Biology subjects

Raby, B.

Publications and source records attributed to Raby, B..

4 recordsLinked to original sources

bioRxiv2025

Single cell transcriptomics in a treatment-segregated cohort exposes a STAT3-regulated therapeutic gap in idiopathic pulmonary fibrosis

Idiopathic pulmonary fibrosis (IPF) is a progressive fibrotic pulmonary disease of unknown etiology. Since approved IPF drugs only slow disease progression, novel therapeutics are required that improve clinical outcomes. Here we report a single cell lung RNA-Seq and gene regulatory network analysis of the largest IPF cohort assembled to date. Segregating this cohort based on status of treatment with approved first-generation IPF antifibrotics (untreated, nintedanib- and pirfenidone-treated), we describe for the first time the transcriptional landscape of untreated IPF across 40 lung cell types, and the elements of this program that are impacted by these antifibrotics. On average, nearly 60% of the untreated IPF-dysregulated transcriptome is refractory to treatment with these drugs, a transcriptional deficit we refer to as the IPF therapeutic gap. Gene regulatory network analysis indicated a dominant functional footprint for the transcription factor STAT3 in both untreated IPF and the IPF therapeutic gap. Validating our analysis in a translational precision cut lung slice platform that recapitulates IPF explants, pharmacological inhibition of STAT3 reduced the IPF therapeutic gap in numerous lung cell types. Finally, we resolved a STAT3-anchored master regulatory network comprising numerous profibrotic transcription factors in IPF alveolar fibroblasts, a critical fibrotic lineage. Our study represents a comprehensive resource for translational lung fibrosis research and introduces a strategy for drug discovery that is adaptable to human disease more broadly.

cell biology↗

bioRxiv2021

Single Cell RNA-seq and Mass Cytometry Reveals a Novel and a Targetable Population of Macrophages in Idiopathic Pulmonary Fibrosis

In this study, we leveraged a combination of single cell RNAseq, cytometry by time of flight (CyTOF), and flow cytometry to study the biology of a unique macrophage population in pulmonary fibrosis. Using the profiling data from 312,928 cells derived from 32 idiopathic pulmonary fibrosis (IPF), 29 healthy control and 18 chronic obstructive pulmonary disease (COPD) lungs, we identified an expanded population of macrophages in IPF that have a unique transcriptional profile associated with pro-fibrotic signature. These macrophages attain a hybrid transitional state between alveolar and interstitial macrophages, are enriched with biological processes of pro-fibrotic immune cells, and express novel surface markers and genes that have not been previously reported. We then applied single cell CyTOF to simultaneously measure 37 markers to precisely phenotype the uniquely expanded macrophage subset in IPF lungs. The SPADE algorithm independently identified an expanded macrophage cluster, and validated CD84 and CD36 as novel surface markers that highly label this cluster. Using a separate validation cohort, we confirmed an increase in CD84++CD36++ macrophage population in IPF compared to control and COPD lungs by flow cytometry. Further, using the signature from the IPF-specific macrophages and the LINCS drug database, we predicted small molecules that could reverse the signature of IPF-specific macrophages, and validated two molecules, CRT and Cucur, using THP-1 derived human macrophages and precision-cut lung slices (PCLS) from IPF patients. Utilizing a multi-dimensional translational approach, our work identified a novel and targetable population of macrophages found in end-stage pulmonary fibrosis. One Sentence SummarySingle cell RNAseq, CyTOF, and flow cytometry reveal the presence of an aberrant macrophage population in pulmonary fibrosis

cell biology↗

bioRxiv2019

Single Cell RNA-seq reveals ectopic and aberrant lung resident cell populations in Idiopathic Pulmonary Fibrosis

We provide a single cell atlas of Idiopathic Pulmonary Fibrosis (IPF), a fatal interstitial lung disease, focusing on resident lung cell populations. By profiling 312,928 cells from 32 IPF, 29 healthy control and 18 chronic obstructive pulmonary disease (COPD) lungs, we demonstrate that IPF is characterized by changes in discrete subpopulations of cells in the three major parenchymal compartments: the epithelium, endothelium and stroma. Among epithelial cells, we identify a novel population of IPF enriched aberrant basaloid cells that co-express basal epithelial markers, mesenchymal markers, senescence markers, developmental transcription factors and are located at the edge of myofibroblast foci in the IPF lung. Among vascular endothelial cells in the in IPF lung parenchyma we identify an expanded cell population transcriptomically identical to vascular endothelial cells normally restricted to the bronchial circulation. We confirm the presence of both populations by immunohistochemistry and independent datasets. Among stromal cells we identify fibroblasts and myofibroblasts in both control and IPF lungs and leverage manifold-based algorithms diffusion maps and diffusion pseudotime to infer the origins of the activated IPF myofibroblast. Our work provides a comprehensive catalogue of the aberrant cellular transcriptional programs in IPF, demonstrates a new framework for analyzing complex disease with scRNAseq, and provides the largest lung disease single-cell atlas to date.

genomics↗

bioRxiv2019

The periphery and the core properties explain the omnigenic model in the human interactome

Understanding the connectivity patterns of genes in a localized disease neighborhood or disease module in a molecular interaction network (interactome) is a key step toward advancing the knowledge about molecular mechanisms underlying a complex disease. In this work, we introduce a framework that detects peripheral and core regions of a disease in the human interactome. We leverage gene expression data on 104 diseases and analyze the connectivity of differentially expressed genes (quantified by a p-value < 0.05) and their topological membership in the network to distinguish between peripheral and core genes. Per definition, peripheral and core genes are topologically different and we show that they also differ biologically. Core genes are more enriched for Genome-wide association study (GWAS) and Online Mendelian Inheritance in Man (OMIM) data, whereas peripheral genes are more shared across different disease states and their overlap helps predict disease proximity in the human interactome. Based on this observation, we propose a flower model to explain the organization of genes in the human interactome, with core genes of different diseases as the petals and the peripheral genes as the (shared) stem. We show that this network model is an important step towards finding novel drug targets and improving disease classification. Overall, we were able to demonstrate how perturbations percolate through the human interactome and contribute to peripheral and core regions, an important novel feature of the omnigenic model.

systems biology↗