Gene expression profile of hepatocellular carcinoma patients in Taiwan
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE101685 | GEO | 2019/07/31
REPOSITORIES: GEO
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Project description:Mongolia has the highest reported incidence of (and mortality from) hepatocellular carcinoma (HCC) in the world. This is the first molecular study aiming to characterize the genomic landscape of Mongolian HCC.
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Project description:CTNNB1 is the most frequently mutated gene in hepatocellular carcinoma (HCC). However, its clinical relevance remains controversial. We determined an evolutionarily conserved β-catenin signature by comparative analysis of gene expression data from human HCC and a mouse model (GSE43628). We generated gene expression data from the tumors of 88 HCC patients who underwent surgical resection as the primary treatment. We used these gene expression data to develop a new prognostification model for prognosis of HCC after surgery. We generated gene expression data from the tumors of 88 HCC patients who underwent surgical resection as the primary treatment.
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Project description:Hepatocellular carcinoma (HCC) is a highly heterogeneous disease, and prior attempts to develop genomic-based classification for HCC have yielded highly divergent results, indicating difficulty in identifying unified molecular anatomy. We performed a meta-analysis of gene expression profiles in data sets from eight independent patient cohorts across the world. In addition, aiming to establish the real world applicability of a classification system, we profiled 118 formalin-fixed, paraffin-embedded tissues from an additional patient cohort. A total of 603 patients were analyzed, representing the major etiologies of HCC (hepatitis B and C) collected from Western and Eastern countries. We observed three robust HCC subclasses (termed S1, S2, and S3), each correlated with clinical parameters such as tumor size, extent of cellular differentiation, and serum alpha-fetoprotein levels. An analysis of the components of the signatures indicated that S1 reflected aberrant activation of the WNT signaling pathway, S2 was characterized by proliferation as well as MYC and AKT activation, and S3 was associated with hepatocyte differentiation. Functional studies indicated that the WNT pathway activation signature characteristic of S1 tumors was not simply the result of beta-catenin mutation but rather was the result of transforming growth factor-beta activation, thus representing a new mechanism of WNT pathway activation in HCC. These experiments establish the first consensus classification framework for HCC based on gene expression profiles and highlight the power of integrating multiple data sets to define a robust molecular taxonomy of the disease. Surgically resected 118 tumor tissues from patients with hepatocellular carcinoma (HCC)
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Project description:CTNNB1 is the most frequently mutated gene in hepatocellular carcinoma (HCC). However, its clinical relevance remains controversial. We determined an evolutionarily conserved β-catenin signature by comparative analysis of gene expression data from human HCC and a mouse model (GSE43628). We generated gene expression data from the tumors of 88 HCC patients who underwent surgical resection as the primary treatment. We used these gene expression data to develop a new prognostification model for prognosis of HCC after surgery.
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Project description:Hepatocellular carcinoma (HCC) is a leading cause of cancer-related death in the world. Mitochondrial fission regulator 2 (MTFR2) is involved in the development of various cancers. However, the roles of MTFR2 in HCC remain unknown. In this study, we conducted a comprehensive analysis of MTFR2 in HCC, which was generated from integrative MTFR2 analyses of eight HCC cell lines, and three datasets (public dataset, real-world dataset, immunotherapy dataset) derived from bulk HCC tissues, survival and immunotherapy data. We demonstrated that the expression level of MTFR2 is up-regulated in HCC, leading to poor prognosis. MTFR2 is positively correlated with the level of immune cell infiltration, multiple immune checkpoints and immunotherapy response prediction pathways, and act important role in cancer-immunity cycle. In conclusion, our work indicates that MTFR2 can shape a barrier of immune microenvironment and result in poor prognosis in hepatocellular carcinoma, but the immune barrier may be broken by immunotherapy.
