title: Interpreting expression profiles of cancers by genome-wide survey of breadth of expression in normal tissues.
abstract: A critical and difficult part of studying cancer with DNA microarrays is data interpretation. Besides the need for data analysis algorithms, integration of additional information about genes might be useful. We performed genome-wide expression profiling of 36 types of normal human tissues and identified 2503 tissue-specific genes. We then systematically studied the expression of these genes in cancers by reanalyzing a large collection of published DNA microarray datasets. We observed that the expression level of liver-specific genes in hepatocellular carcinoma (HCC) correlates with the clinically defined degree of tumor differentiation. Through unsupervised clustering of tissue-specific genes differentially expressed in tumors, we extracted expression patterns that are characteristic of individual cell types, uncovering differences in cell lineage among tumor subtypes. We were able to detect the expression signature of hepatocytes in HCC, neuron cells in medulloblastoma, glia cells in glioma, basal and luminal epithelial cells in breast tumors, and various cell types in lung cancer samples. We also demonstrated that tissue-specific expression signatures are useful in locating the origin of metastatic tumors. Our study shows that integration of each gene's breadth of expression (BOE) in normal tissues is important for biological interpretation of the expression profiles of cancers in terms of tumor differentiation, cell lineage, and metastasis.
authors.affiliation: Genome Science Division, Research Center for Advanced Science and Technology, The University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8904, Japan. xge@northwestern.edu
authors.forename: Xijin
authors.initials: X
authors.lastname: Ge
authors.forename: Shogo
authors.initials: S
authors.lastname: Yamamoto
authors.forename: Shuichi
authors.initials: S
authors.lastname: Tsutsumi
authors.forename: Yutaka
authors.initials: Y
authors.lastname: Midorikawa
authors.forename: Sigeo
authors.initials: S
authors.lastname: Ihara
authors.forename: San Ming
authors.initials: SM
authors.lastname: Wang
authors.forename: Hiroyuki
authors.initials: H
authors.lastname: Aburatani
mesh_terms: D000465:Algorithms; D001932:Brain Neoplasms / Q000235:genetics; D006528:Carcinoma, Hepatocellular / Q000235:genetics; D002454:Cell Differentiation; D019070:Cell Lineage; D016000:Cluster Analysis; D005786:Gene Expression Regulation; D019398:Genes, BRCA1; D015894:Genome, Human; D006801:Humans; D008113:Liver Neoplasms / Q000235:genetics; D008175:Lung Neoplasms; D008957:Models, Genetic; D005810:Multigene Family; D009362:Neoplasm Metastasis; D020411:Oligonucleotide Array Sequence Analysis; D010802:Phylogeny; D011401:Promoter Regions, Genetic; D012313:RNA / Q000378:metabolism; D014018:Tissue Distribution
chemical_list: D012313:RNA