Interpreting expression profiles of cancers by genome-wide survey of breadth of expression in normal tissues

Xijin Ge, Shogo Yamamoto, Shuichi Tsutsumi, Yutaka Midorikawa, Sigeo Ihara, San Ming Wang, Hiroyuki Aburatani

Research output: Contribution to journalArticle

194 Citations (Scopus)

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 hepatoctyes 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.

Original languageEnglish (US)
Pages (from-to)127-141
Number of pages15
JournalGenomics
Volume86
Issue number2
DOIs
StatePublished - Aug 1 2005

Fingerprint

Genome
Neoplasms
Cell Lineage
Oligonucleotide Array Sequence Analysis
Genes
Hepatocellular Carcinoma
Gene Expression
Medulloblastoma
Neoplasm Genes
Surveys and Questionnaires
Glioma
Neuroglia
Cluster Analysis
Lung Neoplasms
Epithelial Cells
Breast Neoplasms
Neoplasm Metastasis
Neurons
Liver

Keywords

  • BRCA1
  • Breadth of expression
  • DNA microarray data interpretation
  • ESR1
  • Tissue-specific gene
  • Tumor differentiation

ASJC Scopus subject areas

  • Genetics

Cite this

Ge, X., Yamamoto, S., Tsutsumi, S., Midorikawa, Y., Ihara, S., Wang, S. M., & Aburatani, H. (2005). Interpreting expression profiles of cancers by genome-wide survey of breadth of expression in normal tissues. Genomics, 86(2), 127-141. https://doi.org/10.1016/j.ygeno.2005.04.008

Interpreting expression profiles of cancers by genome-wide survey of breadth of expression in normal tissues. / Ge, Xijin; Yamamoto, Shogo; Tsutsumi, Shuichi; Midorikawa, Yutaka; Ihara, Sigeo; Wang, San Ming; Aburatani, Hiroyuki.

In: Genomics, Vol. 86, No. 2, 01.08.2005, p. 127-141.

Research output: Contribution to journalArticle

Ge, X, Yamamoto, S, Tsutsumi, S, Midorikawa, Y, Ihara, S, Wang, SM & Aburatani, H 2005, 'Interpreting expression profiles of cancers by genome-wide survey of breadth of expression in normal tissues', Genomics, vol. 86, no. 2, pp. 127-141. https://doi.org/10.1016/j.ygeno.2005.04.008
Ge, Xijin ; Yamamoto, Shogo ; Tsutsumi, Shuichi ; Midorikawa, Yutaka ; Ihara, Sigeo ; Wang, San Ming ; Aburatani, Hiroyuki. / Interpreting expression profiles of cancers by genome-wide survey of breadth of expression in normal tissues. In: Genomics. 2005 ; Vol. 86, No. 2. pp. 127-141.
@article{b1aaa6d43de3474289900e72785acb5f,
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 hepatoctyes 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.",
keywords = "BRCA1, Breadth of expression, DNA microarray data interpretation, ESR1, Tissue-specific gene, Tumor differentiation",
author = "Xijin Ge and Shogo Yamamoto and Shuichi Tsutsumi and Yutaka Midorikawa and Sigeo Ihara and Wang, {San Ming} and Hiroyuki Aburatani",
year = "2005",
month = "8",
day = "1",
doi = "10.1016/j.ygeno.2005.04.008",
language = "English (US)",
volume = "86",
pages = "127--141",
journal = "Genomics",
issn = "0888-7543",
publisher = "Academic Press Inc.",
number = "2",

}

TY - JOUR

T1 - Interpreting expression profiles of cancers by genome-wide survey of breadth of expression in normal tissues

AU - Ge, Xijin

AU - Yamamoto, Shogo

AU - Tsutsumi, Shuichi

AU - Midorikawa, Yutaka

AU - Ihara, Sigeo

AU - Wang, San Ming

AU - Aburatani, Hiroyuki

PY - 2005/8/1

Y1 - 2005/8/1

N2 - 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 hepatoctyes 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.

AB - 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 hepatoctyes 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.

KW - BRCA1

KW - Breadth of expression

KW - DNA microarray data interpretation

KW - ESR1

KW - Tissue-specific gene

KW - Tumor differentiation

UR - http://www.scopus.com/inward/record.url?scp=21444445235&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=21444445235&partnerID=8YFLogxK

U2 - 10.1016/j.ygeno.2005.04.008

DO - 10.1016/j.ygeno.2005.04.008

M3 - Article

C2 - 15950434

AN - SCOPUS:21444445235

VL - 86

SP - 127

EP - 141

JO - Genomics

JF - Genomics

SN - 0888-7543

IS - 2

ER -