Abstract
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.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Amant F, Moerman P, Neven P, et al. Endometrial cancer. Lancet. 2005;366:491–505.
Bucca G, Carruba G, Saetta A, et al. Gene expression profiling of human cancers. Ann N Y Acad Sci. 2004;1028:28–37.
Quackenbush J. Microarray analysis and tumor classification. N Engl J Med. 2006;354:2463–2472.
Sorlie T, Perou CM, Tibshirani R, et al. Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications. Proc Natl Acad Sci USA. 2001;98:10869–10874.
Alizadeh AA, Eisen MB, Davis RE, et al. Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling. Nature. 2000;403:503–511.
Dave SS, Fu K, Wright GW, et al. Lymphoma/leukemia molecular profiling project. Molecular diagnosis of Burkitt’s lymphoma. N Engl J Med. 2006;354:2431–2442.
van’ t Veer LJ, Dai H, van de Vijver MJ, et al. Gene expression profiling predicts clinical outcome of breast cancer. Nature. 2002;415:530–536.
Ouellet V, Provencher DM, Maugard CM, et al. Discrimination between serous low malignant potential and invasive epithelial ovarian tumors using molecular profiling. Oncogene. 2005;24:4672–4687.
Smid-Koopman E, Blok LJ, Chadha-Ajwani S, et al. Gene expression profiles of human endometrial cancer samples using a cDNA-expression array technique: assessment of an analysis method. Br J Cancer. 2000;83:246–251.
Eisen MB, Spellman PT, Brown PO, et al. Cluster analysis and display of genome-wide expression patterns. Proc Natl Acad Sci USA. 1998;95:14863–14868.
Li B, Wu L, Li S, et al. Multivariate analysis of prognostic factors in endometrial carcinoma. Chin J Cancer. 2004;23:1085–1088.
Meng Y, Wei L, Wang J. Monitoring gene expression profile changes in endometrial cancer using cDNA microarray technology. Natl Med J Chin. 2001;81:665–668.
Zhou H, Shi Y, Li J, et al. Preliminary study on gene expression profile of endometrial adenocarcinoma. Chin J Oncol. 2003;25:464–467.
Wan X, Cai B, Liu L, et al. Study of differential gene expression in differen t stage human endometrial cancer. Chin J Obstet Gynecol. 2006;41:38–42.
Cai B, Liu L, Wan X, et al. Hierarchical clustering analysis of gene expression profile of 32 cases of endometrial cancer. Tumor. 2006;26:456–460.
Ferguson SE, Olshen AB, Viale A, et al. Stratification of intermediate-risk endometrial cancer patients into groups at high risk or low risk for recurrence based on tumor gene expression profiles. Clin Cancer Res. 2005;11:2252–2257.
Gunter Kieback D, Fischer DC. Gene expression profile in endometrioid endometrial carcinoma. Gynecol Oncol. 2001;83:175–176.
Bidus MA, Risinger JI, Chandramouli GV, et al. Prediction of lymph node metastasis in patients with endometrioid endometrial cancer using expression microarray. Clin Cancer Res. 2006;12:83–88.
Smid-Koopman E, Blok LJ, Helmerhorst TJ, et al. Gene expression profiling in human endometrial cancer tissue samples: utility and diagnostic value. Gynecol Oncol. 2004;93:292–300.
Wrobel G, Roerig P, Kokocinski F, et al. Microarray-based gene expression profiling of benign, atypical and anaplastic meningiomas identifies novel genes associated with meningioma progression. Int J Cancer. 2005;114:249–256.
Kim DS, Hubbard SL, Peraud A, et al. Analysis of mammalian septin expression in human malignant brain tumors. Neoplasia. 2004;6:168–178.
Mar KC, Eimoto T, Nagaya S, et al. Cell proliferation marker MCM2, but not Ki67, is helpful for distinguishing between minimally invasive follicular carcinoma and follicular adenoma of the thyroid. Histopathology. 2006;48:801–807.
Casey G, Neville PJ, Liu X, et al. Podocalyxin variants and risk of prostate cancer and tumor aggressiveness. Hum Mol Genet. 2006;15:735–741.
Author information
Authors and Affiliations
Corresponding author
Additional information
This work was supported by a grant from the National Natural Science Foundation of China (No.30371481), the Natural Science Foundation of Shanghai (No. 06ZR14053) and the Key Project of the Shanghai Health Bureau (No.2005ZD002).
About this article
Cite this article
Cai, B., Hogg, D., Lu, G. et al. Studies of differentially-expressed genes in human endometrial cancer of various differentiated grades. Chin. J. Clin. Oncol. 4, 77–82 (2007). https://doi.org/10.1007/s11805-007-0077-9
Received:
Accepted:
Issue Date:
DOI: https://doi.org/10.1007/s11805-007-0077-9