Mouse Hepatocellular Carcinoma Study
Ontology highlight
ABSTRACT:
ORGANISM(S): Mus musculus
PROVIDER: GSE1897 | GEO | 2004/10/28
SECONDARY ACCESSION(S): PRJNA90983
REPOSITORIES: GEO
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Project description:Genetically modified mice have been extensively used for analyzing the molecular events that occur during the tumor development. However, in many cases, if not all, it is uncertain to what extent the mouse models reproduce features observed in the corresponding human conditions. This is due largely to lack of precise methods for direct and comprehensive comparison at the molecular level of the mouse and human tumors. We used global gene expression patterns of 68 hepatocellular carcinoma (HCC) from 7 different mouse models and 91 human HCC from pre-defined subclasses to obtain direct comparison of the molecular features of mouse and human HCC. Total RNAs were isolated from frozen liver tissue using CsCl density gradient centrifugation methods. Total RNA from the livers of 10 wild type mice were pooled and used as reference in entire microarray experiments. To obtain gene expression profile data from four transgenic HCC mouse models, 20 μg of total RNAs from tissues were used to drive fluorescently (Cy-5 or Cy-3) labeled cDNA. At least two hybridizations were carried out for each tissue using dye-swap strategy to eliminate dye labeling bias.
2004-10-28 | E-GEOD-1897 | biostudies-arrayexpress
Project description:Global gene expression patterns of 91 human hepatocellular carcinomas (HCC) were analyzed to define the molecular characteristics of the tumors and to test the prognostic value of the expression profiles. Total RNAs were isolated from frozen liver tissue using CsCl density gradient centrifugation methods. Total RNA from 18 normal livers were pooled and used as reference in entire microarray experiments. To obtain gene expression profile data from human HCC, 20 μg of total RNAs from tissues were used to drive fluorescently (Cy-5 or Cy-3) labeled cDNA. At least two hybridizations were carried out for each tissue using dye-swap strategy to eliminate dye labeling bias. Unsupervised classification methods revealed two distinctive subclasses of HCC that are highly associated with survival of the patients. This association was validated by five independent supervised learning methods. Genes most strongly associated with survival were identified by using the Cox proportional hazards survival analysis. This approach identified a limited number of genes that accurately predicted the length of survival and provides new molecular insight into the pathogenesis of HCC. Tumors from the low survival subclass have strong cell proliferation and anti-apoptosis gene expression signatures. In addition, the low survival subclass displayed higher expression of genes involved in ubiquitination and histone modification suggesting an etiological involvement of these processes in accelerating the progression of HCC. The biological differences identified in the HCC subclasses should provide an attractive source for the development of therapeutic targets (e.g. HIF1a) for selective treatment(s) of HCC patients. Keywords: other
2004-10-28 | GSE1898 | GEO
Project description:The variability in the prognosis of hepatocellular carcinoma (HCC) patients suggests that HCC may comprise several distinctive biological phenotypes. These phenotypes may result from different neoplastic pathways during the tumorigenesis and/or from a different cell of origin. Here we address if the transcriptional characteristics of the HCC would provide insight into the cellular origin of the tumors. We integrated gene expression data from rat fetal hepatoblasts and adult hepatocytes, HCC from mouse models, and human HCC. The HCC patients who shared gene expression patterns with fetal hepatoblasts showed extremely poor prognosis when compared with those lacking the hepatoblast signature. The gene expression program that distinguishes this novel subtype from the rest of HCC includes well known markers of hepatic oval cells, suggesting that HCC in this subtype may arise from hepatic progenitor cells. Two independent gene network analyses of the gene expression signature characteristic for the tumors sharing the hepatoblast expression patterns revealed that activation of AP-1 transcription factors might play key roles in tumor development in the newly identified HCC subtype. In addition, by applying hepatoblast-specific and genome-wide global signatures, HCC patients were further stratified into three distinct subgroups with a significant association with overall survival and recurrence. Total RNAs from 19 normal livers were pooled and used as the reference for all microarray experiments. To obtain gene expression profile data from 49 human HCC, 20 µg of total RNAs from tissues were used to drive fluorescently (Cy-5 or Cy-3) labeled cDNA. At least two hybridizations were carried out for each tissue using a dye-swap strategy to eliminate dye labeling bias.
2010-07-01 | E-GEOD-4024 | biostudies-arrayexpress
Project description:Global gene expression patterns of 91 human hepatocellular carcinomas (HCC) were analyzed to define the molecular characteristics of the tumors and to test the prognostic value of the expression profiles. Total RNAs were isolated from frozen liver tissue using CsCl density gradient centrifugation methods. Total RNA from 18 normal livers were pooled and used as reference in entire microarray experiments. To obtain gene expression profile data from human HCC, 20 μg of total RNAs from tissues were used to drive fluorescently (Cy-5 or Cy-3) labeled cDNA. At least two hybridizations were carried out for each tissue using dye-swap strategy to eliminate dye labeling bias. Unsupervised classification methods revealed two distinctive subclasses of HCC that are highly associated with survival of the patients. This association was validated by five independent supervised learning methods. Genes most strongly associated with survival were identified by using the Cox proportional hazards survival analysis. This approach identified a limited number of genes that accurately predicted the length of survival and provides new molecular insight into the pathogenesis of HCC. Tumors from the low survival subclass have strong cell proliferation and anti-apoptosis gene expression signatures. In addition, the low survival subclass displayed higher expression of genes involved in ubiquitination and histone modification suggesting an etiological involvement of these processes in accelerating the progression of HCC. The biological differences identified in the HCC subclasses should provide an attractive source for the development of therapeutic targets (e.g. HIF1a) for selective treatment(s) of HCC patients.
2004-10-28 | E-GEOD-1898 | biostudies-arrayexpress
Project description:Hepatocellular carcinoma (HCC) is a deadly disease, often unnoticed till the late stages, where treatment options become limited. Thus, there is a critical need to identify early biomarkers for detection of the developing HCC, as well as molecular pathways that would be amenable to therapeutic intervention. While efforts using human serum and tissues from late stage patients have been undertaken, progress has been limited. We have therefore explored the possibility of utilizing established mouse models for the discovery of biomarkers, as well as to understand in a systematic manner the molecular pathways that are progressively deregulated by the various etiological factors in contributing to HCC formation. As an initial effort, we have used the Hepatitis B surface antigen (HBsAg) transgenic mice as a hepatitis model, which have been exposed to aflatoxin B1 (AFB1). In this report, we present the initial findings from a extensive longitudinal study, which confirms the synergistic effect of both these etiological factors, with a gender bias towards male mice. Tumors from the mouse models were validated both histologically as well as by molecular transcriptome analysis by comparison with human HCCs. In addition, using these models, we have identified carnitine as a novel biomarker for HCC development, which was again validated using human HCC samples. Conclusion: This study therefore highlights the utility of these mouse models in identifying biomarkers for detection of human HCCs, as well as for the systematic analysis of molecular pathways that are affected by various etiological agents during the progression of HCC from an untransformed hepatocyte, which could provide novel options for targeted therapy. liver obtained from Mus musculus which was intraperitoneally injected with AFB/oil at Day 7 and sacrificed at 15 month age. We intend to compare molecular transcriptome analysis of mouse HCC with human HCCs.
