Computational approach to identifying universal macrophage biomarker

Abstract

Abstract Macrophages are a type of white blood cell, of the immune system, that engulfs and digests cellular debris, cancer cells, and anything else that does not have the type of proteins specific to healthy body cells on its surface. Understanding gene expression dynamics in macrophages are crucial for studying human diseases. Recent advances in high-throughput technologies have enabled the collection of immense amounts of biological data. A reliable marker of macrophage is essential to study their function. Traditional approaches use a number of markers that may have tissue specific expression patterns. To identify universal biomarker of macrophage, we used a previously published computational approach called BECC (Boolean Equivalent Correlated Clusters) that was originally used to identify universal cell cycle genes. We performed BECC analysis on a seed gene CD14, a known macrophage marker. FCER1G and TYROBP were among the top candidates which were validated as strong candidates for universal biomarkers for macrophages in human and mouse tissues. To our knowledge, such a finding is first of its kind.