Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Whole-exome sequencing of hepatocellular carcinoma biopsies (proteogenomic study)

ABSTRACT: We performed a proteogenomic analysis of hepatocellular carcinomas (HCCs) across clinical stages and etiologies to define the deregulated pathways and heterogeneity among HCCs. We identified pathways that are differentially regulated on the genomic, transcriptomic, proteomic and phosphoproteomic levels. Integrative clustering identified HCC subgroups that show distinct regulation of biological processes, metabolic reprogramming and kinase activation.

PROVIDER: EGAS00001005073 | EGA |

REPOSITORIES: EGA

ACCESS DATA

Json Xml

Similar Datasets

Transcriptome sequencing of hepatocellular carcinoma biopsies (proteogenomic study)

Project description:We performed a proteogenomic analysis of hepatocellular carcinomas (HCCs) across clinical stages and etiologies to define the deregulated pathways and heterogeneity among HCCs. We identified pathways that are differentially regulated on the genomic, transcriptomic, proteomic and phosphoproteomic levels. Integrative clustering identified HCC subgroups that show distinct regulation of biological processes, metabolic reprogramming and kinase activation.

| EGAS00001005074 | EGA

Proteogenomic characterization of human early-onset gastric cancer

Project description:We report proteogenomic analysis of diffuse gastric cancers (GCs) in young population. Phosphoproteome data elucidated signaling pathways associated with somatic mutations based on mutation-phosphorylation correlations. Moreover, correlations between mRNA and protein abundances provided potential oncogenes and tumor suppressors associated with patient survival. Furthermore, integrated clustering of mRNA, protein, phosphorylation, and N-glycosylation data identified four subtypes of diffuse GCs. Distinguishing these subtypes was possible by proteomic data. Four subtypes were associated with proliferation, immune response, metabolism, and invasion, respectively; and associations of the subtypes with immune- and invasion-related pathways were identified mainly by phosphorylation and N-glycosylation data. Therefore, our proteogenomic analysis provides additional information beyond genomic analyses, which can improve understanding of cancer biology and patient stratification in diffuse GCs.

2018-12-06 | GSE122401 | GEO

Proteogenomic characterization analysis of human large cell lung cancer

Project description:Current clinical therapy of non-small cell lung cancer depends on histo-pathological classification. This approach poorly predicts clinical outcome for individual patients. Proteogenomic characterization analysis holds promise to improve clinical stratification, thus paving the way for individualized therapy. We investigated proteogenomic characterization and performed comprehensive integrative genomic analysis of human large cell lung cancer. Here we analyzed proteomes of 29 paired normal lung tissues and large cell lung cancer, identified significantly deregulated proteins associated with large cell lung cancer.

2019-01-16 | PXD012393 |

Proteogenomic Analysis of Medulloblastoma

Project description:Proteogenomic Analysis of Medulloblastoma

| PRJNA430801 | ENA

CPTAC Proteogenomic Confirmatory Study

Project description:CPTAC Proteogenomic Confirmatory Study

| PRJNA279694 | ENA

Proteogenomic characterization and comprehensive integrative genomic analysis of human colorectal cancer liver metastasis

Project description:Colorectal cancer (CRC) is the third most common cancer worldwide and liver metastasis remains the major cause of death in CRC. Extensive genomic analysis provided valuable insight into the pathogenesis and progression of CRC. However, the major proteogenomic characterization of CRC liver metastasis is still unknown. We investigated proteogenomic characterization and performed comprehensive integrative genomic analysis of human colorectal cancer liver metastasis.

2019-12-27 | GSE93286 | GEO

Strong Activation of Retroviral LTRs in HCC

Project description:<p>The ncRNA transcriptome of human hepatocellular carcinoma (HCC) is largely unexplored. We used CAGE to characterize transcription start sites across different etiologies of human HCCs with emphasis on ncRNAs. Here we report that retroviral LTR promoters, expressed in healthy tissues such as testis and placenta but not liver, are widely activated in HCC. Despite HCC heterogeneity, a subset of LTR-derived ncRNAs were more than 10-fold up-regulated in the vast majority of samples. HCCs with a high LTR activity mostly had a viral etiology, were less differentiated and showed higher risk of recurrence. CAGE enabled us to build a promoter map for HCC, which uncovers a new layer of complexity in HCC genomics.</p>

| phs000885 | dbGaP

Comprehensive Proteogenomic Analysis of Human Embryonic and Induced Pluripotent Stem Cells

Project description:Although the concepts of reprogramming and human induced pluripotent stem cells (hiPSCs) generation have undergone to several analysis to strengthen the usefulness of these cells in research and clinic, it still remains controversial whether the hiPSCs are really equivalent to human embryonic stem cells, pointing to the need of further characterizations in order to gain a more comprehensive understanding of human stem cells pluripotency. Most of the experimental evidence comes from the transcriptome analysis, while a little information is available on protein data, and even less is known about the post-translational modifications. Here we report a combined strategy of nLC-MS/MS and gene expression profiling for proteogenomic analysis of two distinct stem cell lines, the commercially available hESCs H9 and the hiPSCs, obtained in our laboratory by reprogramming of peripheral blood T-lymphocytes with the Sendai virus-driven Yamanaka’s 4-transcription factors cocktail. The analysis was further enriched by the study of the phosphoproteomic profile of the two PSC lines. The results obtained through this integrated, multi -“omics” approach, indicate that a small number of distinct pathways is enriched in reprogrammed versus naïve pluripotent stem cells, supporting the view that pluripotency is an extremely complex, multifaceted phenomenon, with peculiarities that are characteristic of each cell type.

2019-06-02 | GSE116716 | GEO

Gene expression profiling in paired human hepatocellular carcinoma and liver parenchyma biopsies and normal liver biopsies.

Project description:Hepatocellular carcinoma (HCC) is a heterogeneous disease, and despite considerable research efforts, no molecular classification of HCC has been introduced in clinical practice. The existing molecular classification systems were established using resected tumors, which introduces a selection bias towards patients without liver cirrhosis and with early stage HCCs. So far, these classification systems have not been validated in liver biopsy specimens from tumors diagnosed at intermediate and late stages. We generated and analyzed expression profiles from 60 HCC biopsies from an unselected patient population with all tumor stages. Unbiased clustering identified 3 HCC classes. Class membership correlated with survival, tumor size, and with Edmondson and BCLC stage. Most biopsy specimens could be assigned to the classes of published classification systems, demonstrating that gene expression profiles obtained from patients with early stage disease are preserved in all stages of HCC. When a reference set of healthy liver samples was integrated in the analysis, we observed that the differentially regulated genes up- or down-regulated in a given class relative to other classes were actually dysregulated in the same direction in all HCCs, with quantitative rather than qualitative differences between the molecular subclasses. With the exception of a subset of samples with a definitive β-catenin gene signature, biological pathway analysis could not identify class specific pathways reflecting the activation of distinct oncogenic programs. Our results suggest that gene expression profiling of HCC biopsies has limited potential to direct therapies that target specific driver pathways, but can identify subgroups of patients with different prognosis.

2016-05-01 | GSE64041 | GEO

Proteogenomic anlalysis of glioblastoma (GBM)

Project description:Proteogenomic anlalysis of glioblastoma (GBM)

| PRJNA627121 | ENA