Project description:Global miRNA expression profiling of human malignancies is gaining popularity in both basic and clinically driven research. But to date, the majority of such analyses have used microarrays and quantitative real-time PCR. With the introduction of digital count technologies, such as next-generation sequencing (NGS) and the NanoString nCounter System, we have at our disposal, many more options. To make effective use of these different platforms, the strengths and pitfalls of several miRNA profiling technologies were assessed, including a microarray platform, NGS technologies and the NanoString nCounter System. These results were compared to gold-standard quantitative real-time PCR. Comparison of non-small cell lung cancer cell lines grown in vitro (n = 5) and in vivo (n = 5) as xenograft models.
Project description:Global miRNA expression profiling of human malignancies is gaining popularity in both basic and clinically driven research. But to date, the majority of such analyses have used microarrays and quantitative real-time PCR. With the introduction of digital count technologies, such as next-generation sequencing (NGS) and the NanoString nCounter System, we have at our disposal, many more options. To make effective use of these different platforms, the strengths and pitfalls of several miRNA profiling technologies were assessed, including a microarray platform, NGS technologies and the NanoString nCounter System. These results were compared to gold-standard quantitative real-time PCR. Comparison of non-small cell lung cancer cell lines grown in vitro (n = 5) and in vivo (n = 5) as xenograft models.
Project description:Amplification and activation of the Met receptor tyrosine kinase occurs up to 23% of gastric cancers, suggesting that Met is a therapeutic target in these cancers. However, the steady-state signaling events that occur during chronic Met activation, and mechanisms for resistance to Met small-molecule inhibitors, are poorly understood. Here we show that multiple gastric cancer cell lines harboring MET amplifications are dependent on Met signaling for proliferation and anchorage-independent growth. In these cells, short-term inhibition of Met leads to coordinated changes in gene expression; these include a rapid loss in expression of immediate-early genes, followed by decreased expression of genes involved in cell cycle and proliferation. Activation of Ras-Erk, PI3K-Akt and STAT3 pathways is attenuated by acute Met inhibition. STAT3 inhibition alone, but not individual inhibition of Mek or Akt, is sufficient to abrogate Met-dependent growth of these cells. However, following chronic Met inhibition, reactivation of Mek-dependent Erk phosphorylation occurs even in the presence of Met inhibitor corresponding with a downregulation of Erk negative regulators DUSP4/6. This provides a mechanism for the emergence of drug resistance. Our findings provide insights into innate resistance to a small-molecule Met inhibitor and highlight rational combination therapies that could be evaluated in clinical trials. Time series experiment, four cell lines, 2 treatments
Project description:Background: Translation deregulation is an important mechanism that causes aberrant cell growth, proliferation and survival. eIF4E, the mRNA 5 prime capâ??binding protein, plays a major role in translational control. To understand how eIF4E affects cellular proliferation and cell survival, we identified mRNA targets that are translationally responsive to eIF4E. Methodology/ principal findings: Microarray analysis of polysomal mRNA from an eIF4E-inducible NIH 3T3 cell line was performed. Induction of eIF4E expression resulted in increased translation of a defined set of mRNAs; many of the mRNAs are novel targets, including those that encode large- and small-subunit ribosomal proteins and cell growthâ??related factors. eIF4E overexpression also led to augmented translation of mRNAs encoding anti-apoptotic proteins, which conferred resistance to endoplasmic reticulumâ??mediated apoptosis. Conclusions/ significance: Our results shed new light on the mechanisms by which eIF4E prevents apoptosis and transforms cells. Downregulation of eIF4E and its downstream targets is a therapeutic option for the development of novel anti-cancer drugs. Keywords: time course Comparison of total and polysomal RNA upon eIF4E iinduction in NIH3T3/parental and NIH3T3/eIF4E cells Each of the following pairs were generated from one hybridization: GSM153931 GSM153932 GSM153933 GSM153934 GSM153935 GSM153936 GSM153937 GSM153938 GSM153939 GSM153940 GSM153941 GSM153942 GSM153943 GSM153944 GSM153945 GSM153946 GSM153947 GSM153948 GSM153949 GSM153950 GSM153951 GSM153952 GSM153953 GSM153954 GSM153955 GSM153956 GSM153957 GSM153958 GSM153959 GSM153960 GSM153961 GSM153962
Project description:We profiled Myc binding in a normal breast cell-line (MCF10A) under basal conditions after ectopic expression of Myc. We showed that ectopic Myc expression increases tumour formation in vivo and in vitro. We then profiled genome-wide Myc binding using Agilent promoter arrays in MCF10A cells expressing wild-type and ectopic Myc. We show that Myc binds to a greater number of spots in wild-type than in Myc cells, but that some targets are unique to each condition. Keywords: genetic-modification and stress-response We compared ectopic Myc to wild-type cells under wild-type and serum-deprived conditions with 4 replicates per condition
