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Prediction of Lymph Node Metastasis in Patients with Endometrioid Endometrial Cancer Using Expression Microarray

Authors' Affiliations: ¹ Walter Reed Army Medical Center and the United States Military Cancer Institute, Washington, DC; ² Laboratory of Biosystems and Cancer, National Cancer Institute, Bethesda, Maryland; and ³ Department of Obstetrics and Gynecology, Division of Gynecologic Oncology, Duke University, Durham, North Carolina

Requests for reprints: G. Larry Maxwell, Division of Gynecologic Oncology, Walter Reed Army Medical Center, 6900 Georgia Avenue, Washington, DC 20307. Fax: 202-782-9278; E-mail: george.maxwell{at}na.amedd.army.mil.

Purpose: To characterize the gene expression profiles of endometrioid endometrial cancers associated with lymph node metastasis in an effort to identify genes associated with metastatic spread.

Experimental Design: Tumors from 41 patients with endometrioid endometrial cancer grossly confined to the uterine cavity were evaluated. Positive lymph nodes were noted in 12 of 41 patients. RNA was analyzed for gene expression using the Affymetrix HG133A and HG133B GeneChip set, representing 45,000 array features covering >28,000 UniGene clusters. Data analysis was done using multidimensional scaling, binary comparison, and hierarchical clustering. Gene expression for several differentially expressed genes was examined using quantitative PCR.

Results: Gene expression data was obtained from 30,964 genes that were detected in at least 5% of the cases. Supervised analysis of node-positive versus node-negative cases indicated that 450 genes were significantly differentially expressed between the two classes at P < 0.005, 81 of which were differentially expressed by at least 2-fold at P < 0.005. Overexpressed genes included two cell cycle checkpoint genes, CDC2 and MAD2L1, which have previously been described in association with lymph node metastasis in other cancer types. The ZIC2 zinc finger gene was overexpressed in endometrial cancers with positive nodes versus those with negative nodes.

Conclusion: Gene expression profiling of the primary tumors in patients with endometrioid endometrial cancers seems promising for identifying genes associated with lymph node metastasis. Future studies should address whether the status of nodal metastasis can be determined from the expression profiles of preoperative tissue specimens.