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Activity Number: 68 - Personalized/Precision Medicine I
Type: Contributed
Date/Time: Sunday, July 29, 2018 : 4:00 PM to 5:50 PM
Sponsor: Biometrics Section
Abstract #330230 Presentation
Title: Spatial Statistics Approach to Develop Novel Protein Cancer Biomarkers
Author(s): Inna Chervoneva*
Companies: Thomas Jefferson University
Keywords: Cancer biomarkers; Marked point process; Spatial index; Conditional expectation and variance; Mark-point interaction; Quantitative immunohistochemistry

Quantitative Immunofluorescence (QIF) is used for immunohistochemistry quantification of proteins that serve as cancer biomarkers. Traditionally, only the mean signal intensity (MSI) of the protein expression across cancer cells is considered for developing protein biomarkers. We propose a new approach for developing biomarkers using the information on spatial distribution of cellular signal intensity (CSI) of protein expression in cancer cell population. We view the protein QIF expression levels as marks in marked point process of cancer cells in the tumor tissue and develop spatial index predictors of clinical outcomes based on nonparametric spatial statistics describing the relationship between marks and points. The utility of new spatial index protein biomarkers is investigated and compared to the standard MSI predictors using the protein expressions in tissue microarrays (TMAs) incorporating tumor tissues from 2,000+ breast cancer patients. The new approach provides new insight into standard biomarkers and identifies novel biomarkers that do not have a prognostic value if only the mean signal intensity is considered.

Authors who are presenting talks have a * after their name.

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