scholarly journals ADAM and ADAMTS Proteins, New Players in the Regulation of Hepatocellular Carcinoma Microenvironment

Cancers ◽  
2021 ◽  
Vol 13 (7) ◽  
pp. 1563
Author(s):  
Nathalie Théret ◽  
Fidaa Bouezzeddine ◽  
Fida Azar ◽  
Mona Diab-Assaf ◽  
Vincent Legagneux
Keyword(s):  
Hepatocellular Carcinoma ◽  
Tumor Microenvironment ◽  
Meta Analysis ◽  
Functional Characterization ◽  
The Cancer Genome Atlas ◽  
Research Network ◽  
Connected Components ◽  
Cancer Genome Atlas ◽  
A Disintegrin And Metalloproteinase ◽  
Using Data

The tumor microenvironment plays a major role in tumor growth, invasion and resistance to chemotherapy, however understanding how all actors from microenvironment interact together remains a complex issue. The tumor microenvironment is classically represented as three closely connected components including the stromal cells such as immune cells, fibroblasts, adipocytes and endothelial cells, the extracellular matrix (ECM) and the cytokine/growth factors. Within this space, proteins of the adamalysin family (ADAM for a disintegrin and metalloproteinase; ADAMTS for ADAM with thrombospondin motifs; ADAMTSL for ADAMTS-like) play critical roles by modulating cell–cell and cell–ECM communication. During last decade, the implication of adamalysins in the development of hepatocellular carcinoma (HCC) has been supported by numerous studies however the functional characterization of most of them remain unsettled. In the present review we propose both an overview of the literature and a meta-analysis of adamalysins expression in HCC using data generated by The Cancer Genome Atlas (TCGA) Research Network.

scholarly journals Identification of RASSF1A Promoter Hypermethylation as a Biomarker for Hepatocellular Carcinoma

2020 ◽  
Author(s):  
Gang Xu ◽  
Xiaoxiang Zhou ◽  
Jiali Xing ◽  
Yao Xiao ◽  
Bao Jin ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Promoter Methylation ◽  
Meta Analysis ◽  
Promoter Hypermethylation ◽  
Analysis Data ◽  
Clinicopathological Characteristics ◽  
The Cancer Genome Atlas ◽  
Large Tumor ◽  
Kaplan Meier ◽  
Cancer Genome Atlas

Abstract Background: RAS association domain family protein 1A (RASSF1A) promoter hypermethylation is suggested to be linked to hepatocellular carcinoma (HCC), but the results remained controversial.Methods: We evaluated how RASSF1A promoter hypermethylation affects HCC risk and its clinicopathological characteristics through meta-analysis. Data on DNA methylation in HCC and relevant clinical data were also collected based on The Cancer Genome Atlas (TCGA) database to investigate the prognostic role of RASSF1A promoter hypermethylation in HCC.Results: Forty-four articles involving 4,777 individuals were enrolled in the pooled analyses. The RASSF1A promoter methylation rate was notably higher in the HCC cases than the non-tumor cases and healthy individuals, and was significantly related to hepatitis B virus (HBV) infection-positivity and large tumor size. Kaplan–Meier survival analysis revealed that HCC cases with RASSF1A promoter hypermethylation had worse outcomes. Receiver operating characteristic curves confirmed that RASSF1A promoter methylation may be a marker of HCC-related prognoses.Conclusions: RASSF1A promoter hypermethylation is a promising biomarker for the diagnosis of HCC from tissue and peripheral blood, and is an emerging therapeutic target against HCC.

scholarly journals Tumor microenvironment-aware, single-transcriptome prediction of microsatellite instability in colorectal cancer using meta-analysis

2021 ◽  
Author(s):  
Mi-Kyoung Seo ◽  
Hyundeok Kang ◽  
Sangwoo Kim
Keyword(s):  
Tumor Microenvironment ◽  
Microsatellite Instability ◽  
Therapeutic Strategy ◽  
Predictive Power ◽  
Meta Analysis ◽  
The Cancer Genome Atlas ◽  
Recursive Feature Elimination ◽  
Novel Approach ◽  
Cancer Genome Atlas ◽  
Cancer Types

Abstract Detecting microsatellite instability (MSI) in colorectal cancers (CRCs) is essential since it is therapeutic strategy determinant feature, including immunotherapy and chemotherapy. Yet, no attempt has been made to exploit transcriptomic profile and tumor microenvironment (TME) of it to unveil MSI status in CRC. Hence, we developed a novel TME-aware, single-transcriptome predictor of MSI for CRC, called MAP (Microsatellite instability Absolute single sample Predictor). MAP was developed utilizing recursive feature elimination-random forest with 466 CRC samples from The Cancer Genome Atlas, and its performance was validated in independent cohorts, including 1118 samples. MAP showed robustness and predictive power in predicting MSI status in CRC. Additional advantages for MAP were demonstrated through comparative analysis with existing MSI classifier and other cancer types. Our novel approach will provide access to untouched vast amounts of publicly available transcriptomic data and widen the door for MSI CRC research and be useful for gaining insights to help with translational medicine.

