A blood-based three-gene signature for the non-invasive detection of early human hepatocellular carcinoma

Shi, Ming; Chen, Min Shan; Sekar, Karthik; Tan, Chee‐Kiat; Ooi, London Lucien; Hui, Kam M.

doi:10.1016/j.ejca.2013.11.026

Cited by 75 publications

(67 citation statements)

References 28 publications

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“…Furthermore, functional enrichment analysis and protein-protein interaction (PPI) network analysis were performed. In contrast to the previous studies of Shi et al (17) and Jiang et al (18), which used the same dataset to identify genes and pathways associated with HCC, the present study also investigated gene and drug interactions using the comparative toxicogenomics database (CTD). The aim of the present study was to identify key genes and pathways associated with HCC progression and investigate potential compounds leading to HCC carcinogenesis.…”

Section: Introductionmentioning

confidence: 85%

“…T he GSE 49515 dataset originally derived from the study by Shi et al (17) was obtained from the Gene Expression Omnibus database (www.ncbi.nlm.nih.gov/geo/). The dataset contains the expression profile of 26 samples of peripheral blood mononuclear cells, including 10 HCC samples, 3 pancreatic carcinoma samples, 3 gastric carcinoma samples and 10 healthy samples.…”

Section: Methodsmentioning

confidence: 99%

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Analysis of expression profile data identifies key genes and pathways in hepatocellular carcinoma

Jiang¹,

Hao²

2017

Oncol Lett

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Abstract. The aims of the present study were to identify key genes and pathways associated with hepatocellular carcinoma (HCC) progression and predict compounds potentially associated with this type of carcinogenesis. The gene expression profile data of the GSE49515 dataset was obtained from the Gene Expression Omnibus database. The limma software package was used to identify the differentially expressed genes (DEGs). Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were performed using the Biological Networks Gene Ontology tool and the Database for Annotation, Visualization and Integrated Discovery, respectively. The Michigan Molecular Interactions database plugin within the Cytoscape software platform was used to perform protein-protein interaction (PPI) network analysis. Chemical-gene interaction data for HCC were obtained from the Comparative Toxicogenomics Database to evaluate the associations between drugs and specific genes. A total of 302 DEGs, including 231 downregulated and 71 upregulated, were identified. Cytokine-cytokine receptor interaction and chemokine signaling were the significantly enriched pathways. Additionally, PPI network analysis indicated a total of 13 highest degree hub nodes, including FBJ murine osteosarcoma viral oncogene homolog (FOS) and DNA damage-inducible transcript 3 protein (DDIT3). Chemical-gene interaction analysis revealed that FUN and FOS were targeted by >500 compounds, while >200 genes were targeted by 2,3,7,8-tetrachlorodibenzodioxin and benzo(α)pyrene. In conclusion, the present study demonstrated that FOS, DDIT3, the cytokine-cytokine receptor interaction pathway and the chemokine signaling pathway may be key genes and pathways associated with the development of HCC. Furthermore, exposure to 2,3,7,8-tetrachlorodibenzodioxin or benzo(α)pyrene may lead to hepatocarcinogenesis.

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Section: Introductionmentioning

confidence: 85%

Section: Methodsmentioning

confidence: 99%

Analysis of expression profile data identifies key genes and pathways in hepatocellular carcinoma

Jiang¹,

Hao²

2017

Oncol Lett

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“…Gene expression profiling of peripheral blood mononuclear cells in HCC patients using microarrays and bioinformatics-driven analysis of the data has identified a blood-based signature of three genes, namely Chemokine (C-X-C motif) receptor 2 (CXCR2), C-C chemokine receptor type 2 (CCR2) and E1A-Binding Protein P400 (EP400), that predicts HCC with an AUC of 0.96 yielding at a sensitivity of 93% with a specificity of 89% [43] . High-throughput metabolomics technologies with the comprehensive analysis of small molecular metabolites may additionally identify serum metabolic profiles that can be used as diagnostic biomarkers.…”

Section: Role Of Biomarkers In Surveillance and Diagnosismentioning

confidence: 99%

Current biomarkers for hepatocellular carcinoma: Surveillance, diagnosis and prediction of prognosis

Schütte

Schulz

Link

et al. 2014

WJH

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“…To now, the future of ramucirumab in the treatment of HCC is still unclear. HCC patients expressing high levels of AFP are thought to represent a specific subgroup of patients carrying a disease with a peculiar gene signature [76,77]. Despite the results observed in the REACH trial suggest the hypothesis that this specific subgroup of HCC patients may selectively benefit from ramucirumab, a prospective validation in patients with baseline high levels of AFP is warranted.…”

Section: Expert Opinionmentioning

confidence: 88%

The coming of ramucirumab in the landscape of anti-angiogenic drugs: potential clinical and translational perspectives

Calvetti

Pilotto

Carbognin

et al. 2015

Expert Opinion on Biological Therapy

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A blood-based three-gene signature for the non-invasive detection of early human hepatocellular carcinoma

Cited by 75 publications

References 28 publications

Analysis of expression profile data identifies key genes and pathways in hepatocellular carcinoma

Analysis of expression profile data identifies key genes and pathways in hepatocellular carcinoma

Current biomarkers for hepatocellular carcinoma: Surveillance, diagnosis and prediction of prognosis

The coming of ramucirumab in the landscape of anti-angiogenic drugs: potential clinical and translational perspectives

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