Project description:This SuperSeries is composed of the following subset Series: GSE9843: Gene expression profiling of 91 hepatocellular carcinomas with hepatitis C virus etiology, Samples with "vascular invasion: Yes/No" were included in the study. GSE20017: Gene Signature to Identify Vascular Invasion in Hepatocellular Carcinoma Refer to individual Series
Project description:Background: The pathogenesis of hepatitis B virus (HBV)-caused hepatocellular carcinoma (HCC) is complex and not fully understood. In clinical, the effective prevention and treatment of HCC rely on the accurate diagnosis. We developed a biology network approach to investigate the potential mechanisms and biomarkers of each stages from HBV infection to HCC. Methods Global gene profiling of healthy individuals (HC), HBV carriers (HBVC), chronic hepatitis B patients (CHB), liver cirrhosis (LC) and HCC was analyzed by gene array. Differentially expressed genes (DEG) were found by RVM (Random variance model) corrective ANOVA and STC (Series Test of Cluster) analysis.
Project description:Saliva is rich in proteins, DNA, RNA and microorganisms, and can be regarded as a biomarker library. In order to explore a noninvasive and simple means of early screening for liver cancer, proteomics was used to screen salivary markers of hepatitis B associated liver cancer. We used mass spectrometry coupled isobaric tags for relative and absolute quantitation (iTRAQ)-technology to identify differentially expressed proteins (DEPs). Western blot, immunohistochemistry and enzyme linked immunosorbent assay were used to detect marker expression of in tissues and saliva. Statistical analysis was used to analyze the diagnostic efficacy of the markers was analyzed through statistical analyses. By comparing the hepatocellular carcinoma (HCC) group with non-HCC groups, we screened out 152 salivary DEPs. We found orosomucoid 1(ORM1) had significantly higher expression in saliva of HCC patients compared with non-HCC groups (p<0.001) and the expression of ORM1 in liver cancer tissues was significantly higher than that in adjacent normal tissues(p<0.001). The combination of salivary ORM1 and alpha-fetoprotein (AFP) showed reasonable specificities and sensitivities for detecting HCC. In a word, salivary ORM1 as a new biomarker of hepatitis B associated hepatocellular carcinoma, combination of salivary ORM1 and AFP as an improved diagnostic tool for hepatocellular carcinoma.
Project description:Using CapitalBio Technology Human CircRNA Array v2 (4x180K) microarray, we compared the expression of circular RNAs in the plasma from five hepatitis B virus-related hepatocellular carcinoma patients and five chronic hepatitis B patients.
Project description:MicroRNAs (miRNAs) exhibit essential regulatory functions related to cell growth, apoptosis, development and differentiation. Dysregulated expression of miRNAs is associated with a wide variety of human diseases. As such miRNA signatures are valuable as biomarkers for disease and for making treatment decisions. Hepatitis B virus (HBV) is a major risk factor for hepatocellular carcinoma (HCC). Here we screened for miRNAs in chronic HBV associated HCC. To evaluate the effect of HBV infection on the change in expression of miRNAs, 12 pairs of samples from HCC and non-tumor tissues (including 6 HBV-positive HCC and 6 HBV-negative HCC and their non-tumor tissues) were collected. The extracted RNAs were evaluated to detect the expression of miRNAs. Using ANOVA to screen the differential expression of miRNAs at P-value ⤠0.01, fold change ⥠2 or ⤠0.5, 225 miRNAs were detected.
Project description:Gene expression profiling of hepatocellular carcinoma (HCC) and background liver has been studied extensively; however, the relationship between the gene expression profiles of different lesions has not been assessed. We examined the expression profiles of 34 HCC specimens (17 hepatitis B virus [HBV]-related and 17 hepatitis C virus [HCV]-related) and 71 non-tumor liver specimens (36 chronic hepatitis B [CH-B] and 35 chronic hepatitis C [CH-C]) using an in-house cDNA microarray consisting of liver-predominant genes. Graphical Gaussian modeling (GGM) was applied to elucidate the interactions of gene clusters among the HCC and non-tumor lesions. Gene expression profiling of HCC and non-tumor lesions revealed the predisposing changes of gene expression in HCC. This approach has potential for the early diagnosis and possible prevention of HCC. We examined the expression profiles of 34 HCC specimens (17 hepatitis B virus [HBV]-related and 17 hepatitis C virus [HCV]-related) and 71 non-tumor liver specimens (36 chronic hepatitis B [CH-B] and 35 chronic hepatitis C [CH-C]) using an in-house cDNA microarray consisting of liver-predominant genes. Graphical Gaussian modeling (GGM) was applied to elucidate the interactions of gene clusters among the HCC and non-tumor lesions.
Project description:Gene expression profiling of hepatocellular carcinoma (HCC) and background liver has been studied extensively; however, the relationship between the gene expression profiles of different lesions has not been assessed. We examined the expression profiles of 34 HCC specimens (17 hepatitis B virus [HBV]-related and 17 hepatitis C virus [HCV]-related) and 71 non-tumor liver specimens (36 chronic hepatitis B [CH-B] and 35 chronic hepatitis C [CH-C]) using an in-house cDNA microarray consisting of liver-predominant genes. Graphical Gaussian modeling (GGM) was applied to elucidate the interactions of gene clusters among the HCC and non-tumor lesions. Gene expression profiling of HCC and non-tumor lesions revealed the predisposing changes of gene expression in HCC. This approach has potential for the early diagnosis and possible prevention of HCC.
Project description:To investigate the role of viral and host factors in HDV-related HCC we analyzed the serum, tissue specimens and laser microdissected hepatocytes obtained at the time of liver transplantation from five patients with HDV-HCC. Livers of seven patients with HDV-cirrhosis without HCC were also analyzed. We carried out an integrated clinicopathological analysis and gene expression profiling,