Retrospective gene expression analysis of human RNA samples from Hepatocellular Carcinoma in relation with survival
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PROVIDER: PRJNA576155 | ENA |
REPOSITORIES: ENA
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Project description:The aim of this study is to identify by Next Generation Sequencing - RNA-seq profiling a molecular signature of Hepatocellular Carcinoma samples that correlates with survival. The samples were retrospectively derived from hepatocellular carcinoma tissue as well as non-tumor tissue from the livers of the same patients. The bioinformatical analysis of 32 pairs RNA-seq datasets were obtained from human RNAs on Illumina Hiseq-PE150. Due to the lack of biological sample duplication, this datasets were used hisat2 2.1.0 and gfold v1.1.4 for expression analysis to identify differences in gene expression between tumors and adjacent tissues. (including up- and down-regulation).
2019-10-08 | GSE138485 | GEO
Project description:The aim of this study is to identify by whole genome microarray expression profiling a molecular signature of HCC samples that correlates with growth rate of the tumor and survival. This signature could eventually be used as prognostic marker. The samples were prospectively derived from hepatocellular carcinoma tissue as well as non-tumor tissue from the livers of the same patients. Expression of five genes (ANGPT2, NETO2,NR4A1,DLL4,ESM1) from this signature was re-evaluated in a validation cohort by real-time PCR, confirming its correlation with growth rate and survival.
2014-01-22 | GSE54236 | GEO
Project description:The aim of this study is to identify by whole genome microarray expression profiling a molecular signature of HCC samples that correlates with growth rate of the tumor and survival. This signature could eventually be used as prognostic marker. The samples were prospectively derived from hepatocellular carcinoma tissue as well as non-tumor tissue from the livers of the same patients. Expression of five genes (ANGPT2, NETO2,NR4A1,DLL4,ESM1) from this signature was re-evaluated in a validation cohort by real-time PCR, confirming its correlation with growth rate and survival. The bioinformatical analysis of 161 microarray datasets were obtained from single color hybridization of human RNAs on Agilent Whole Human Genome Oligo Microarrays after T7 RNA amplification. For the purpose of this study, two discriminatory gene sets analysis were performed: up-regulated and down regulated in fast-growing tumors. For the discrimination between fast- and slow-growing tumors, the fastest quartile of the growth rate spectrum was compared with the three other quartiles. For a gene to be included, a significant discrimination (uncorrected p-value <0.01) and a 2-fold expression difference was required.
2014-01-22 | E-GEOD-54236 | biostudies-arrayexpress
Project description:Retrospective gene expression analysis of human RNA samples from Hepatocellular Carcinoma in relation with survival
| PRJNA575731 | ENA
Project description:Background and aims: Liver transplantation (LT) is the most radical treatment for hepatocellular carcinoma (HCC) with high rates of long-term survival, but tumor recurrence after LT is an unresolved problem. The aim of our study was to identify predictive markers for tumor recurrence after liver transplantation. Methods: In a retrospective single-center study, we included all patients with LT for HCC in our institution (01/2007-12/2012). Beside demographic data, we analyzed course, bridging therapies, Serum-AFP, time point of tumor recurrence, as well as the correlation of imaging and histopathology of our recipients. Additionally, we performed a microarray analysis to identify different miRNA profiles of patients with and without HCC recurrence after LT. Single assay stem-loop real-time PCR (Q-RT-PCR) was used for validation of the results. Results: During the study period, we performed 92 LT in patients with HCC (22 women, 70 men). Twenty-two (23.9%) patients developed a recurrent HCC after LT. Our subgroup with tumor recurrence after LT, presented with a mean disease-free survival of 10 months (3-55 months) and an overall survival of 25.5 months (4-77 months). Milan criteria, AFP levels and pathologic grading had an influence on the tumor recurrence. Performing miRNA analysis, we could identify significant upregulation of 8 miRNAs and downregulation of another 5 miRNAs in patients with tumor recurrence. Consecutively, array data were successfully validated using Q-RT-PCR. Multivariate Cox regression, ROC analysis and Kaplan-Meier showed that a score consisting of two miRNAs and Milan criteria are an independent predictor for tumor recurrence-free survival. Conclusions: Despite careful selection of patients, an early recurrence of HCC after LT cannot be avoided completely. Reliable prognostic markers related to tumor biology are still missing. Analysis and validation of specific miRNAs combined with radiological parameters might lead to a promising strategy for the prediction of tumor recurrence, but prospective studies have to follow. 8 macrodissected hepatocellular carcinoma (recurrent HCC) and 10 macrodissected hepatocellular carcinoma (non-recurrent HCC).
2016-03-01 | E-GEOD-64989 | biostudies-arrayexpress
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: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. 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.
2010-05-19 | E-GEOD-10142 | 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:Epigenetic deregulation is a critical event in human malignancies. A number of DNA methylation markers are currently under evaluation as diagnostic and prognostic biomarkers for many cancers. However, its potential role in hepatocellular carcinoma (HCC) is under-explored. Aims: To develop a DNA methylation-based prognostic signature in surgically resected HCC
2015-02-13 | GSE56588 | 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. 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.
2010-05-18 | E-GEOD-10140 | biostudies-arrayexpress