scholarly journals Interpreting the Molecular Mechanisms of Yinchenhao Decoction on Hepatocellular Carcinoma through Absorbed Components Based on Network Pharmacology

2021 ◽  
Vol 2021 ◽  
pp. 1-22
Author(s):  
Jijia Sun ◽  
Tao Han ◽  
Tao Yang ◽  
Yunhui Chen ◽  
Jihan Huang
Keyword(s):  
Gene Expression ◽  
Hepatocellular Carcinoma ◽  
Molecular Mechanisms ◽  
Gene Expression Omnibus ◽  
The Cancer Genome Atlas ◽  
Network Pharmacology ◽  
Cancer Genome Atlas ◽  
Target Set ◽  
Cellular Components ◽  
Coexpression Network Analysis

To investigate the mechanisms through which Yinchenhao decoction (YCHD) inhibits hepatocellular carcinoma (HCC), we analyzed YCHD ingredients absorbed into the bloodstream by using network pharmacology. We conducted a weighted gene coexpression network analysis on gene expression data collected from the Gene Expression Omnibus and The Cancer Genome Atlas databases to derive an HCC gene set; moreover, we used four online prediction system databases to predict the potential targets of YCHD ingredients absorbed into the bloodstream. We discovered that YCHD directly interfered with 17 HCC-related disease targets. Subsequent gene ontology enrichment analyses of these 17 disease targets revealed that YCHD exhibited effects through 17 biological processes, 7 molecular functions, and 9 cellular components. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses indicated 14 pathways through which YCHD inhibits HCC. We observed similar trends in how the 17 small molecules interfered with the key target set. We surmised that YCHD inhibits HCC by regulating inflammatory and metabolic pathways. Network pharmacological analysis of YCHD ingredients absorbed into the bloodstream may provide new insights and serve as a new method for discovering the molecular mechanisms through which YCHD inhibits HCC.

scholarly journals An independent poor-prognosis subtype of hepatocellular carcinoma based on the tumor microenvironment

2021 ◽  
Vol 49 (2) ◽  
pp. 030006052098064
Author(s):  
Junfeng Wang ◽  
Jianying Lou ◽  
Lei Fu ◽  
Qu Jin
Keyword(s):  
Gene Expression ◽  
Hepatocellular Carcinoma ◽  
Tumor Microenvironment ◽  
Poor Prognosis ◽  
Molecular Mechanisms ◽  
Immune Cell ◽  
Gene Expression Omnibus ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Using Data

Background Hepatocellular carcinoma (HCC) is a highly malignant tumor with a particularly poor prognosis. The tumor microenvironment (TME) is closely associated with tumorigenesis, progression, and treatment. However, the relationship between TME genes and HCC patient prognosis is poorly understood. Methods In this study, we identified two prognostic subtypes based on the TME using data from The Cancer Genome Atlas and Gene Expression Omnibus. The Microenvironment Cell Populations-counter method was used to evaluate immune cell infiltration in HCC. Differentially expressed genes between molecular subtypes were calculated with the Limma package, and clusterProfiler was used for Gene Ontology and Kyoto Encyclopedia of Genes and Genomes functional enrichment analyses to identify genes related to the independent subtypes. We also integrated mRNA expression data into our bioinformatics analysis. Results We identified 4227 TME-associated genes and 640 genes related to the prognosis of HCC. We defined two major subtypes (Clusters 1 and 2) based on the analysis of TME-associated gene expression. Cluster 1 was characterized by increased expression of immune-associated genes and a worse prognosis than Cluster 2. Conclusions The identification of these HCC subtypes based on the TME provides further insight into the molecular mechanisms and prediction of HCC prognosis.

