Development and Validation of a Nine Gene Set Predicting Risk of Recurrence and Survival of Human Breast Carcinoma Patients.

Abstract

Abstract Background: The Human Genome Project has provided opportunities to develop precise tests for diagnostics, therapy selection and monitoring. From analyses of various published microarray studies, 32 candidate genes were identified, whose expression appears related to clinical outcome of breast cancer (Andres et al., Cancer Res: 69(Suppl): 403s-404s, 2009). Expression of these genes was validated by qPCR as candidates for development of a prognostic test predicting risk of breast cancer recurrence regardless of estrogen and progestin receptor status.Materials and Methods: RNA was isolated from tissue sections of 126 de-identified frozen biopsies of invasive ductal carcinoma using the RNeasy® Mini kit (Qiagen) and analyzed for quality and quantity using the Bioanalyzer (Agilent). cDNA for qPCR measurements was prepared in Tris-HCl buffer containing KCl, MgCl2, DTT (Invitrogen), dNTPs (Invitrogen), RNasin® (Promega) and Superscript® RT III (Invitrogen). qPCR reactions were performed using Power Sybr® Green PCR Master Mix (Applied Biosystems), forward/reverse primers and cDNA obtained from the reverse transcription reaction. Relative gene expression was calculated with the ddCt method, using β-actin as the reference gene and Universal Human Reference RNA (Stratagene) as a calibrator. qPCR reactions were performed in triplicate with duplicate wells in each 384-well plate, to ensure reproducibility.Results: Gene expression results from qPCR were correlated with disease-free and overall survival outcome data stored in our extensive IRB-approved database. Expression of TBC1D9, RABEP1, SLC39A6, FUT8, and PTP4A2 correlated with disease-free survival using univariate Cox proportional hazards analyses (P < 0.05). Expression of RABEP1, SLC39A6, FUT8, and PTP4A2 appeared to be related to overall survival using univariate analysis (P < 0.05). Multivariate analyses were performed with backwards stepwise selection to predict disease-free survival using expression levels of ESR1, GABRP, RABEP1, SLC39A6, TCEAL1, ATAD2, PTP4A2, LRBA, and SLC43A3. ROC curves were composed to illustrate the sensitivity and specificity of the model for disease-free and overall survival with areas under the curves equal to 0.78 and 0.76, respectively. Consideration of additional parameters, e.g., estrogen and progestin receptor status, menopausal status and lymph node involvement, did not improve the model.Conclusion: A molecular signature was identified consisting of expression profiles of nine of the 32 candidate genes, in a multivariate Cox proportional hazards model of breast cancer recurrence. The model also predicted overall survival. Collectively, results suggest that these nine genes may form the basis for developing a clinical laboratory test to predict clinical outcome of breast cancer. Supported in part by grants from Phi Beta Psi Charity Trust and the University of Louisville's Executive Vice President for Research. SAA is a recipient of IPIBS Graduate Fellowship. Citation Information: Cancer Res 2009;69(24 Suppl):Abstract nr 6137.