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Patient Outcomes Linked to Biomarker Levels by Quantitative Technology

Patient Outcomes Linked to Biomarker Levels by Quantitative Technology

Patient Outcomes Linked to Biomarker Levels by Quantitative Technology

Patient Outcomes Linked to Biomarker Levels by Quantitative Technology

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According to a study published in the Journal of the National Cancer Institute, there are inherent limitations in the current pathology methodology used in protein biomarker studies.

Use of Automated Quantitative Analysis (AQUA™) technology from HistoRx, Inc. elucidated that the concentration of antibodies used as tags to identify biomarkers of interest in patient tissue dramatically affects the apparent relationship between the biomarker’s expression and clinical outcome. 

These findings are particularly relevant to translational medicine, as the relationship between protein expression and disease gains an increasing role in the way physicians treat patients and individualize therapeutic regimes.

"Variations in expression levels and patient response or outcome have been previously highlighted in the literature, but unfortunately researchers have had no effective method to standardize their biomarker detection techniques," said David L. Rimm, M.D., Ph.D., associate professor of pathology at Yale University School of Medicine, and co-author of the study.

"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."

"This study challenges the way pathologists have viewed immunohistochemistry, and sheds light on the fact that studies of biomarker expression are in need of further development and analysis."

HistoRx claims that, by providing an increased level of quantization, standardization, and special information not afforded by other technologies, HistoRx’s AQUA technology can improve current pathology methods and practices.

The system is designed to measure and localize disease-specific variations in protein expression within tissue automatically, with a high level of precision.

The multi-tissue proteomic analysis system combines fluorescence-based imaging with automated microscopy and high-throughput tissue microarray technologies.

The study was published in the December 21st issue of the Journal of the National Cancer Institute accompanied by an editorial by Donald Earl Henson, M.D., of the George Washington University Cancer Institute, entitled "Back to the Drawing Board on Immunohistochemistry and Predictive Factors."

In the editorial, Dr. Henson noted that, "biomarkers may have the power to provide diagnostic, therapeutic, and prognostic information for personalized medicine."

"However, immunohistochemistry, a popular technique for evaluating biomarker expression, may contain procedural flaws that jeopardize its promise."

"Previous reports have described changes in the relation between protein expression, detection technique, and outcome."

In follow up to the editorial, Dennis C. Sgroi, M.D., a leading pathologist with the Massachusetts General Hospital noted, "AQUA has proven to be a very effective tool in determining the flaws and inconsistencies associated with immunohistochemistry."

"These findings warrant review by pathologists in questioning the validity of current practices and before the data from predictive biomarker studies is formally integrated into practice and patient treatment."

"The ability of AQUA to accurately measure protein expression and localization in diseased tissue with such high precision may enable pathologists to overcome many of the challenges associated with linking biomarker expression and patient outcomes we’ve seen in the literature to date."

This study evaluated conventional immunohistochemistry techniques as compared with the AQUA system from HistoRx, developed to assess biomarker expression in tissue sections.

Researchers assessed the expression of HER2, p53, and estrogen receptor (ER), common breast cancer biomarkers, in a tissue microarray containing specimens from 250 breast cancer patients with long-term survival data available.

Use of the AQUA system elucidated that the use of high antibody concentration showed a decreased survival rate if the patient’s HER2 expression levels were low and that if a low concentration was used, a high patient HER2 expression was associated with decreased survival. 

Antibodies are used to in conventional immunohistochemistry to probe or tag biomarkers of interest in tissue samples.

Results for p53 were similar to those of HER2, and only ER expression was always associated with increased survival, regardless of antibody concentration or expression level.

These results suggest that conventional immunohistochemistry did not detect the relationship between antibody concentration/dilution and outcome as detected with the AQUA-based assay, and also suggest that the antibody concentration arbitrarily chosen by the pathologist may not be adequate to cover the expression range of the biomarker of interest.

The apparent reversal of the relationship between expression and survival rate occurs when there is a non-linear relationship and when they follow a U-shaped curve. ER was always predicted correctly due to its linear relationship.