Functional Insight of the Master Regulators in Hepatocellular Carcinoma by Integrative Network Analysis

2019 ◽  
Author(s):  
Zhihui Li ◽  
Yi Lou ◽  
Guoyan Tian ◽  
Jianyue Wu ◽  
Anqian Lu ◽  
...  
2021 ◽  
Author(s):  
Seungyeul Yoo ◽  
Abhilasha Sinha ◽  
Dawei Yang ◽  
Nasser Altorki ◽  
Radhika Tandon ◽  
...  

Abstract We present a gene signature distinguishing invasive and indolent tumors among early-stage lung adenocarcinoma (esLUAD). An Invasiveness Score estimated using the gene signature was strongly associated with survival of esLUAD patients in multiple independent cohorts and with the invasiveness phenotype in lung cancer cell lines. Regulatory network analysis identified aurora kinase as one of master regulators of the gene signature and perturbation of aurora kinases in vitro and in vivo reduced tumor invasion. Our study suggests aurora kinases as a novel target for treating early-stage invasive lung adenocarcinoma.


2021 ◽  
Vol 27 ◽  
Author(s):  
Wanbang Zhou ◽  
Yiyang Chen ◽  
Ruixing Luo ◽  
Zifan Li ◽  
Guanwei Jiang ◽  
...  

Hepatocellular carcinoma (HCC) is a common cancer with poor prognosis. Due to the lack of effective biomarkers and its complex immune microenvironment, the effects of current HCC therapies are not ideal. In this study, we used the GSE57957 microarray data from Gene Expression Omnibus database to construct a co-expression network. The weighted gene co-expression network analysis and CIBERSORT algorithm, which quantifies cellular composition of immune cells, were used to identify modules related to immune cells. Four hub genes (EFTUD2, GAPDH, NOP56, PA2G4) were identified by co-expression network and protein-protein interactions network analysis. We examined these genes in TCGA database, and found that the four hub genes were highly expressed in tumor tissues in multiple HCC groups, and the expression levels were significantly correlated with patient survival time, pathological stage and tumor progression. On the other hand, methylation analysis showed that the up-regulation of EFTUD2, GAPDH, NOP56 might be due to the hypomethylation status of their promoters. Next, we investigated the correlations between the expression levels of four hub genes and tumor immune infiltration using Tumor Immune Estimation Resource (TIMER). Gene set variation analysis suggested that the four hub genes were associated with numerous pathways that affect tumor progression or immune microenvironment. Overall, our results showed that the four hub genes were closely related to tumor prognosis, and may serve as targets for treatment and diagnosis of HCC. In addition, the associations between these genes and immune infiltration enhanced our understanding of tumor immune environment and provided new directions for the development of drugs and the monitoring of tumor immune status.


Medicine ◽  
2020 ◽  
Vol 99 (41) ◽  
pp. e22549
Author(s):  
Mingyan Sheng ◽  
Haofei Tong ◽  
Xiaoyan Lu ◽  
Ni Shanshan ◽  
Xingguo Zhang ◽  
...  

2020 ◽  
Vol 8 (1) ◽  
pp. e001126
Author(s):  
Catherine E Cioffi ◽  
K M Venkat Narayan ◽  
Ken Liu ◽  
Karan Uppal ◽  
Dean P Jones ◽  
...  

IntroductionBody fat distribution is strongly associated with cardiometabolic disease (CMD), but the relative importance of hepatic fat as an underlying driver remains unclear. Here, we applied a systems biology approach to compare the clinical and molecular subnetworks that correlate with hepatic fat, visceral fat, and abdominal subcutaneous fat distribution.Research design and methodsThis was a cross-sectional sub-study of 283 children/adolescents (7–19 years) from the Yale Pediatric NAFLD Cohort. Untargeted, high-resolution metabolomics (HRM) was performed on plasma and combined with existing clinical variables including hepatic and abdominal fat measured by MRI. Integrative network analysis was coupled with pathway enrichment analysis and multivariable linear regression (MLR) to examine which metabolites and clinical variables associated with each fat depot.ResultsThe data divided into four communities of correlated variables (|r|>0.15, p<0.05) after integrative network analysis. In the largest community, hepatic fat was associated with eight clinical biomarkers, including measures of insulin resistance and dyslipidemia, and 878 metabolite features that were enriched predominantly in amino acid (AA) and lipid pathways in pathway enrichment analysis (p<0.05). Key metabolites associated with hepatic fat included branched-chain AAs (valine and isoleucine/leucine), aromatic AAs (tyrosine and tryptophan), serine, glycine, alanine, and pyruvate, as well as several acylcarnitines and glycerophospholipids (all q<0.05 in MLR adjusted for covariates). The other communities detected in integrative network analysis consisted of abdominal visceral, superficial subcutaneous, and deep subcutaneous fats, but no clinical variables, fewer metabolite features (280, 312, and 74, respectively), and limited findings in pathway analysis.ConclusionsThese data-driven findings show a stronger association of hepatic fat with key CMD risk factors compared with abdominal fats. The molecular network identified using HRM that associated with hepatic fat provides insight into potential mechanisms underlying the hepatic fat–insulin resistance interface in youth.


2006 ◽  
Vol 14 (7S_Part_19) ◽  
pp. P1016-P1017
Author(s):  
Burcu F. Darst ◽  
Qiongshi Lu ◽  
Rebecca L. Koscik ◽  
Erin Jonaitis ◽  
Lindsay R. Clark ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document