Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

MicroRNAs expression profile in human hepatocellular carcinoma

ABSTRACT: Liver cancer tissue could be indentified from corresponding non-cancerous tissues and normal liver tissue with a microRNA expression profile including 69 microRNAs.Besides, one single microRNA could be used to predict the outcome of liver cancer patients. Keywords: molecular marker, predict prognosis

ORGANISM(S): Homo sapiens

PROVIDER: GSE10694 | GEO | 2008/12/31

SECONDARY ACCESSION(S): PRJNA107567

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Five microRNAs in serum are able to differentiate breast cancer patients from healthy individuals

Project description:Breast Cancer is the cancer with most incidence and mortality in women. microRNAs are emerging as novel prognosis/diagnostic tools. Our aim was to identify a serum microRNA signature useful to predict cancer development. We focused on studying the expression levels of 30 microRNAs in the serum of 96 breast cancer patients versus 92 control individuals. Bioinformatic studies provide a microRNA signature, designated as a predictor, based upon the expression levels of 5 microRNAs. Then, we tested the predictor in a group of 60 randomly chosen women. Lastly, a proteomic study unveiled the over-expression and down-regulation of proteins differently expressed in the serum of breast cancer patients versus that of control individuals. Twenty-six microRNAs differentiate cancer tissue from healthy tissue and 16 microRNAs differentiate the serum of cancer patients from that of the control group. The tissue expression of miR-99a-5p, mir-497-5p, miR-362, and miR-1274, and the serum levels of miR-141 correlated with patient survival. Moreover, the predictor consisting of mir-125b-5p, miR-29c-3p, mir-16-5p, miR-1260, and miR-451a was able to differentiate breast cancer patients from controls. The predictor was validated in 20 new cases of breast cancer patients and tested in 60 volunteer women, assigning 11 out of 60 women to the cancer group. An association of low levels of mir-16-5p with a high content of CD44 protein in serum was found. Circulating microRNAs in serum can represent biomarkers for cancer prediction. Their clinical relevance and use of the predictor here described might be of potential importance for breast cancer prediction.

2020-09-18 | PXD020795 | Pride

Genome-wide DNA methylation analysis of liver tissue samples obtained from patients with hepatitis virus-related hepatocellular carcinomas

Project description:Genome-wide DNA methylation profiling was performed in paired samples of non-cancerous liver tissue and the corresponding cancerous tissue obtained from patients with hepatitis virus-related hepatocellular carcinomas using the Illumina Infinium HumanMethylation450 Beadchip.

2017-04-15 | GSE89852 | GEO

Comparative Proteomic Analysis of Six Pairs of Hepatocellular Carcinoma Tissues and Adjacent Non-tumor Tissues

Project description:Applying 4D-label free method to detect differential proteins in cancer tissue and para-cancerous tissue in 6 patients with hepatocellular carcinoma.

2024-07-03 | PXD043544 | Pride

Transcriptome map of cancerous and para-cancerous tissues in patients with liver hepatocellular carcinoma

Project description:To validate CXCL12 and IL7R expression between cancerous and paracancerous, five cancer and five paracancerous tissues，wihch were obtained from five LIHC patients undergoing liver cancer surgery at the Guangdong Second Provincial General Hospital，were performed RNA-seq. The RNA-seq data showed a significant difference in CXCL12 expression between cancerous and paracancerous tissues (p =0.04), as well as the IL7R expression (p<0.01). There was also a significant difference between cancerous and paracancerous samples in NK cells (resting) (p = 0.0014), M1 macrophages (p = 0.0058), CD8+ T cells (p = 0.0026), and Tregs (p = 0.0015) in the immunocyte infiltration analysis.

2020-12-02 | GSE154964 | GEO

Comparative Analysis of Primary and Metastatic Colorectal Cancer

Project description:<p>Molecular profiling for somatic mutations that predict response to anti-EGFR therapy in colorectal cancer (CRC) has become standard practice. However, abundant tissue from metastatic lesions is not always available from patients with metastatic CRC. Concerns involving genetic heterogeneity between primary and metastatic lesions have called into question the suitability of profiling primary tumors in patients with metastatic disease. Further, the identification of discordant mutations between matched primary and metastatic tumors would be of biological interest for the delineation of biomarkers of tumor progression and metastasis.</p> <p>To explore the degree of genetic heterogeneity between matched primary and metastatic tumors in CRC, we performed whole genome sequencing of four patient "trios" comprised of a primary colon tumor, a liver metastasis, and matched normal (non-cancerous) tissue. Somatic mutations and indels were called in each tumor and compared between primary and metastatic lesions.</p>

| phs000790 | dbGaP

microRNA profile of human liver tissues: hepatocellular carcinoma vs. matched noncancerous liver tissue

