Gene expression study in hepatocellular carcinoma
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
SUBMITTER: IS Chu
PROVIDER: E-GEOD-16757 | biostudies-arrayexpress |
REPOSITORIES: biostudies-arrayexpress
Similar Datasets
Project description:Gene expression data from 100 human hepatocellular carcinomas (HCC) were generated and analyzed as part of effort for validating prognostic gene expression signatures from previous studies. Using four different classification algorithms and leave-one-out cross-validation approaches, four different prognostic signatures were applied to test the robustness and concordance of predicted outcome in individual patients. All four tumor-derived signatures were significantly associated with prognosis and had a high rate of concordance with predicted outcomes for individual patients.
2010-06-18 | GSE16757 | GEO
Project description:Full title: Predictive Gene Signatures as Strong Prognostic Indicators of the Effectiveness of Bacillus Calmetteâ??Guérin (BCG) Immunotherapy in Primary pT1 Bladder Cancers Intravesical BCG immunotherapy is effective in prevention of recurrence and progression in many cases of non-muscle invasive bladder cancer, but many patients fail to respond. This study identified predictive gene signatures in primary pT1 bladder cancer with BCG immunotherapy. Fourty-Eight patients with primary pT1 bladder cancer treated with BCG immunotherapy were used. Microarray gene expression analysis of the 48 primary bladder cancers was carried out. Predictive gene signatures were individually selected based on the recurrence and progression status. Among 43,148 unique genes, 424 and 287 candidate predictive genes that could predict recurrence and progression, respectively, were selected. Time to recurrence or progression was shorter for patients with poor-predictive gene signatures than good-predictive gene signatures (log-rank test, p <0.001, respectively). Validation of predictive gene signatures with RT-PCR was nearly identical to those of microarray (log-rank test, p <0.05, respectively). In multivariate regression analysis, predictive gene signatures were the only independent predictors of recurrence (HR 3.38, p = 0.048) or progression (HR 10.49, p = 0.048) in validation cohorts. Predictive gene signatures have strong diagnostic value for determining the response to intravesical BCG immunotherapy in primary pT1 bladder cancer. Keywords: Gene expression, Bladder cancer, BCG Total RNA, extracted from the fresh frozen tissues of 48 pT1 bladder cancers, was isolated by TRIzol reagent (Life Technologies, NY, USA), according to the manufacturer's protocol. The quality and integrity of the RNA were confirmed by agarose gel electrophoresis and ethidium bromide staining, followed by visual examination under ultraviolet light. Five-hundred nanograms of total RNA were used for labeling hybridization according to the manufacturerâ??s protocol (Illumina HumanWG-6 BeadChip, version 2, Illumina, Inc., San Diego, CA, USA). Arrays were scanned with an Illumina Bead Array Reader confocal scanner (BeadStation 500GXDW; Illumina, Inc.) according to the manufacturer's instructions. Initial microarray gene expression data were obtained using Bead Studio software with gene expression analysis module (version 3.1.3, Illumina, Inc.).
2010-04-07 | E-GEOD-19423 | biostudies-arrayexpress
Project description:Background: Hepatocellular carcinoma (HCC) is among the top-five cancer killers worldwide. Here, we describe our analysis of 20 gene signatures with reported prognostic value in a cohort of patients with early stage HCC treated with surgical resection. Methods: We performed gene-expression profiling of 164 formalin-fixed, paraffin-embedded HCC from three hepatology centers participating the HCC Genomic Consortium. We utilized IlluminaM-bM-^@M-^Ys whole-genome DASL assay measuring ~24,000 annotated human genes. We evaluated genomic concordance and prognostic performance of 20 already reported prognostic gene signatures. Additionally, since only the largest nodule was profiled, we also excluded patients with multiple tumors to avoid biases related to intra-individual genomic tumor heterogeneity. Results: Among the 20 signatures evaluated, 15 were able to confidently allocate patients (FDR<0.05) within their predicted poor-outcome subclass. Pairwise comparisons showed a significant overlap between almost all poor-outcome signatures derived from the tumor (P<0.001), except for the metastatic HCC signature. Interestingly, poor-outcome signatures from the tumor were not significantly associated with those obtained from non-tumor adjacent tissue in the same patient. The prognosis analysis for earliest stages (BCLC 0 or A) with single nodules revealed that the G3 signature reported by Boyault et al. Conclusions: We present a composite genomic model for prediction of tumor recurrence in early HCC. It will allow risk stratification, personalized surveillance, and eventually customized interventions in patients with early HCC candidates for resection. Samples with "used for prognostic prediction: yes" were included in the study. This SuperSeries is composed of the SubSeries listed below. Refer to individual Series