scholarly journals A Disintegrin and Metalloproteinase 9 (ADAM9) in Advanced Hepatocellular Carcinoma and Their Role as a Biomarker During Hepatocellular Carcinoma Immunotherapy

Cancers ◽  
2020 ◽  
Vol 12 (3) ◽  
pp. 745 ◽  
Author(s):  
Sooyeon Oh ◽  
YoungJoon Park ◽  
Hyun-Jung Lee ◽  
Jooho Lee ◽  
Soo-Hyeon Lee ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Clinical Response ◽  
Mrna Level ◽  
The Cancer Genome Atlas ◽  
Advanced Hepatocellular Carcinoma ◽  
Mrna Levels ◽  
Tumor Tissues ◽  
Cancer Genome Atlas ◽  
Group 2 ◽  
A Disintegrin And Metalloproteinase

The chemotherapeutics sorafenib and regorafenib inhibit shedding of MHC class I-related chain A (MICA) from hepatocellular carcinoma (HCC) cells by suppressing a disintegrin and metalloprotease 9 (ADAM9). MICA is a ligand for natural killer (NK) group 2 member D (NKG2D) and is expressed on tumor cells to elicit attack by NK cells. This study measured ADAM9 mRNA levels in blood samples of advanced HCC patients (n = 10). In newly diagnosed patients (n = 5), the plasma ADAM9 mRNA level was significantly higher than that in healthy controls (3.001 versus 1.00, p < 0.05). Among four patients treated with nivolumab therapy, two patients with clinical response to nivolumab showed significant decreases in fold changes of serum ADAM9 mRNA level from 573.98 to 262.58 and from 323.88 to 85.52 (p < 0.05); however, two patients with no response to nivolumab did not. Using the Cancer Genome Atlas database, we found that higher expression of ADAM9 in tumor tissues was associated with poorer survival of HCC patients (log-rank p = 0.00039), while ADAM10 and ADAM17 exhibited no such association. In addition, ADAM9 expression showed a positive correlation with the expression of inhibitory checkpoint molecules. This study, though small in sample size, clearly suggested that ADAM9 mRNA might serve as biomarker predicting clinical response and that the ADAM9-MICA-NKG2D system can be a good therapeutic target for HCC immunotherapy. Future studies are warranted to validate these findings.

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.

scholarly journals Dynamics and predicted drug response of a gene network linking dedifferentiation with β-catenin dysfunction in hepatocellular carcinoma

2018 ◽  
Author(s):  
Claude Gérard ◽  
Mickaël Di-Luoffo ◽  
Léolo Gonay ◽  
Stefano Caruso ◽  
Gabrielle Couchy ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Gene Regulatory Networks ◽  
Regulatory Networks ◽  
The Cancer Genome Atlas ◽  
Pharmacological Agents ◽  
Distinct Cell ◽  
Cancer Genome Atlas ◽  
Gene Regulatory ◽  
Using Data ◽  
Insight Into

AbstractAlterations of individual genes variably affect development of hepatocellular carcinoma (HCC), prompting the need to characterize the function of tumor-promoting genes in the context of gene regulatory networks (GRN). Here, we identify a GRN which functionally links LIN28B-dependent dedifferentiation with dysfunction of CTNNB1 (β-CATENIN). LIN28B and CTNNB1 form a functional GRN with SMARCA4 (BRG1), Let-7b, SOX9, TP53 and MYC. GRN activity is detected in HCC and gastrointestinal cancers; it negatively correlates with HCC prognosis and contributes to a transcriptomic profile typical of the proliferative class of HCC. Using data from The Cancer Genome Atlas and from transcriptomic, transfection and mouse transgenic experiments, we generated and validated a quantitative mathematical model of the GRN. The model predicts how the expression of GRN components changes when the expression of another GRN member varies or is inhibited by a pharmacological drug. The dynamics of GRN component expression reveal distinct cell states that can switch reversibly in normal condition, and irreversibly in HCC. We conclude that identification and modelling of the GRN provides insight into prognosis, mechanisms of tumor-promoting genes and response to pharmacological agents in HCC.

scholarly journals Identification of RASSF1A promoter hypermethylation as a biomarker for hepatocellular carcinoma

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Gang Xu ◽  
Xiaoxiang Zhou ◽  
Jiali Xing ◽  
Yao Xiao ◽  
Bao Jin ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Promoter Methylation ◽  
Meta Analysis ◽  
Promoter Hypermethylation ◽  
Analysis Data ◽  
Clinicopathological Characteristics ◽  
The Cancer Genome Atlas ◽  
Large Tumor ◽  
Kaplan Meier ◽  
Cancer Genome Atlas

