Patient outcomes linked to biomarker levels by quantitative technology

December 21, 2005

New Haven, Conn. - Researchers in the Department of Pathology at Yale University School of Medicine report that when using current pathology methods of biomarker detection, the concentration of antibodies used dramatically alters the apparent relationship of biomarker level to clinical outcome. The paper appears in the December issue of the Journal of the National Cancer Institute

The study, led by David L. Rimm, M.D., associate professor of pathology and member of the Yale Cancer Center, was designed to make sense of inconsistencies in traditional immunohistochemistry, a technique widely used for evaluating biomarker levels. The researchers evaluated levels of the common breast cancer biomarkers HER2, p53 and estrogen receptor (ER) to determine the importance of antibody standardization. They used a tissue microarray format containing specimens from 250 breast cancer patients with available long-term survival data.

"We found that the antibody concentration chosen by pathologists can dramatically affect and even reverse the apparent relationships between biomarker expression levels and patient outcomes," said Rimm. "This work challenges the way pathologists have viewed immunohistochemistry, and points out that biomarker expression studies need further development and analysis."

To standardize measurements, the study used the Automated Quantitative Analysis (AQUATM) technology, a system originally developed to assess biomarker expression in tissue sections. It combined fluorescence-based imaging with automated microscopy and high-throughput tissue microarray analysis technologies.

Their results with AQUATM showed that when a high antibody concentration was used in the assay, low HER2 marker levels were associated with decreased survival. However, if a low antibody concentration was used, high HER2 levels were associated with decreased survival. Results for p53 were similar to those for HER2 but, increased ER levels were associated with increased survival regardless of antibody concentration.

These results suggest that an antibody concentration arbitrarily chosen by the pathologist may not be adequate for the expression range of the biomarker being tested. The apparent reversal of the relationship between marker level and survival rate occurs when there is a non-linear relationship between the antibody concentration and its target. ER was predicted consistently due to a linear relationship.

The findings are of importance as the relationship between protein expression and disease has an increasing role in patient treatments and individualized therapies. Variations in biomarker levels and patient response or outcome have been previously highlighted in the literature, but until now researchers have had no effective method to standardize detection techniques. Creating a new quantitative level of standardization may improve current pathology methods and practices.

"Biomarkers may have the power to provide diagnostic, therapeutic, and prognostic information for personalized medicine." said Donald Earl Henson, M.D., of the George Washington University Cancer Institute, in "Back to the Drawing Board on Immunohistochemistry and Predictive Factors," an accompanying editorial. "However, immunohistochemistry, a popular technique for evaluating biomarker expression, may contain procedural flaws that jeopardize its promise."

Yale University

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