Single cell transcriptome signature of hepatocellular carcinoma (HCC) at different stages along with tumor development
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA996884 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR25375615.fastq.gz | Fastqsanger.gz | |||
| SRR25375616.fastq.gz | Fastqsanger.gz | |||
| SRR25375617.fastq.gz | Fastqsanger.gz | |||
| SRR25375618.fastq.gz | Fastqsanger.gz |
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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.
2015-05-21 | E-GEOD-43619 | biostudies-arrayexpress
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:Background: The presence of vascular invasion (VI) in pathology specimens has been widely described as closely linked to poor outcome in hepatocellular carcinoma (HCC) patients after tumor resection. Previous attempts have been conducted to achieve molecular markers or signatures to predict HCC recurrence in HCC. Here, we aim to develop a diagnostic model combining clinical and genomic variables able to detect the presence of VI prior to surgery and link it to survival estimation. Methods: Seventy-nine HCV related HCC samples from patients that underwent surgical resection as a treatment for HCC were subjected to Genome-wide gene expression profiling and a predictive model of vascular invasion was constructed. The model was tested in an independent-validation set of 153 fixed tissue samples of resected HCC. Quantitative RTPCR and inmunohistochemistry were performed in HCC samples to test a potential biomarker. Results: A 39-gene signature was able to accurately (72%) identify vascular invasion in HCC patients treated with resection. A model including tumor size and the signature is able to predict presence of VI with 85% accuracy in HCV-related HCC patients, and is able to exclude VI in up to 87% cases in HCC from all etiologies. Conclusions: Using the VI gene signature together with tumor size, VI can be successfully detected in HCC patients. The diagnostic model, integrated in a previously reported survival chart is able to provide an estimated survival for selected cases. Clinical implications of this fact are relevant to provide objective data to further apply expanded indication of curative treatments in HCC. Gene-expression profiling was performed using formalin-fixed, paraffin-embedded hepatocellular carcinoma tissues obtained at the time of surgical resection.
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Project description:In this study we investigated the miRNA expression profile of Hepatocellular carcinoma (HCC) specimens from radical resection. We developed a unique 20 miRNA signature that could significantly distinguish HCC venous metastasis from metastasis-free HCC. In contrast to HCC staging systems, this signature was capable of predicting survival and recurrence of HCC patients with multinodular or solitary tumors, including those with early-stage disease. Moreover, the signature was an independent and significant predictor of patient prognosis and relapse when compared to other available clinical parameters. Our study suggests that these 20 miRNAs can enable HCC prognosis and may have clinical utility for the advance identification of HCC patients with a propensity towards metastasis/recurrence. Keywords: disease state design
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Project description:In this study we investigated the miRNA expression profile of Hepatocellular carcinoma (HCC) specimens from radical resection. We developed a unique 20 miRNA signature that could significantly distinguish HCC venous metastasis from metastasis-free HCC. In contrast to HCC staging systems, this signature was capable of predicting survival and recurrence of HCC patients with multinodular or solitary tumors, including those with early-stage disease. Moreover, the signature was an independent and significant predictor of patient prognosis and relapse when compared to other available clinical parameters. Our study suggests that these 20 miRNAs can enable HCC prognosis and may have clinical utility for the advance identification of HCC patients with a propensity towards metastasis/recurrence. Keywords: disease state design Gene expression profiles were conducted in primary HCC and corresponding noncancerous hepatic tissues from 244 Chinese HCC patients. A total of 134 well-defined cases were used as a training group. Among them, 30 had primary HCC lesions accompanied by tumor emboli and 104 had solitary HCC with no metastasis/recurrence found at follow-up (3 yr). We used a testing group of 110 independent cases. The testing cases included 43 multinodular and 67 solitary HCC. In addition, eight normal liver tissues from disease-free patients were included as normal controls. In the analysis of the 244 HCC cases, RNA was isolated in a pairwise fashion from tumor or non-tumor tissue and samples were selected in random order for miRNA analysis to avoid grouping bias.
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