Development and validation of a m6A-related gene signature for predicting the prognosis of hepatocellular carcinoma

2020 ◽  
Vol 14 (13) ◽  
pp. 1217-1228
Author(s):  
Weihao Kong ◽  
Xutong Li ◽  
Honghai Xu ◽  
Yufeng Gao
Keyword(s):  
Gene Expression ◽  
Hepatocellular Carcinoma ◽  
Multivariate Regression Analysis ◽  
Gene Signature ◽  
Gene Expression Omnibus ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Risk Genes ◽  
Related Risk ◽  
Cancer Genome Atlas

Background: This study aimed to investigate the prognostic role of m6A methylation regulators in hepatocellular carcinoma (HCC). Materials & methods: Gene expression matrices were downloaded from The Cancer Genome Atlas (TCGA), International Cancer Genome Consortium, and Gene Expression Omnibus databases. Univariate and multivariate regression analysis were utilized to determine the m6A risk genes. Results: Two m6A-related risk genes (YTHDF1, YTHDF2) were identified in the TCGA HCC cohort. The m6A-correlated risk score is an independent risk factor for the overall survival of the TCGA HCC cohort. Finally, we verified the reliability of our results using three external datasets. Conclusion: The m6A-correlated gene signature has prognostic value in HCC patients and thus provides guidance for the treatment of HCC.

scholarly journals RAP1GAP is a novel marker of trabecular pattern and poor sorafenib treatment response in hepatocellular carcinoma

2021 ◽  
Author(s):  
Xue Wen ◽  
Kunkai Su ◽  
Zhikun Liu ◽  
Sunbin Ling ◽  
Di Lu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Hepatocellular Carcinoma ◽  
Molecular Mechanisms ◽  
Gene Expression Omnibus ◽  
Trabecular Structure ◽  
The Cancer Genome Atlas ◽  
Sequencing Data ◽  
Sorafenib Treatment ◽  
Trabecular Pattern ◽  
Geo Database

Abstract Background The trabecular pattern is one of the most common features of hepatocellular carcinoma (HCC). In this study, we aimed to identify the molecular mechanisms underlying different trabecular patterns in HCC, and their interaction with current therapies. Methods To screen potential biomarkers of different trabecular patterns, we first linked gene expression data to haematoxylin and eosin (H&E) images from The Cancer Genome Atlas (TCGA). The Gene Expression Omnibus (GEO) database was used to explore potential targets of sorafenib treatment. Selected candidate biomarkers were further verified by immunohistochemistry, and their relationship with sorafenib efficacy was evaluated in 107 HCC samples with trabecular patterns. Results Analysis of RNA sequencing data from TCGA showed that the increasing number of cells in the trabecular structure correlated with increase in the expression of related signalling pathways—Ras, Rap1, IL17, TNF, AGE-RAGE, oestrogen, toll-like receptor signalling, and ubiquitin-mediated proteolysis—and genes related to response to oxygen levels and neoangiogenesis. In contrast, the expression of bile acid and carton, tryptophan, butanoate, and lipid metabolism-related pathways was reduced. The GEO database showed that RAP1GAP, TOB1, ACO2, and SCNN1D expression levels were selectively up-regulated in sorafenib non-responders. Based on the combined analysis of the two datasets and our previous studies, two candidate biomarkers, RAP1GAP and HIF1α, were selected. Immunohistochemical staining showed that RAP1GAP and HIF1α were expressed in the tumour tissues. Interestingly, RAP1GAP was also expressed in the tumour sinusoids. Overexpression of RAP1GAP in sinusoids were associated with trabecular patterns. Multivariate analysis also showed that RAP1GAP expression in the sinusoid was an independent predictor of progressive free survival (PFS) and overall survival (OS) in response to sorafenib treatment. Conclusions RAP1GAP is an essential microenvironment marker in the trabecular structure of HCC and exhibits an adverse association with outcome in sorafenib treatment.

scholarly journals Functions and clinical significance of KLRG1 in the development of lung adenocarcinoma and immunotherapy

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Xiaodong Yang ◽  
Yuexin Zheng ◽  
Zhihai Han ◽  
Xiliang Zhang
Keyword(s):  
Gene Expression ◽  
Overall Survival ◽  
Lung Adenocarcinoma ◽  
Molecular Mechanisms ◽  
Killer Cell ◽  
Gene Expression Omnibus ◽  
The Cancer Genome Atlas ◽  
Normal Lung ◽  
Using Data ◽  
Low Expression

