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Stratification of Intermediate-Risk Endometrial Cancer Patients into Groups at High Risk or Low Risk for Recurrence Based on Tumor Gene Expression Profiles

Departments of ¹ Surgery, ² Epidemiology and Biostatistics, and ³ Medicine and ⁴ Molecular Biology Program, Memorial Sloan-Kettering Cancer Center, New York, New York

Requests for reprints: Jeff Boyd, Department of Surgery, Memorial Sloan-Kettering Cancer Center, Box 201, New York, NY 10021. Phone: 212-639-8608; Fax: 212-717-3538; E-mail: boydj{at}mskcc.org.

Purpose: Endometrial cancers classified as "intermediate risk" based on clinical and/or pathologic features are associated with a 15% to 20% risk of recurrence. Here, we test whether global gene expression profiling can distinguish intermediate-risk tumors into high-risk and low-risk subgroups.

Experimental Design: Tumor specimens were obtained from 75 intermediate-risk endometrial cancer patients, 13 who had recurred and 62 who had not recurred with a median follow-up of 24 months. Gene expression profiles were obtained using the Affymetrix U133A GeneChip oligonucleotide microarray. The genes most associated with risk of recurrence were used to create a risk score using a leave-one-out cross-validation method and the univariate Cox proportional hazards regression model. Time to recurrence curves for the high-risk and low-risk subgroups were estimated using the Kaplan-Meier method, and the difference in time to recurrence between these two subgroups was tested using the log-rank test.

Results: There was a significant difference in time to recurrence between high-risk and low-risk patients using risk scores as defined above (P = 0.04). The estimated hazard ratio (95% confidence interval) was 3.07 (1.00-9.43).

Conclusions: Patients with intermediate-risk endometrial cancers identified as high-risk for recurrence according to a gene expression–based risk score have a significantly increased risk for recurrence compared with those classified as low risk. These findings suggest that gene expression profiling can potentially contribute to the clinical classification and management of intermediate-risk endometrial cancers.

Key Words: uterine cancer • gynecologic cancer • microarray • prognosis

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