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Gene expression profiling analysis of hepatocellular carcinoma.

ABSTRACT: BACKGROUND: Primary hepatocellular carcinoma (HCC) is one of the most common malignancies in the world. However, the molecular pathogenesis of HCC is not well-understood, and the prognosis for patients with HCC remains very poor. METHODS: To disclose detailed genetic mechanisms in hepatocellular carcinoma (HCC) with a view toward development of novel therapeutic targets, we analyzed expression profiles HCCs and their corresponding noncancerous tissues by using bioinformatics method. RESULTS: In this paper, we report the identification of genes whose expression has been altered and the changed bio-pathways during hepatocarcinogenesis. Hepatoma cells infect intracellular and intercellular signal transduction through Focal adhesion and cause abnormal expression of important intracellular signaling pathway. In addition, it is worth mentioning that some small molecules still restored to the state similar to normal cells, such as bambuterol and lovastatin. This member gene set would serve as a pool of lead gene targets for the identification and development of novel diagnostic and therapeutic biomarkers to greatly improve the clinical management of HCC patients with different risks of recurrence after curative partial hepatectomy. CONCLUSIONS: The study has great significance for gene therapy and pharmacotherapy and provides a new treatment entry point and a potential new clinical drug for HCC patients.

SUBMITTER: Kong D

PROVIDER: S-EPMC4177135 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

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Gene expression profiling analysis of hepatocellular carcinoma.

Kong Deyong D Chen Heming H Chen Weiqun W Liu Shuiyi S Wang Hui H Wu Tangwei T Lu Hongda H Kong Qingzhi Q Huang Xiaodong X Lu Zhongxin Z

European journal of medical research 20131114

<h4>Background</h4>Primary hepatocellular carcinoma (HCC) is one of the most common malignancies in the world. However, the molecular pathogenesis of HCC is not well-understood, and the prognosis for patients with HCC remains very poor.<h4>Methods</h4>To disclose detailed genetic mechanisms in hepatocellular carcinoma (HCC) with a view toward development of novel therapeutic targets, we analyzed expression profiles HCCs and their corresponding noncancerous tissues by using bioinformatics method. ...[more]

PMID: 24229431

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Project description:Objective: The study aimed to elucidate the significance of CLEC4G, CAMK2β, SLC22A1, CBFA2T3, and STAB2 in the prognosis of hepatocellular carcinoma (HCC) patients and their associated molecular biological characteristics. Additionally, the research sought to identify new potential biomarkers with therapeutic and diagnostic relevance for clinical applications. Methods and Materials: We utilized a publicly available high throughput phosphoproteomics and proteomics data set of HCC to focus on the analysis of 12 downregulated phosphoproteins in HCC. Our approach integrates bioinformatic analysis with pathway analysis, encompassing gene ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, and the construction of a protein-protein interaction (PPI) network. Results: In total, we quantified 11547 phosphorylation sites associated with 4043 phosphoproteins from a cohort of 159 HCC patients. Within this extensive data set, our specific focus was on 19 phosphorylation sites displaying significant downregulation (log2 FC ≤ -2 with p-values < 0.0001). Remarkably, our investigation revealed distinct pathways exhibiting differential regulation across multiple dimensions, including the genomic, transcriptomic, proteomic, and phosphoproteomic levels. These pathways encompass a wide range of critical cellular processes, including cellular component organization, cell cycle control, signaling pathways, transcriptional and translational control, and metabolism. Furthermore, our bioinformatics analysis unveiled noteworthy insights into the subcellular localizations, biological processes, and molecular functions associated with these proteins and phosphoproteins. Within the context of the PPI network, we identified 12 key genes CLEC4G, STAB2, ADH1A, ADH1B, CAMK2B, ADH4, CHGB, PYGL, ADH1C, AKAP12, CBFA2T3, and SLC22A1 as the top highly interconnected hub genes. Conclusions: The findings related to CLEC4G, ADH1B, SLC22A1, CAMK2β, CBFA2T3, and STAB2 indicate their reduced expression in HCC, which is associated with an unfavorable prognosis. Furthermore, the results of KEGG and GO pathway analyses suggest that these genes may impact liver cancer by engaging various targets and pathways, ultimately promoting the progression of hepatocellular carcinoma. These results underscore the significant potential of CLEC4G, ADH1B, SLC22A1, CAMK2β, CBFA2T3, and STAB2 as key contributors to HCC development and advancement. This insight holds promise for identifying therapeutic targets and charting research avenues to enhance our understanding of the intricate molecular mechanisms underlying hepatocellular carcinoma.