Abstract Background As a marker of differentiation, Killer cell lectin like receptor G1 (KLRG1) plays an inhibitory role in human NK cells and T cells. However, its clinical role remains inexplicit. This work intended to investigate the predictive ability of KLRG1 on the efficacy of immune-checkpoint inhibitor in the treatment of lung adenocarcinoma (LUAD), as well as contribute to the possible molecular mechanisms of KLRG1 on LUAD development. Methods Using data from the Gene Expression Omnibus, the Cancer Genome Atlas and the Genotype-Tissue Expression, we compared the expression of KLRG1 and its related genes Bruton tyrosine kinase (BTK), C-C motif chemokine receptor 2 (CCR2), Scm polycomb group protein like 4 (SCML4) in LUAD and normal lung tissues. We also established stable LUAD cell lines with KLRG1 gene knockdown and investigated the effect of KLRG1 knockdown on tumor cell proliferation. We further studied the prognostic value of the four factors in terms of overall survival (OS) in LUAD. Using data from the Gene Expression Omnibus, we further investigated the expression of KLRG1 in the patients with different responses after immunotherapy. Results The expression of KLRG1, BTK, CCR2 and SCML4 was significantly downregulated in LUAD tissues compared to normal controls. Knockdown of KLRG1 promoted the proliferation of A549 and H1299 tumor cells. And low expression of these four factors was associated with unfavorable overall survival in patients with LUAD. Furthermore, low expression of KLRG1 also correlated with poor responses to immunotherapy in LUAD patients. Conclusion Based on these findings, we inferred that KLRG1 had significant correlation with immunotherapy response. Meanwhile, KLRG1, BTK, CCR2 and SCML4 might serve as valuable prognostic biomarkers in LUAD.

scholarly journals Data mining of immune-related prognostic genes in metastatic melanoma microenvironment

2020 ◽  
Vol 40 (11) ◽  
Author(s):  
Wei Han ◽  
Biao Huang ◽  
Xiao-Yu Zhao ◽  
Guo-Liang Shen
Keyword(s):  
Gene Expression ◽  
Tumor Microenvironment ◽  
Metastatic Melanoma ◽  
Interaction Network ◽  
Gene Expression Omnibus ◽  
The Cancer Genome Atlas ◽  
Protein Protein Interaction ◽  
Subtype Identification ◽  
Cancer Genome Atlas ◽  
Immune Related Genes

Abstract Skin cutaneous melanoma (SKCM) is one of the most deadly malignancies. Although immunotherapies showed the potential to improve the prognosis for metastatic melanoma patients, only a small group of patients can benefit from it. Therefore, it is urgent to investigate the tumor microenvironment in melanoma as well as to identify efficient biomarkers in the diagnosis and treatments of SKCM patients. A comprehensive analysis was performed based on metastatic melanoma samples from the Cancer Genome Atlas (TCGA) database and ESTIMATE algorithm, including gene expression, immune and stromal scores, prognostic immune-related genes, infiltrating immune cells analysis and immune subtype identification. Then, the differentially expressed genes (DEGs) were obtained based on the immune and stromal scores, and a list of prognostic immune-related genes was identified. Functional analysis and the protein–protein interaction network revealed that these genes enriched in multiple immune-related biological processes. Furthermore, prognostic genes were verified in the Gene Expression Omnibus (GEO) databases and used to predict immune infiltrating cells component. Our study revealed seven immune subtypes with different risk values and identified T cells as the most abundant cells in the immune microenvironment and closely associated with prognostic outcomes. In conclusion, the present study thoroughly analyzed the tumor microenvironment and identified prognostic immune-related biomarkers for metastatic melanoma.

scholarly journals Identification of Hub Gene GRIN1 Correlated with Histological Grade and Prognosis of Glioma by Weighted Gene Coexpression Network Analysis

