Concordance between Immunohistochemistry and Microarray Gene Expression Profiling for Estrogen Receptor, Progesterone Receptor, and HER2 Receptor Statuses in Breast Cancer Patients in Lebanon

Introduction. Accurate evaluation of estrogen and progesterone receptors and HER2 is critical when diagnosing invasive breast cancer for optimal treatment. The current evaluation method is via immunohistochemistry (IHC). In this paper, we compared results of ER, PR, and HER2 from microarray gene expression to IHC in 81 fresh breast cancer specimens. Methods. Gene expression profiling was performed using the GeneChip Human Genome U133 Plus 2.0 arrays (Affymetrix Inc). Immunohistochemical staining for estrogen receptor, progesterone receptor, and HER2 status was performed using standard methods at a CAP-accredited pathology laboratory. Concordance rates, agreement measures, and kappa scores were calculated for both methods. Results. For ER, Kappa score was 0.918 (95% CI, 0.77.3–1.000) and concordance rate was 97.5% (95% CI, 91.4%–99.7%). For PR, Kappa score was 0.652 (95% CI, 0.405–0.849) and concordance rate was 86.4% (95% CI, 77%–93%). For HER2, Kappa score was 0.709 (95% CI, 0.428–0.916) and concordance rate was 97.5% (95% CI, 91.4%–99.7%). Conclusion. Our results are in line with the available evidence with the concordance rate being the lowest for the progesterone receptor. In general, microarray gene expression and IHC proved to have high concordance rates. Several factors can increase the discordance rate such as differences in sample processing.

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Discovery of prostate cancer biomarkers by microarray gene expression profiling

Expert Review of Molecular Diagnostics ◽

10.1586/erm.09.74 ◽

2010 ◽

Vol 10 (1) ◽

pp. 49-64 ◽

Cited By ~ 49

Author(s):

Karina Dalsgaard Sørensen ◽

Torben Falck Ørntoft

Keyword(s):

Gene Expression ◽

Prostate Cancer ◽

Gene Expression Profiling ◽

Expression Profiling ◽

Cancer Biomarkers ◽

Microarray Gene Expression ◽

Microarray Gene

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Study of Basic Concepts on the Development of Protein Microarray - Gene Expression Profiling

Handbook of Research on Computational Intelligence Applications in Bioinformatics - Advances in Bioinformatics and Biomedical Engineering ◽

10.4018/978-1-5225-0427-6.ch013 ◽

2016 ◽

pp. 263-295

Author(s):

P. Sivashanmugam ◽

Arun C. ◽

Selvakumar P.

Keyword(s):

Gene Expression ◽

Gene Expression Profiling ◽

Expression Profiling ◽

Protein Microarray ◽

Microarray Technology ◽

Microarray Gene Expression ◽

High Throughput Technology ◽

Multiple Cell ◽

Stressed Cell ◽

Microarray Gene

The physical and biological activity of any organisms is mainly depended on the genetic information which stored in DNA. A process at which a gene gives rise to a phenotype is called as gene expression. Analysis of gene expression can be used to interpret the changes that occur at biological level of a stressed cell or tissue. Hybridization technology helps to study the gene expression of multiple cell at a same time. Among them microarray technology is a high- throughput technology to study the gene expression at transcription level (DNA) or translation level (Protein). Analysis the protein only can predict the accurate changes that happens in a tissue, when they are infected by a disease causing organisms. Protein microarray mainly used to identify the interactions and activities of proteins with other molecules, and to determine their function for a system at normal state and stressed state. The scope of this chapter is to outline a detail description on the fabrication, types, data analysis, and application of protein microarray technology towards gene expression profiling.

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