Comprehensive analysis of transcriptome and metabolome in Intrahepatic Cholangiocarcinoma and Hepatocellular Carcinoma (part II)
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ABSTRACT:
ORGANISM(S): Homo Sapiens
TISSUE(S): Liver
DISEASE(S): Cancer
PROVIDER: ST000231 | MetabolomicsWorkbench |
REPOSITORIES: MetabolomicsWorkbench
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Project description:Intrahepatic cholangiocarcinoma (ICC) and hepatocellular carcinoma (HCC) are liver originated malignant tumors. Of the two, ICC has the worse prognosis because it has no reliable diagnostic markers and its carcinogenic mechanism is not fully understood. The aim of this study was to integrate metabolomics and transcriptomics datasets to identify variances if any in the carcinogenic mechanism of ICC and HCC. Ten ICC and 6 HCC who were resected surgically, were enrolled. miRNA and mRNA expression analysis were performed by microarray on ICC and HCC and their corresponding non-tumor tissues (ICC_NT and HCC_NT). Compound analysis was performed using capillary electrophoresis time-of-flight mass spectrometry (CE-TOFMS). Principle component analysis (PCA) revealed that among the four sample groups (ICC, ICC_NT, HCC, and HCC_NT) there were 14 compounds, 62 mRNAs and 17 miRNAs with two distinct patterns: tumor and non-tumor, and ICC and non-ICC. We accurately (84.38%) distinguished ICC by the distinct pattern of its compounds. Pathway analysis using transcriptome and metabolome showed that several pathways varied between tumor and non-tumor samples. Based on the results of the PCA, we believe that ICC and HCC have different carcinogenic mechanism therefore knowing the specific profile of genes and compounds can be useful in diagnosing ICC.
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Project description:BackgroundHepatocellular carcinoma is the second most deadly cancer with late presentation and limited treatment options, highlighting an urgent need to better understand HCC to facilitate the identification of early-stage biomarkers and uncover therapeutic targets for the development of novel therapies for HCC.MethodsDeep transcriptome sequencing of tumor and paired non-tumor liver tissues was performed to comprehensively evaluate the profiles of both the host and HBV transcripts in HCC patients. Differential gene expression patterns and the dys-regulated genes associated with clinical outcomes were analyzed. Somatic mutations were identified from the sequencing data and the deleterious mutations were predicted. Lastly, human-HBV chimeric transcripts were identified, and their distribution, potential function and expression association were analyzed.ResultsExpression profiling identified the significantly upregulated TP73 as a nodal molecule modulating expression of apoptotic genes. Approximately 2.5% of dysregulated genes significantly correlated with HCC clinical characteristics. Of the 110 identified genes, those involved in post-translational modification, cell division and/or transcriptional regulation were upregulated, while those involved in redox reactions were downregulated in tumors of patients with poor prognosis. Mutation signature analysis identified that somatic mutations in HCC tumors were mainly non-synonymous, frequently affecting genes in the micro-environment and cancer pathways. Recurrent mutations occur mainly in ribosomal genes. The most frequently mutated genes were generally associated with a poorer clinical prognosis. Lastly, transcriptome sequencing suggest that HBV replication in the tumors of HCC patients is rare. HBV-human fusion transcripts are a common observation, with favored HBV and host insertion sites being the HBx C-terminus and gene introns (in tumors) and introns/intergenic-regions (in non-tumors), respectively. HBV-fused genes in tumors were mainly involved in RNA binding while those in non-tumors tissues varied widely. These observations suggest that while HBV may integrate randomly during chronic infection, selective expression of functional chimeric transcripts may occur during tumorigenesis.ConclusionsTranscriptome sequencing of HCC patients reveals key cancer molecules and clinically relevant pathways deregulated/mutated in HCC patients and suggests that while HBV may integrate randomly during chronic infection, selective expression of functional chimeric transcripts likely occur during the process of tumorigenesis.
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Project description:BackgroundDNA polymerase delta 1 catalytic subunit (POLD1) plays a key role in DNA replication and damage repair. A defective DNA proofreading function caused by POLD1 mutation contributes to carcinogenesis, while POLD1 overexpression predicts poor prognosis in cancers. However, the effect of POLD1 in hepatocellular carcinoma (HCC) is not well-understood.MethodsExpression patterns of POLD1 were evaluated in TCGA and the HPA databases. Kaplan-Meier curves and Cox regression were used to examine the prognostic value of POLD1. The prognostic and predictive value of POLD1 was further validated by another independent cohort from ICGC database. The influences of DNA copy number variation, methylation and miRNA on POLD1 mRNA expression were examined. The correlation between infiltrating immune cells and POLD1 expression was analyzed. GO and KEGG enrichment analyses were performed to detect biological pathways associated with POLD1 expression in HCC.ResultsPOLD1 was overexpressed in HCC (n = 369) compared with adjacent normal liver (n = 50). POLD1 upregulation was significantly correlated with positive serum AFP and advanced TNM stage. Kaplan-Meier and multivariate analyses suggested that POLD1 overexpression predicts poor prognosis in HCC. DNA copy gain, low POLD1 methylation, and miR‑139-3p downregulation were associated with POLD1 overexpression. Besides, POLD1 expression was associated with the infiltration levels of dendritic cell, macrophage, B cell, and CD4 + T cell in HCC. Functional enrichment analysis suggested "DNA replication", "mismatch repair" and "cell cycle" pathways might be involved in the effect of POLD1 on HCC pathogenesis. Additionally, POLD1 mRNA expression was significantly associated with tumor mutation burden, microsatellite instability, and prognosis in various tumors.ConclusionsPOLD1 may be a potential prognostic marker and promising therapeutic target in HCC.
