scholarly journals A Unique Immune-Related Gene Signature Represents Advanced Liver Fibrosis and Reveals Potential Therapeutic Targets

Biomedicines ◽  
2022 ◽  
Vol 10 (1) ◽  
pp. 180
Author(s):  
Pil-Soo Sung ◽  
Chang-Min Kim ◽  
Jung-Hoon Cha ◽  
Jin-Young Park ◽  
Yun-Suk Yu ◽  
...  
Keyword(s):  
Liver Fibrosis ◽  
Meta Analysis ◽  
Therapeutic Targets ◽  
Gene Signature ◽  
Chronic Liver ◽  
High Grade ◽  
Related Gene ◽  
Chronic Liver Diseases ◽  
Immune Related Gene ◽  
Advanced Liver Fibrosis

Innate and adaptive immune responses are critically associated with the progression of fibrosis in chronic liver diseases. In this study, we aim to identify a unique immune-related gene signature representing advanced liver fibrosis and to reveal potential therapeutic targets. Seventy-seven snap-frozen liver tissues with various chronic liver diseases at different fibrosis stages (1: n = 12, 2: n = 12, 3: n = 25, 4: n = 28) were subjected to expression analyses. Gene expression analysis was performed using the nCounter PanCancer Immune Profiling Panel (NanoString Technologies, Seattle, WA, USA). Biological meta-analysis was performed using the CBS Probe PINGSTM (CbsBioscience, Daejeon, Korea). Using non-tumor tissues from surgically resected specimens, we identified the immune-related, five-gene signature (CHIT1_FCER1G_OSM_VEGFA_ZAP70) that reliably differentiated patients with low- (F1 and F2) and high-grade fibrosis (F3 and F4; accuracy = 94.8%, specificity = 91.7%, sensitivity = 96.23%). The signature was independent of all pathological and clinical features and was independently associated with high-grade fibrosis using multivariate analysis. Among these genes, the expression of inflammation-associated FCER1G, OSM, VEGFA, and ZAP70 was lower in high-grade fibrosis than in low-grade fibrosis, whereas CHIT1 expression, which is associated with fibrogenic activity of macrophages, was higher in high-grade fibrosis. Meta-analysis revealed that STAT3, a potential druggable target, highly interacts with the five-gene signature. Overall, we identified an immune gene signature that reliably predicts advanced fibrosis in chronic liver disease. This signature revealed potential immune therapeutic targets to ameliorate liver fibrosis.

scholarly journals Comparative study between liver biopsy and non-invasive biomarkers in assessment of hepatic fibrosis in children with chronic liver diseases

2021 ◽  
Vol 69 (1) ◽  
Author(s):  
Ola Galal Behairy ◽  
Ola Samir El-Shimi ◽  
Naglaa Hamed Shalan
Keyword(s):  
Liver Fibrosis ◽  
Liver Biopsy ◽  
Liver Diseases ◽  
Area Under The Curve ◽  
Chronic Liver ◽  
Fibrosis Score ◽  
Chronic Liver Diseases ◽  
Non Invasive ◽  
Advanced Liver Fibrosis ◽  
Early Fibrosis

Abstract Background Liver biopsy is the gold standard for detecting the degree of liver fibrosis; however, invasiveness constitutes its main limiting factor in clinical application, so we aimed to evaluate the non-invasive biomarker formulas (APRI and FIB-4) and their modified forms by BMI z-score (M-APRI, M-FIB-4, and B-AST) compared to liver biopsy in the assessment of liver fibrosis in children with chronic liver diseases. Two hundred children aged 6.3 ± 3.8 years (98 males, 102 females) with chronic liver diseases underwent liver biopsy. The stage of fibrosis was assessed according to the METAVIR system for all children, and the following non-invasive biomarker formulas were calculated: APRI, modified APRI (M-APRI: BMI z-score × APRI), Fibrosis-4 index (FIB-4), modified FIB-4 (M-FIB-4: BMI z-score × FIB-4), and B-AST (BMI z-score × AST). The best cutoff value was calculated to detect early fibrosis (F1–F2) from advanced liver fibrosis (F3–F4). Results There were positive correlations between all studied non-invasive biomarker models (APRI, FIB-4, M-APRI, M-FIB-4, B-AST) and fibrosis score as an increase in fibrosis score was associated with an increase in mean ± SD of all studied biomarker formulas. The best cutoff values of non-invasive biomarker models in the diagnosis of early fibrosis (F1–F2) were APRI > 0.96, M-APRI > 0.16, FIB-4 > 0.019, M-FIB-4 > 0.005, and B-AST > −8 with an area under the curve above 0.7 each, while the best cutoff values of non-invasive biomarker models (APRI, M-APRI, FIB-4, M-FIB-4, and B-AST) in the diagnosis of advanced liver fibrosis (F3–F4) were >1.96, >2.2, >0.045, and >0.015, >92.1, respectively, with an area under the curve above 0.8 each. Conclusion APRI, M-APRI, FIB-4, M-FIB-4, and B-AST are good non-invasive alternatives to liver biopsy in the detection of liver fibrosis in children with chronic liver diseases of different etiologies especially those that include BMI z-scores in their formulas.

