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).

Influence of whole arm loss of chromosome 16q on gene expression patterns in oestrogen receptor-positive, invasive breast cancer.

A whole chromosome arm loss of 16q belongs to the most frequent and earliest chromosomal alterations in invasive and in situ breast cancers of all common subtypes. Besides E-cadherin, several putative tumour suppressor genes residing on 16q in breast cancer have been investigated. However, the significance of these findings has remained unclear. Thus, other mechanisms leading to gene loss of function (eg haploinsufficiency, or distortion of multiple regulative subnetworks) remain to be tested as a hypothesis. To define the effect on gene expression of whole-arm loss of chromosome 16q in invasive breast cancer, we performed global gene expression analysis on a series of 18 genetically extensively characterized invasive ductal breast carcinomas and verified the results by quantitative real-time PCR (qRT-PCR). The distribution of the differential genes across the genome and their expression status was studied. A second approach by qRT-PCR in an independent series of 30 breast carcinomas helped to narrow down the observed effect. Whole-arm chromosome 16q losses, irrespective of other chromosomal changes, are associated with decreased expression of a number of candidate genes located on 16q (eg CDA08, CGI-128, SNTB2, NQO1, SF3B3, KIAA0174, ATBF1, GABARAPL2, KARS, GCSH, MBTPS1 and ZDHHC7) in breast carcinomas with a low degree of genetic instability. qRT-PCR provided evidence to suggest that the expression of these genes was reduced in a gene dosage-dependent manner. The differential expression of the candidate genes according to the chromosomal 16q-status vanished in genetically advanced breast cancer cases and changed ER status. These results corroborate previous reports about the importance of whole-arm loss of chromosome 16q in breast carcinogenesis and give evidence for the first time that haploinsufficiency, in the sense of a gene dosage effect, might be an important contributing factor in the early steps of breast carcinogenesis.

Enriched partial correlations in genome-wide gene expression profiles of hybrids (A. thaliana): a systems biological approach towards the molecular basis of heterosis.

Heterosis is a well-known phenomenon but the underlying molecular mechanisms are not yet established. To contribute to the understanding of heterosis at the molecular level, we analyzed genome-wide gene expression profile data of Arabidopsis thaliana in a systems biological approach. We used partial correlations to estimate the global interaction structure of regulatory networks. Our hypothesis states that heterosis comes with an increased number of partial correlations which we interpret as increased numbers of regulatory interactions leading to enlarged adaptability of the hybrids. This hypothesis is true for mid-parent heterosis for our dataset of gene expression in two homozygous parental lines and their reciprocal crosses. For the case of best-parent heterosis just one hybrid is significant regarding our hypothesis based on a resampling analysis. Summarizing, both metabolome and gene expression level of our illustrative dataset support our proposal of a systems biological approach towards a molecular basis of heterosis.

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.

Deep Sequencing in Conjunction with Expression and Functional Analyses Reveals Activation of FGFR1 in Ewing Sarcoma.

PURPOSE: A low mutation rate seems to be a general feature of pediatric cancers, in particular in oncofusion gene-driven tumors. Genetically, Ewing sarcoma is defined by balanced chromosomal EWS/ETS translocations, which give rise to oncogenic chimeric proteins (EWS-ETS). Other contributing somatic mutations involved in disease development have only been observed at low frequency. EXPERIMENTAL DESIGN: Tumor samples of 116 Ewing sarcoma patients were analyzed here. Whole-genome sequencing was performed on two patients with normal, primary, and relapsed tissue. Whole-exome sequencing was performed on 50 Ewing sarcoma and 22 matched normal tissues. A discovery dataset of 14 of these tumor/normal pairs identified 232 somatic mutations. Recurrent nonsynonymous mutations were validated in the 36 remaining exomes. Transcriptome analysis was performed in a subset of 14 of 50 Ewing sarcomas and DNA copy number gain and expression of FGFR1 in 63 of 116 Ewing sarcomas. RESULTS: Relapsed tumors consistently showed a 2- to 3-fold increased number of mutations. We identified several recurrently mutated genes at low frequency (ANKRD30A, CCDC19, KIAA0319, KIAA1522, LAMB4, SLFN11, STAG2, TP53, UNC80, ZNF98). An oncogenic fibroblast growth factor receptor 1 (FGFR1) mutation (N546K) was detected, and the FGFR1 locus frequently showed copy number gain (31.7%) in primary tumors. Furthermore, high-level FGFR1 expression was noted as a characteristic feature of Ewing sarcoma. RNA interference of FGFR1 expression in Ewing sarcoma lines blocked proliferation and completely suppressed xenograft tumor growth. FGFR1 tyrosine kinase inhibitor (TKI) therapy in a patient with Ewing sarcoma relapse significantly reduced 18-FDG-PET activity. CONCLUSIONS: FGFR1 may constitute a promising target for novel therapeutic approaches in Ewing sarcoma.

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.