Automated quantitative analysis (AQUA) of in situ protein expression, antibody concentration, and prognosis

Abstract

Background: Disparate results in the immunohistochemistry literature regarding the relationship between biomarker expression and patient outcome decrease the credibility of tissue biomarker studies. We investigated whether some of these disparities result from subjective optimization of antibody concentration.

Methods: We used the automated quantitative analysis (AQUA) system and various concentrations of antibodies against HER2 (1 : 500 to 1 : 8000 dilutions), p53 (1 : 50 to 1 : 800 dilutions), and estrogen receptor (ER; 1 : 100 and 1 : 1000 dilutions) to assess expression of HER2 and p53 in a tissue microarray containing specimens from 250 breast cancer patients with long-term survival data available. HER2 expression in the tissue microarray was also assessed by conventional immunohistochemistry. Relative risk (RR) of disease-specific mortality was assessed for every cutpoint with the X-tile program. Cumulative disease-specific survival was assessed by the Kaplan-Meier method. All statistical tests were two-sided.

Results: For HER2 and p53 and an optimal cutpoint, when a high antibody concentration (i.e., 1 : 500 dilution) was used with the AQUA system, low expression was associated with poorer survival than high expression; however, when a low antibody concentration (i.e., 1 : 8000 dilution) was used, high expression was associated with poorer survival. For example, for a 1 : 8000 dilution of HER2 antibody and high expression defined as the top 15% of HER2 expression, high HER2 expression was associated with increased disease-specific mortality (RR = 1.98, 95% confidence interval [CI] = 1.21 to 3.23; P = .007), compared with low expression. However, for a 1 : 500 dilution of HER2 antibody and high expression defined as the top 85% of HER2 expression, high HER2 expression was associated with decreased disease-specific mortality (RR = 0.47, 95% CI = 0.29 to 0.76; P = .002), compared with low HER2 expression.

Conclusions: Biomarker antibody concentration appears to dramatically affect the apparent relationship between biomarker expression and outcome.