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 Master Regulators, Regulatory Networks, and Pathways of Glioblastoma Subtypes

2014 ◽  
Vol 13s3 ◽  
pp. CIN.S14027 ◽  
Author(s):  
Serdar Bozdag ◽  
Aiguo Li ◽  
Mehmet Baysan ◽  
Howard A. Fine
Keyword(s):  
Gene Regulatory Networks ◽  
Regulatory Networks ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Gene Set Enrichment ◽  
Master Regulators ◽  
Cancer Genome Atlas ◽  
Gene Regulatory ◽  
Comprehensive Study

Glioblastoma multiforme (GBM) is the most common malignant brain tumor. GBM samples are classified into subtypes based on their transcriptomic and epigenetic profiles. Despite numerous studies to better characterize GBM biology, a comprehensive study to identify GBM subtype-specific master regulators, gene regulatory networks, and pathways is missing. Here, we used FastMEDUSA to compute master regulators and gene regulatory networks for each GBM subtype. We also ran Gene Set Enrichment Analysis and Ingenuity Pathway Analysis on GBM expression dataset from The Cancer Genome Atlas Project to compute GBM- and GBM subtype-specific pathways. Our analysis was able to recover some of the known master regulators and pathways in GBM as well as some putative novel regulators and pathways, which will aide in our understanding of the unique biology of GBM subtypes.

scholarly journals Upregulation and cell specificity of C4 genes are derived from ancestral C3 gene regulatory networks

2020 ◽  
Author(s):  
Pallavi Singh ◽  
Sean R. Stevenson ◽  
Ivan Reyna-Llorens ◽  
Gregory Reeves ◽  
Tina B. Schreier ◽  
...  
Keyword(s):  
Transcription Factors ◽  
Gene Regulatory Networks ◽  
Regulatory Networks ◽  
Cell Types ◽  
Chromatin Accessibility ◽  
Transcript Accumulation ◽  
Specific Expression ◽  
Cell Specificity ◽  
Distinct Cell ◽  
Gene Regulatory

ABSTRACTThe efficient C4 pathway is based on strong up-regulation of genes found in C3 plants, but also compartmentation of their expression into distinct cell-types such as the mesophyll and bundle sheath. Transcription factors associated with these phenomena have not been identified. To address this, we undertook genome-wide analysis of transcript accumulation, chromatin accessibility and transcription factor binding in C4Gynandropsis gynandra. From these data, two models relating to the molecular evolution of C4 photosynthesis are proposed. First, increased expression of C4 genes is associated with increased binding by MYB-related transcription factors. Second, mesophyll specific expression is associated with binding of homeodomain transcription factors. Overall, we conclude that during evolution of the complex C4 trait, C4 cycle genes gain cis-elements that operate in the C3 leaf such that they become integrated into existing gene regulatory networks associated with cell specificity and photosynthesis.

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 Regulation of PD1 signaling is associated with prognosis in glioblastoma multiforme

2021 ◽  
Author(s):  
Camila Lopes-Ramos ◽  
Tatiana Belova ◽  
Tess Brunner ◽  
John Quackenbush ◽  
Marieke L. Kuijjer
Keyword(s):  
Gene Regulatory Networks ◽  
Transcriptional Repression ◽  
Regulatory Networks ◽  
Treatment Options ◽  
Neoadjuvant Treatment ◽  
The Cancer Genome Atlas ◽  
Therapeutic Interventions ◽  
Short Term ◽  
Term Survival ◽  
Gene Regulatory

Glioblastoma is an aggressive cancer of the brain and spine. While analysis of glioblastoma ‘omics data has somewhat improved our understanding of the disease, it has not led to direct improvement in patient survival. Cancer survival is often characterized by differences in expression of particular genes, but the mechanisms that drive these differences are generally unknown. We therefore set out to model the regulatory mechanisms that associate with glioblastoma survival. We inferred individual patient gene regulatory networks using data from two different expression platforms from The Cancer Genome Atlas (n=522 and 431). We performed a comparative network analysis between patients with long- and short-term survival, correcting for patient age, sex, and neoadjuvant treatment status. We identified seven pathways associated with survival, all of which were involved in immune system signaling. Differential regulation of PD1 signaling was validated in an independent dataset from the German Glioma Network (n=70). We found that transcriptional repression of genes in this pathway—for which treatment options are available—was lost in short-term survivors and that this was independent of mutation burden and only weakly associated with T-cell infiltrate. These results provide a new way to stratify glioblastoma patients that uses network features as biomarkers to predict survival, and identify new potential therapeutic interventions, thus underscoring the value of analyzing gene regulatory networks in individual cancer patients.

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