28,889 research outputs found

    Complex-based analysis of dysregulated cellular processes in cancer

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    Background: Differential expression analysis of (individual) genes is often used to study their roles in diseases. However, diseases such as cancer are a result of the combined effect of multiple genes. Gene products such as proteins seldom act in isolation, but instead constitute stable multi-protein complexes performing dedicated functions. Therefore, complexes aggregate the effect of individual genes (proteins) and can be used to gain a better understanding of cancer mechanisms. Here, we observe that complexes show considerable changes in their expression, in turn directed by the concerted action of transcription factors (TFs), across cancer conditions. We seek to gain novel insights into cancer mechanisms through a systematic analysis of complexes and their transcriptional regulation. Results: We integrated large-scale protein-interaction (PPI) and gene-expression datasets to identify complexes that exhibit significant changes in their expression across different conditions in cancer. We devised a log-linear model to relate these changes to the differential regulation of complexes by TFs. The application of our model on two case studies involving pancreatic and familial breast tumour conditions revealed: (i) complexes in core cellular processes, especially those responsible for maintaining genome stability and cell proliferation (e.g. DNA damage repair and cell cycle) show considerable changes in expression; (ii) these changes include decrease and countering increase for different sets of complexes indicative of compensatory mechanisms coming into play in tumours; and (iii) TFs work in cooperative and counteractive ways to regulate these mechanisms. Such aberrant complexes and their regulating TFs play vital roles in the initiation and progression of cancer.Comment: 22 pages, BMC Systems Biolog

    ProcessDriver: A Computational Pipeline to Identify Copy Number Drivers and Associated Disrupted Biological Processes in Cancer

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    Copy number amplifications and deletions that are recurrent in cancer samples harbor genes that confer a fitness advantage to cancer tumor proliferation and survival. One important challenge in computational biology is to separate the causal (i.e., driver) genes from passenger genes in large, aberrated regions. Many previous studies focus on the genes within the aberration (i.e., cis genes), but do not utilize the genes that are outside of the aberrated region and dysregulated as a result of the aberration (i.e., trans genes). We propose a computational pipeline, called ProcessDriver, that prioritizes candidate drivers by relating cis genes to dysregulated trans genes and biological processes. ProcessDriver is based on the assumption that a driver cis gene should be closely associated with the dysregulated trans genes and biological processes, as opposed to previous studies that assume a driver cis gene should be the most correlated gene to the copy number of an aberrated region. We applied our method on breast, bladder and ovarian cancer data from the Cancer Genome Atlas database. Our results included previously known driver genes and cancer genes, as well as potentially novel driver genes. Additionally, many genes in the final set of drivers were linked to new tumor events after initial treatment using survival analysis. Our results highlight the importance of selecting driver genes based on their widespread downstream effects in trans

    Alcohol-dysregulated miR-30a and miR-934 in head and neck squamous cell carcinoma.

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    BackgroundAlcohol consumption is a well-established risk factor for head and neck squamous cell carcinoma (HNSCC); however, the molecular mechanisms by which alcohol promotes HNSCC pathogenesis and progression remain poorly understood. Our study sought to identify microRNAs that are dysregulated in alcohol-associated HNSCC and investigate their contribution to the malignant phenotype.MethodUsing RNA-sequencing data from 136 HNSCC patients, we compared the expression levels of 1,046 microRNAs between drinking and non-drinking cohorts. Dysregulated microRNAs were verified by qRT-PCR in normal oral keratinocytes treated with biologically relevant doses of ethanol and acetaldehyde. The most promising microRNA candidates were investigated for their effects on cellular proliferation and invasion, sensitivity to cisplatin, and expression of cancer stem cell genes. Finally, putative target genes were identified and evaluated in vitro to further establish roles for these miRNAs in alcohol-associated HNSCC.ResultsFrom RNA-sequencing analysis we identified 8 miRNAs to be significantly upregulated in alcohol-associated HNSCCs. qRT-PCR experiments determined that among these candidates, miR-30a and miR-934 were the most highly upregulated in vitro by alcohol and acetaldehyde. Overexpression of miR-30a and miR-934 in normal and HNSCC cell lines produced up to a 2-fold increase in cellular proliferation, as well as induction of the anti-apoptotic gene BCL-2. Upon inhibition of these miRNAs, HNSCC cell lines exhibited increased sensitivity to cisplatin and reduced matrigel invasion. miRNA knockdown also indicated direct targeting of several tumor suppressor genes by miR-30a and miR-934.ConclusionsAlcohol induces the dysregulation of miR-30a and miR-934, which may play crucial roles in HNSCC pathogenesis and progression. Future investigation of the alcohol-mediated pathways effecting these transformations will prove valuable for furthering the understanding and treatment of alcohol-associated HNSCC

