Biomarkers Predicting Endometrial Cancer Stage: Identifying Patients Benefitting Most from Surgical Staging
S Westin, P Schlumbrecht, D Urbauer, D Loose, R Broaddus. M.D. Anderson Cancer Center, Houston, TX; U.T.-Houston Medical School, Houston, TX
Background: On-going controversy exists regarding the surgical management of endometrial cancer patients. Identification of those who would benefit most from complete surgical staging is unresolved. Many patients with endometrial cancer are poor candidates for extended surgeries due to obesity, hypertension, and diabetes. Intra-operative frozen section is not universally available and is not always reliable, as up-grading and up-staging are relatively common upon pathological analysis of the final hysterectomy specimen. The goal of our study is to determine if a panel of molecular markers can potentially assist in the decision to perform complete surgical staging on women diagnosed with endometrial cancer. Given the relationship between estrogen exposure and endometrial cancer, especially low grade endometrial cancer, we hypothesized that such a biomarker panel will provide a clinically useful biomarker score to assist in the decision to perform complete surgical staging on women diagnosed with endometrial cancer.
Design: Microarray was performed in baseline and post-treatment endometrial biopsies from women taking estrogen-based HRT to identify genes regulated by estrogen. The expression six genes most strongly induced by estrogen (RALDH2, sFRP1, sFRP4, EIG121, IGF-I, and IGF-IR) were then quantified by qRT-PCR in 56 endometrioid-type endometrial carcinomas. Expression data was compared to clinico-pathologic characteristics, and an unsupervised cluster analysis was performed. Time to recurrence by cluster was analyzed using the Kaplan-Meier method. A receiver operating characteristic (ROC) curve was generated to determine the clinical utility of the panel to predict endometrial cancer stage.
Results: Unsupervised cluster analysis revealed two distinct groups based on estrogen-regulated gene expression. The low gene expression cluster had a recurrence rate 4.35 times higher than that of the high expression cluster. ROC analysis allowed for the prediction of endometrial cancer stage Ic or higher with a false negative rate of only 4.5% based on level of gene expression.
Conclusions: This biomarker panel was highly accurate in stratifying endometrial cancer patients into low risk (stage Ia or Ib) vs. high risk (stage Ic or higher) groups. The panel has a lower false negative rate than that reported in the literature for frozen section. The panel may therefore help to better identify the patients who would most benefit from extensive endometrial cancer staging.
Tuesday, March 10, 2009 9:00 AM
Platform Session: Section D, Tuesday Morning