2011-02-17 | E-GEOD-20140 | biostudies-arrayexpress
Project description:This study aimed to identify the genetic signatures associated with disease prognosis in bladder cancer. We used 165 primary bladder cancer samples, 23 recurrent non-muscle invasive tumor tissues, 58 normal looking bladder mucosae surrounding cancer and 10 normal bladder mucosae for microarray analysis. Hierarchical clustering was used to stratify the prognosis-related gene classifiers. For validation, real-time reverse-transcriptase polymerase chain reaction (RT-PCR) of top-ranked 14 genes was performed. On unsupervised hierarchical clustering using prognosis related gene-classifier, tumors were divided into 2 groups. The high risk gene signatures had significantly poor prognosis compared to low risk gene signatures (P<0.001 by the log-rank test, respectively). The prognosis-related gene classifiers correlated significantly with recurrence of non-muscle invasive bladder cancer (hazard ratio, 4.09; 95% confidence interval [CI], 1.94 to 8.64; P<0.001), and progression (hazard ratio, 23.68; 95% confidence interval [CI], 4.91 to 114.30; P<0.001), cancer-specific survival (hazard ratio, 29.25; 95% confidence interval [CI], 3.47 to 246.98; P=0.002) and overall survival (hazard ratio, 23.33; 95% confidence interval [CI], 4.97 to 109.50; P<0.001) of muscle invasive bladder cancer (p < 0.001, respectively). No patient with non-muscle invasive bladder cancer experienced cancer progression in low risk gene signature group. Prognosis-related gene classifiers validated by RT- PCR showed identical results. Prognosis related gene-classifiers provided strong predictive value for disease outcome. These gene classifiers could assist in selecting patients who might benefit from more aggressive therapeutic intervention or surveillance. Keywords: Gene expression, Bladder cancer, Prognosis 165 primary bladder cancer samples and 23 recurrent non-muscle invasive tumor tissues from 14 patients were taken in the Chungbuk National University Hospital. Only histologically verified transitional cell carcinoma samples were selected. Simultaneously 58 normal looking bladder mucosae surrounding cancer were obtained during the operation, which were histologically confirmed normal. Also, 10 normal bladder mucosae were obtained from patients with benign disease. The normal controls were determined to be free of cancer after revealing no malignant cells on urine cytology and no observable bladder cancer on cystoscopic examination during operation for their diseases, and were histologically reconfirmed normal.
2010-05-28 | E-GEOD-13507 | biostudies-arrayexpress
Project description:Background: Hepatocellular carcinoma (HCC) is among the top-five cancer killers worldwide. Here, we describe our analysis of 20 gene signatures with reported prognostic value in a cohort of patients with early stage HCC treated with surgical resection. Methods: We performed gene-expression profiling of 164 formalin-fixed, paraffin-embedded HCC from three hepatology centers participating the HCC Genomic Consortium. We utilized Illumina’s whole-genome DASL assay measuring ~24,000 annotated human genes. We evaluated genomic concordance and prognostic performance of 20 already reported prognostic gene signatures. Additionally, since only the largest nodule was profiled, we also excluded patients with multiple tumors to avoid biases related to intra-individual genomic tumor heterogeneity. Results: Among the 20 signatures evaluated, 15 were able to confidently allocate patients (FDR<0.05) within their predicted poor-outcome subclass. Pairwise comparisons showed a significant overlap between almost all poor-outcome signatures derived from the tumor (P<0.001), except for the metastatic HCC signature. Interestingly, poor-outcome signatures from the tumor were not significantly associated with those obtained from non-tumor adjacent tissue in the same patient. The prognosis analysis for earliest stages (BCLC 0 or A) with single nodules revealed that the G3 signature reported by Boyault et al. Conclusions: We present a composite genomic model for prediction of tumor recurrence in early HCC. It will allow risk stratification, personalized surveillance, and eventually customized interventions in patients with early HCC candidates for resection. Samples with "used for prognostic prediction: yes" were included in the study. This SuperSeries is composed of the SubSeries listed below.
2011-02-17 | GSE20140 | GEO
Project description:Background: The identification of new high sensitivity and specificity markers for HCC are essential. We aimed to identify serum microRNAs for diagnosing hepatitis B virus (HBV) â??related HCC. Methods: Serum microRNA expression was investigated with four cohorts including 667 participants (261 HCC patients ,233 cirrhosi patients and 173 healthy controls), recruited between August 2010 and June 2013. First, An initial screening of miRNA expression by Illumina sequencing was performed using serum samples pooled from HCC patients and controls,respectively. Quantitative reverse-transcriptase polymerase chain reaction assay was then applied to evaluate the expression of selected microRNAs. A logistic regression model was constructed using a training cohort (n=357) and then validated using a cohort(n=241). The area under the receiver operating characteristic curve (AUC) was used to evaluate diagnostic accuracy. Results: , We identified 8 miRNAs(hsa-miR-206, hsa-miR-141-3p, hsa-miR-433-3p, hsa-miR-1228-5p, hsa-miR-199a-5p, hsa-miR-122-5p, hsa-miR-192-5p and hsa-miR-26a-5p.) formed a miRNA panel that provided a high diagnostic accuracy of HCC (AUC=0.887 and 0.879 for training and validation data set, respectively). The microRNA panel can also differentiate HCC from healthy (AUC =0.894) and cirrhosis (AUC = 0.892), respectively. Conclusions:We found a serum microRNAs panel that has considerable clinical value in diagnosing HCC. 9 serum samples pooled from 3 healthy control donors and 3 HCC patients, 3 cirrhosi patients treated at The First Affiliated Hospital of Soochow University were subjected to Illumina HiSeq 2000 deep sequencing to identify the miRNAs that were significantly differentially expressed.
2015-12-20 | E-GEOD-59418 | biostudies-arrayexpress
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:Recently, senescence has been suggested as a defense mechanism to block sporadic induction of cancer cells. Radiation treatment induces proliferating cancer cells to turn into non-proliferating senescent cells in vitro. To characterize transcriptional reprogramming after radiation treatment, we measured the gene expression profiles of MCF7 at different time points after treatment. In these experiments, we found that IR induced premature senescence in MCF7 cells, and IR treatment resulted in significant changes in the expression of 305 marker genes (less than 1% FDR), which were strongly correlated (|r|>0.9) with IR treatment in a time-dependent manner. Functional analysis of these markers indicated that the dynamics of cytoskeletal structure and lysosomal activity gradually increased. The expression of marker genes for modulator proteins, that were responsible for the dynamics of actin stress fibers and focal adhesion, displayed a particularly strong positive correlation with senescence-associated (SA) morphological changes through time. We also observed a strong induction of genes related to lysosomal metabolic activity, which was accompanied by an increase in the number of SA-beta-Gal positive cells. However, the expression of genes for the cell cycle progression, the post-transcription and the translation activities gradually decreased after radiation treatment. Especially, we observed clear cell cycle arrest specifically at the S and G2/M phases with consistent down-regulation of genes for microtubule assembly/disassembly or spindle biogenesis. Gene expression profiles were obtained from human MCF7 cells after ionizing radiation (6 Gy) at day 0 (no ionizing radiation), day 1 (after ionizing radiation), day 2, day 3, and day 4.
