Gene Expression Analysis Of Samples Research Articles

FaStaNMF: a Fast and Stable Non-negative Matrix Factorization for Gene Expression.

Gene expression analysis of samples with mixed cell types only provides limited insight to the characteristics of specific tissues. In silico deconvolution can be applied to extract cell type specific expression, thus avoiding prohibitively expensive techniques such as cell sorting or single-cell sequencing. Non-negative matrix factorization (NMF) is a deconvolution method shown to be useful for gene expression data, in part due to its constraint of non-negativity. Unlike other methods, NMF provides the capability to deconvolve without prior knowledge of the components of the model. However, NMF is not guaranteed to provide a globally unique solution. In this work, we present FaStaNMF, a method that balances achieving global stability of the NMF results, which is essential for inter-experiment and inter-lab reproducibility, with accuracy and speed. Results: FaStaNMF was applied to four datasets with known ground truth, created based on publicly available data or by using our simulation infrastructure, RNAGinesis. We assessed FaStaNMF on three criteria - speed, accuracy, and stability, and it favorably compared to the standard approach of achieving reproduceable results with NMF. We expect that FaStaNMF can be applied successfully to a wide array of biological data, such as different tumor/immune and other disease microenvironments.

The Influence of Tonality on Auditory Sensitivity in Different Types of Musical Texture

Bovine tuberculosis (bTB), caused by Mycobacterium bovis (M. bovis) infection, disrupts conservation programs of threatened species such as the white rhinoceros (Ceratotherium simum). Interferon gamma release assays have been developed for the diagnosis of M. bovis infection in rhinoceros, however, the discovery of additional diagnostic biomarkers might improve the accuracy of case detection. The aim of this pilot study was therefore to evaluate a novel unbiased approach to candidate biomarker discovery and preliminary validation. Whole blood samples from twelve white rhinoceros were incubated in Nil and TB antigen tubes of the QuantiFERON® TB Gold (In-Tube) system after which RNA was extracted and reverse transcribed. Using the equine RT2 profiler PCR array, relative gene expression analysis of samples from two immune sensitized rhinoceros identified CCL4, CCL8, IL23A, LTA, NODAL, TNF, CSF3, CXCL10 and GPI as upregulated in response to antigen stimulation. Novel gene expression assays (GEAs) were designed for selected candidates, i.e. CCL4, CXCL10 and IFNG, and analysis of QFT-processed samples showed the CXCL10 GEA could distinguish between five M. bovis-infected and five uninfected rhinoceros. These findings confirm the value of the equine RT2 profiler PCR array as a useful tool for screening biomarkers for the diagnosis of M. bovis infection in rhinoceros.

Cytokine biomarker discovery in the white rhinoceros (Ceratotherium simum)

Bovine tuberculosis (bTB), caused by Mycobacterium bovis (M. bovis) infection, disrupts conservation programs of threatened species such as the white rhinoceros (Ceratotherium simum). Interferon gamma release assays have been developed for the diagnosis of M. bovis infection in rhinoceros, however, the discovery of additional diagnostic biomarkers might improve the accuracy of case detection. The aim of this pilot study was therefore to evaluate a novel unbiased approach to candidate biomarker discovery and preliminary validation. Whole blood samples from twelve white rhinoceros were incubated in Nil and TB antigen tubes of the QuantiFERON® TB Gold (In-Tube) system after which RNA was extracted and reverse transcribed. Using the equine RT2 profiler PCR array, relative gene expression analysis of samples from two immune sensitized rhinoceros identified CCL4, CCL8, IL23A, LTA, NODAL, TNF, CSF3, CXCL10 and GPI as upregulated in response to antigen stimulation. Novel gene expression assays (GEAs) were designed for selected candidates, i.e. CCL4, CXCL10 and IFNG, and analysis of QFT-processed samples showed the CXCL10 GEA could distinguish between five M. bovis-infected and five uninfected rhinoceros. These findings confirm the value of the equine RT2 profiler PCR array as a useful tool for screening biomarkers for the diagnosis of M. bovis infection in rhinoceros.

