The long non-coding RNA PARTICLE is associated with WWOX and the absence of FRA16D breakage in osteosarcoma patients.

Breakage of the fragile site FRA16D disrupts the WWOX (WW Domain Containing Oxidoreductase) tumor suppressor gene in osteosarcoma. However, the frequency of breakage is not sufficient to explain the rate of WWOX loss in pathogenesis. The involvement of non-coding RNA transcripts is proposed due to their accumulation at fragile sites, where they are advocated to influence specific chromosomal regions associated with malignancy. The long ncRNA PARTICLE (promoter of MAT2A antisense radiation-induced circulating long non-coding RNA) is transiently elevated in response to irradiation and influences epigenetic silencing modification within WWOX. It now emerges that elevated PARTICLE levels are significantly associated with FRA16D non-breakage in OS patients. Although not associated with overall survival, high PARTICLE levels were found to be significantly linked to metastasis free outcome. The transcription of both PARTICLE and WWOX are transiently responsive to exposure to low doses of radiation in osteosarcoma cell lines. Herein, a relationship between WWOX and PARTICLE transcription is suggested in human osteosarcoma cell lines representing alternative genetic backgrounds. PARTICLE over-expression ameliorated WWOX promoter activity in U2OS harboring FRA16D non-breakage. It can be concluded that the lncRNA PARTICLE influences the WWOX tumor suppressor and in the absence of WWOX FRA16D breakage, it is associated with OS metastasis-free survival.

PARTICLE triplexes cluster in the tumor suppressor WWOX and may extend throughout the human genome.

The long non-coding RNA PARTICLE (Gene PARTICL- 'Promoter of MAT2A-Antisense RadiaTion Induced Circulating LncRNA) partakes in triple helix (triplex) formation, is transiently elevated following low dose irradiation and regulates transcription of its neighbouring gene - Methionine adenosyltransferase 2A. It now emerges that PARTICLE triplex sites are predicted in many different genes across all human chromosomes. In silico analysis identified additional regions for PARTICLE triplexes at >1600 genomic locations. Multiple PARTICLE triplexes are clustered predominantly within the human and mouse tumor suppressor WW Domain Containing Oxidoreductase (WWOX) gene. Surface plasmon resonance diffraction and electrophoretic mobility shift assays were consistent with PARTICLE triplex formation within human WWOX with high resolution imaging demonstrating its enrichment at this locus on chromosome 16. PARTICLE knockdown and over-expression resulted in inverse changes in WWOX transcripts levels with siRNA interference eliminating PARTICLEs elevated transcription to irradiation. The evidence for a second functional site of PARTICLE triplex formation at WWOX suggests that PARTICLE may form triplex-mediated interactions at multiple positions in the human genome including remote loci. These findings provide a mechanistic explanation for the ability of lncRNAs to regulate the expression of numerous genes distributed across the genome.

Long non-coding RNA PARTICLE bridges histone and DNA methylation.

PARTICLE (Gene PARTICL- 'Promoter of MAT2A-Antisense RadiaTion Induced Circulating LncRNA) expression is transiently elevated following low dose irradiation typically encountered in the workplace and from natural sources. This long non-coding RNA recruits epigenetic silencers for cis-acting repression of its neighbouring Methionine adenosyltransferase 2A gene. It now emerges that PARTICLE operates as a trans-acting mediator of DNA and histone lysine methylation. Chromatin immunoprecipitation sequencing (ChIP-seq) and immunological evidence established elevated PARTICLE expression linked to increased histone 3 lysine 27 trimethylation. Live-imaging of dbroccoli-PARTICLE revealing its dynamic association with DNA methyltransferase 1 was confirmed by flow cytometry, immunoprecipitation and direct competitive binding interaction through electrophoretic mobility shift assay. Acting as a regulatory docking platform, the long non-coding RNA PARTICLE serves to interlink epigenetic modification machineries and represents a compelling innovative component necessary for gene silencing on a global scale.

New small molecules targeting apoptosis and cell viability in osteosarcoma.

Despite the option of multimodal therapy in the treatment strategies of osteosarcoma (OS), the most common primary malignant bone tumor, the standard therapy has not changed over the last decades and still involves multidrug chemotherapy and radical surgery. Although successfully applied in many patients a large number of patients eventually develop recurrent or metastatic disease in which current therapeutic regimens often lack efficacy. Thus, new therapeutic strategies are urgently needed. In this study, we performed a phenotypic high-throughput screening campaign using a 25,000 small-molecule diversity library to identify new small molecules selectively targeting osteosarcoma cells. We could identify two new small molecules that specifically reduced cell viability in OS cell lines U2OS and HOS, but affected neither hepatocellular carcinoma cell line (HepG2) nor primary human osteoblasts (hOB). In addition, the two compounds induced caspase 3 and 7 activity in the U2OS cell line. Compared to conventional drugs generally used in OS treatment such as doxorubicin, we indeed observed a greater sensitivity of OS cell viability to the newly identified compounds compared to doxorubicin and staurosporine. The p53-negative OS cell line Saos-2 almost completely lacked sensitivity to compound treatment that could indicate a role of p53 in the drug response. Taken together, our data show potential implications for designing more efficient therapies in OS.

