the Shanghai Health Bureau(No.2005ZD002).
文摘OBJECTIVE To study the gene expression profiles of human endometrial cancers at various differentia0ted grade levels and to identify the genes related to differentiation of the endometrial cancers. METHODS cDNA microarray technology was used to analyze the differentially-expressed genes among different differentiated grades of 32 cases of endometrial cancer. Hierarchical cluster analysis （HCA） for the gene expression profiles of the cases was employed. RESULTS The tissue samples were grouped based on the various differentiated tumor grades with 33 differentiation-related genes identified out （P〈0.001）. Based on the results from the HCA, the conformity rate was 91% among the 33 differentially-expressed genes, and the analysis of pathological classification.CONCLUSION Genes related to the differentiation of endometrial cancer can be identified by using gene chips to analyze the expression profiles of endometrial cancers at various differentiated grades; HCA of the gene expression profiles can be helpful for distinguishing high-risk endometrial cancers before surgery.