Bona fide gene expression analysis of samples from the bovine reproductive system by microfluidic platform

Sample types such as those from reproductive systems often yield scarce material, which limits RT-qPCR analysis to only a few targets. Recently developed high-throughput systems can potentially change this scenario, however, the nanoliter scale of such platforms requires extra processing, e.g., preamplification, which needs to be defined through observation and experience. In order to establish best practices in high-throughput PCR approaches using samples from reproductive systems, we evaluated the Biomark™ HD performance using 11 different sample types from the bovine reproductive system: blastocyst (single/pool), oocyte (pool), cumulus, granulosa, and theca cells, oviduct tissue, fetal ovary, testicle (adult/fetal), and uterine horn. We observed that the preamplification step is not just reliable, but mandatory. Our results indicated that 14-preamplification cycles associated to 5- and 7-fold-dilution is the best approach for those samples. Additionally, the Biomark™ HD system has a high intra and inter reproducibility, therefore its performance in duplicate is unnecessary for the ΔCq analysis, taking in consideration the cutoff value 4 < Cq < 22. In summary, this high-throughput approach is a reliable and excellent tool for studying the bovine reproductive system, especially using quantitatively-limited samples, as a larger number of target genes can be assessed from a very low amount of starting material.

Alidation of reference genes for quantitative expression analysis by qPCR in various tissues of date mussel (Lithophagalithophaga)

qPCR is a very popular method for identifying nucleotide sequences as a result of its sensitivity and relatively low cost and technical simplicity. Normalization is one of the most important steps in analyzing qPCR data and the use of reference genes is the most common normalization strategy. In the present study five commonly used reference genes (18S, 28S, ef1a, ß-act, and ?-tub) were evaluated for their stability in the mantle, gill, foot, and pallial gland of date mussel (L. lithophaga) in different seasons. Four different software packages were used for evaluation: geNorm, NormFinder, BestKeeper, and RefFinder. Although these programs contain different algorithms and analytical procedures, their ranking of the candidate reference genes was similar. Of the five selected reference genes 18S, 28S, and ef1a were determined as the three most stable in different tissues and seasons. A-tub was evaluated as the least stable reference gene and therefore inappropriate for normalization of quantitative gene expression data. The results will help improve the accuracy of gene expression analysis in samples of date mussel and at the same time provide guidance for selection of reference genes in future qPCR studies in the species.

Abstract 2792: The small molecule imipridone ONC201 is active in tumor types with dysregulation of the DRD2 pathway

Abstract ONC201 is the lead small molecule of the imipridone class of anti-cancer compounds that is currently being evaluated in phase I/II advanced cancer clinical trials. ONC201 is a highly selective antagonist of the G protein-coupled receptor dopamine receptor D2 (DRD2) that has exhibited promising anti-cancer efficacy and an exceptional safety profile. In the current study, we evaluated the influence of the DRD2 pathway on the responsiveness of tumors to ONC201 in preclinical and clinical studies. In vitro and in vivo studies have previously demonstrated robust ONC201 efficacy in glioblastoma (Allen et al 2013) and lymphoma (Ishizawa et al 2016) models. ONC201 Phase I trials have also revealed evidence of clinical benefit in endometrial cancer (Stein et al 2016). In vitro efficacy profiling of ONC201 in the Genomic of Drug Sensitivity in Cancer (GDSC) collection of cell lines confirmed broad-spectrum anti-cancer efficacy with particularly high sensitivity in lymphoma, neuroblastoma, endometrial and brain cancer. DRD2 is overexpressed in many cancers and DRD2 antagonism kills cancer cells via the same signaling pathways that are altered in response to ONC201. Results from the Project Achilles screen indicate that anti-cancer effects of DRD2 knockdown in various tumor types correlated with overall ONC201 efficacy. In particular, we noted that lymphoma cells are highly sensitive to DRD2 knockdown- a tumor type where ONC201 performs well. Gene expression analysis of samples in the Cancer Genome Atlas (TCGA) revealed high DRD2 expression in ONC201-sensitive tumor types, such as lymphoma and glioblastoma, and that high expression of DRD2 in glioma was associated with a poor prognosis. High DRD2 expression was also observed in neuroendocrine prostate cancer relative to other prostate cancer subtypes. In immunohistochemistry analyses of patient-derived tumor tissue microarrays, DRD2 overexpression was particularly noted in endometrial cancer, neuroblastoma and pheochromocytoma relative to normal tissues. The anti-cancer activity of ONC201 in pheochromocytoma and neuroendocrine prostate cancer was confirmed in cell viability assays. In ONC201-treated patients, ELISA was used to quantitate serum prolactin levels, a clinical biomarker of DRD2 antagonism. A 2-fold mean induction of prolactin, was detected in the serum of ONC201-treated patients, in accordance with physiological DRD2 antagonism. Interestingly, expression of DRD5 (a D1-like dopamine receptor), which counteracts DRD2 signaling, was significantly negatively correlated with ONC201 in vitro potency in the NCI60 and GDSC dataset (P &amp;lt;.05). Furthermore, a missense DRD5 mutation was identified in cancer cells with acquired resistance to ONC201. In conclusion, the DRD2 pathway is expressed in ONC201-sensiive tumors and may provide biomarkers of response. Citation Format: Neel Madhukar, Varun Vijay Prabhu, Etienne Dardenne, Faye Doherty, Alexander VanEngelenburg, Rohinton Tarapore, Mathew Garnett, Ultan McDermott, Cyril Benes, Wolfgang Oster, Wafik El-Deiry, Mark Stein, David Rickman, Joshua Allen, Olivier Elemento. The small molecule imipridone ONC201 is active in tumor types with dysregulation of the DRD2 pathway [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 2792. doi:10.1158/1538-7445.AM2017-2792

Abstract 1155: Potent anti-cancer effects of selective GPR132/G2A agonist imipridone ONC212 in leukemia and lymphoma

Abstract ONC201, founding member of the imipridone class of compounds, is a highly selective small molecule G protein-coupled receptor (GPCR) antagonist that is in Phase I/II advanced cancer clinical trials. In this study, we evaluated GPCR engagement and antitumor activity of ONC212, an imipridone that is a chemical analogue of ONC201. Experimental GPCR profiling using the PathHunter® β-Arrestin assay, determined that ONC212 is a selective agonist of the orphan GPCR GPR132/G2A. Multidose validation confirmed nanomolar GPR132 agonist activity (EC50 ~400nM). GPR132 is a stress-inducible orphan GPCR that causes G2/M arrest. The tumor suppressive role of GPR132 has been demonstrated most notably in lymphoid leukemia. Gene expression analysis of samples in the Cancer Genome Atlas (TCGA) revealed GPR132 is expressed in a range of tumor types with highest expression in leukemia and lymphoma. The in vitro efficacy of ONC212 was assessed in the Genomic of Drug Sensitivity in Cancer (GDSC) collection of cell lines (&amp;gt;1,000 cell lines). Cell viability assays were performed at 72 hours post-treatment to generate dose responses curves at concentrations from 78nM up to 20μM. ONC212 was broadly efficacious across most solid tumors and hematological malignancies in the low nanomolar range. Ranking the sensitivity of cancer lines to ONC212 by tumor type revealed that leukemia and lymphoma are the most responsive tumor types based on completeness of response (area under the dose-response curve). Interestingly, we also observed that high expression of GPR132 significantly correlated with ONC212 efficacy in GDSC cell lines, suggesting the importance of GPR132 agonist activity for ONC212 efficacy. ONC212 was tested in 62 human leukemia cell lines that included acute myeloid leukemia (AML), acute lymphoblastic leukemia (ALL), chronic myelogenous leukemia (CML) and hairy cell leukemia. ONC212 demonstrated broad spectrum anti-leukemic activity and was equally efficacious across all leukemia subtypes tested. Most cell lines (60/62) were responsive to ONC212 with GI50 ranging from &amp;lt;78nM to 456nM. Within ALL, both B-cell and T-cell ALL were highly sensitive to ONC212. ONC212 reduced cell viability in AML independent of complex karyotypes and p53 mutations that are associated with poor clinical prognoses. ONC212 was also tested in 58 lymphoma cell lines comprised of anaplastic large cell lymphoma, Burkitt's lymphoma, cutaneous T-cell lymphoma (CTCL), diffuse large B-cell lymphoma (DLBCL), Mantle cell lymphoma (MCL), Follicular Lymphoma and Hodgkin’s lymphoma. ONC212 reduced cell viability in most cell lines (56/58) and was equally efficacious regardless of subtypes with GI50 ranging from &amp;lt;78nM to 261nM. Thus, GPR132 agonist ONC212 possesses robust anti-cancer activity in hematological malignancies irrespective of leukemia and lymphoma subtype and provides further validation of the anti-cancer efficacy of the novel imipridone class of small molecules. Citation Format: Varun Vijay Prabhu, Neel Madhukar, Rohinton Tarapore, Mathew Garnett, Ultan McDermott, Cyril Benes, Neil Charter, Sean Deacon, Wolfgang Oster, Michael Andreeff, Olivier Elemento, Martin Stogniew, Joshua Allen. Potent anti-cancer effects of selective GPR132/G2A agonist imipridone ONC212 in leukemia and lymphoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 1155. doi:10.1158/1538-7445.AM2017-1155

