Dataset Information

Cluster of Differentiation 44 Promotes Liver Fibrosis and Serves as a Biomarker in Congestive Hepatopathy.

ABSTRACT: Congestive hepatopathy (CH) with chronic passive congestion is characterized by the progression of liver fibrosis without prominent inflammation and hepatocellular damage. Currently, the lack of reliable biomarkers for liver fibrosis in CH often precludes the clinical management of patients with CH. To explore fibrosis biomarkers, we performed proteome analysis on serum exosomes isolated from patients with CH after the Fontan procedure. Exosomal cluster of differentiation (CD)44 levels were increased in patients with CH compared to healthy volunteers and was accompanied by increases in serum levels of soluble CD44 and CD44 expression in the liver. To address the roles of CD44 in CH, we established a mouse model of chronic liver congestion by partial inferior vena cava ligation (pIVCL) that mimics CH by fibrosis progression with less inflammation and cellular damage. In the pIVCL mice, enhanced CD44 expression in hepatic stellate cells (HSCs) and deposition of its ligand hyaluronan were observed in the liver. Blood levels of soluble CD44 were correlated with liver fibrosis. The blockade of CD44 with specific antibody inhibited liver fibrosis in pIVCL mice and was accompanied by a reduction in S100 calcium-binding protein A4 expression following activation of HSCs. Conclusion: Chronic liver congestion promotes fibrosis through CD44. This identifies CD44 as a novel biomarker and therapeutic target of liver fibrosis in patients with CH.

SUBMITTER: Osawa Y

PROVIDER: S-EPMC8369942 | biostudies-literature | 2021 Aug

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Cluster of Differentiation 44 Promotes Liver Fibrosis and Serves as a Biomarker in Congestive Hepatopathy.

Osawa Yosuke Y Kawai Hironari H Tsunoda Tomoyuki T Komatsu Haruki H Okawara Miku M Tsutsui Yuriko Y Yoshida Yuichi Y Yoshikawa Shiori S Mori Taizo T Yamazoe Taiji T Yoshio Sachiyo S Oide Takashi T Inui Ayano A Kanto Tatsuya T

Hepatology communications 20210408 8

Congestive hepatopathy (CH) with chronic passive congestion is characterized by the progression of liver fibrosis without prominent inflammation and hepatocellular damage. Currently, the lack of reliable biomarkers for liver fibrosis in CH often precludes the clinical management of patients with CH. To explore fibrosis biomarkers, we performed proteome analysis on serum exosomes isolated from patients with CH after the Fontan procedure. Exosomal cluster of differentiation (CD)44 levels were incr ...[more]

PMID: 34430787

Similar Datasets

Project description:IntroductionCD44 is a transmembrane glycoprotein implicated in tissue inflammation and fibrosis. We investigated its role in kidney inflammation and fibrosis in a murine model of lupus nephritis (LN), and the clinico-pathological association of serum CD44 level in patients with biopsy-proven Class III/IV ± V LN.MethodsNZB/W F1 mice were treated with control IgG or anti-CD44 monoclonal antibody for 4 weeks and disease parameters assessed. Serum CD44 level in LN patients was determined by ELISA. Control groups included healthy subjects and patients with non-renal SLE or non-lupus renal disease.ResultsCD44 expression was absent in the normal kidney, but it was expressed in proximal and distal tubular epithelial cells and infiltrating cells in renal biopsies from patients with active proliferative LN. ScRNA-Seq datasets confirmed that CD44 was predominantly expressed in tubular cells and all immune cells identified in LN patients including tissue resident, inflammatory and phagocytic macrophages, Treg cells, effector and central memory CD4+ T cells, resident memory CD8+ T cells and naïve and activated B cells. Treatment of NZB/W F1 mice with anti-CD44 antibody preserved kidney histology and reduced proteinuria, tubulo-interstitial infiltration of CD3+, CD4+ and CD19+ immune cells, and mediators of kidney fibrosis compared to Control mice. Longitudinal studies showed that serum CD44 level increased prior to clinical renal flare by 4.5 months and the level decreased after treatment. ROC curve analysis showed that CD44 level distinguished patients with active LN from healthy subjects and patients with quiescent LN, active non-renal lupus, and non-lupus CKD (ROC AUC of 0.99, 0.96, 0.99 and 0.99 respectively). CD44 level correlated with leukocyte infiltration and interstitial inflammation scores in active LN kidney biopsies.DiscussionOur findings suggest that CD44 plays a pathogenic role in renal parenchymal inflammation and fibrosis in active LN and monitoring CD44 may facilitate early diagnosis of flare.

