CDNA microarray of hepatocellular carcinoma and nontumor liver tissues
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE34674 | GEO | 2011/12/23
SECONDARY ACCESSION(S): PRJNA150319
REPOSITORIES: GEO
Similar Datasets
Project description:In order to identify the deregulated genes in hepatocellular carcinama, we applied the Agilent two-color chip cDNA microarray to explore the expression of genes in hepatocellular carcinoma and nontumor liver tissue samples. Hepatocellular carcinoma tissues and nontumor liver tissues were obtained from hepatocellular carcinoma patients during surgery. In these samples, RNA was extracted and cDNA microarray was performed to identify the differentially expressed genes in these samples. Hepatocellular carcinoma tissues and nontumor liver tissues were obtained from hepatocellular carcinoma patients during surgery. We included four hepatocellular carcinoma patients in this study, and there are four nontumor tissues and four hepatocellular carcinoma tissues.
2011-12-23 | E-GEOD-34674 | biostudies-arrayexpress
Project description:cDNA microarray of hepatocellular carcinoma and nontumor liver tissues
| PRJNA150319 | ENA
Project description:Transcription profiling of hepatocellular carcinoma using two color microarray. Experimental samples: Hepatocellular carcinoma, Common reference: Normal liver tissue. One replicate per array.
2014-02-15 | E-GEOD-55039 | biostudies-arrayexpress
Project description:Hepatocellular carcinoma (HCC) remains a major health problem worldwide, and HCC patients have a poor prognostic outcome. In this study, we systematically disclose mechanisms of hepatocarcinogenesis, and also effectively identify and validate novel anticancer targets in HCCs. Keywords: disease state analysis total 58 cDNA microarrays, all experiment samples are hepatocellular carcinoma. RNAs from 33 corresponding noncancerous livers and 5 normal livers were used as the reference, respectively. The tumor samples were labeled with Cy5-dUTP.The nontumor samples were labeled with Cy3-dUTP.
2009-01-06 | E-GEOD-4108 | biostudies-arrayexpress
Project description:Transcription profiling of hepatocellular carcinoma using two color microarray.
2014-02-15 | GSE55039 | GEO
Project description:BACKGROUND & AIMS: In approximately 70% of patients with hepatocellular carcinoma (HCC) treated by resection or ablation, disease recurs within 5 years. Although gene expression signatures have been associated with outcome, there is no method to predict recurrence based on combined clinical, pathology, and genomic data (from tumor and cirrhotic tissue). We evaluated gene expression signatures associated with outcome in a large cohort of patients with early stage (Barcelona-Clinic Liver Cancer 0/A), single-nodule HCC and heterogeneity of signatures within tumor tissues. METHODS: We assessed 287 HCC patients undergoing resection and tested genome-wide expression platforms using tumor (n = 287) and adjacent nontumor, cirrhotic tissue (n = 226). We evaluated gene expression signatures with reported prognostic ability generated from tumor or cirrhotic tissue in 18 and 4 reports, respectively. In 15 additional patients, we profiled samples from the center and periphery of the tumor, to determine stability of signatures. Data analysis included Cox modeling and random survival forests to identify independent predictors of tumor recurrence. RESULTS: Gene expression signatures that were associated with aggressive HCC were clustered, as well as those associated with tumors of progenitor cell origin and those from nontumor, adjacent, cirrhotic tissues. On multivariate analysis, the tumor-associated signature G3-proliferation (hazard ratio [HR], 1.75; P = .003) and an adjacent poor-survival signature (HR, 1.74; P = .004) were independent predictors of HCC recurrence, along with satellites (HR, 1.66; P = .04). Samples from different sites in the same tumor nodule were reproducibly classified. CONCLUSIONS: We developed a composite prognostic model for HCC recurrence, based on gene expression patterns in tumor and adjacent tissues. These signatures predict early and overall recurrence in patients with HCC, and complement findings from clinical and pathology analyses. Center and peripheral portions of hepatocellular carcinoma tumors as well as surrounding non-tumor cirrhotic liver tissues were obtained from fresh frozen surgically resected tissues, and isolated total RNA samples were analyzed for genome-wide expression profiles.
2014-03-25 | E-GEOD-56140 | biostudies-arrayexpress
Project description:microRNA profiling of 10 human healthy liver and 9 human hepatocellular carcinoma tissues using bead-based technology microRNA expression profiling was performed using freshly frozen healthy liver and hepatocellular carcinoma tissues obtained at the time of surgical treatment. keywords: healthy liver, hepatocellular carcinoma, expression array, microRNA
2012-07-21 | E-GEOD-31383 | biostudies-arrayexpress
Project description:The human circRNA profiles of Hepatocellular carcinoma are rarely reported. Surgically removed human HCC tissues and matched normal liver tissues (5cm away from tumor) were collected to make an Agilent microarray.
2023-12-20 | GSE242797 | GEO
Project description:Background: It is a challenge to identify those patients who, after undergoing potentially curative treatments for hepatocellular carcinoma, are at greatest risk of recurrence. Such high-risk patients could receive novel interventional measures. An obstacle to the development of genome-based predictors of outcome in patients with hepatocellular carcinoma has been the lack of a means to carry out genomewide expression profiling of fixed, as opposed to frozen, tissues. Methods: We aimed to demonstrate the feasibility of gene-expression profiling of more than 6000 human genes in formalin-fixed paraffin-embedded tissues. We applied the method to tissues from 307 patients with hepatocellular carcinoma, from four series of patients, to discover and validate a gene-expression signature associated with survival. Results: The expression-profiling method for formalin-fixed, paraffin-embedded tissue was highly effective: samples from 90% of the patients yielded data of high quality, including samples that had been archived for more than 24 years. Gene-expression profiles of tumor tissue failed to yield a significant association with survival. In contrast, profiles of the surrounding nontumoral liver tissue were highly correlated with survival in a training set of 82 Japanese patients, and the signature was validated in tissues from an independent group of 225 patients from the United States and Europe (p = 0.04). Conclusions: We have demonstrated the feasibility of genomewide expression profiling of formalin-fixed, paraffin-embedded tissues and have shown that a reproducible gene-expression signature correlating with survival is present in liver tissue adjacent to the tumor in patients with hepatocellular carcinoma. This SuperSeries is composed of the following subset Series: GSE10140: Gene Expression in Fixed Tissues and Outcome in Hepatocellular Carcinoma (Training Set, Liver) GSE10141: Gene Expression in Fixed Tissues and Outcome in Hepatocellular Carcinoma (Training Set, HCC) GSE10142: Gene Expression in Fixed Tissues and Outcome in Hepatocellular Carcinoma (Validation Set) Keywords: Hepatocellular carcinoma, Expression array, Illumina, Signatures, Outcome prediction Training cohort: 80 tumor and 82 non-tumor liver tissues surgically resected from patients with hepatocellular carcinoma (HCC); Validation cohort: 225 non-tumor liver tissues surgically resected from patients with HCC. Clinical data has been withheld from GEO due to privacy concerns.
2010-05-20 | E-GEOD-10143 | biostudies-arrayexpress
Project description:Immune checkpoint inhibitors elicit durable antitumor effects in multiple cancers, yet not all patients respond. Here, we aimed to develop and validate a molecular classification of hepatocellular carcinoma (HCC) patients based on 42 fatty acid degradation genes and demonstrate its predictive ability in the clinical response of anti-PD1 therapy in HCC patients. We studied global mRNA expression profiles from 41 primary tumor tissues and 25 nontumor tissues derived from 41 HCC patients. 17 patients received anti-PD1 therapy and were available with clinical response. 63 samples were also sent for lipidomics analysis. Methods for the study included gene expression analysis, consensus clustering analysis, pathway enrichment analysis, and Single-Sample Gene Set Enrichment Analysis (ssGSEA). This study identified and validated a novel molecular classification based on fatty acid degradation that predicts clinical response to anti-PD-1 therapy in hepatocellular carcinoma.
2023-05-01 | GSE202069 | GEO