Tomas Tokar

Identification of synovial fluid microRNA signature in knee osteoarthritis: differentiating early- and late-stage knee osteoarthritis.

OBJECTIVES This study aimed to identify circulating microRNA (miRNA) signatures in knee synovial fluid (SF) from early-stage and late-stage knee osteoarthritis (OA) patients. METHODS miRNAs were screened by miRNA-PCR-arrays and validated by Real-time quantitative polymerase chain reaction (RT-qPCR) in SF from early-stage (Kellgren-Lawrence (KL): Grade: I/II) and late-stage OA patients (Grade: III/IV). OA cartilage or synovial explants were cultured to study the source/release of identified miRNAs. Computational-approach was utilized to predict gene/pathway targets. RESULTS Our screening/validation analysis identified a panel of seven (out of 752) circulating miRNAs (23a-3p, 24-3p, 27a-3p, 27b-3p, 29c-3p, 34a-5p and 186-5p) that were significantly differentially expressed in late-stage vs early-stage OA-SF, irrespective of age, gender and Body Mass Index (BMI). miR-378a-5p was mostly detectable in majority of late-stage OA-SF. Cartilage explants stimulated with IL-1β showed a significant reduction in miR-23a-3p, 27a-3p and 27b-3p expression with no significant changes in other validated miRNAs. However, IL-1β-stimulated OA synovial explants exhibited significantly increased expression of miR-23a-3p, 24-3p, 27a-3p, 27b-3p, 29c-3p, 186-5p and 378a-5p, and release of only 23a-3p and 27b-3p in supernatants, suggesting that IL-1β contributes to the release of 23a-3p and 27b-3p into the SF from synovium. Computational-analysis identified 2 genes (ROQUIN-1 [RC3H1] and quaking-gene [QKI]) that are targeted by six out of eight miRNAs; miR-27b-3p exhibited greatest association with RC3H1 and QKI genes. Indeed, synovial explants treated with miR-27b-3p-mimic show significant suppression of both RC3H1 and QKI genes. CONCLUSIONS We provide first evidence of the differential expression of circulating miRNAs in early-stage vs late-stage knee OA-SF. Further, we provide source, release and genes/pathways regulated by identified miRNAs.

Integrative transcriptome analysis identifies deregulated microRNA-transcription factor networks in lung adenocarcinoma

Herein, we aimed at identifying global transcriptome microRNA (miRNA) changes and miRNA target genes in lung adenocarcinoma. Samples were selected as training (N = 24) and independent validation (N = 34) sets. Tissues were microdissected to obtain >90% tumor or normal lung cells, subjected to miRNA transcriptome sequencing and TaqMan quantitative PCR validation. We further integrated our data with published miRNA and mRNA expression datasets across 1,491 lung adenocarcinoma and 455 normal lung samples. We identified known and novel, significantly over- and under-expressed (p ≤ 0.01 and FDR≤0.1) miRNAs in lung adenocarcinoma compared to normal lung tissue: let-7a, miR-10a, miR-15b, miR-23b, miR-26a, miR-26b, miR-29a, miR-30e, miR-99a, miR-146b, miR-181b, miR-181c, miR-421, miR-181a, miR-574 and miR-1247. Validated miRNAs included let-7a-2, let-7a-3, miR-15b, miR-21, miR-155 and miR-200b; higher levels of miR-21 expression were associated with lower patient survival (p = 0.042). We identified a regulatory network including miR-15b and miR-155, and transcription factors with prognostic value in lung cancer. Our findings may contribute to the development of treatment strategies in lung adenocarcinoma.

STAT3 pathway regulates lung-derived brain metastasis initiating cell capacity through miR-21 activation.

Brain metastases (BM) represent the most common tumor to affect the adult central nervous system. Despite the increasing incidence of BM, likely due to consistently improving treatment of primary cancers, BM remain severely understudied. In this study, we utilized patient-derived stem cell lines from lung-to-brain metastases to examine the regulatory role of STAT3 in brain metastasis initiating cells (BMICs). Annotation of our previously described BMIC regulatory genes with protein-protein interaction network mapping identified STAT3 as a novel protein interactor. STAT3 knockdown showed a reduction in BMIC self-renewal and migration, and decreased tumor size in vivo. Screening of BMIC lines with a library of STAT3 inhibitors identified one inhibitor to significantly reduce tumor formation. Meta-analysis identified the oncomir microRNA-21 (miR-21) as a target of STAT3 activity. Inhibition of miR-21 displayed similar reductions in BMIC self-renewal and migration as STAT3 knockdown. Knockdown of STAT3 also reduced expression of known downstream targets of miR-21. Our studies have thus identified STAT3 and miR-21 as cooperative regulators of stemness, migration and tumor initiation in lung-derived BM. Therefore, STAT3 represents a potential therapeutic target in the treatment of lung-to-brain metastases.

