Serologic extracellular matrix remodeling markers are related to fibrosis stage and prognosis in a phase 2b trial of simtuzumab in patients with primary sclerosing cholangitis.

BACKGROUND: Novel noninvasive predictors of disease severity and prognosis in primary sclerosing cholangitis (PSC) are needed. This study evaluated the ability of extracellular matrix remodeling markers to diagnose fibrosis stage and predict PSC-related fibrosis progression and clinical events. METHODS: Liver histology and serum markers of collagen formation (propeptide of type III collagen [Pro-C3], propeptide of type IV collagen, propeptide of type V collagen), collagen degradation (type III collagen matrix metalloproteinase degradation product and type IV collagen matrix metalloproteinase degradation product), and fibrosis (enhanced liver fibrosis [ELF] score and its components [metalloproteinase-1, type III procollagen, hyaluronic acid]) were assessed in samples from baseline to week 96 in patients with PSC enrolled in a study evaluating simtuzumab (NCT01672853). Diagnostic performance for advanced fibrosis (Ishak stages 3-6) and cirrhosis (Ishak stages 5-6) was evaluated by logistic regression and AUROC. Prognostic performance for PSC-related clinical events and fibrosis progression was assessed by AUROC and Wilcoxon rank-sum test. RESULTS: Among 234 patients, 51% had advanced fibrosis and 11% had cirrhosis at baseline. Baseline Pro-C3 and ELF score and its components provided moderate diagnostic ability for discrimination of advanced fibrosis (AUROC 0.73-0.78) and cirrhosis (AUROC 0.73-0.81). Baseline Pro-C3, ELF score, and type III procollagen provided a moderate prognosis for PSC-related clinical events (AUROC 0.70-0.71). Among patients without cirrhosis at baseline, median changes in Pro-C3 and ELF score to week 96 were higher in those with than without progression to cirrhosis (both p < 0.001). CONCLUSIONS: Pro-C3 correlated with fibrosis stage, and Pro-C3 and ELF score provided discrimination of advanced fibrosis and cirrhosis and predicted PSC-related events and fibrosis progression. The results support the clinical utility of Pro-C3 and ELF score for staging and as prognostic markers in PSC.

Cluster analysis of blood biomarkers to identify molecular patterns in pulmonary fibrosis: assessment of a multicentre, prospective, observational cohort with independent validation.

BACKGROUND: Pulmonary fibrosis results from alveolar injury, leading to extracellular matrix remodelling and impaired lung function. This study aimed to classify patients with pulmonary fibrosis according to blood biomarkers to differentiate distinct disease patterns, known as endotypes. METHODS: In this cluster analysis, we first classified patients from the PROFILE study, a multicentre, prospective, observational cohort of individuals with incident idiopathic pulmonary fibrosis or non-specific interstitial pneumonia in the UK (Nottingham University Hospitals, Nottingham; and Royal Brompton Hospital, London). 13 blood biomarkers representing extracellular matrix remodelling, epithelial stress, and thrombosis were measured by ELISA in the PROFILE study. We classified patients by unsupervised consensus clustering. To evaluate generalisability, a machine learning classifier trained on biomarker signatures derived from consensus clustering was applied to a replication dataset from the Australian Idiopathic Pulmonary Fibrosis Registry (AIPFR). Biomarker associations with mortality and change in percentage of predicted forced vital capacity (FVC%) were assessed, adjusting for age, gender, baseline FVC%, and antifibrotic treatment and steroid treatment before and after baseline. Mortality risk associated with the clusters in the PROFILE cohort was evaluated with Cox proportional hazards models, and mixed-effects models were used to analyse how clustering was associated with longitudinal FVC% in the PROFILE and AIPFR cohorts. FINDINGS: 455 of 580 participants from the PROFILE study (348 [76%] men and 107 [24%] women; mean age 72·4 years [SD 8·3]) were included in the analysis. Within this group, three clusters were identified based on blood biomarkers. A basement membrane collagen (BM) cluster (n=248 [55%]) showed high concentrations of PRO-C4, PRO-C28, C3M, and C6M, whereas an epithelial injury (EI) cluster (n=109 [24%]) showed high concentrations of MMP-7, SP-D, CYFRA211, CA19-9, and CA-125. The third cluster (crosslinked fibrin [XF] cluster; n=98 [22%]) had high concentrations of X-FIB. In the replication dataset (117 of 833 patients from AIPFR; 87 [74%] men and 30 [26%] women; mean age 72·9 years [SD 7·9]), we identified the same three clusters (BM cluster, n=93 [79%]; EI cluster, n=8 [7%]; XF cluster, n=16 [14%]). These clusters showed similarities with clusters in the PROFILE dataset regarding blood biomarkers and phenotypic signatures. In the PROFILE dataset, the EI and XF clusters were associated with increased mortality risk compared with the BM cluster (EI vs BM: adjusted hazard ratio [HR] 1·88 [95% CI 1·42-2·49], p<0·0001; XF vs BM: adjusted HR 1·53 [1·13-2·06], p=0·0058). The EI cluster showed the greatest annual FVC% decline, followed by the BM and XF clusters. A similar FVC% decline pattern was observed in these clusters in the AIPFR replication dataset. INTERPRETATION: Blood biomarker clustering in pulmonary fibrosis identified three distinct blood biomarker signatures associated with lung function and prognosis, suggesting unique pulmonary fibrosis biomarker patterns. These findings support the presence of pulmonary fibrosis endotypes with the potential to guide targeted therapy development. FUNDING: None.