Molecular heterogeneity of multinodular hepatocellular carcinoma
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA273840 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Genome-wide DNA copy number profiles of multiple hepatocellular carcinoma tumors and non-tumor liver tissues from the same patients. Introduction: Hepatocellular Carcinoma (HCC) is the second cause of cancer-related death worldwide. Understanding tumor heterogeneity is relevant for the pathogenesis and treatment of this neoplasm. Particularly, whether multinodular tumors result from intrahepatic metastasis (IM or clonal tumors) or de novo cancers (synchronic tumors) have direct implications in treatment decisionmaking for resection and transplantation. We aimed to assess the genomic heterogeneity of multifocal HCC using single-nucleotide polymorphism (SNP) and gene expression analyses. Methods: Among 544 HCC patients consecutively transplanted at Mount Sinai Hospital between 1990- 2007, we selected 18 patients with a total of 42 multinodular tumors (2-3 non-satellite foci HCCs) for this molecular study. Formalin-fixed blocks were collected for each tumor along with corresponding clinico-pathological data. SNP array and gene expression profiling was generated. Clonality was defined by measuring the similarity of genome-wide copy number variation (CNV) profiles between two nodules. Unsupervised hierarchical clustering based on gene expression data was performed to measure genetic proximity between each tumor. Prediction of previously published signatures was performed using Nearest Template Prediction (NTP). Association of clonality with clinic-pathological parameters was assessed. Results: A total of 42 tumors have been analyzed (10 patients- 2 tumors; 8- 3 tumors). Most patients were male (17/18, 95%) with median age of 53-yr-old (range 39–67), HCV (10/18, 56%) or HBV infection (6/18, 33%). Median tumor size was 3 cm (range 1.5-6.5), satellites were present in 3 (17%) and vascular invasion in 11 patients (61%), respectively. CNV profiles predicted clonal tumors in 38% (6/16) and non-clonality in 62% of cases (10/16). CNV profiles of the remaining 2 cases were not informative. Clonal tumors were significantly associated with HCV infected patients (5/6 vs 3/10, p=0.007), whereas all HBV-induced HCC were synchronic tumors (0/6 vs 6/10, p=0.03). Furthermore, clonal tumors were significantly associated with presence of satellites and shorter time-torecurrence. Assessment of genetic proximity based on gene expression revealed that each clonal tumor showed proximity to its paired tumor and clustered around the same node (6/6,100%) as opposed to non-clonal (2/9,22%). When exploring molecular subclasses within clonal tumors (intrahepatic metastases), while half of them retained the molecular fingerprint, the other half switch to more aggressive subclasses. Conversely, all non-clonal tumors within the same patient belonged to distinct molecular subclasses. Conclusion: Multinodular HCCs undergoing transplantation are molecularly heterogeneous. Using CNV profiling we identified clonal multinodular tumors (true intrahepatic metastasis) in 40% of cases and de novo tumors in 60%. Clonal tumors were significantly associated with HCV infection, satellites and recurrence. Genetic proximity was observed in clonal tumors, but molecular subclasses prediction revealed that intrahepatic metastases share more aggressive subclasses in half of cases.
2018-01-28 | GSE65371 | GEO
Project description:Genome-wide gene expression profiles of multiple hepatocellular carcinoma tumors and non-tumor liver tissues from the same patients. Introduction: Hepatocellular Carcinoma (HCC) is the second cause of cancer-related death worldwide. Understanding tumor heterogeneity is relevant for the pathogenesis and treatment of this neoplasm. Particularly, whether multinodular tumors result from intrahepatic metastasis (IM or clonal tumors) or de novo cancers (synchronic tumors) have direct implications in treatment decisionmaking for resection and transplantation. We aimed to assess the genomic heterogeneity of multifocal HCC using single-nucleotide polymorphism (SNP) and gene expression analyses. Methods: Among 544 HCC patients consecutively transplanted at Mount Sinai Hospital between 1990- 2007, we selected 18 patients with a total of 42 multinodular tumors (2-3 non-satellite foci HCCs) for this molecular study. Formalin-fixed blocks were collected for each tumor along with corresponding clinico-pathological data. SNP array and gene expression profiling was generated. Clonality was defined by measuring the similarity of genome-wide copy number variation (CNV) profiles between two nodules. Unsupervised hierarchical clustering based on gene expression data was performed to measure genetic proximity between each tumor. Prediction of previously published signatures was performed using Nearest Template Prediction (NTP). Association of clonality with clinic-pathological parameters was assessed. Results: A total of 42 tumors have been analyzed (10 patients- 2 tumors; 8- 3 tumors). Most patients were male (17/18, 95%) with median age of 53-yr-old (range 39–67), HCV (10/18, 56%) or HBV infection (6/18, 33%). Median tumor size was 3 cm (range 1.5-6.5), satellites were present in 3 (17%) and vascular invasion in 11 patients (61%), respectively. CNV profiles predicted clonal tumors in 38% (6/16) and non-clonality in 62% of cases (10/16). CNV profiles of the remaining 2 cases were not informative. Clonal tumors were significantly associated with HCV infected patients (5/6 vs 3/10, p=0.007), whereas all HBV-induced HCC were synchronic tumors (0/6 vs 6/10, p=0.03). Furthermore, clonal tumors were significantly associated with presence of satellites and shorter time-torecurrence. Assessment of genetic proximity based on gene expression revealed that each clonal tumor showed proximity to its paired tumor and clustered around the same node (6/6,100%) as opposed to non-clonal (2/9,22%). When exploring molecular subclasses within clonal tumors (intrahepatic metastases), while half of them retained the molecular fingerprint, the other half switch to more aggressive subclasses. Conversely, all non-clonal tumors within the same patient belonged to distinct molecular subclasses. Conclusion: Multinodular HCCs undergoing transplantation are molecularly heterogeneous. Using CNV profiling we identified clonal multinodular tumors (true intrahepatic metastasis) in 40% of cases and de novo tumors in 60%. Clonal tumors were significantly associated with HCV infection, satellites and recurrence. Genetic proximity was observed in clonal tumors, but molecular subclasses prediction revealed that intrahepatic metastases share more aggressive subclasses in half of cases.
2018-01-28 | GSE65372 | GEO
Project description:Molecular heterogeneity of multinodular hepatocellular carcinoma [gene expression]
| PRJNA273843 | ENA
Project description:Molecular heterogeneity of multinodular hepatocellular carcinoma [genomic DNA copy number]
| PRJNA273841 | ENA
Project description:The Alb-R26Met liver cancer mouse model recapitulates molecular features and heterogeneity of hepatocellular carcinoma patients
| PRJNA1132968 | ENA
Project description:Clinical heterogeneity of hepatocellular carcinoma (HCC) reflected in unequal outcome of treatment is poorly defined in molecular level, and molecular subtypes and their associated biomarkers have not been established to improve prognostification and treatment of HCC. Using microarray technologies, we analyzed gene expression profiling data from HCC patients, uncovered mesenchymal subtype, and identified gene expression signature associated with mesenchymal phenotype of HCC.
2020-07-01 | GSE134568 | GEO
Project description:The inter-patient variability of tumor proteomes has been investigated on a large scale but many tumors display also intra-tumoral heterogeneity (ITH) regarding morphological and genetic features. To what extent the local proteome of tumors intrinsically differs remains largely unknown. Here, we used hepatocellular carcinoma (HCC) as a model system, to quantify both inter- and intra-tumor heterogeneity across human patient specimens with spatial resolution. We first defined proteomic features that robustly distinguish neoplastic from the directly adjacent non-neoplastic tissue by integrating proteomic data from human patient samples and genetically defined mouse models with available gene expression data. We then demonstrated the existence of intra-tumoral variations in protein abundance that re-occur across different patient samples, and affect clinically relevant proteins, even in the absence of obvious morphological differences or genetic alterations. Our work demonstrates the suitability and the benefits of using mass spectrometry based proteomics to analyze diagnostic tumor specimens with spatial resolution
2018-01-24 | PXD007052 | Pride
Project description:Molecular Signature of Hepatitis D Virus-Associated Hepatocellular Carcinoma
| PRJNA419216 | ENA
Project description:Molecular Dysregulation Underlying Racial Disparity in Hepatocellular Carcinoma (HCC)
| PRJNA928394 | ENA
Project description:Hepatocellular carcinoma (HCC) is a common malignancy with high mortality due to a lack of effective therapies. HCC represents a collection of highly heterogeneous tumor types but a general molecular classification of HCC is lacking. Here, we define three molecular subtypes of HCC that are observed across various independent patient cohorts and profiling platforms. Analysis of the expression signatures indicates that a limited number of pathways and processes drive the clustering of these subtypes. Notably, TGF-beta signaling is a critical factor that distinguishes two subtypes of high-grade tumors, and is associated with early tumor recurrence. Furthermore, both bioinformatics and functional analyses reveal molecular crosstalk between TGF-beta and WNT signaling pathways. These findings suggest that TGF-beta plays a critical role in a subclass of HCC tumors and may enhance WNT pathway activation in the absence of activating mutations in canonical pathway components. This study is an example of how robust molecular subclassification can be used to interrogate molecular abnormalities in the context of human cancer. Experiment Overall Design: Four hepatocellular carcinoma (HCC) cell line samples treated or untreated by TGF-beta
2009-09-17 | E-GEOD-10393 | biostudies-arrayexpress