2021 ◽  
Vol 2021 ◽  
pp. 1-22
Author(s):  
Aoran Yang ◽  
Xinhuan Wang ◽  
Yaofeng Hu ◽  
Chao Shang ◽  
Yang Hong
Keyword(s):  
Gene Expression ◽  
Network Analysis ◽  
Molecular Mechanisms ◽  
The Cancer Genome Atlas ◽  
Coexpression Network ◽  
Normal Brain ◽  
Gene Coexpression Network ◽  
Gene Coexpression ◽  
Coexpression Network Analysis ◽  
Core Genes

The function of glutamate ionotropic receptor NMDA type subunit 1 (GRIN1) in neurodegenerative diseases has been widely reported; however, its role in the occurrence of glioma remains less explored. We obtained clinical data and transcriptome data from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA). Hub gene’s expression differential analysis and survival analysis were conducted by browsing the Gene Expression Profiling Interactive Analysis (GEPIA) database, Human Protein Atlas database, and LOGpc database. We conducted a variation analysis of datasets obtained from GEO and TCGA and performed a weighted gene coexpression network analysis (WGCNA) using the R programming language (3.6.3). Kaplan-Meier (KM) analysis was used to calculate the prognostic value of GRIN1. Finally, we conducted Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. Using STRING, we constructed a protein–protein interaction (PPI) network. Cytoscape software, a prerequisite of visualizing core genes, was installed, and CytoHubba detected the 10 most tumor-related core genes. We identified 185 differentially expressed genes (DEGs). GO and KEGG enrichment analyses illustrated that the identified DEGs are imperative in different biological functions and ascertained the potential pathways in which the DEGs may be enriched. The overall survival calculated by KM analysis showed that patients with lower expression of GRIN1 had worse prognoses than patients with higher expression of GRIN1 ( p = 0.004 ). The GEPIA and LOGpc databases were used to verify the expression difference of GRIN1 among GBM, LGG, and normal brain tissues. Ultimately, immunohistochemical assay results showed that GRIN1 was detected in normal tissue and not in the tumor specimens. Our results highlight a potential target for glioma treatment and will further our understanding of the molecular mechanisms underlying the treatment of glioma.

scholarly journals The role of miR-92b in cholangiocarcinoma patients

2018 ◽  
Vol 33 (3) ◽  
pp. 293-300 ◽  
Author(s):  
Min-hang Zhou ◽  
Hong-wei Zhou ◽  
Mo Liu ◽  
Jun-zhong Sun
Keyword(s):  
Gene Expression ◽  
Overall Survival ◽  
Gene Expression Omnibus ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Positive Regulation ◽  
Cancer Genome Atlas ◽  
High Level ◽  
Genome Atlas

Purpose: The role of microRNA (miRNA) in cholangiocarcinoma was not clear. The aim of this study was to find the potential diagnostic and prognostic miRNA in cholangiocarcinoma patients. Methods: The miRNA expression profiles in cholangiocarcinoma patients from The Cancer Genome Atlas and Gene Expression Omnibus (GSE53870) were analyzed. The comparison of overall survival was performed using the Kaplan–Meier method. The targeted genes of prognostic miRNA were identified in miRanda, PicTar, or TargetScan, and their cell signaling pathways were analyzed by the Database for Annotation, Visualization and Integrated Discovery. Results: In The Cancer Genome Atlas and the Gene Expression Omnibus miRNA dataset, miR-92b and miR-99a were found with concordant directionality, up-regulated and down-regulated, respectively. In The Cancer Genome Atlas survival data, patients with the high level of miR-99b had obviously shorter overall survival time ( P=0.038). However, the level of miR-99a was not found to be significant. The 17 shared target genes of miR-92b were identified, such as DAB21IP, BCL21L11, SPHK2, PER2, and TSC1. The related pathways included positive regulation of transcription, positive regulation of cellular biosynthetic process, regulation of programmed cell death, etc. Conclusion: miR-92b was up-regulated in cholangiocarcinoma compared with normal controls. The high level of miR-92b was associated with adverse outcomes in cholangiocarcinoma patients, which might be partly explained by the targeted genes of miR-92b and their signaling pathways.