Transcriptomic analysis reveals a previously unknown role for CD8+ T-cells in rVSV-EBOV mediated protection

Ebola virus (EBOV) poses a significant threat to human health as highlighted by the recent epidemic in West Africa. Data from animal studies and a ring vaccination clinical trial conducted in Guinea during the recent epidemic demonstrated that a recombinant VSV where G protein is replaced with EBOV GP (rVSV-EBOV) is safe and highly efficacious. We previously established that antibodies are essential for rVSV-EBOV mediated protection against EBOV; however, the mechanisms by which this vaccine induces a humoral response and the role of T-cells in rVSV-EBOV mediated protection remain poorly understood. Since this is the only vaccine platform that has completed Phase III clinical studies, it is imperative to gain a better understanding of its mechanisms of protection. Therefore, we performed a longitudinal gene expression analysis of samples collected from controls and T-cell-depleted macaques after rVSV-EBOV vaccination and EBOV challenge. We show that rVSV-EBOV vaccination induces gene expression changes consistent with anti-viral immunity and B-cell proliferation. We also report a previously unappreciated role for CD8+ T-cells in mediating rVSV-EBOV protection. Finally, limited viral transcription in surviving animals may boost protective responses after EBOV challenge by maintaining transcriptional changes. This study presents a novel approach in determining mechanisms of vaccine efficacy.

Multiplex Amplification Targets for Gene Expression Analysis in a 1-Step Probe-Based RT-qPCR System

