Abstract

INTRODUCTION AND OBJECTIVES: Genes of androgen and estrogen signaling and stem cell (SC)-like cells have crucial roles in prostate cancer (PC). This study aimed to predict clinical failure (CF) by estimating these PC-related genes. METHODS: We developed models to predict CF using biopsy samples from a training set of 46 and independent validation set of 30 patients with bony metastatic PC. Cancerous and stromal tissues were separately collected by laser-captured microdissection. The association between mRNA expression of the following genes and CF was analyzed: androgen receptor (AR) and its related genes (APP, FOX family, TRIM 36, Oct1, and ACSL 3), stem cell (SC)-like molecules (Klf4, c-Myc, Oct 3/4, and Sox2), estrogen receptor (ER), Her2, PSA, and CRP. RESULTS: Logistic analyses to predict PSA recurrence showed an area under the curve (AUC) of 1.0 in both sets for Sox2, Her2, and CRP expression in cancer cells; AR and ERa expression in stromal cells; and clinical parameters. We identified 10 prognostic factors for cancer-specific survival (CSS): Oct1, TRIM36, Sox2, and cMyc expression in cancer cells; AR, Klf4, and ERf ? expression in stromal cells; and PSA, Gleason score, and extent of disease. On the basis of these factors, patients were divided into favorable-, intermediate-, and poor-risk groups according to the number of factors present. Five-year CSS rates for the 3 groups were 90%, 32%, and 12% in training set and 75%, 48%, and 0% in validation set, respectively (Figure 1). CONCLUSIONS: Expression levels of androgen and estrogen signaling components and SC markers are powerful prognostic tools. Source of Funding: This work was supported by Grants of the Cell Innovation Program (S. I.) from the MEXT, Japan; by Grants (T.F., S.T., and S. I.) from the JSPS, Japan; by Grants-in-Aid (S. I.) from the MHLW, Japan; by the Advanced Research for Medical Products Mining Program in Health Sciences (S. I.), NIBIO, Japan.

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