GEO series

Unique MicroRNA Expression Signature Predicts Survival, Metastases and Recurrence of HCC

GSE6857 Homo sapiens (human) Non-coding RNA profiling 482 samples Submitted 2008/01/14 Platform GPL4700

At a glance

Non-coding RNA profiling · human · 482 samples

What it is: Non-coding RNA profilingLevels of RNAs that do not code for proteins, such as miRNA or lncRNA.
Organism: Homo sapiens (human)
Topic: Hepatocellular carcinomaThis series is part of our curated briefing on it.
Samples: 482 samples
Data you can get: A processed expression table (series matrix) and the array files, from NCBI.

Summary (written by the submitters)

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.

Read the full summary ↓

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

This dataset

Open GSE6857 in finder → Find more datasets → Hepatocellular carcinoma landscape →

Download · which file do I need?

Direct links to NCBI, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.

1 · Just have a look

Processed table

The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.

Series matrix ↓

2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need.

All supplementary files ↗

3 · The original raw files

Whole study · RAW.tar

Everything the authors deposited as one archive (GSE6857_RAW.tar), including the raw array or instrument files. Can be large; the picker in step 2 takes just the samples you need.

Whole study · RAW.tar ↓

Also filed as BioProject PRJNA99101. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 18176954) ↗

Samples in this study

The sample list for this study is not cached yet. Press Load samples and it will be fetched from NCBI.

+ 482 more — browse all 482 samples with per-sample file links →

More Hepatocellular carcinoma datasets

GSE14520 Gene expression data of human hepatocellular carcinoma (HCC) 488 samples same disease briefing · shares hcc
GSE114564 Identification of novel serum biomarkers in early-stage HCC patients. 118 samples same disease briefing · shares hcc
GSE134630 Profiling of N6-Adenosine (m6A) methylation in HCCLM3 cells with shCtrl or shKIAA1429 6 samples same disease briefing · shares hcc
GSE107170 Molecular Signature of Hepatitis D Virus-Associated Hepatocellular Carcinoma 307 samples same disease briefing · shares signature
GSE112790 Comprehensive molecular characterization of liver cancer and inheritance of the phenotypic traits during tumor recurrence [tissue] 198 samples same disease briefing · shares recurrence
GSE104580 Using a novel gene signature for predicting the efficacy of the transarterial chemoembolization in patients with hepatocellular carcinoma. 147 samples same disease briefing · shares signature
GSE109211 Molecular predictors of prevention of recurrence in hepatocellular carcinoma with sorafenib as adjuvant treatment in the phase 3 STORM trial 140 samples same disease briefing · shares recurrence
GSE10143 Gene Expression in Fixed Tissues and Outcome in Hepatocellular Carcinoma 387 samples same disease briefing

Search all datasets in GEO →

Share this dataset

Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.