BioTechniquesVol. 61, No. 1 Sponsored Paper - Application ForumOpen AccessMultiplex amplification targets for gene expression analysis in a 1-step probe-based RT-qPCR systemSamantha Lewis & Trista SchagatSamantha LewisSearch for more papers by this author & Trista SchagatSearch for more papers by this authorPublished Online:16 Mar 2018https://doi.org/10.2144/000114437AboutSectionsPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack Citations ShareShare onFacebookTwitterLinkedInReddit OverviewThe ability to multiplex amplification targets for probe-based gene expression analysis of samples can save researchers time and money. Promega has developed an optimized set of reagents for 1-step probe-based chemistry detection, the GoTaq® Probe 1-Step RT-qPCR System, which we will show can be used for multiplex gene expression analysis with RNA samples. This master mix is also resistant to many of the common PCR inhibitors that challenge researchers.Benefits of Multiplexing:Saves money, time, and reagentsUses less sample and Master MixMaximizes instrumentation timeMethods and discussionsGene expression analysis of RNaseP, GAPDH, HPRT, and B2M was performed with human total colon RNA (Clonetech Laboratories) using the GoTaq® Probe 1-Step RT-qPCR System. An Applied Biosystems® 7500 FAST Real Time PCR System was used for amplification. Serial dilutions of RNA were run in single or 4-plex (Figure 1A-D). Cq values and amplification efficiencies were comparable for reactions in multiplex and singleplex reactions over a wide range of RNA concentrations. These results demonstrate successful multiplexing with four targets in a single reaction.Figure 1. Expression of the B2M (a), HPRT (b), GAPDH (c) and RNaseP (d) genes analyzed with a serial dilution of human total colon RNA in 4-plex or single reaction. Bars and error represent average ± standard deviation of N=4. PCR efficiencies are: 98.81% for B2M singleplex and 92.42% for B2M 4-plex, 98.22% for HPRT singleplex and 103.79% for HPRT 4-plex, 106.22% for RNaseP singleplex and 107.39% for RNaseP 4-plex, and 97.90% for GAPDH singleplex and 91.58% for GAPDH 4-plex.ConclusionThe GoTaq® Probe 1-Step RT-qPCR System can be used in qPCR studies that require multiple genes of interest to be analyzed in the same reaction well. We demonstrated that the GoTaq® Probe 1-Step RT-qPCR System can be successfully used for multiplex reactions with four targets.The benefits of this system include:Sensitive detection for earlier quantitation of low- and high-copy number targets.Resistance to a wide range of PCR inhibitors.Room temperature setups, suitable for automation and high-throughput detection.Compatible with both fast and standard qPCR cycling methodsBacked by Promega's PCR Satisfaction GuaranteeLearn more at www.promega.com/ProbeAndDyeFiguresReferencesRelatedDetails Vol. 61, No. 1 Follow us on social media for the latest updates Metrics History Published online 16 March 2018 Published in print July 2016 Information© 2016 Future Science LtdPDF download

Comparative Genomic Analysis of Drechmeria coniospora Reveals Core and Specific Genetic Requirements for Fungal Endoparasitism of Nematodes.

Drechmeria coniospora is an obligate fungal pathogen that infects nematodes via the adhesion of specialized spores to the host cuticle. D. coniospora is frequently found associated with Caenorhabditis elegans in environmental samples. It is used in the study of the nematode’s response to fungal infection. Full understanding of this bi-partite interaction requires knowledge of the pathogen’s genome, analysis of its gene expression program and a capacity for genetic engineering. The acquisition of all three is reported here. A phylogenetic analysis placed D. coniospora close to the truffle parasite Tolypocladium ophioglossoides, and Hirsutella minnesotensis, another nematophagous fungus. Ascomycete nematopathogenicity is polyphyletic; D. coniospora represents a branch that has not been molecularly characterized. A detailed in silico functional analysis, comparing D. coniospora to 11 fungal species, revealed genes and gene families potentially involved in virulence and showed it to be a highly specialized pathogen. A targeted comparison with nematophagous fungi highlighted D. coniospora-specific genes and a core set of genes associated with nematode parasitism. A comparative gene expression analysis of samples from fungal spores and mycelia, and infected C. elegans, gave a molecular view of the different stages of the D. coniospora lifecycle. Transformation of D. coniospora allowed targeted gene knock-out and the production of fungus that expresses fluorescent reporter genes. It also permitted the initial characterisation of a potential fungal counter-defensive strategy, involving interference with a host antimicrobial mechanism. This high-quality annotated genome for D. coniospora gives insights into the evolution and virulence of nematode-destroying fungi. Coupled with genetic transformation, it opens the way for molecular dissection of D. coniospora physiology, and will allow both sides of the interaction between D. coniospora and C. elegans, as well as the evolutionary arms race that exists between pathogen and host, to be studied.

THU0027 Response to Infliximab Therapy can be Predicted Using Distinct, Non-Overlapping Gene Panels of Peripheral Blood Gene Expression in Rheumatoid Arthritis and Crohn’s Disease

BackgroundBiological therapies targeting tumor necrosis factor α (TNF-α) have been widely used to treat chronic inflammatory disorders including rheumatoid arthritis (RA) and Crohn’s disease (CD). As these treatment modalities are...