Circulating plant miRNAs can regulate human gene expression in vitro

While Brassica oleracea vegetables have been linked to cancer prevention, the exact mechanism remains unknown. Regulation of gene expression by cross-species microRNAs has been previously reported; however, its link to cancer suppression remains unexplored. In this study we address both issues. We confirm plant microRNAs in human blood in a large nutrigenomics study cohort and in a randomized dose-controlled trial, finding a significant positive correlation between the daily amount of broccoli consumed and the amount of microRNA in the blood. We also demonstrate that Brassica microRNAs regulate expression of human genes and proteins in vitro, and that microRNAs cooperate with other Brassica-specific compounds in a possible cancer-preventive mechanism. Combined, we provide strong evidence and a possible multimodal mechanism for broccoli in cancer prevention.

mirDIP 4.1—integrative database of human microRNA target predictions

Abstract MicroRNAs are important regulators of gene expression, achieved by binding to the gene to be regulated. Even with modern high-throughput technologies, it is laborious and expensive to detect all possible microRNA targets. For this reason, several computational microRNA–target prediction tools have been developed, each with its own strengths and limitations. Integration of different tools has been a successful approach to minimize the shortcomings of individual databases. Here, we present mirDIP v4.1, providing nearly 152 million human microRNA–target predictions, which were collected across 30 different resources. We also introduce an integrative score, which was statistically inferred from the obtained predictions, and was assigned to each unique microRNA–target interaction to provide a unified measure of confidence. We demonstrate that integrating predictions across multiple resources does not cumulate prediction bias toward biological processes or pathways. mirDIP v4.1 is freely available at http://ophid.utoronto.ca/mirDIP/.

RNAi screen identifies essential regulators of human brain metastasis-initiating cells

Brain metastases (BM) are the most common brain tumor in adults and are a leading cause of cancer mortality. Metastatic lesions contain subclones derived from their primary lesion, yet their functional characterization is limited by a paucity of preclinical models accurately recapitulating the metastatic cascade, emphasizing the need for a novel approach to BM and their treatment. We identified a unique subset of stem-like cells from primary human patient brain metastases, termed brain metastasis-initiating cells (BMICs). We now establish a BMIC patient-derived xenotransplantation (PDXT) model as an investigative tool to comprehensively interrogate human BM. Using both in vitro and in vivo RNA interference screens of these BMIC models, we identified SPOCK1 and TWIST2 as essential BMIC regulators. SPOCK1 in particular is a novel regulator of BMIC self-renewal, modulating tumor initiation and metastasis from the lung to the brain. A prospective cohort of primary lung cancer specimens showed that SPOCK1 was overexpressed only in patients who ultimately developed BM. Protein–protein interaction network mapping between SPOCK1 and TWIST2 identified novel pathway interactors with significant prognostic value in lung cancer patients. Of these genes, INHBA, a TGF-β ligand found mutated in lung adenocarcinoma, showed reduced expression in BMICs with knockdown of SPOCK1. In conclusion, we have developed a useful preclinical model of BM, which has served to identify novel putative BMIC regulators, presenting potential therapeutic targets that block the metastatic process, and transform a uniformly fatal systemic disease into a locally controlled and eminently more treatable one.

Machine Learning for In Silico Modeling of Tumor Growth

The various interplaying variables of tumor growth remain key questions in cancer research, in particular what makes such a growth malignant and what are possible therapies to stop the growth and prevent re-growth. Given the complexity and heterogeneity of the disease, as well as the steadily growing set of publicly available big data sets, there is an urgent need for approaches to make sense out of these open data sets. Machine learning methods for tumor growth profiles and model validation can be of great help here, particularly, discrete multi-agent approaches.

Large-scale discovery of previously undetected microRNAs specific to human liver

MicroRNAs (miRNAs) are crucial regulators of gene expression in normal development and cellular homeostasis. While miRNA repositories contain thousands of unique sequences, they primarily contain molecules that are conserved across several tissues, largely excluding lineage and tissue-specific miRNAs. By analyzing small non-coding RNA sequencing data for abundance and secondary RNA structure, we discovered 103 miRNA candidates previously undescribed in liver tissue. While expression of some of these unannotated sequences is restricted to non-malignant tissue, downregulation of most of the sequences was detected in liver tumors, indicating their importance in the maintenance of liver homeostasis. Furthermore, target prediction revealed the involvement of the unannotated miRNA candidates in fatty-acid metabolism and tissue regeneration, which are key pathways in liver biology. Here, we provide a comprehensive analysis of the undiscovered liver miRNA transcriptome, providing new resources for a deeper exploration of organ-specific biology and disease.

Retraction: Circulating plant miRNAs can regulate human gene expression in vitro

We are retracting this Article as we no longer have confidence in the data to support our central conclusion – the detection of Brassica oleracea microRNAs in the bloodstream of humans who consumed broccoli.

Differentially expressed microRNAs in lung adenocarcinoma invert effects of copy number aberrations of prognostic genes

In many cancers, significantly down- or upregulated genes are found within chromosomal regions with DNA copy number alteration opposite to the expression changes. Generally, this paradox has been overlooked as noise, but can potentially be a consequence of interference of epigenetic regulatory mechanisms, including microRNA-mediated control of mRNA levels. To explore potential associations between microRNAs and paradoxes in non-small-cell lung cancer (NSCLC) we curated and analyzed lung adenocarcinoma (LUAD) data, comprising gene expressions, copy number aberrations (CNAs) and microRNA expressions. We integrated data from 1,062 tumor samples and 241 normal lung samples, including newly-generated array comparative genomic hybridization (aCGH) data from 63 LUAD samples. We identified 85 “paradoxical” genes whose differential expression consistently contrasted with aberrations of their copy numbers. Paradoxical status of 70 out of 85 genes was validated on sample-wise basis using The Cancer Genome Atlas (TCGA) LUAD data. Of these, 41 genes are prognostic and form a clinically relevant signature, which we validated on three independent datasets. By meta-analysis of results from 9 LUAD microRNA expression studies we identified 24 consistently-deregulated microRNAs. Using TCGA-LUAD data we showed that deregulation of 19 of these microRNAs explains differential expression of the paradoxical genes. Our results show that deregulation of paradoxical genes is crucial in LUAD and their expression pattern is maintained epigenetically, defying gene copy number status.