Dataset Information

Identification of a blood-borne miRNA signature of synovial sarcoma.

ABSTRACT: Synovial sarcoma account for approximately 10 % of all soft-tissue tumors and occur most frequently in young adults. A specific translocation in this sarcoma induces fusion of the SYT gene on chromosome 18 to the SSX genes on chromosome X, leading to proliferation of the tumor cells. The need for non-invasive biomarkers indicating recurrence and activity of this disease has sparked research into short non-coding RNA known as microRNA (miRNA).Blood samples of patients with active synovial sarcoma and of synovial sarcoma patients in complete remission as well as of healthy donors and patients with active leiomyosarcoma, MPNST, Ewing sarcoma and liposarcoma were collected. Whole blood RNA was extracted and samples of patients with active synovial sarcoma and of healthy donors were analyzed using an Affymetrix GeneChip miRNA Array v. 4.0. qRT-PCR was carried out to confirm a panel of miRNAs which where differentially expressed in the miRNA array. This miRNA-panel was further evaluated in patients with synovial sarcoma in complete remission and patients with active leiomyosarcoma, MPNST, Ewing sarcoma and liposarcoma as well as in an independent cohort of synovial sarcoma patients.Unsupervised hierarchical clustering of the miRNA arrays separated patients with active synovial sarcoma from healthy controls. A panel of seven miRNAs (miR-99a-5p, miR-146b-5p, miR-148b-3p, miR-195-5p, miR-223-3p, miR-500b-3p and miR-505-3p) was further validated by qRT-PCR to be significantly upregulated in synovial sarcoma patients. Moreover, most of the analyzed miRNAs were shown to be significantly upregulated in synovial sarcoma patients compared to leiomyosarcoma, MPNST, Ewing sarcoma and liposarcoma patients. Validation of the miRNA panel in an independent cohort of synovial sarcoma patients confirmed higher expression levels compared to healthy controls and patients in complete remission.Our results have identified a specific whole blood miRNA signature that may serve as an independent biomarker for the diagnosis of local recurrence or distant metastasis of synovial sarcoma. It even distinguishes synovial sarcoma from other sarcoma subtypes, thus potentially serving as a specific biomarker for synovial sarcoma.

SUBMITTER: Fricke A

PROVIDER: S-EPMC4528907 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Identification of a blood-borne miRNA signature of synovial sarcoma.

Fricke Alba A Ullrich Prisca V PV Heinz Jürgen J Pfeifer Dietmar D Scholber Jutta J Herget Georg W GW Hauschild Oliver O Bronsert Peter P Stark G Björn GB Bannasch Holger H Eisenhardt Steffen U SU Braig David D

Molecular cancer 20150807

<h4>Background</h4>Synovial sarcoma account for approximately 10 % of all soft-tissue tumors and occur most frequently in young adults. A specific translocation in this sarcoma induces fusion of the SYT gene on chromosome 18 to the SSX genes on chromosome X, leading to proliferation of the tumor cells. The need for non-invasive biomarkers indicating recurrence and activity of this disease has sparked research into short non-coding RNA known as microRNA (miRNA).<h4>Methods</h4>Blood samples of pa ...[more]

PMID: 26250552

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Project description:ObjectivesIn our previous studies we reported a panel of 24 miRNAs that allowed discrimination between blood of lung tumor patients independent of the histological subtype and blood of healthy controls with an accuracy of 95.4% [94.9%-95.9%]. Here, we now separately analyzed the miRNA expression in blood of non-small cell lung cancer (NSCLC), including squamous cell lung cancer and adenocarcinoma, and small cell lung cancer (SCLC) patients.Patients and methodsIn total, we examined the expression levels of 1,205 miRNAs in blood samples from 20 patients from each of the three histological groups and determined differentially expressed miRNAs between histological subtypes and metastatic and non-metastatic lung cancer. We further determined the overlap of miRNAs expressed in each subgroup with the 24-miRNA signature of lung tumor patients.ResultsBased on a raw p-value < 0.05, only 18 blood-borne miRNAs were differentially expressed between patients with adenocarcinoma and with squamous cell lung carcinoma, 11 miRNAs between adenocarcinoma and SCLC, and 2 between squamous cell lung carcinoma and SCLC. Likewise, the comparison based on a fold change of 1.5 did not reveal major differences of the blood-borne miRNA expression pattern between NSCLC and SCLC. In addition, we found a large overlap between the blood-borne miRNAs detected in the three histological subgroups and the previously described 24-miRNA signature that separates lung cancer patients form controls. We identified several miRNAs that allowed differentiating between metastatic and non-metastatic tumors both in blood of patients with adenocarcinoma and in blood of patients with SCLC.ConclusionThere is a common miRNA expression pattern in blood of lung cancer patients that does not allow a reliable further subtyping into NSCLC or SCLC, or into adenocarcinoma and squamous cell lung cancer. The previously described 24-miRNA signature for lung cancer appears not primarily dependent on histological subtypes. However, metastatic adenocarcinoma and SCLC can be predicted with 75% accuracy.

Project description:Synovial sarcoma (SS) is a highly aggressive soft tissue tumor with high risk of local recurrence and metastasis. However, the mechanisms underlying SS metastasis are still largely unclear. The purpose of this study is to screen metastasis-associated biomarkers in SS by integrated bioinformatics analysis. Two mRNA datasets (GSE40018 and GSE40021) were selected to analyze the differentially expressed genes (DEGs). Using the Database for Annotation, Visualization and Integrated Discovery (DAVID) and gene set enrichment analysis (GSEA), functional and pathway enrichment analyses were performed for DEGs. Then, the protein-protein interaction (PPI) network was constructed via the Search Tool for the Retrieval of Interacting Genes (STRING) database. The module analysis of the PPI network and hub genes validation were performed using Cytoscape software. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of the hub genes were performed using WEB-based GEne SeT AnaLysis Toolkit (WebGestalt). The expression levels and survival analysis of hub genes were further assessed through Gene Expression Profiling Interactive Analysis (GEPIA) and the Kaplan-Meier plotter database. In total, 213 overlapping DEGs were identified, of which 109 were upregulated and 104 were downregulated. GO analysis revealed that the DEGs were predominantly involved in mitosis and cell division. KEGG pathways analysis demonstrated that most DEGs were significantly enriched in cell cycle pathway. GSEA revealed that the DEGs were mainly enriched in oocyte meiosis, cell cycle and DNA replication pathways. A key module was identified and 10 hub genes (CENPF, KIF11, KIF23, TTK, MKI67, TOP2A, CDC45, MELK, AURKB, and BUB1) were screened out. The expression and survival analysis disclosed that the 10 hub genes were upregulated in SS patients and could result in significantly reduced survival. Our study identified a series of metastasis-associated biomarkers involved in the progression of SS, and may provide novel therapeutic targets for SS metastasis.

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Identification of a blood-borne miRNA signature of synovial sarcoma.

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Identification of a blood-borne miRNA signature of synovial sarcoma.

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