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.
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 reverse phase protein arrays (RPPA) technologies, we analyzed protein expression profiling data from HCC patients, uncovered mesenchymal subtype, and identified gene expression signature associated with mesenchymal phenotype of HCC.
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
Project description:To identify the prognostic subtypes of hepatocellular carcinoma with potential progenitor cell origin. Keywords: disease state design
Project description:To identify the prognostic subtypes of hepatocellular carcinoma with potential progenitor cell origin. Keywords: disease state design We used our in-house oligonucleotide microarray data of 238 HBV-positive HCC cases.
Project description:To explore the miRNA expression profiles between HBV-related Hepatocellular carcinoma and no HBV-related Hepatocellular carcinoma To performe microarray analysis to detect the miRNA expression profiles between HBV-related Hepatocellular carcinoma and no HBV-related Hepatocellular carcinoma
Project description:Previously, we have found a specific subtype of HCCs named solitary large hepatocellular carcinoma (SLHCC), which was >5 cm in diameter, had just single lesion, and always grew expansively within an intact capsule or pseudocapsule. Accordingly, we classified HCCs into 3 different subtypes: SLHCC, nodular HCC (NHCC, node number ≥ 2) and small HCC (SHCC, solitary nodular, diameter ≤ 5 cm). Further study confirmed that SLHCC had unique clinical and pathological characteristics, and its metastatic potential was comparable with SHCC, but significantly lower than NHCC. After hepatic resection, SLHCC exhibited a similar long-term overall and disease-free survival with SHCC, but much better than NHCC. To gain a better understanding of the molecular biologic characteristics of SLHCC, we performed miRNAs array analysis in there three subtypes of HCC.
Project description:Hepatocellular carcinoma (HCC) accounts for approximately 90% of primary liver cancers, the second leading cause of cancer mortality worldwide. Although HCC surgical treatment may be curative in the early stages, its five-year overall survival is only 50-70%. Advances in proteomic technologies have expanded the breadth and depth of cancer proteome characterization. Here, we present the largest characterization effort on proteomic profiling of 222 tumor and paired non-tumor tissues in clinically early HCC (Barcelona Clinic Liver Cancer (BCLC) stage 0 and A). Quantitative proteomic data identified three more-refined subtypes in the early- stage cohort of HCC (termed S-I, S-II and S-III) with different clinical outcomes. S-I retained hepatic detoxification and metabolic functions with the best prognosis, S-II increased molecular expression related to proliferation, and S-III showed distinct enrichment of tumor metastasis and immune response pathways and the poorest prognosis. The subtype specific signatures targeted by known FDA approved drugs or inhibitors under clinical investigations for HCC provide a novel resource for HCC therapeutic targets. A new mechanism of disrupted cholesterol homeostasis with aberrant accumulation of cholesteryl esters was also highlighted in S-III. Thus, this study represents the first proteomic stratification of early-stage HCC, providing insights into tumor biology and personalized targeted therapy.
Project description:To explore the lncRNAs and mRNA expression profiles between HBV-related Hepatocellular carcinoma and no HBV-related Hepatocellular carcinoma To performe microarray analysis to detect the lncRNAs and mRNA expression profiles between HBV-related Hepatocellular carcinoma and no HBV-related Hepatocellular carcinoma