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Project description:<p><strong>BACKGROUND & AIMS: </strong>The effectiveness of surveillance for hepatocellular carcinoma (HCC) in patients with cirrhosis is limited, due to inadequate risk stratification and suboptimal performance of current screening modalities.</p><p><strong>METHODS: </strong>We developed a multicenter prospective cohort of patients with cirrhosis undergoing surveillance with MRI and applied global untargeted metabolomics to 612 longitudinal serum samples from 203 patients. Among them, 37 developed HCC during follow-up.</p><p><strong>RESULTS: </strong>We identified 150 metabolites with significant abundance changes in samples collected prior to HCC (Cases) compared to samples from patients who did not develop HCC (Controls). Tauro-conjugated bile acids and gamma-glutamyl amino acids were increased, while acyl-cholines and deoxycholate derivatives were decreased. Seven amino acids including serine and alanine had strong associations with HCC risk, while strong protective effects were observed for N-acetylglycine and glycerophosphorylcholine. Machine learning using the 150 metabolites, age, gender, and PNPLA3 and TMS6SF2 single nucleotide polymorphisms, identified 15 variables giving optimal performance. Among them, N-acetylglycine had the highest AUC in discriminating Cases and Controls. When restricting Cases to samples collected within 1 year prior to HCC (Cases-12M), additional metabolites including microbiota-derived metabolites were identified. The combination of the top six variables identified by machine learning (alpha-fetoprotein, 6-bromotryptophan, N-acetylglycine, salicyluric glucuronide, testosterone sulfate and age) had good performance in discriminating Cases-12M from Controls (AUC 0.88, 95% CI 0.83-0.93). Finally, 23 metabolites distinguished Cases with LI-RADS-3 lesions from Controls with LI-RADS-3 lesions, with reduced abundance of acyl-cholines and glycerophosphorylcholine-related lysophospholipids in Cases.</p><p><strong>CONCLUSIONS: </strong>This study identified N-acetylglycine, amino acids, bile acids and choline-derived metabolites as biomarkers of HCC risk, and microbiota-derived metabolites as contributors to HCC development.</p>
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Project description:Transgenic mice (n= 40) overexpressing FEAT in the thymus, spleen, liver, and lung developed malignant lymphoma (47.5%, 19/40) and liver cancer (hepatocellular carcinoma, HCC) (35%, 14/40). Notably, HCC arose in half (13/26) of the male transgenic mice, indicating a strong male predilection similar to human HCC. Microarray-based comparative genomic hybridization (array-CGH) suggested that HCC in FEAT transgenic mice recapitulates human hepatocarcinogenesis.
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Project description:It is known that exosomes (endosome derived vesicles) play important roles in the formation of the tumor microenvironment. Hepatocellular carcinoma (HCC) is a highly malignant cancer, whose malignancy is largely influenced by the tumor microenvironment. The possible role and the specific content of the HCC derived exosomes are however largely unknown. We performed super-SILAC-based mass spectrometry (MS) analyses to interrogate the differential proteins in the exosome of three human HCC cell lines, MHCC97H, MHCCLM3 and Hep3B cells. Exosomal proteins were systematically compared with multi-omics strategies, considering both proteomics and translatomics. With stringent data quality control (quantified unique peptides ≥ 2, FDR ≤ 0.01 at both protein and peptide level), 1907 exosomal proteins were confidently identified from the three HCC cell lines, out of which 469 and 443 exosomal proteins significantly altered in the highly malignant cell lines (MHCC97H/Hep3B and MHCCLM3/Hep3B), respectively. ClueGo and IPA analyses on the differentially expressed proteins (DEPs) revealed that translation and ubiquitination biological processes pathways were significantly more encapsulated in the exosome of higher malignant cell lines. We further observed significantly negative correlation of exosomal protein to cellular protein and translating mRNA in terms of relative abundances comparing the higher malignant cell lines with the low malignant cell line. The negatively correlated genes are also translation regulation-centric. In conclusion, we demonstrated that the exosomal enrichment of translation regulatory proteins is related to the malignant level of HCC cells.
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Project description:Long noncoding RNAs (lncRNAs) are a class of non-coding RNAs longer than 200 nt that function in endogenous gene regulation and tumorigenesis. Hepatocellular carcinoma (HCC) is a heterogeneous disease with different treatment outcome. It is a challenge to develop a prognostic marker to identify HCC patients who are at greatest risk for recurrence or death. In this study, we try to screen lncRNAs whose expression levels are associated with recurrence or death of HCC patients through an extensive lncRNA profiling study on a cohort of 59 HCC patients.
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