scholarly journals Tumor microenvironment characterization in stage IV gastric cancer

2021 ◽  
Vol 41 (1) ◽  
Author(s):  
Xianxue Zhang ◽  
Feng Yang ◽  
Zhenbao Wang
Keyword(s):  
Gene Expression ◽  
Gastric Cancer ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Stage Iv ◽  
Gene Expression Omnibus ◽  
The Cancer Genome Atlas ◽  
Stage Iv Gastric Cancer ◽  
Th 17 ◽  
Cancer Genome Atlas

Abstract Immunotherapy is remarkably affected by the immune environment of the principal tumor. Nonetheless, the immune environment’s clinical relevance in stage IV gastric cancer (GC) is largely unknown. The gene expression profiles of 403 stage IV GC patients in the three cohorts: GEO (Gene Expression Omnibus, GSE84437 (n=292) and GSE62254 (n=77), and TCGA (The Cancer Genome Atlas, n=34) were used in the present study. Using four publicly available stage IV GC expression datasets, 29 immune signatures were expression profiled, and on this basis, we classified stage IV GC. The classification was conducted using the hierarchical clustering method. Three stage IV GC subtypes L, M, and H were identified representing low, medium, and high immunity, respectively. Immune correlation analysis of these three types revealed that Immune H exhibited a better prognostic outcome as well as a higher immune score compared with other subtypes. There was a noticeable difference in the three subgroups of HLA genes. Further, on comparing with other subtypes, CD86, CD80, CD274, CTLA4, PDCD1, and PDCD1LG2 had higher expression in the Immunity H subtype. In stage IV GC, potentially positive associations between immune and pathway activities were displayed, due to the enrichment of pathways including TNF signaling, Th-17 cell differentiation, and JAK-STAT signaling pathways in Immunity H vs Immunity L subtypes. External cohorts from TCGA cohort ratified these results. The identification of stage IV GC subtypes has potential clinical implications in stage IV GC treatment.

scholarly journals YTHDC1-mediated VPS25 regulates cell cycle by targeting JAK-STAT signaling in human glioma cells

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Xiaolong Zhu ◽  
Hui Yang ◽  
Mengying Zhang ◽  
Xingwei Wu ◽  
Lan Jiang ◽  
...  
Keyword(s):  
Cell Cycle ◽  
Molecular Mechanisms ◽  
Target Genes ◽  
Glioma Cells ◽  
Prognostic Indicator ◽  
Gene Expression Omnibus ◽  
The Cancer Genome Atlas ◽  
Endosomal Sorting ◽  
Cancer Genome Atlas

Abstract Background Glioma is a common type of malignant brain tumor with a high mortality and relapse rate. The endosomal sorting complex required for transport (ESCRT) has been reported to be involved in tumorigenesis. However, the molecular mechanisms have not been clarified. Methods Bioinformatics was used to screen the ESCRT subunits highly expressed in glioma tissues from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. The function of the ESCRT subunits in glioma cells was examined in vitro. Transcriptome sequencing analyzed the target genes and signaling pathways affected by the ESCRT subunit. Finally, the relationship between m6A (N6-methyladenosine) modification and high expression of the ESCRT subunit was studied. Results VPS25 was upregulated in glioma tissues, which was correlated with poor prognosis in glioma patients. Furthermore, VPS25 knockdown inhibited the proliferation, blocked the cell cycle, and promoted apoptosis in glioma cells. Meanwhile, VPS25 induced a G0/G1 phase arrest of the cell cycle in glioma cells by directly mediating p21, CDK2, and cyclin E expression, and JAK-signal transducer and activator of transcription (STAT) activation. Finally, YTHDC1 inhibited glioma proliferation by reducing the expression of VPS25. Conclusion These results suggest that VPS25 is a promising prognostic indicator and a potential therapeutic target for glioma.

Sign in / Sign up

Export Citation Format

Share Document