The Fibro-Immune Landscape Across Organs: A Single-Cell Comparative Study of Human Fibrotic Diseases
Guofei Deng, Yusheng Luo, Xiaorong Lin, Yuzhi Zhang, Yuqing Lin, Yuxi Pan, Yueheng Ruan, Xiaocong Mo, Shuo Fang

TL;DR
This study uses single-cell RNA sequencing to compare fibrotic tissues across four organs, revealing shared and organ-specific immune and fibroblast interactions that could guide precision therapies.
Contribution
The paper presents a cross-organ single-cell atlas of fibrotic diseases, uncovering conserved and organ-specific fibro-immune interactions and signaling pathways.
Findings
Fibroblasts dominate ECM production in liver and lung, while endothelial-derived stromal cells are key in heart and kidney.
Immune infiltration patterns vary by organ, with distinct macrophage polarization, T cell subsets, and B cell heterogeneity.
Organ-specific signaling programs include TGF-β/TNF-α in heart, NOTCH/mTOR in kidney, glycolysis/ROS in lung, and KRAS/interferon in liver.
Abstract
Fibrosis is a hallmark of the tumor microenvironment in many solid cancers, driving tumor progression, immune evasion, and treatment resistance; however, the molecular and cellular mechanisms underlying fibrogenesis—particularly stromal–immune crosstalk across organs—remain incompletely understood, compounded by organ-specific heterogeneity and a lack of reliable immune-related biomarkers. To address this, we performed an integrative single-cell RNA sequencing (scRNA-seq) analysis of fibrotic tissues from four major organs—liver, lung, heart, and kidney—alongside non-fibrotic controls, applying unsupervised clustering, trajectory inference, cell–cell communication modeling, and gene set variation analysis (GSVA) to map the fibro-immune landscape. Our analysis revealed both conserved and organ-specific features: fibroblasts were the dominant extracellular matrix (ECM)-producing cells in…
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Taxonomy
TopicsSingle-cell and spatial transcriptomics · Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis · Cancer Immunotherapy and Biomarkers