    Atypical miRNA expression in temporal cortex associated with dysregulation of immune, cell cycle, and other pathways in autism spectrum disorders.

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    BackgroundAutism spectrum disorders (ASDs) likely involve dysregulation of multiple genes related to brain function and development. Abnormalities in individual regulatory small non-coding RNA (sncRNA), including microRNA (miRNA), could have profound effects upon multiple functional pathways. We assessed whether a brain region associated with core social impairments in ASD, the superior temporal sulcus (STS), would evidence greater transcriptional dysregulation of sncRNA than adjacent, yet functionally distinct, primary auditory cortex (PAC).MethodsWe measured sncRNA expression levels in 34 samples of postmortem brain from STS and PAC to find differentially expressed sncRNA in ASD compared with control cases. For differentially expressed miRNA, we further analyzed their predicted mRNA targets and carried out functional over-representation analysis of KEGG pathways to examine their functional significance and to compare our findings to reported alterations in ASD gene expression.ResultsTwo mature miRNAs (miR-4753-5p and miR-1) were differentially expressed in ASD relative to control in STS and four (miR-664-3p, miR-4709-3p, miR-4742-3p, and miR-297) in PAC. In both regions, miRNA were functionally related to various nervous system, cell cycle, and canonical signaling pathways, including PI3K-Akt signaling, previously implicated in ASD. Immune pathways were only disrupted in STS. snoRNA and pre-miRNA were also differentially expressed in ASD brain.ConclusionsAlterations in sncRNA may underlie dysregulation of molecular pathways implicated in autism. sncRNA transcriptional abnormalities in ASD were apparent in STS and in PAC, a brain region not directly associated with core behavioral impairments. Disruption of miRNA in immune pathways, frequently implicated in ASD, was unique to STS

    Modeling cancer metabolism on a genome scale

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    Cancer cells have fundamentally altered cellular metabolism that is associated with their tumorigenicity and malignancy. In addition to the widely studied Warburg effect, several new key metabolic alterations in cancer have been established over the last decade, leading to the recognition that altered tumor metabolism is one of the hallmarks of cancer. Deciphering the full scope and functional implications of the dysregulated metabolism in cancer requires both the advancement of a variety of omics measurements and the advancement of computational approaches for the analysis and contextualization of the accumulated data. Encouragingly, while the metabolic network is highly interconnected and complex, it is at the same time probably the best characterized cellular network. Following, this review discusses the challenges that genome‐scale modeling of cancer metabolism has been facing. We survey several recent studies demonstrating the first strides that have been done, testifying to the value of this approach in portraying a network‐level view of the cancer metabolism and in identifying novel drug targets and biomarkers. Finally, we outline a few new steps that may further advance this field

    Differential expression of microRNAs in bovine papillomavirus type 1 transformed equine cells

