Integrative genomic and epigenetic analysis in cholangiocarcinoma
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ABSTRACT:
PROVIDER: PRJNA353080 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Analysis of gene expression in cholangiocarcinoma patients. Please download the supplementary file GSE89748_CCA_batch02_illumina_Gene_expression_noNorm_noBKGD.txt.gz (link below) to obtain gene expression matrix with sample IDs used in the publication.
2017-07-03 | GSE89748 | GEO
Project description:Analysis of gene expression in cholangiocarcinoma patients. Please download the supplementary file GSE89747_CCA_batch01_illumina_Gene_expression_noNorm_noBKGD.txt.gz (link below) to obtain gene expression matrix with sample IDs used in the publication.
2017-07-03 | GSE89747 | GEO
Project description:Intrahepatic cholangiocarcinoma (iCCA) is the second most common primary liver cancer. It is defined by cholangiocytic differentiation and has poor prognosis. Recently, epigenetic processes have been shown to play an important role in cholangiocarcinogenesis. We performed an integrative analysis on 52 iCCAs using both genetic and epigenetic data with a specific focus on DNA methylation components. We identified four major iCCA subgroups with widespread genomic and epigenomic differences and prognostic implications. Furthermore, our data suggest differences in the cell-of-origin of the iCCA subtypes.
2022-08-12 | GSE201241 | GEO
Project description:Integrative genomic analysis in HCC samples
| PRJNA430680 | ENA
Project description:This SuperSeries is composed of the following subset Series: GSE32879: Integrative Transcriptomic Profiling reveals Hepatic Stem-like Phenotype and Interplay of EMT and miR-200c in Intrahepatic Cholangiocarcinoma [mRNA] GSE32957: Integrative Transcriptomic Profiling reveals Hepatic Stem-like Phenotype and Interplay of EMT and miR-200c in Intrahepatic Cholangiocarcinoma [miRNA] Refer to individual Series
2012-09-28 | E-GEOD-32958 | biostudies-arrayexpress
Project description:As genomic analysis technology has advanced, it has become possible to sub-classify intrahepatic cholangiocarcinoma (ICC) at the histological or molecular level. However, there are no truly representative models of ICC subtypes for use in studying developmental differences, carcinogenesis, and personalized drug response. Here, we sought to verify recent suggested two subgroup of ICC in organoids model, compare the characteristics between LD and SD type of ICC, and find the type-specific gene expression profile and targetable pathway as a therapeutic target. ICC organoids from 16 patients pathologically diagnosed with cholangiocarcinoma were prepared according to a previously established organoid culture protocol. ICC patients were subclassified into small-duct (SD) type and large-duct (LD) type according to histological characteristics and S100P, N-cadherin, and CD56 expression. ICC organoids were successfully established within one month and exhibited a morphology similar to that of their matching primary cancer. LD- and SD-type organoids exhibited histologic phenotypes and staining patterns characteristic of the corresponding ICC subtypes. ICC organoids showed high concordance of somatic mutations with primary tumors. Unsupervised principal component analysis clustering effectively separated each type of ICC. Differential gene expression revealed significant enrichment on KRAS, TGFβ and ERBB2 signaling pathways in LD-type compared with SD-type ICC (P<0.05). Gene set enrichment analysis further demonstrated that the cholangiocarcinoma class 2 signature, defined by Andersen et al., was significantly enriched in the LD-type (enrichment score=2.19, P<0.001). A protein-protein interaction network analysis identified ZNF217 as a significant hub protein (odds ratio=4.96, P=0.0105). We successfully performed prospective modeling of histological subtype specification using patient-derived ICC organoids. Moreover, gene expression profiling of ICC organoids enabled identification of type-specific targetable pathways.
2022-11-26 | GSE215997 | GEO
Project description:BACKGROUND & AIMS: Cholangiocarcinoma, the second most common liver cancer, can be classified as intrahepatic (ICC) or extrahepatic. We performed an integrative genomic analysis of ICC samples from a large series of patients. METHODS: We performed gene expression profile, high-density single nucleotide polymorphism array, and mutation analyses using formalin-fixed ICC samples from 149 patients. Associations with clinico-pathological traits and patient outcomes were examined for 119 cases. Class discovery was based on a non-negative matrix factorization algorithm and significant copy number variations (CNV) were identified by GISTIC analysis. Gene set enrichment analysis was used to identify signaling pathways activated in specific molecular classes of tumors, and to analyze their genomic overlap with hepatocellular carcinoma (HCC). RESULTS: We identified 2 main biological classes of ICC. The inflammation class (38% of ICCs) is characterized by activation of inflammatory signaling pathways, overexpression of cytokines, and STAT3 activation. The proliferation class (62%) is characterized by activation of oncogenic signaling pathways (including RAS, mitogen-activated protein kinase, and MET), DNA amplifications at 11q13.2, deletions at 14q22.1, mutations in KRAS and BRAF, and gene expression signatures previously associated with poor outcomes for patients with HCC. CNV-based clustering was able to further refine these molecular groups. We identified high-level amplifications in 5 regions, including 1p13 (9%) and 11q13.2 (4%), and several focal deletions, such as 9p21.3 (18%) and 14q22.1 (12% in coding regions for the SAV1 tumor suppressor). In a complementary approach, we identified a gene expression signature that was associated with reduced survival times of patients with ICC; this signature was enriched in the proliferation class (P<0.001). CONCLUSIONS: We used an integrative genomic analysis to identify 2 classes of ICC. The proliferation class has specific copy number alterations, many features of the poor-prognosis signatures for HCC, and is associated with worse outcome. Different classes of ICC, based on molecular features, might therefore require different treatment approaches. This SuperSeries is composed of the SubSeries listed below. Refer to individual Series
2013-01-24 | E-GEOD-33327 | biostudies-arrayexpress
Project description:Integrative genomic analysis in HCC samples [CEP104]
| PRJNA430682 | ENA
Project description:Integrative genomic analysis in HCC samples [RRS1]
| PRJNA430683 | ENA
Project description:Integrative genomic analysis in HCC samples [SNP]
| PRJNA430685 | ENA