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Microarray Analysis of Endometrial Carcinomas and Mixed Mullerian Tumors Reveals Distinct Gene Expression Profiles Associated with Different Histologic Types of Uterine Cancer

Authors :
G. Larry Maxwell
Gadisetti V.R. Chandramouli
John I. Risinger
Lou A. Dainty
Andrew Berchuck
J. Carl Barrett
Tracy Litzi
Source :
Clinical Cancer Research. 11:4056-4066
Publication Year :
2005
Publisher :
American Association for Cancer Research (AACR), 2005.

Abstract

Previous studies using cDNA microarray have indicated that distinct gene expression profiles characterize endometrioid and papillary serous carcinomas of the endometrium. Molecular studies have observed that mixed mullerian tumors, characterized by both carcinomatous and sarcomatous components, share features that are characteristic of endometrial carcinomas. The objective of this analysis was to more precisely define gene expression patterns that distinguish endometrioid and papillary serous histologies of endometrial carcinoma and mixed mullerian tumors of the uterus. One hundred nineteen pathologically confirmed uterine cancer samples were studied (66 endometrioid, 24 papillary serous, and 29 mixed mullerian tumors). Gene expressions were analyzed using the Affymetrix Human Genome Arrays U133A and U133B Genechip set. Unsupervised analysis revealed distinct global gene expression patterns of endometrioid, papillary serous, mixed mullerian tumors, and normal tissues as grossly separated clusters. Two-sample t tests comparing endometrioid and papillary serous, endometrioid and mixed mullerian tumor, and papillary serous and mixed mullerian tumor pairs identified 1,055, 5,212, and 1,208 differentially expressed genes at P < 0.001, respectively. These data revealed that distinct patterns of gene expression characterize various histologic types of uterine cancer. Gene expression profiles for select genes were confirmed using quantitative PCR. An understanding of the molecular heterogeneity of various histologic types of endometrial cancer has the potential to lead to better individualization of treatment in the future.

Details

ISSN :
15573265 and 10780432
Volume :
11
Database :
OpenAIRE
Journal :
Clinical Cancer Research
Accession number :
edsair.doi.dedup.....a6a5d0ac689e2196616a531e55c91a90
Full Text :
https://doi.org/10.1158/1078-0432.ccr-04-2001