Project description:Congestive hepatopathy is becoming increasingly recognized among Fontan-palliated patients. Elevated central venous pressure is thought to drive the pathologic progression, characterized by sinusoidal dilatation, congestion, and fibrosis. A clinically relevant large animal model for congestive hepatopathy would provide a valuable platform for researching novel biomarkers, treatment, and prevention. Here, we report on a titratable, sheep pulmonary artery banding model for this disease application. Pulmonary artery banding was achieved by progressively inflating the implanted pulmonary artery cuff. Right ventricular catheter was implanted to draw venous blood samples and measure pressure. The pulmonary artery cuff pressure served as a surrogate for the intensity of pulmonary artery banding and was measured weekly. After about 9 wk, animals were euthanized, and the liver was harvested for histopathological assessment. Nine animal subjects received pulmonary artery banding for 64 ± 8 days. Four of the nine subjects exhibited moderate to severe liver injury, and three of those four exhibited bridging fibrosis. Increasing pulmonary artery cuff pressure significantly correlated with declining mixed venous oxygen saturation (P = 3.29 × 10-5), and higher congestive hepatic fibrosis score (P = 0.0238), suggesting that pulmonary artery banding strategy can be titrated to achieve right-sided congestion and liver fibrosis. Blood analyses demonstrated an increase in plasma bile acids, aspartate aminotransferase, and γ-glutamyltransferase among subjects with moderate to severe injury, further corroborating liver tissue findings. Our large animal pulmonary artery banding model recapitulates congestive hepatopathy and provides a basis to bridge the current gaps in scientific and clinical understanding about the disease.NEW & NOTEWORTHY We present here a large animal platform for congestive hepatopathy, a disease growing in clinical prevalence due to the increasing number of Fontan-palliated patients. Further data are needed to develop a better clinical management strategy for this poorly characterized patient population. Previous reports of animal models to study this disease have mostly been in small animals with limited fidelity. We show that congestive hepatopathy can be replicated in a chronic, progressive pulmonary artery banding model in sheep. We also show that the banding strategy can be controlled to titrate the level of liver injury. To date, we do not know of any other large animal model that can achieve this level of control over disease phenotype and clinical relevance.

Project description:Background and objectiveLiver cancer is a malignancy with a poor prognosis. G protein signaling modulator 2 is mainly related to cell division and cell cycle regulation. In this review, the relationship between G protein signaling modulator 2 and clinical characteristics of patients with liver cancer has been explored, especially with respect to its prognostic value.MethodsG protein signaling modulator 2 messenger RNA expression and clinicopathological characteristics of patients with liver cancer were obtained from The Cancer Genome Atlas. The expression level of G protein signaling modulator 2 RNA-Seq was validated by using Gene Expression Omnibus. Chi-square test was performed to evaluate the relationship between G protein signaling modulator 2 expression and clinical characteristics. The threshold value of G protein signaling modulator 2 in the diagnosis of liver cancer was evaluated by a receiver-operating characteristic curve. Cox regression analysis and Kaplan-Meier curves were performed to evaluate the relationship between G protein signaling modulator 2 and liver cancer prognosis, which included overall and residual-free survival, and explored the prognostic value of G protein signaling modulator 2. Liver cancer survival analyses were validated by using the data of G protein signaling modulator 2 RNA-Seq from the International Cancer Genome Consortium.ResultsThe expression level of G protein signaling modulator 2 messenger RNA was remarkably higher in liver cancer than that in healthy tissues (P < 2.2 × e-16), which was also validated by data from the GSE14520 database. In addition, high G protein signaling modulator 2 expression significantly correlated with histological grade (P = .020), vital status (P < .001), clinical (P = .001), and T stage (P = .001). The receiver-operating characteristic curves showed G protein signaling modulator 2 to be an advantageous diagnostic molecule for liver cancer (area under curve = 0.893). Furthermore, the results of Cox analysis and Kaplan-Meier curves suggested that the upregulation of G protein signaling modulator 2 expression is linked to poor prognosis and G protein signaling modulator 2 messenger RNA could be an independent predictor for liver cancer, which was validated by data from the International Cancer Genome Consortium database.ConclusionsG protein signaling modulator 2 messenger RNA was overexpressed in liver cancer, and G protein signaling modulator 2 is an independent prognostic factor. G protein signaling modulator 2 is expected to be a treatment target for cancer.

Dataset Information

Cluster of Differentiation 44 Promotes Liver Fibrosis and Serves as a Biomarker in Congestive Hepatopathy.

Publications

Cluster of Differentiation 44 Promotes Liver Fibrosis and Serves as a Biomarker in Congestive Hepatopathy.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets