Biology subjects

Schmitz, F.

Publications and source records attributed to Schmitz, F..

3 recordsLinked to original sources

bioRxiv2019

Multiple Myeloma DREAM Challenge Reveals Epigenetic Regulator PHF19 As Marker of Aggressive Disease

While the past decade has seen meaningful improvements in clinical outcomes for multiple myeloma patients, a subset of patients do not benefit from current therapeutics for unclear reasons. Many gene expression-based models of risk have been developed, but each model uses a different combination of genes and often involve assaying many genes making them difficult to implement. We organized the Multiple Myeloma DREAM Challenge, a crowdsourced effort to develop models of rapid progression in newly diagnosed myeloma patients and to benchmark these against previously published models. This effort lead to more robust predictors and found that incorporating specific demographic and clinical features improved gene expression-based models of high risk. Furthermore, post challenge analysis identified a novel expression-based risk marker and histone modifier, PHF19, which featured prominently in several independent models. Lastly, we show that a simple four feature predictor composed of age, International Staging System stage (ISS), and expression of PHF19 and MMSET performs similarly to more complex models with many more gene expression features included.\n\nKey pointsO_LIMost comprehensive and unbiased assessment of prognostic biomarkers in MM resulting in a robust and parsimonious model.\nC_LIO_LIIdentification of PHF19 as the expression based biomarker most strongly associated with rapid progression in MM patients.\nC_LI

cancer biology↗

bioRxiv2019

ADAPTS: Automated Deconvolution Augmentation of Profiles for Tissue Specific cells

Immune cell infiltration of tumors can be an important component for determining patient outcomes, e.g. by inferring immune cell presence by deconvolving gene expression data drawn from a heterogenous mix of cell types. One particularly powerful family of deconvolution techniques uses signature matrices of genes that uniquely identify each cell type as determined from cell type purified gene expression data. Many methods of this type have been recently published, often including new signature matrices appropriate for a single purpose, such as investigating a specific type of tumor. The package ADAPTS helps users make the most of this expanding knowledge base by introducing a framework for cell type deconvolution. ADAPTS implements modular tools for customizing signature matrices for new tissue types by adding custom cell types or building new matrices de novo, including from single cell RNAseq data. It includes a common interface to several popular deconvolution algorithms that use a signature matrix to estimate the proportion of cell types present in heterogenous samples. ADAPTS also implements a novel method for clustering cell types into groups that are hard to distinguish by deconvolution and then re-splitting those clusters using hierarchical deconvolution. We demonstrate that the techniques implemented in ADAPTS improve the ability to reconstruct the cell types present in a single cell RNAseq data set in a blind predictive analysis. ADAPTS is currently available for use in R on CRAN and GitHub.

biophysics↗

bioRxiv2019

Phospho-tuning immunity through Denisovan, modern human, and mouse TNFAIP3 gene variants

Resisting or tolerating microbes are alternative strategies to survive infection, but little is known about the evolutionary mechanisms controlling this balance. Here, genomic analyses of anatomically modern humans, extinct Denisovan hominins, and mice revealed a series of missense variants in the immune response inhibitor A20 (encoded by TNFAIP3), substituting non-catalytic residues of the ubiquitin protease domain to diminish I{kappa}B-dependent phosphorylation and activation of A20. Two A20 variants with partial phosphorylation deficits appeared beneficial: one originating in Denisovans and introgressed in modern humans throughout Oceania, and another in a mouse strain resistant to Coxsackievirus. By contrast, a variant with 95% loss of phosphorylation caused spontaneous inflammatory disease in humans and mice. Analysis of the partial phosphorylation variant in mice revealed diminished tolerance of bacterial lipopolysaccharide or to poxvirus inoculation as trade-offs for enhanced immunity.\n\nOne Sentence SummaryModern and ancient variants reveal a genetically tunable element for balancing immunity and microbial tolerance.

immunology↗