Project description:Objective - The TRIB1 locus has been linked to hepatic triglyceride metabolism in mice and to plasma triglycerides and coronary artery disease (CAD) in humans. The lipid associated SNPs identified by genome-wide association studies (GWAS) are located ~ 30 kb downstream from TRIB1 suggesting complex regulatory effects on genes or pathways relevant to hepatic triglyceride metabolism. The goal of this study was to investigate the functional relationship between common SNPs at the TRIB1 locus and plasma lipid traits. Methods & Results - Characterization of the risk locus reveals that it encompasses a gene, TRIB1 associated locus (TRIBAL) comprised of a well conserved promoter region and an alternatively spliced transcript. Bioinformatic analysis and re-sequencing identified a single nucleotide polymorphism (SNP), rs2001844, within the promoter region that associates with increased plasma triglycerides, reduced HDL-C and CAD risk. Furthermore, we show that rs2001844 is an expression trait locus (eQTL) for TRIB1 expression in blood and alters TRIBAL promoter activity in a reporter assay model. The TRIBAL transcript has features typical of long noncoding RNAs (lncRNA), including poor sequence conservation. Modulation of TRIBAL expression had limited impact on either TRIB1 or lipid regulatory genes mRNA levels in human hepatocyte models. In contrast, TRIB1 knockdown markedly increased TRIBAL expression in HepG2 cells and primary human hepatocytes. Conclusions - These studies demonstrate an interplay between a novel locus,TRIBAL, and TRIB1. TRIBAL is located in the GWAS identified risk locus, responds to altered expression of TRIB1, harbors a risk SNP that is an eQTL for TRIB1 expression and associates with plasma triglyceride concentrations. HepG2 hepatoma cells were stably infected with TRIBAL1 or no insert carrying lentiviruses
Project description:Background: As costs decline, the size and scope of microarray experiments have increased. In multi-centre studies there is a need to ensure consistency of data pre-processing across centres. Similarly, in smaller scale studies the evolution of microarray platforms means that there is often a need to compare data generated on earlier microarrays to that generated on newer ones. It is important in such studies to ensure that platform-dependent biases are removed so that meta-analysis of different datasets can be performed reliably. In both these cases the optimal scenario is to have a small subset of samples repeated at each site or on each platform. These replicates can then be used to learn a relationship between probe intensities on the two platforms. Results: I introduce here a simple, linear-modelling-based method for normalizing data from multiple-platforms by using replicate hybridizations. A dataset of 20 rat liver samples is used as a benchmark. Eight samples are hybridized to two separate versions of Affymetrix microarrays, while the other 12 are hybridized to one, for a total of 28 arrays. Our linear modelling method removes platform bias as assessed using both unsupervised machine-learning and two-group statistical analyses. The method is computationally efficient and works well for data pre-processed by the GCRMA, RMA and MAS5 algorithms and using either default or alternative probe-mappings. The method is very stable towards the number of replicate samples used, with even two replicates greatly reducing platform-specific bias. Conclusions: A simple linear-modelling method can remove platform-specific bias independent of the pre-processing algorithm and ProbeSet-mapping used. This technique can readily be extended to multi-site experiments, and suggests the benefits of including a small number of replicate hybridizations in each new study as a normalization control. Twenty rats livers were processed, eight on both RAE230-A and RAE230-2 arrays, 8 on only RAE230-A arrays, and 4 on RAE230-2 arrays only.
Project description:Expression data from Total RNA extracted from murine spleen. Sepsis was induced in C57Bl/6J mice by cecal ligation and puncture (CLP), followed 6 hours later by an intravenous injection of Mesenchymal Stem Cell (MSC) or saline. Twenty-eight hours after CLP, plasma, bronchoalveolar lavage (BAL) fluid and tissues were collected for analyses. Total RNA was extracted using Trizol (as per manufactures' instruction) followed by clean-up procedure using Qiagen RNA easy Prep (as per manufactures instructions) In the following study we hypothesized that mesenchymal stem cells (MSCs), which have documented immunomodulatory properties, would reduce sepsis-associated inflammation and organ injury in a clinically relevant model of sepsis. To identify the molecular changes associated with decreased inflammation in CLP-injured mice treated with MSCs, we analyzed the gene expression profiles from spleens collected at 28 hours from 4 animals per group: sham/saline, CLP/saline, and CLP/MSCs.
Project description:We developed Del-Read, an algorithm targeting medium-sized deletions (6-100 BPs) in short-reads, which are challenging for current variant callers relying on alignment. Our focus was on Micro-Homology mediated End Joining deletions (MMEJ-dels), prevalent in myeloid malignancies. MMEJ-dels follow a distinct pattern, occurring between two homologies, allowing us to generate a comprehensive list of MMEJ-dels in the exome. Using Del-Read, we identified numerous novel germline and somatic MMEJ-dels in Beat AML and TCGA-breast datasets. Validation in 500 healthy individuals confirmed their presence.