Genomic heterogeneity of osteosarcoma - shift from single candidates to functional modules.

Osteosarcoma (OS), a bone tumor, exhibit a complex karyotype. On the genomic level a highly variable degree of alterations in nearly all chromosomal regions and between individual tumors is observable. This hampers the identification of common drivers in OS biology. To identify the common molecular mechanisms involved in the maintenance of OS, we follow the hypothesis that all the copy number-associated differences between the patients are intercepted on the level of the functional modules. The implementation is based on a network approach utilizing copy number associated genes in OS, paired expression data and protein interaction data. The resulting functional modules of tightly connected genes were interpreted regarding their biological functions in OS and their potential prognostic significance. We identified an osteosarcoma network assembling well-known and lesser-known candidates. The derived network shows a significant connectivity and modularity suggesting that the genes affected by the heterogeneous genetic alterations share the same biological context. The network modules participate in several critical aspects of cancer biology like DNA damage response, cell growth, and cell motility which is in line with the hypothesis of specifically deregulated but functional modules in cancer. Further, we could deduce genes with possible prognostic significance in OS for further investigation (e.g. EZR, CDKN2A, MAP3K5). Several of those module genes were located on chromosome 6q. The given systems biological approach provides evidence that heterogeneity on the genomic and expression level is ordered by the biological system on the level of the functional modules. Different genomic aberrations are pointing to the same cellular network vicinity to form vital, but already neoplastically altered, functional modules maintaining OS. This observation, exemplarily now shown for OS, has been under discussion already for a longer time, but often in a hypothetical manner, and can here be exemplified for OS.

Structuring osteosarcoma knowledge: an osteosarcoma-gene association database based on literature mining and manual annotation.

Osteosarcoma (OS) is the most common primary bone cancer exhibiting high genomic instability. This genomic instability affects multiple genes and microRNAs to a varying extent depending on patient and tumor subtype. Massive research is ongoing to identify genes including their gene products and microRNAs that correlate with disease progression and might be used as biomarkers for OS. However, the genomic complexity hampers the identification of reliable biomarkers. Up to now, clinico-pathological factors are the key determinants to guide prognosis and therapeutic treatments. Each day, new studies about OS are published and complicate the acquisition of information to support biomarker discovery and therapeutic improvements. Thus, it is necessary to provide a structured and annotated view on the current OS knowledge that is quick and easily accessible to researchers of the field. Therefore, we developed a publicly available database and Web interface that serves as resource for OS-associated genes and microRNAs. Genes and microRNAs were collected using an automated dictionary-based gene recognition procedure followed by manual review and annotation by experts of the field. In total, 911 genes and 81 microRNAs related to 1331 PubMed abstracts were collected (last update: 29 October 2013). Users can evaluate genes and microRNAs according to their potential prognostic and therapeutic impact, the experimental procedures, the sample types, the biological contexts and microRNA target gene interactions. Additionally, a pathway enrichment analysis of the collected genes highlights different aspects of OS progression. OS requires pathways commonly deregulated in cancer but also features OS-specific alterations like deregulated osteoclast differentiation. To our knowledge, this is the first effort of an OS database containing manual reviewed and annotated up-to-date OS knowledge. It might be a useful resource especially for the bone tumor research community, as specific information about genes or microRNAs is quick and easily accessible. Hence, this platform can support the ongoing OS research and biomarker discovery. Database URL: http://osteosarcoma-db.uni-muenster.de.

How microRNA and transcription factor co-regulatory networks affect osteosarcoma cell proliferation.

Osteosarcomas (OS) are complex bone tumors with various genomic alterations. These alterations affect the expression and function of several genes due to drastic changes in the underlying gene regulatory network. However, we know little about critical gene regulators and their functional consequences on the pathogenesis of OS. Therefore, we aimed to determine microRNA and transcription factor (TF) co-regulatory networks in OS cell proliferation. Cell proliferation is an essential part in the pathogenesis of OS and deeper understanding of its regulation might help to identify potential therapeutic targets. Based on expression data of OS cell lines divided according to their proliferative activity, we obtained 12 proliferation-related microRNAs and corresponding target genes. Therewith, microRNA and TF co-regulatory networks were generated and analyzed regarding their structure and functional influence. We identified key co-regulators comprising the microRNAs miR-9-5p, miR-138, and miR-214 and the TFs SP1 and MYC in the derived networks. These regulators are implicated in NFKB- and RB1-signaling and focal adhesion processes based on their common or interacting target genes (e.g., CDK6, CTNNB1, E2F4, HES1, ITGA6, NFKB1, NOTCH1, and SIN3A). Thus, we proposed a model of OS cell proliferation which is primarily co-regulated through the interactions of the mentioned microRNA and TF combinations. This study illustrates the benefit of systems biological approaches in the analysis of complex diseases. We integrated experimental data with publicly available information to unravel the coordinated (post)-transcriptional control of microRNAs and TFs to identify potential therapeutic targets in OS. The resulting microRNA and TF co-regulatory networks are publicly available for further exploration to generate or evaluate own hypotheses of the pathogenesis of OS (http://www.complex-systems.uni-muenster.de/co_networks.html).