Gene expression profiling for prediction of treatment response

9594 Background: We designed a strategy for patient stratification aimed at identifying tumor gene expression profiles that predict a favorable response to chemotherapy and allow selection of patients who would most benefit from treatment. Methods: A statistical model was developed based on global gene expression analysis of samples from 119 individuals. Two approaches were compared for their ability to disclose predictive gene expression profiles: (1) Compare normal ovary and ovarian adenocarcinoma and test that gene profile as a marker set to distinguish responsive from similarly treated, non-responsive carcinomas or (2) Directly compare gene expression profiles of responders and non-responders and apply this profile to patient samples to predict outcome. Samples were involved tissues from patients with ovarian cystadenocarcinoma obtained prior to treatment (n = 26) and histologically normal ovaries from controls (n = 93). 85% (22/26) of the ovarian carcinoma patients were advanced (Stage III-IV) disease and all were treated with paclitaxel-carboplatin. Follow-up was 6–59 months with an overall response rate of 61.5%. Gene expression was determined using Affymetrix U133 microarrays that contain >40,000 known genes and ESTs. Marker profiles were sought from pair-wise comparisons and successive validation performed by drop-replace analysis within the training sets. Results: Gene expression profiles were identified from the normal-disease comparison and were predictive of patient response to treatment. Genes can be individually weighted for their value in predicting treatment response and potentially chosen and assembled into a prognostic marker set. Conclusion: Cross-validation of the training set of 26 ovarian cancers, gives preliminary evidence that a gene set predicts outcome. The reference database of normal samples adds dimension to the building of classification models for patient disease stratification. This approach can now be compared to the predictive value of within-disease gene sets derived in the absence of normal samples. Gene expression promises to be valuable in selecting patients for clinical trials and disease management. Author Disclosure Employment or Leadership Consultant or Advisory Stock Ownership Honoraria Research Funding Expert Testimony Other Remuneration Gene Logic, Inc. Gene Logic, Inc. Gene Logic, Inc.

Gene expression profiling for prediction of treatment response

9594 Background: We designed a strategy for patient stratification aimed at identifying tumor gene expression profiles that predict a favorable response to chemotherapy and allow selection of patients who would most benefit from treatment. Methods: A statistical model was developed based on global gene expression analysis of samples from 119 individuals. Two approaches were compared for their ability to disclose predictive gene expression profiles: (1) Compare normal ovary and ovarian adenocarcinoma and test that gene profile as a marker set to distinguish responsive from similarly treated, non-responsive carcinomas or (2) Directly compare gene expression profiles of responders and non-responders and apply this profile to patient samples to predict outcome. Samples were involved tissues from patients with ovarian cystadenocarcinoma obtained prior to treatment (n = 26) and histologically normal ovaries from controls (n = 93). 85% (22/26) of the ovarian carcinoma patients were advanced (Stage III-IV) disease and all were treated with paclitaxel-carboplatin. Follow-up was 6–59 months with an overall response rate of 61.5%. Gene expression was determined using Affymetrix U133 microarrays that contain >40,000 known genes and ESTs. Marker profiles were sought from pair-wise comparisons and successive validation performed by drop-replace analysis within the training sets. Results: Gene expression profiles were identified from the normal-disease comparison and were predictive of patient response to treatment. Genes can be individually weighted for their value in predicting treatment response and potentially chosen and assembled into a prognostic marker set. Conclusion: Cross-validation of the training set of 26 ovarian cancers, gives preliminary evidence that a gene set predicts outcome. The reference database of normal samples adds dimension to the building of classification models for patient disease stratification. This approach can now be compared to the predictive value of within-disease gene sets derived in the absence of normal samples. Gene expression promises to be valuable in selecting patients for clinical trials and disease management. Author Disclosure Employment or Leadership Consultant or Advisory Stock Ownership Honoraria Research Funding Expert Testimony Other Remuneration Gene Logic, Inc. Gene Logic, Inc. Gene Logic, Inc.