April 23, 2020 Webinar
Quantification of spatial tumor heterogeneity in immunohistochemistry staining images
Inna Chervoneva, PhD
Abstract:
Quantitative Immunofluorescence (QIF) is used for immunohistochemistry (IHC) quantification of proteins that serve as cancer biomarkers. Advanced image analysis systems for pathology allow capturing expression levels in each individual cell or subcellular compartment. However, only the Mean Signal Intensity (MSI) within the cancer tissue region of interest is usually considered as a biomarker, completely ignoring the known issue of tumor heterogeneity. We propose using IHC image-derived information on spatial distribution of cellular signal intensity (CSI) of protein expression in cancer cell population to quantify tumor heterogeneity of CSI levels. A simulation study is conducted to demonstrate that the proposed methodology provides objective means to quantify cell-to-cell heterogeneity in protein expressions and discriminate between different patterns of heterogeneity. The prognostic utility of the new spatial heterogeneity metric is investigated and compared to the standard MSI biomarkers using the cohort of ∼1,800 breast cancer patients. This is a joint work with Amy R. Peck, Misung Yi, Boris Freydin and Hallgeir Rui.
Short Bio:
Dr Inna Chervoneva is a Professor at the Division of Biostatistics, Department of Pharmacology and Experimental Therapeutics, Thomas Jefferson University. Her research program is centered on developing statistical methods for modern technologies employed in clinical studies and basic science. Dr. Chervoneva's current research interests focus on quantification of cancer biomarkers using immunofluorescence-based immunohistochemistry, quantitative RT-PCR, and Next-Generation Sequencing as well as on microscopy image analysis using spatial statistics approaches.