Biochemistry & Molecular Biology
Glutamine Synthetase (GLUL) and Glutaminase GLS Immunohistochemistry in Breast Cancer in Tissue Microarrays with Quantitative Image Analysis
Document Type
Poster Presentation
Location
Indianapolis, IN
Start Date
13-4-2018 2:30 PM
End Date
13-4-2018 4:00 PM
Sponsor
George Sandusky (Indiana University-Purdue University Indianapolis)
Description
Today, breast cancer is one of the most common cancer in women. Approximately 1 out of 8 women in the United States will develop invasive breast cancer over the course of their lifetime. Breast cancer has a greater potential of being cured if diagnosed in earlier stages. New biomarkers are needed to predict patient outcomes/survival and which treatments are selected for the patient’s disease. New tailored treatments based on biomarker assessment by immunohistochemistry are commonly used in translational research. Tissue microarrays (TMAs) are being used for immunohistochemistry and allow for analysis of multiple patients at once. In this study 6 TMAs containing approximately 100 cores on each slide were stained with the glutamine synthetase and glutaminase (GLUL and GLS) antibodies. Immunostainings with the antibodies (DAKO) were performed using the DAKO-flex immunostaining platform system. The whole TMA slides were digitally imaged using the Aperio Digital Imaging System. The created SVS digital images were quantified using the Aperio positive pixel algorithm (TMALab) image analysis software and the other was QuPath.
Comparison of the two software methodologies were similar. Aperio calculated a 97% positivity for GLUL and 93% for GLS. QuPath calculated a 93% for GLUL and 92% for GLS. The correlation coefficient was 0.7669 for the GLS antibody and 0.7788 for the GLUL antibody when comparing positivity of the two software. In conclusion, both image analysis software were consist with both clinical antibodies.
Glutamine Synthetase (GLUL) and Glutaminase GLS Immunohistochemistry in Breast Cancer in Tissue Microarrays with Quantitative Image Analysis
Indianapolis, IN
Today, breast cancer is one of the most common cancer in women. Approximately 1 out of 8 women in the United States will develop invasive breast cancer over the course of their lifetime. Breast cancer has a greater potential of being cured if diagnosed in earlier stages. New biomarkers are needed to predict patient outcomes/survival and which treatments are selected for the patient’s disease. New tailored treatments based on biomarker assessment by immunohistochemistry are commonly used in translational research. Tissue microarrays (TMAs) are being used for immunohistochemistry and allow for analysis of multiple patients at once. In this study 6 TMAs containing approximately 100 cores on each slide were stained with the glutamine synthetase and glutaminase (GLUL and GLS) antibodies. Immunostainings with the antibodies (DAKO) were performed using the DAKO-flex immunostaining platform system. The whole TMA slides were digitally imaged using the Aperio Digital Imaging System. The created SVS digital images were quantified using the Aperio positive pixel algorithm (TMALab) image analysis software and the other was QuPath.
Comparison of the two software methodologies were similar. Aperio calculated a 97% positivity for GLUL and 93% for GLS. QuPath calculated a 93% for GLUL and 92% for GLS. The correlation coefficient was 0.7669 for the GLS antibody and 0.7788 for the GLUL antibody when comparing positivity of the two software. In conclusion, both image analysis software were consist with both clinical antibodies.