scholarly journals The Role of the Gut Microbiome in Liver Cirrhosis Treatment

2020 ◽  
Vol 22 (1) ◽  
pp. 199
Author(s):  
Na Young Lee ◽  
Ki Tae Suk
Keyword(s):  
Liver Cirrhosis ◽  
Liver Disease ◽  
Liver Fibrosis ◽  
Gut Microbiota ◽  
Gut Microbiome ◽  
Liver Diseases ◽  
Sclerosing Cholangitis ◽  
Chronic Liver ◽  
Chronic Liver Diseases

Liver cirrhosis is one of the most prevalent chronic liver diseases worldwide. In addition to viral hepatitis, diseases such as steatohepatitis, autoimmune hepatitis, sclerosing cholangitis and Wilson’s disease can also lead to cirrhosis. Moreover, alcohol can cause cirrhosis on its own and exacerbate chronic liver disease of other causes. The treatment of cirrhosis can be divided into addressing the cause of cirrhosis and reversing liver fibrosis. To this date, there is still no clear consensus on the treatment of cirrhosis. Recently, there has been a lot of interest in potential treatments that modulate the gut microbiota and gut-liver axis for the treatment of cirrhosis. According to recent studies, modulation of the gut microbiome by probiotics ameliorates the progression of liver disease. The precise mechanism for relieving cirrhosis via gut microbial modulation has not been identified. This paper summarizes the role and effects of the gut microbiome in cirrhosis based on experimental and clinical studies on absorbable antibiotics, probiotics, prebiotics, and synbiotics. Moreover, it provides evidence of a relationship between the gut microbiome and liver fibrosis.

scholarly journals Identification of Immune-Related Biomarkers for Sciatica in Peripheral Blood

2021 ◽  
Vol 12 ◽  
Author(s):  
Xin Jin ◽  
Jun Wang ◽  
Lina Ge ◽  
Qing Hu
Keyword(s):  
Peripheral Blood ◽  
Training Model ◽  
Gene Signature ◽  
Training Dataset ◽  
Support Vector ◽  
Consensus Clustering ◽  
Related Gene ◽  
Clustering Method ◽  
Immune Related Gene ◽  
Immune Related Genes

Objective: Sciatica pertains to neuropathic pain that has been associated with inflammatory response. We aimed to identify significant immune-related biomarkers for sciatica in peripheral blood.Methods: We utilized the GSE150408 expression profiling data from the Gene Expression Omnibus (GEO) database as the training dataset and extracted immune-related genes for further analysis. Differentially expressed immune-related genes (DEIRGs) between healthy controls and patients with sciatica were selected using the “limma” package and verified in clinical specimens by quantitative reverse transcription PCR (RT-qPCR). A diagnostic immune-related gene signature was established using the training model and random forest (RF), generalized linear model (GLM), and support vector machine (SVM) models. Sciatica patient subtypes were identified using the consensus clustering method.Results: Thirteen significant DEIRGs were acquired, of which five (CRP, EREG, FAM19A4, RLN1, and WFIKKN1) were selected to establish a diagnostic immune-related gene signature according to the most appropriate training model, namely, the RF model. A clinical application nomogram model was established based on the expression level of the five DEIRGs. The sciatica patients were divided into two subtypes (C1 and C2) according to the consensus clustering method.Conclusions: Our research established a diagnostic five immune-related gene signature to discriminate sciatica and identified two sciatica subtypes, which may be beneficial to the clinical diagnosis and treatment of sciatica.