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    Bovine papillomavirus (BPV) types 1 and 2 play an important role in the pathogenesis of equine sarcoids (ES), the most common cutaneous tumour affecting horses. MicroRNAs (miRNAs), small non-coding RNAs that regulate essential biological and cellular processes, have been found dysregulated in a wide range of tumours. The aim of this study was to identify miRNAs associated with ES. Differential expression of miRNAs was assessed in control equine fibroblasts (EqPalFs) and EqPalFs transformed with the BPV-1 genome (S6-2 cells). Using a commercially available miRNA microarray, 492 mature miRNAs were interrogated. In total, 206 mature miRNAs were differentially expressed in EqPalFs compared with S6-2 cells. Aberrant expression of these miRNAs in S6-2 cells can be attributed to the presence of BPV-1 genomes. Furthermore, we confirm the presence of 124 miRNAs previously computationally predicted in the horse. Our data supports the involvement of miRNAs in the pathogenesis of ES

    MicroRNA and transcription factor co-regulatory networks and subtype classification of seminoma and non-seminoma in testicular germ cell tumors

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    Recent studies have revealed that feed-forward loops (FFLs) as regulatory motifs have synergistic roles in cellular systems and their disruption may cause diseases including cancer. FFLs may include two regulators such as transcription factors (TFs) and microRNAs (miRNAs). In this study, we extensively investigated TF and miRNA regulation pairs, their FFLs, and TF-miRNA mediated regulatory networks in two major types of testicular germ cell tumors (TGCT): seminoma (SE) and non-seminoma (NSE). Specifically, we identified differentially expressed mRNA genes and miRNAs in 103 tumors using the transcriptomic data from The Cancer Genome Atlas. Next, we determined significantly correlated TF-gene/miRNA and miRNA-gene/TF pairs with regulation direction. Subsequently, we determined 288 and 664 dysregulated TF-miRNA-gene FFLs in SE and NSE, respectively. By constructing dysregulated FFL networks, we found that many hub nodes (12 out of 30 for SE and 8 out of 32 for NSE) in the top ranked FFLs could predict subtype-classification (Random Forest classifier, average accuracy ≥90%). These hub molecules were validated by an independent dataset. Our network analysis pinpointed several SE-specific dysregulated miRNAs (miR-200c-3p, miR-25-3p, and miR-302a-3p) and genes (EPHA2, JUN, KLF4, PLXDC2, RND3, SPI1, and TIMP3) and NSE-specific dysregulated miRNAs (miR-367-3p, miR-519d-3p, and miR-96-5p) and genes (NR2F1 and NR2F2). This study is the first systematic investigation of TF and miRNA regulation and their co-regulation in two major TGCT subtypes

    Assessing the carcinogenic potential of low-dose exposures to chemical mixtures in the environment: the challenge ahead.

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    Lifestyle factors are responsible for a considerable portion of cancer incidence worldwide, but credible estimates from the World Health Organization and the International Agency for Research on Cancer (IARC) suggest that the fraction of cancers attributable to toxic environmental exposures is between 7% and 19%. To explore the hypothesis that low-dose exposures to mixtures of chemicals in the environment may be combining to contribute to environmental carcinogenesis, we reviewed 11 hallmark phenotypes of cancer, multiple priority target sites for disruption in each area and prototypical chemical disruptors for all targets, this included dose-response characterizations, evidence of low-dose effects and cross-hallmark effects for all targets and chemicals. In total, 85 examples of chemicals were reviewed for actions on key pathways/mechanisms related to carcinogenesis. Only 15% (13/85) were found to have evidence of a dose-response threshold, whereas 59% (50/85) exerted low-dose effects. No dose-response information was found for the remaining 26% (22/85). Our analysis suggests that the cumulative effects of individual (non-carcinogenic) chemicals acting on different pathways, and a variety of related systems, organs, tissues and cells could plausibly conspire to produce carcinogenic synergies. Additional basic research on carcinogenesis and research focused on low-dose effects of chemical mixtures needs to be rigorously pursued before the merits of this hypothesis can be further advanced. However, the structure of the World Health Organization International Programme on Chemical Safety 'Mode of Action' framework should be revisited as it has inherent weaknesses that are not fully aligned with our current understanding of cancer biology
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