Expression of Aurora A (but not Aurora B) is predictive of survival in breast cancer

Abstract

Purpose: The cell cycle mediators Aurora A and B are targets of drugs currently in clinical development. As with other targeted therapies in breast cancer, response to therapy might be associated with target expression in tumors. We therefore assessed expression of Aurora A and B in breast tumors and studied associations with clinical/pathologic variables.

Experimental design: Tissue microarrays containing primary specimens from 638 patients with 15-year follow-up were employed to assess expression of Aurora A and B using our automated quantitative analysis method; we used cytokeratin to define pixels as breast cancer (tumor mask) within the array spot and measured Aurora A and B expression within the mask using Cy5-conjugated antibodies.

Results: Aurora A and B expression was variable in primary breast tumors. High Aurora A expression was strongly associated with decreased survival (P = 0.0005). On multivariable analysis, it remained an independent prognostic marker. High Aurora A expression was associated with high nuclear grade and high HER-2/neu and progesterone receptor expression. Aurora B expression was not associated with survival.

Conclusions: Aurora A expression defines a population of patients with decreased survival, whereas Aurora B expression does not, suggesting that Aurora A might be the preferred drug target in breast cancer. Aurora A expression in early-stage breast cancer may identify a subset of patients requiring more aggressive or pathway-targeted treatment. Prospective studies are needed to confirm the prognostic role of Aurora A as well as the predictive role of Aurora A expression in patients treated with Aurora A inhibitors.

Conflict of interest statement

Disclosure of Potential Conflicts of Interest

R.L. Camp and David L. Rimm are founders stockholders and consultants of HistoRx, a private corporation to which Yale University has given exclusive rights to produce and distribute software and technologies embedded in AQUA. Yale University retains patent rights for the AQUA technology. The other authors declare that they have no competing interests.

Figures

Fig. 1

Western blots of a panel of breast cancer cell lines probed for expression of Aurora A and B.

Fig. 2

Immunoflourescent staining of Aurora A and B: predominantly cytoplasmic Aurora A (top) and nuclear Aurora B (bottom) staining in a breast cancer histospot using cytokeratin to the define tumor mask, 4′,6-diamidino-2-phenylindole to define the nuclear compartment, and Cy5 to define the target (Aurora A and B). Images on right panels represent higher magnifications of the histospots shown on the left.

Fig. 3

Kaplan-Meier survival curves for Aurora A and B AQUA scores divided by quartiles for the entire cohort of patients (A), node-negative patients (B), and node-positive patients (C).1, first quartile; 2, second quartile; 3, third quartile; 4, fourth quartile.

Fig. 4

A, actual survival as a function of predicted survival probabilities evaluated in a cross-validation approach. The curves shown correspond to three multivariate Cox models: (a) a model with four binary covariates, nodal status, age (>50 or ≥50), nuclear grade (1 versus 2-3), and tumor size (<2 or ≥2 cm); (b) a model with the above four covariates and ER, PR, and HER-2/neu; and (c) a model containing the continuous Aurora A scores and all the covariates in model b. The quality of each model is detected visually in a manner similar to Q-Q plots and is estimated by similarity (correlation) or dissimilarity (root mean square of residuals) between the curve and the optimal dashed (y = x) line. The curve involving Aurora A has the highest correlation and lowest root mean square of residuals with respect to the optimal dashed (y = x) line. B, box plots of actual survival as a function of predicted survival probabilities evaluated using a bootstrap procedure applied to the cross-validation approach of A. Gray and black box plots, bootstrap results for models b and c, respectively. The bins shown on the X axis are associated with the low survival probability range of [0.0-0.2]. These bins correspond to the first 20 bins of A. The figure shows the superiority of model c over model b in this range, as the actual survival probability (black squares) is contained within each of the interquartile ranges of model c (black boxes) but underestimated by model b (gray boxes).