Matrisome gene-based subclassification of patients with liver fibrosis identifies clinical and molecular heterogeneities
- 27 April 2023
- journal article
- research article
- Published by Wolters Kluwer Health in Hepatology
- Vol. 78 (4) , 1118-1132
Abstract
Background & Aims: Excessive deposition and crosslinking of extracellular matrix increases liver density and stiffness, promotes fibrogenesis, and increases resistance to fibrinolysis. An emerging therapeutic opportunity in liver fibrosis is to target the composition of the extracellular matrix or block pathogenic communication with surrounding cells. However, the type and extent of extracellular changes triggering liver fibrosis depend on the underlying etiology. Our aim was to unveil matrisome genes not dependent on etiology, which are clinically relevant to liver fibrosis. Approach & Results: We used transcriptomic profiles from liver fibrosis cases of different etiologies to identify and validate liver fibrosis-specific matrisome genes (LFMGs) and their clinical and biological relevance. Dysregulation patterns and cellular landscapes of LFMGs were further explored in mouse models of liver fibrosis progression and regression by bulk and single-cell RNA sequencing. We identified 35 LFMGs, independent of etiology, representing an LFMG signature defining liver fibrosis. Expression of the LFMG signature depended on histological severity and was reduced in regressive livers. Patients with liver fibrosis, even with identical pathological scores, could be subclassified into LFMGLow and LFMGHigh, with distinguishable clinical, cellular, and molecular features. Single-cell RNA sequencing revealed that microfibrillar-associated protein 4+ activated HSC increased in LFMGHigh patients and were primarily responsible for the LFMG signature expression and dysregulation. Conclusions: The microfibrillar-associated protein 4+ -activated HSC-derived LFMG signature classifies patients with liver fibrosis with distinct clinical and biological characteristics. Our findings unveil hidden information from liver biopsies undetectable using traditional histologic assessments.Keywords
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