Abstract
Abstract Purpose: The feasibility of Quantitative Dot Blot (QDB) method for absolute quantification of diagnostic biomarkers was investigated here using diagnostic antibodies for biomarkers in breast cancer tissues, including 4B5 and EP3 for Her2, MIB1 for Ki67. SP2 for Estrogen Receptor and SP1 for progesterone receptor (PR) in more than 300 FFPE specimens. The specificity and accuracy of this method, and the inter-relationship among biomarkers were explored by the absolute expression levels of these biomarkers. Methods: FFPE specimens of 332 breast cancer patients were provided by local hospital, tissue slices of 2X15 um was de-paraffined and total protein was extracted for QDB analysis, with each sample measured in triplicate in three indepedent experiments. Purified protein standards were included to convert the measurement into absolute levels. IHC and FISH results from local hospital were used to validate the sensitivity and specificity of QDB method. Results: The results show high consistency with intra-cv less than 7% and inter-cv less than 14%. With Her2, 99.5% concordance was achieved with IHC method, and 92 to 94% concordance with FISH analysis. Both Her2 level and Ki67 levels were significantly increased in patients at grade III based on Nottingham histologic scores. Conclusion: The QDB method was used here to achieve digitalization of biomarkersl in breast cancer tissue with existing diagnostic antibodies for IHC analysis. The method is simple, objective, consistent, comprehensive and suitable for high throughput analysis. We expect this method to be extended to other diagnostic IHCs with existing diagnostic antibodies, and the easy adoption of this method in clinical practice should have instant impact on pathological practice. Citation Format: Zhang J, Zhang W, Yu G, Tang F, Lv J. Digitalizing immunohistochemistry analysis (IHC) with quantitative dot blot analysis (QDB) by absolute quantification of biomarkers in FFPE specimens [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr P4-02-14.
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