Project description:BACKGROUND:Liver cirrhosis is the most important risk factor for hepatocellular carcinoma (HCC) but the role of liver disease aetiology in cancer development remains under-explored. We investigated global gene expression profiles from HCC arising in different liver diseases to test whether HCC development is driven by expression of common or different genes, which could provide new diagnostic markers or therapeutic targets. METHODOLOGY AND PRINCIPAL FINDINGS:Global gene expression profiling was performed for 4 normal (control) livers as well as 8 background liver and 7 HCC from 3 patients with hereditary haemochromatosis (HH) undergoing surgery. In order to investigate different disease phenotypes causing HCC, the data were compared with public microarray repositories for gene expression in normal liver, hepatitis C virus (HCV) cirrhosis, HCV-related HCC (HCV-HCC), hepatitis B virus (HBV) cirrhosis and HBV-related HCC (HBV-HCC). Principal component analysis and differential gene expression analysis were carried out using R Bioconductor. Liver disease-specific and shared gene lists were created and genes identified as highly expressed in hereditary haemochromatosis HCC (HH-HCC) were validated using quantitative RT-PCR. Selected genes were investigated further using immunohistochemistry in 86 HCC arising in liver disorders with varied aetiology. Using a 2-fold cut-off, 9 genes were highly expressed in all HCC, 11 in HH-HCC, 270 in HBV-HCC and 9 in HCV-HCC. Six genes identified by microarray as highly expressed in HH-HCC were confirmed by RT qPCR. Serine peptidase inhibitor, Kazal type 1 (SPINK1) mRNA was very highly expressed in HH-HCC (median fold change 2291, p?=?0.0072) and was detected by immunohistochemistry in 91% of HH-HCC, 0% of HH-related cirrhotic or dysplastic nodules and 79% of mixed-aetiology HCC. CONCLUSION:HCC, arising from diverse backgrounds, uniformly over-express a small set of genes. SPINK1, a secretory trypsin inhibitor, demonstrated potential as a diagnostic HCC marker and should be evaluated in future studies.

Project description:Renal cell carcinoma (RCC) is the most common cancer in adult kidney. The accuracy of current diagnosis and prognosis of the disease and the effectiveness of the treatment for the disease are limited by the poor understanding of the disease at the molecular level. To better understand the genetics and biology of RCC, we profiled the expression of 7,129 genes in both clear cell RCC tissue and cell lines using oligonucleotide arrays.Total RNAs isolated from renal cell tumors, adjacent normal tissue and metastatic RCC cell lines were hybridized to affymatrix HuFL oligonucleotide arrays. Genes were categorized into different functional groups based on the description of the Gene Ontology Consortium and analyzed based on the gene expression levels. Gene expression profiles of the tissue and cell line samples were visualized and classified by singular value decomposition. Reverse transcription polymerase chain reaction was performed to confirm the expression alterations of selected genes in RCC.Selected genes were annotated based on biological processes and clustered into functional groups. The expression levels of genes in each group were also analyzed. Seventy-four commonly differentially expressed genes with more than five-fold changes in RCC tissues were identified. The expression alterations of selected genes from these seventy-four genes were further verified using reverse transcription polymerase chain reaction (RT-PCR). Detailed comparison of gene expression patterns in RCC tissue and RCC cell lines shows significant differences between the two types of samples, but many important expression patterns were preserved.This is one of the initial studies that examine the functional ontology of a large number of genes in RCC. Extensive annotation, clustering and analysis of a large number of genes based on the gene functional ontology revealed many interesting gene expression patterns in RCC. Most notably, genes involved in cell adhesion were dominantly up-regulated whereas genes involved in transport were dominantly down-regulated. This study reveals significant gene expression alterations in key biological pathways and provides potential insights into understanding the molecular mechanism of renal cell carcinogenesis.

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Gene expression profiling analysis of hepatocellular carcinoma.

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Gene expression profiling analysis of hepatocellular carcinoma.

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