Sparse feature selection identifies H2A.Z as a novel, pattern-specific biomarker for asymmetrically self-renewing distributed stem cells

• There is a long standing unmet need for biomarkers for distributed stem cells (DSCs).
• We used engineered cells that undergo deterministic asymmetric self-renewal in response to varied triggers.
• Analysis of gene expression data from multiple experiments used unconventional, sparse gene selection.
• Identified H2A.Z as a novel, pattern-specific biomarker for asymmetrically self-renewing DSCs.
• The DSC specificity of this biomarker was validated in subsequent experiments.

There is a long-standing unmet clinical need for biomarkers with high specificity for distributed stem cells (DSCs) in tissues, or for use in diagnostic and therapeutic cell preparations (e.g., bone marrow). Although DSCs are essential for tissue maintenance and repair, accurate determination of their numbers for medical applications has been problematic. Previous searches for biomarkers expressed specifically in DSCs were hampered by difficulty obtaining pure DSCs and by the challenges in mining complex molecular expression data. To identify such useful and specific DSC biomarkers, we combined a novel sparse feature selection method with combinatorial molecular expression data focused on asymmetric self-renewal, a conspicuous property of DSCs. The analysis identified reduced expression of the histone H2A variant H2A.Z as a superior molecular discriminator for DSC asymmetric self-renewal. Subsequent molecular expression studies showed H2A.Z to be a novel “pattern-specific biomarker” for asymmetrically self-renewing cells, with sufficient specificity to count asymmetrically self-renewing DSCs in vitro and potentially in situ.