Homo sapiens
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA270585 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR1720590_1.fastq.gz | Fastqsanger.gz | |||
| SRR1720590_2.fastq.gz | Fastqsanger.gz | |||
| SRR1720600_1.fastq.gz | Fastqsanger.gz | |||
| SRR1720600_2.fastq.gz | Fastqsanger.gz | |||
| SRR1720610_1.fastq.gz | Fastqsanger.gz |
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Project description:Despite advances in DNA methylome analyses of cells and tissues, current techniques for genome-scale profiling of DNA methylation in circulating cell-free DNA (ccfDNA) remain limited. Here we describe a methylated CpG tandems amplification and sequencing (MCTA-Seq) method that can detect thousands of hypermethylated CpG islands simultaneously in ccfDNA. This highly sensitive technique can work with genomic DNA as little as 7.5 pg, which is equivalent to 2.5 copies of the haploid genome. We have analyzed a cohort of tissue and plasma samples (n=151) of hepatocellular carcinoma (HCC) patients and control subjects, identifying dozens of high-performance markers in blood for detecting small HCC (<=3 cm). Among these markers, 4 (RGS10, ST8SIA6, RUNX2 and VIM) are mostly specific for cancer detection, while the other 15, classified as a novel set, are already hypermethylated in the normal liver tissues. Two corresponding classifiers have been established, combination of which achieves a sensitivity of 94% with a specificity of 89% for the plasma samples from HCC patients (n=36) and control subjects including cirrhosis patients (n=17) and normal individuals (n=38). Notably, all 15 alpha-fetoprotein-negative HCC patients were successfully identified. Comparison between matched plasma and tissue samples indicates that both the cancer and noncancerous tissues contribute to elevation of the methylation markers in plasma. MCTA-Seq will facilitate the development of ccfDNA methylation biomarkers and contribute to the improvement of cancer detection in a clinical setting.
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Project description:The remarkable molecular heterogeneity in hepatocellular carcinoma (HCC) continues to challenge development of effective treatments and biomarkers. Here we report that the gene encoding a secreted glycoprotein, ADAMTSL5, is overexpressed and displays hypermethylated CpG islands in its gene body region in a clinically relevant mouse genetic model of HCC as well as in a significant proportion of human HCC patients. Immunohistological analysis of human HCCs revealed strong ADAMTSL5 immunostaining in tumour cells and histiocytes, in contrast to normal liver. Functional targeting of ADAMTSL5 in oncogenesis using shRNA interfered with tumorigenic properties of HCC cells both in vitro and in vivo. Furthermore, ADAMTSL5 overexpression conferred tumorigenic capability to genetically sensitized, non-transformed hepatocytes in nude mice. Mechanistically, ADAMTSL5 abrogation led to reduction of several oncogenic inputs, including the receptor tyrosine kinases MET, EGFR, PDGFRβ, IGF1Rβ, and FGFR4, suggesting it as a master regulator of HCC tumorigenicity when overexpressed.
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Project description:Circular RNAs (circRNAs) are recently found to be promising kind of biomarkers for tumors. However, plasma exosomal circRNAs in the diagnosis of hepatocellular carcinoma (HCC) is largely unknown. In this study, we report the application of next-generation sequencing technology for high-throughput profiling of plasma exosome general transcriptome between 3 cases of hepatocellular carcinoma patients and 3 cases of healthy control. We obtained exosomes through ultrahigh-speed centrifugation techniques and verified exosomes through immunoblotting, NanoSight NS300(Malvern Panalytical, Malvern, UK) and JEM-1230 transmission electron microscope (TEM) (JEOL, Tokyo, Japan). And then, we find that there are 41 circRNAs that have differential expression. This study discovered the differences between hepatocellular carcinoma and healthy people preliminarily.
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Project description:We examine genome-wide DNA methylation profiles in 66 pairs of HCC tumor and adjacent non-tumor tissues. After Bonferroni adjustment, a total of 130,512 CpG sites significantly differed in methylation level in tumor compared to non-tumor tissues, with 28,017 CpG sites hypermethylated and 102,495 hypomethylated in tumor tissues. Most (60.1%) significantly hypermethylated CpG sites are located in CpG islands. These results demonstrate the significance of aberrant DNA methylation in HCC tumorigenesis.
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Project description:The aim of the present study was to identify novel DNA methylation markers in bladder cancer (BCa) through genome-wide profiling of bladder cancer cell lines and subsequent MSP screening in urine samples. Experimental Design: MBD methylCap/seq was carried out to screen differentially methylated CpG islands using two BCa cell lines (5637 and T24) and two normal bladder mucosa (BM) samples. The top one hundred most hypermethylated targets were screened using Methylation Specific PCR (MSP) in small and big cohort of urine samples from BCa patients and normal controls. The diagnostic performance of the gene panel was further evaluated in different clinical scenarios. Results: In total, 1,627 gene promoter regions hypermethylated in BCa cell line were identified in genomic level methylation profiling. The followed screening procedure in clinical urine sample generated eight genes (VAX1, KCNV1, ECEL1, TMEM26, TAL1, PROX1, SLC6A20, and LMX1A) capable of differentiating BCa from normal control. Subsequent validation in a large sample size enabled the optimisation of 5 methylation targets (VAX1, KCNV1, TAL1, PPOX1 and CFTR) for BCa diagnosis with sensitivity and specificity of 86.32% and 87.13%, respectively. In addition, VAX1 and LMX1A methylation could predict the tumour recurrence. Conclusions: Tumor specific biomarkers of BCa could be established by first performing genome level methylation profiling with cell lines and then screening the potential targets in urine samples. The panel of methylated genes identified was promising for the early non-invasive detection and surveillance of BCa. MBD methylCap/seq was carried out to screen differentially methylated CpG islands using two BCa cell lines (5637 and T24), and two normal bladder tissue mix as control.
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