Project description:microRNA profiling of hepatocellular carcinoma vs. matched noncancerous liver tissue

2011-08-16 | GSE31384 | GEO

microRNA profile of human liver tissues: hepatocellular carcinoma vs. matched noncancerous liver tissue

Project description:microRNA profiling of hepatocellular carcinoma vs. matched noncancerous liver tissue 166 pairs of hepatocellular carcinoma and matched noncancerous liver tissues

2011-08-15 | E-GEOD-31384 | biostudies-arrayexpress

Novel Rank-Based Statistical Methods Reveal MicroRNAs with Differential Expression in Multiple Cancer Types

Project description:The data collected in this study consisted of 32 paired samples of cancerous and normal origins from 14 different patients and 8 different cancer types. Each pair of samples was taken from different parts of the same tissue in the same patient - one collected and extracted from the tumor and one collected and extracted from adjacent normal tissue. One pair from each of the breast, lymphoma and prostate tissues, 2 pairs from liver and lung tissues and 3 pairs from colon, ovary and testes tissues. 2 of the ovary and testes pairs were technical replicates. We use commercial adjacent tissue tumor-normal total RNA samples purchased from Ambion/ABI. The samples were hybridized to Agilent's miRNA microarray version 2.0. Keywords: miRNA

2009-12-07 | GSE14985 | GEO

Differential expression of microRNAs between oral squamous cell carcinoma and healthy control tongues

Project description:In order to identify aberrantly expressed microRNAs in oral squamous cell carcinomas (OSCCs), we have employed microRNA microarray profile using healthy tongue samples as control. All seventeen human OSCCs and three normal tongue tissues were collected from the Tissue Bank at the Moffitt Cancer Center and approved by the University of Florida institutional review board. Majority (15 out of 17) of the OSCCs were derived from tongue cancers. The tumor samples contained greater than 80% of cancerous cells, confirmed by microscopic examination by a head and neck pathologist. The normal tongues were taken from a non-cancerous region. Tissues were snap-frozen and stored at -80M-BM-0C until further use. Total RNAs were isolated from human tissues using mirVana miRNA Isolation kit (Ambion/Applied Biosystems, Austin, TX) according to the manufacturerM-bM-^@M-^Ys instruction. NanoDropM-BM-. ND-100 spectrophotometer (Thermo Scientific, Wilmington, DE) was used to quantify the isolated RNA. The Agilent 2100 Bioanalyzer from the Interdisciplinary Center for Biotechnology Research at the University of Florida was used to detect the size distribution of total RNA and to determine the quality as well. Expression of microRNAs from this signature was quantified in the same RNA samples by real-time PCR, confirming the expression pattern. Human tissues of oral squamous cell carcinoma and healthy normal tongues were used for microRNA microarray profile to identify aberrantly expressed microRNAs in oral squamous cell carcinomas.

2012-09-05 | E-GEOD-28100 | biostudies-arrayexpress

Efficient identification of microRNAs for classification of tumor origin (I)

Project description:Carcinomas of unknown primary origin constitute 3-5% of all newly diagnosed metastatic cancers, of which the primary source is difficult to classify with current histological methods. Effective cancer treatment depends on early and accurate identification of the tumor, which is why patients with metastases of unknown origin have poor prognosis and short survival. Because microRNA expression is highly tissue specific, the microRNA profile of a metastasis may be used to identify its origin. As a first step to realize this goal, we evaluated the potential of microRNA profiling for identification of the primary tumor of known metastases. 208 formalin-fixed paraffin-embedded samples representing 15 different histologies were profiled on an LNA-enhanced microarray platform, which allows for highly sensitive and specific detection of microRNA. Based on these data, we developed and cross-validated a novel classification algorithm, LASSO (Least Absolute Shrinkage and Selection Operator), which had an overall accuracy of 85%. When the classifier was applied on an independent test set of 48 metastases, the primary site was correctly identified in 42 cases (88% accuracy). Our findings suggest that microRNA expression profiling on paraffin tissue can efficiently predict the primary origin of a tumor, and may provide pathologists with a molecular diagnostic tool that can improve their capability to correctly identify the origin of hitherto unidentifiable metastatic tumors, and eventually, enable tailored therapy. 94 samples

2013-12-01 | E-GEOD-50890 | biostudies-arrayexpress

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data