Prognostication of a 13-immune-related-gene signature in patients with early triple-negative breast cancer

2020 ◽  
Vol 184 (2) ◽  
pp. 325-334
Author(s):  
Ji-Yeon Kim ◽  
Hae Hyun Jung ◽  
Insuk Sohn ◽  
Sook Young Woo ◽  
Hyun Cho ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Triple Negative Breast Cancer ◽  
Triple Negative ◽  
Gene Signature ◽  
Related Gene ◽  
Immune Related Gene

scholarly journals Development of a Predictive Immune-Related Gene Signature Associated With Hepatocellular Carcinoma Patient Prognosis

2020 ◽  
Vol 27 (1) ◽  
pp. 107327482097711
Author(s):  
Jiasheng Lei ◽  
Dengyong Zhang ◽  
Chao Yao ◽  
Sheng Ding ◽  
Zheng Lu
Keyword(s):  
Hepatocellular Carcinoma ◽  
Overall Survival ◽  
Cox Regression ◽  
R Package ◽  
Gene Signature ◽  
Differentially Expressed ◽  
Related Gene ◽  
Patient Cohort ◽  
Immune Related Gene ◽  
Related Risk

Background: Hepatocellular carcinoma (HCC) remains the third leader cancer-associated cause of death globally, but the etiological basis for this complex disease remains poorly clarified. The present study was thus conceptualized to define a prognostic immune-related gene (IRG) signature capable of predicting immunotherapy responsiveness and overall survival (OS) in patients with HCC. Methods: Five differentially expressed IRG associated with HCC were established the immune-related risk model through univariate Cox regression and least absolute shrinkage and selection operator (LASSO) regression analyses. Patients were separated at random into training and testing cohorts, after which the association between the identified IRG signature and OS was evaluated using the “survival” R package. In addition, maftools was leveraged to assess mutational data, with tumor mutation burden (TMB) scores being calculated as follows: (total mutations/total bases) × 106. Immune-related risk term abundance was quantified via “ssGSEA” algorithm using the “gsva” R package. Results: HCC patients were successfully stratified into low-risk and high-risk groups based upon a signature composed of 5 differentially expressed IRGs, with overall survival being significantly different between these 2 groups in training cohort, testing cohort and overall patient cohort ( P = 1.745e-06, P = 1.888e-02, P = 4.281e-07). No association was observed between TMB and this IRG risk score in the overall patient cohort ( P = 0.461). Notably, 19 out of 29 immune-related risk terms differed substantially in the overall patient dataset. These risk terms mainly included checkpoints, human leukocyte antigens, natural killer cells, dendritic cells, and major histocompatibility complex class I. Conclusion: In summary, an immune-related prognostic gene signature was successfully developed and used to predict survival outcomes and immune system status in patients with HCC. This signature has the potential to help guide immunotherapeutic treatment planning for patients affected by this deadly cancer.

scholarly journals The ability of Hepascore to predict liver fibrosis in chronic liver disease: a meta-analysis

2016 ◽  
Vol 37 (1) ◽  
pp. 121-131 ◽  
Author(s):  
Yi Huang ◽  
Leon A. Adams ◽  
John Joseph ◽  
Max K. Bulsara ◽  
Gary P. Jeffrey
Keyword(s):  
Liver Disease ◽  
Liver Fibrosis ◽  
Chronic Liver Disease ◽  
Meta Analysis ◽  
Chronic Liver

Identification of immune-related gene signature predicting survival in the tumor microenvironment of lung adenocarcinoma

2020 ◽  
Vol 72 (9-10) ◽  
pp. 455-465
Author(s):  
Mengnan Zhao ◽  
Ming Li ◽  
Zhencong Chen ◽  
Yunyi Bian ◽  
Yuansheng Zheng ◽  
...  
Keyword(s):  
Tumor Microenvironment ◽  
Lung Adenocarcinoma ◽  
Gene Signature ◽  
Related Gene ◽  
Immune Related Gene
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