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Project description:Hepatocellular carcinoma (HCC) is one of the leading cause of cancer-associated death in the world. However, due to the complexity of HCC, it is urgent for us to find a reliable and accurate biomarker for HCC gene therapy.TopBP1-interacting checkpoint and replication regulator (TICRR), known as Treslin in vertebrate and sld3 in yeast, is involved in the tumorigenesis, progression, matastasis, diagnosis, and predicting prognosis of HCC. Disappointingly, the mechanism of TICRR expression in HCC is still not described in detail and requires further analysis. In this study, TCGA ( www.tcga-data.nci.nih.gov/tcga/ ) datasets and GEO ( www.ncbi.nlm.nih.gov/geo ) datasets were used to analyze the expression of TICRR in HCC, the relevance of TICRR mRNA expression and clinicopathological characteristics in patients with HCC, and the relationship between TICRR expression and immune infiltration level in Patients with HCC. Based on MethSurv database, the impact of TICRR in patients with HCC was investigated. In addition, GO/KEGG enrichment analysis of TICRR co-expression was performed using the R package. TICRR was found drastically highly expressed in a variety of cancer types including HCC.ROC curve analysis showed that TICRR had higher accuracy in predicting HCC compared with AFP. The expression level of TICRR was marked positively correlated with tumor stage and prognosis in Patients with HCC.GO/KEGG enrichment analysis showed that TICRR was associated with cell division and cell cycle as well as p53 signaling pathway. In addition, patients with high TICRR methylation of cg05841809, cg09403165, and cg03312532 CpG sites were significantly correlated with poor prognosis of HCC. This study demonstrated that increased TICRR expression in HCC might play an important role in the tumorigenesis, progression, diagnosis, and predicting prognosis of HCC. Therefore, TICRR might be used as a promising diagnostic and prognostic biomarker for HCC gene therapy.
| S-EPMC10902024 | biostudies-literature
Project description:Hepatocellular carcinoma (HCC) is rapidly becoming one of the most prevalent cancers worldwide. With a rising rate, it is a prominent source of mortality. Patients with advanced fibrosis, predominantly cirrhosis and hepatitis B are predisposed to developing HCC. Individuals with chronic hepatitis B and C infections are most commonly afflicted. Different therapeutic options, including liver resection, transplantation, systemic and local therapy, must be tailored to each patient. Liver transplantation offers leading results to achieve a cure. The Milan criteria is acknowledged as the model to classify the individuals that meet requirements to undergo transplantation. Mean survival remains suboptimal because of long waiting times and limited donor organ resources. Recent debates involve expansion of these criteria to create options for patients with HCC to increase overall survival.
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Project description:IntroductionHepatocellular carcinoma (HCC) is one of the most common cancers worldwide. Despite the therapeutic advances in HCC in the past few decades, the mortality rate of HCC is still high. Hepatitis C (HCV) infection is one of the major etiological risk factors of HCCs. However, the underlying mechanisms of HCV-induced hepatocarcinogenesis remain largely unclear.Material and methodsOur study represented the comprehensive analysis of differentially expressed lncRNAs in HCV-positive HCC for the first time by analyzing the public dataset GSE17856. Co-expression network and gene ontology (GO) analysis revealed the functions of those differentially expressed lncRNAs.ResultsWe identified 256 upregulated lncRNAs and 198 downregulated lncRNAs in HCV- positive HCC compared to the normal liver tissues. Co-expression network and GO analysis showed that these lncRNAs were involved in regulating metabolism, energy pathways, proliferation and the immune response. Seven lncRNAs (LOC341056, CCT6P1, PTTG3P, LOC643387, LOC100133920, C3P1 and C22orf45) were identified as key lncRNAs and co-expressed with more than 100 differentially expressed genes (DEGs) in HCV-related HCC. Kaplan-Meier analysis showed that higher expression levels of LOC643387, PTTG3P, LOC341056, CCT6P1 and lower expression levels of C3P1 and C22orf45 were associated with shorter survival time in the TCGA dataset.ConclusionsWe believe that this study can provide novel potential therapeutic and prognostic biomarkers for HCV-positive HCC.
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