2014-01-15 | E-GEOD-54054 | biostudies-arrayexpress
Project description:Two groupsHepatocellular carcinoma (HCC) is a heterogeneous malignant disease with molecularly and clinically distinct subtypes discovered in genomic studies. Mouse models are commonly used as preclinical model to study hepatocarcinogenesis, but how well these models recapitulate molecular subtypes of human HCC is unclear. Thus, we aimed to correlate nine mouse HCC models with clinical subtypes of human HCC by systematically comparing their genomic data. By integrating nine molecularly and clinically defined genomic signatures for human HCC with genomic data from nine mouse HCC models, we identified the mouse models that best resembled subtypes of human HCC and determined the clinical relevance of each model. Mst1/2 KO, Sav1 KO, and SV40 T antigen mouse model best recapitulated poor prognostic subtypes of human HCC, whereas the Myc transgenic model best resembled human HCCs with more favorable prognoses. The Myc model was also significantly associated with activation of β-catenin. E2f1, E2f1/Myc, E2f1/Tgfa, and diethylnitrosamine (DENA)-induced models were heterogeneous and were unequally split to poor and favorable prognoses. Most interestingly, Mst1/2 KO and Sav1 KO models best resembles human HCC with hepatic stem cell characteristics. When we applied a genomic predictor for immunotherapy, the six-gene interferon-γ (IFNG6) score, Mst1/2 KO, Sav1 KO, SV40, and DEN models were predicted to be the least responsive to immunotherapy. Further analysis of immune checkpoint genes showed that high expression of immune inhibitory genes (Cd276 and Pvrl2) in Mst1/2 KO, Sav1 KO, SV40 and low expression of immune stimulatory genes (Cd86) in DENA model might be accountable for lack of predictive response to immunotherapy. Conclusion: Most of the mouse models effectively recapitulated molecular characteristics of human subtypes, including response to immunotherapy. of samples are included: 1.SKOV3-ip1 2.SKOV3-OM3. Gene expression profiles of SKOV3-OM3 cells were compared to that of parental SKOV3 ip1 cells.
2019-01-01 | GSE110627 | GEO
Project description:The transcriptome approach was used to characterize the of the global change in Synechocystis gene expression in response to continuous exposure to cadmium (50 microM). Total RNA were isolated from stressed and unstressed cells, reverse-transcribed, differentially labelled (dye swapped), hybridized together (stressed versus unstressed samples) and analyzed with DNA glass microarrays (two slides per each time point) (Custom-commercial array : IntelliGeneTM CyanoCHIP version 2.0, TAKARA). To identify differentially expressed genes, the median of the normalized ratio of Cy5/Cy3 intensity was calculated for each spot of the replicated dye-swap. The results of the analysis were carefully examined to exclude the dye effect between the 2 Cy-swapped arrays. Keywords: stress responses
2005-12-07 | GSE3718 | GEO
Project description:In this study, we identified and validated a molecular classification of hepatocellular carcinoma (HCC) based on 42 fatty acid degradation (FAD) genes in clinical samples. We further searched PubMed for the RNA sequencing datasets of mouse models to identify the FAD subtypes in mouse HCC models. A total of 90 samples were collected from five publicly available datasets including 11 mouse HCC models. In addition, the transcriptome sequencing data of 8 samples from our two mouse models (NRAS.MYC.ND and AKT1.MYC.KD) were also included. This dataset aims to explore the transcriptomic characteristics of these two models.
2023-05-01 | GSE202070 | GEO
Project description:The transcriptome approach was used to characterize of the global change (2 time points) in Synechocystis gene expression in response to continuous exposure to iron excess (17 mM), compared to standard medium (17 microM). For each time point, total RNA were isolated from stressed and unstressed cells, reverse-transcribed, differentially labelled (dye swapped), hybridized together (stressed versus unstressed samples) and analyzed with DNA glass microarrays (two slides per each time point) (Custom-commercial array : IntelliGeneTM CyanoCHIP version 2.0, TAKARA). To identify differentially expressed genes, the median of the normalized ratio of Cy5/Cy3 intensity was calculated for each spot of the replicated dye-swap. The results of the analysis were carefully examined to exclude the dye effect between the 2 Cy-swapped arrays. Keywords: stress responses
2005-12-07 | GSE3715 | GEO
Project description:The transcriptome approach was used to characterize the kinetics (5 time points) of the global change in Synechocystis gene expression in response to continuous exposure to H2O2 (3 mM). For each time point, total RNA were isolated from stressed and unstressed cells, reverse-transcribed, differentially labelled (dye swapped), hybridized together (stressed versus unstressed samples) and analyzed with DNA glass microarrays (two slides per each time point) (Custom-commercial array : IntelliGeneTM CyanoCHIP version 2.0, TAKARA). To identify differentially expressed genes, the median of the normalized ratio of Cy5/Cy3 intensity was calculated for each spot of the replicated dye-swap. The results of the analysis were carefully examined to exclude the dye effect between the 2 Cy-swapped arrays. Keywords: time course, stress responses
2005-12-07 | GSE3703 | GEO