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)

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

Defining a Characteristic Gene Expression Set Responsible for Cancer Stem Cell-Like Features in a Sub-Population of Ewing Sarcoma Cells CADO-ES1

One of the still open questions in Ewing sarcoma, a rare bone tumor with weak therapeutic options, is to identify the tumor-driving cell (sub) population and to understand the specifics in the biological network of these cells. This basic scientific insight might foster the development of more specific therapeutic target patterns. The experimental approach is based on a side population (SP) of Ewing cells, based on the model cell line CADO-ES1. The SP is established by flow cytometry and defined by the idea that tumor stem-like cells can be identified by the time-course in clearing a given artificial dye. The SP was characterized by a higher colony forming activity, by a higher differentiation potential, by higher resistance to cytotoxic drugs, and by morphology. Several SP and non-SP cell fractions and bone marrow-derived mesenchymal stem cell reference were analyzed by short read sequencing of the full transcriptome. The double-differential analysis leads to an altered expression structure of SP cells centered around the AP-1 and APC/c complex. The SP cells share only a limited proportion of the full mesenchymal stem cell stemness set of genes. This is in line with the expectation that tumor stem-like cells share only a limited subset of stemness features which are relevant for tumor survival

MicroRNA expression in serum samples of sulfur mustard veterans as a diagnostic gateway to improve care

Sulfur mustard is a vesicant chemical warfare agent, which has been used during Iraq-Iran-war. Many veterans and civilians still suffer from long-term complications of sulfur mustard exposure, especially in their lung. Although the lung lesions of these patients are similar to Chronic Obstructive Pulmonary Disease (COPD), there are some differences due to different etiology and clinical care. Less is known on the molecular mechanism of sulfur mustard patients and specific treatment options. microRNAs are master regulators of many biological pathways and proofed to be stable surrogate markers in body fluids. Based on that microRNA expression for serum samples of sulfur mustard patients were examined, to establish specific microRNA patterns as a basis for diagnostic use and insight into affected molecular pathways. Patients were categorized based on their long-term complications into three groups and microRNA serum levels were measured. The differentially regulated microRNAs and their corresponding gene targets were identified. Cell cycle arrest, ageing and TGF-beta signaling pathways showed up to be the most deregulated pathways. The candidate microRNA miR-143-3p could be validated on all individual patients. In a ROC analysis miR-143-3p turned out to be a suitable diagnostic biomarker in the mild and severe categories of patients. Further microRNAs which might own a link to the biology of the sulfur mustard patients are miR-365a-3p, miR-200a-3p, miR-663a. miR-148a-3p, which showed up only in a validation study, might be linked to the airway complications of the sulfur mustard patients. All the other candidate microRNAs do not directly link to COPD phenotype or lung complications. In summary the microRNA screening study characterizes several molecular differences in-between the clinical categories of the sulfur mustard exposure groups and established some useful microRNA biomarkers. qPCR raw data is available via the Gene Expression Omnibus https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE110797

Digital Holographic Microscopy for Label-Free Detection of Leukocyte Alternations Associated with Perioperative Inflammation after Cardiac Surgery

In a prospective observational pilot study on patients undergoing elective cardiac surgery with cardiopulmonary bypass, we evaluated label-free quantitative phase imaging (QPI) with digital holographic microscopy (DHM) to describe perioperative inflammation by changes in biophysical cell properties of lymphocytes and monocytes. Blood samples from 25 patients were investigated prior to cardiac surgery and postoperatively at day 1, 3 and 6. Biophysical and morphological cell parameters accessible with DHM, such as cell volume, refractive index, dry mass, and cell shape related form factor, were acquired and compared to common flow cytometric blood cell markers of inflammation and selected routine laboratory parameters. In all examined patients, cardiac surgery induced an acute inflammatory response as indicated by changes in routine laboratory parameters and flow cytometric cell markers. DHM results were associated with routine laboratory and flow cytometric data and correlated with complications in the postoperative course. In a subgroup analysis, patients were classified according to the inflammation related C-reactive protein (CRP) level, treatment with epinephrine and the occurrence of postoperative complications. Patients with regular courses, without epinephrine treatment and with low CRP values showed a postoperative lymphocyte volume increase. In contrast, the group of patients with increased CRP levels indicated an even further enlarged lymphocyte volume, while for the groups of epinephrine treated patients and patients with complicative courses, no postoperative lymphocyte volume changes were detected. In summary, the study demonstrates the capability of DHM to describe biophysical cell parameters of perioperative lymphocytes and monocytes changes in cardiac surgery patients. The pattern of correlations between biophysical DHM data and laboratory parameters, flow cytometric cell markers, and the postoperative course exemplify DHM as a promising diagnostic tool for a characterization of inflammatory processes and course of disease