Abstract Background RAS association domain family protein 1A (RASSF1A) promoter hypermethylation is suggested to be linked to hepatocellular carcinoma (HCC), but the results remained controversial. Methods We evaluated how RASSF1A promoter hypermethylation affects HCC risk and its clinicopathological characteristics through meta-analysis. Data on DNA methylation in HCC and relevant clinical data were also collected based on The Cancer Genome Atlas (TCGA) database to investigate the prognostic role of RASSF1A promoter hypermethylation in HCC. Results Forty-four articles involving 4777 individuals were enrolled in the pooled analyses. The RASSF1A promoter methylation rate was notably higher in the HCC cases than the non-tumor cases and healthy individuals, and was significantly related to hepatitis B virus (HBV) infection-positivity and large tumor size. Kaplan–Meier survival analysis revealed that HCC cases with RASSF1A promoter hypermethylation had worse outcomes. Receiver operating characteristic curves confirmed that RASSF1A promoter methylation may be a marker of HCC-related prognoses. Conclusions RASSF1A promoter hypermethylation is a promising biomarker for the diagnosis of HCC from tissue and peripheral blood, and is an emerging therapeutic target against HCC.

scholarly journals Identification of RASSF1A Promoter Hypermethylation as a Biomarker for Hepatocellular Carcinoma

2020 ◽  
Author(s):  
Gang Xu ◽  
Xiaoxiang Zhou ◽  
Jiali Xing ◽  
Yao Xiao ◽  
Bao Jin ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Promoter Methylation ◽  
Meta Analysis ◽  
Promoter Hypermethylation ◽  
Analysis Data ◽  
Clinicopathological Characteristics ◽  
The Cancer Genome Atlas ◽  
Large Tumor ◽  
Kaplan Meier ◽  
Cancer Genome Atlas

Abstract Background: RAS association domain family protein 1A (RASSF1A) promoter hypermethylation is suggested to be linked to hepatocellular carcinoma (HCC), but the results remained controversial. Methods: We evaluated how RASSF1A promoter hypermethylation affects HCC risk and its clinicopathological characteristics through meta-analysis. Data on DNA methylation in HCC and relevant clinical data were also collected based on The Cancer Genome Atlas (TCGA) database to investigate the prognostic role of RASSF1A promoter hypermethylation in HCC. Results: Forty-four articles involving 4,777 cases were enrolled in the pooled analyses. The RASSF1A promoter methylation rate was notably higher in the HCC cases than the non-tumor cases and healthy individuals, and was significantly related to hepatitis B virus (HBV) infection-positivity and large tumor size. Kaplan–Meier survival analysis revealed that HCC cases with RASSF1A promoter hypermethylation had worse outcomes. Receiver operating characteristic curves confirmed that RASSF1A promoter methylation may be a marker of HCC-related prognoses. Conclusions: RASSF1A promoter hypermethylation is a promising biomarker for the diagnosis of HCC from tissue and peripheral blood, and is an emerging therapeutic target against HCC.

scholarly journals CYSTM1: A Novel Biomarker for Hepatocellular Carcinoma Prognosis

2021 ◽  
Author(s):  
Jun Du ◽  
Jinguo Wang
Keyword(s):  
Hepatocellular Carcinoma ◽  
Poor Prognosis ◽  
Early Stage ◽  
Human Tumor ◽  
The Cancer Genome Atlas ◽  
Data Set ◽  
Kaplan Meier ◽  
Cancer Genome Atlas ◽  
Cox Proportional Hazard Regression ◽  
The Relationship

Abstract Background: The expression and molecular mechanism of cysteine rich transmembrane module containing 1 (CYSTM1) in human tumor cells remains unclear. The aim of this study was to determine whether CYSTM1 could be used as a potential prognostic biomarker for hepatocellular carcinoma (HCC).Methods: We first demonstrated the relationship between CYSTM1 expression and HCC in various public databases. Secondly, Kaplan–Meier analysis and Cox proportional hazard regression model were performed to evaluate the relationship between the expression of CYSTM1 and the survival of HCC patients which data was downloaded in the cancer genome atlas (TCGA) database. Finally, we used the expression data of CYSTM1 in TCGA database to predict CYSTM1-related signaling pathways through bioinformatics analysis.Results: The expression level of CYSTM1 in HCC tissues was significantly correlated with T stage (p = 0.039). In addition, Kaplan–Meier analysis showed that the expression of CYSTM1 was significantly associated with poor prognosis in patients with early-stage HCC (p = 0.003). Multivariate analysis indicated that CYSTM1 is a potential predictor of poor prognosis in HCC patients (p = 0.036). The results of biosynthesis analysis demonstrated that the data set of CYSTM1 high expression was mainly enriched in neurodegeneration and oxidative phosphorylation pathways.Conclusion: CYSTM1 is an effective biomarker for the prognosis of patients with early-stage HCC and may play a key role in the occurrence and progression of HCC.

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