2010-06-08 | E-GEOD-21748 | biostudies-arrayexpress
Project description:Gene-expression profiles of hepatitis C-related, early-stage liver cirrhosis Background & Aims: Liver cirrhosis affects 1%M-bM-^HM-^R2% of population and is the major risk factor of hepatocellular carcinoma (HCC). Hepatitis C cirrhosis-related HCC is the most rapidly increasing cause of cancer death in the US. Non-invasive methods have been developed to identify patients with asymptomatic, early-stage cirrhosis, increasing the burden of HCC surveillance, but biomarkers are needed to identify patients with cirrhosis who are most in need of surveillance. We investigated whether a liver-derived 186-gene signature previously associated with outcomes of patients with HCC is prognostic for patients newly diagnosed with cirrhosis but without HCC. Methods: We performed gene expression profile analysis of formalin-fixed needle biopsies from the livers of 216 patients with hepatitis C-related early-stage (Child-Pugh class A) cirrhosis who were prospectively followed for a median of 10 years at an Italian center. We evaluated whether the 186-gene signature was associated with death, progression of cirrhosis, and development of HCC. Results: Fifty-five (25%), 101 (47%), and 60 (28%) patients were classified as having poor-, intermediate-, and good-prognosis signatures, respectively. In multivariable Cox regression modeling, the poor-prognosis signature was significantly associated with death (P=.004), progression to advanced cirrhosis (P<.001), and development of HCC (P=.009). The 10-year rates of survival were 63%, 74%, and 85% and the annual incidences of HCC were 5.8%, 2.2%, and 1.5% for patients with poor-, intermediate-, and good-prognosis signatures, respectively. Conclusions: A 186-gene signature used to predict outcomes of patients with HCC is also associated with outcomes of patients with hepatitis C-related early-stage cirrhosis. This signature might be used to identify patients with cirrhosis in most need of surveillance and strategies to prevent their development of HCC. 216 liver biopsy specimens
2013-01-22 | E-GEOD-15654 | biostudies-arrayexpress
Project description:Purpose: To identify orthologous genes in Xenopus that are implicated in deafness and vestibular disorders in humans and to compare RNA-Seq and microarray to determine the advantages of each technology for Xenopus transcriptomic analysis. Methods: Inner ear RNA from X. laevis stages 56-58 was isolated with the Qiagen® RNeasy® Mini Kit. RNA quality was assessed using the Agilent 2100 Bioanalyzer. The RNA was sent to the National Center for Genome Resources, for Illumina-Solexa sequencing using the genome analyzer II and to MIT for microarray processing usign the Affymetrix GeneChip® X. laevis Genome 2.0 Array. The OMIM database was mined for identification of genes causing deafness and vestibular disorder in humans. Human sequences for each of the deafness and vestibular disorders genes were downloaded from Ensembl. Blast-2.2.27+ was used to mapped the human sequences against X. tropicalis predicted proteins from JGI or to Xenopus consensus sequences downloaded from Affymetrix. The alignment of the human sequences to the predicted proteins resulted in the identification of the protein designation number. The protein designation number was used to obtain the sacaffold number and coordinates from JGI genome browser. The scaffold number and coordinates were input into Alpheus sequence variant detection pipeline to obtain the number of reads associated with each gene. The reads were log2 transformed for comparison to the microarray. In the case of the alignment of the human sequences to the Xenopus consensus sequences resulted in the PSID. The PSID was used to obtain the GCRMA intensity value. The GCRMA value and the number of reads were compared to determine which technology detected more genes. Results: Using Affymetrix GeneChip® X. laevis Genome 2.0 Arrays and Illumina-Solexa sequencing methods, we determined that the transcriptional profile of the Xenopus inner ear comprises hundreds of genes that are orthologous to OMIM® genes implicated in deafness and vestibular disorders in humans. Analysis of genes that mapped to both technologies showed that RNA-Seq detected more of both deafness and vestibular disorder than the Microarray. RNA-Seq and microarray detected 108 genes but RNA-Seq detected 48 genes that were below threshold criteria for microarray. While the microarray detected 11 genes that were below the expression criteria for RNA-Seq and 23 genes were below the threshold criteria for both technologies. Further analysis of the 108 genes detected by both technologies showed a minor correlation between the two technologies. Conclusions: As part of this study we identified candidate scaffold regions of the Xenopus tropicalis genome that can be used for gene mutagenesis. Furthermore, results from this study showed that the two technologies can complement each other and that a combination of both approaches can provide a more complete analysis of gene expression than either method alone. Inner ear RNA from X. laevis larval stages 56-58 was isolated and shipped to the National Center for Genome Resources, for Illumina-Solexa sequencing or to the Massachusetts Institute of Technology BioMicro Center for microarray analysis with the Affymetrix GeneChip® X. laevis Genome 2.0 Array. RNA-Sequencing was completed using the Illumina-Solexa platform for sequencing by synthesis. Short-insert paired end (SIPE) libraries were prepared from total RNA according to Illuminaâ??s mRNA-Seq Sample Prep Protocol v2.0 (Illumina, San Diego, CA, USA). The resultant double-stranded cDNA concentration was measured on a NanoDrop spectrophotometer, and size and purity were determined on the 2100 Bioanalyzer using a DNA 1000 Nano kit. The cDNA libraries were cluster amplified on Illumina flowcells, sequenced on the GAII Sequencer as 36-cycle single-end reads, and processed using Illumina software v1.0. Illumina reads were aligned to the X. tropicalis genome using the algorithm for genomic mapping and alignment program (GMAP) and Alpheus® Sequence Variant Detection System v3.1.
2016-02-28 | E-GEOD-69701 | biostudies-arrayexpress