Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

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MiRNA gene expression profiles from osteosarcoma samples and cell lines

ABSTRACT: Although the introduction of combined neoadjuvant chemotherapy has significantly prolonged the survival, the outcome of OS patients with poor response to chemotherapy is still unfavorable. To develop new therapeutics the elucidation of the entire molecular pathway regulating OS cell proliferation is warranted. We analysed the expression levels of 933 miRNA probes in surgical 24 samples and 8 cell lines of osteosarcoma with 3D-Gene human miRNA oligo chips. Total RNA was extracted from 24 fresh frozen tumour specimens and 8 OS cell lines. We analysed the global miRNA exprssion profiles of these osteosarcoma cases in order to find new novel potential targets for the development of therapeutic targeting OS.

ORGANISM(S): Homo sapiens

SUBMITTER: Satoshi Kondo

PROVIDER: E-GEOD-30934 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Project description:Background: Only a subset of radically-resected pancreatic ductal adenocarcinoma (PDAC) patients benefit from chemotherapy, and identification of novel prognostic factors is warranted. Recently miRNAs emerged as diagnostic biomarkers and innovative therapeutic targets, while high-throughput arrays are opening new opportunities to evaluate whether they can also predict clinical outcome. The present study evaluated whether comprehensive miRNA expression profiling correlated with overall survival (OS) in resected PDAC patients. Methodology/Principal Findings: High-resolution miRNA profiles were obtained with the Toray’s 3D-GeneTM miRNA chip, detecting more than 1200 types of human miRNA. RNA was isolated from paraffin-embedded primary tumors of 26 radically resected stage-pT3N1 homogeneously treated patients (adjuvant gemcitabine 1000mg/m2/day, days-1/8/15, every 28days), carefully selected according to their outcome (OS<12 vs. OS>30 months, i.e. short/long-OS). Highly stringent statistics included t-test, distance matrix with Spearman-ranked correlation, and iterative approaches. Unsupervised hierarchical analysis revealed that PDAC specimens clustered according to their short/long-OS classification, while the feature selection algorithm RELIEF identified the top-4 discriminating miRNAs between the two groups. These miRNAs target more than 1500 transcripts, including 169 targeted by two or more of these miRNAs. MiR-211 emerged as the best discriminating miRNA, with significantly higher expression in long- vs. short-OS patients. The expression of this miRNA was subsequently assessed by quantitative-PCR in an independent cohort of laser microdissected tumors from 60 resected stage-pT3N1 PDAC patients treated with the same gemcitabine regimen. Patients with low miR-211 expression according to median value had a significantly shorter median OS (14.8, 95%CI=13.1-16.5, vs. 25.7 months, 95%CI=16.2-35.1, log-rank P=0.004). Multivariate analysis demonstrated that low miR-211 expression was an independent factor of poor prognosis (hazard ratio 2.3, P=0.03) after adjusting for all the factors influencing outcome. 19 samples, duplicated gene spots

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MiRNA gene expression profiles from osteosarcoma samples and cell lines

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