COEXPRESSIONFINDER: A NEW ALGORITHM FOR FINDING GROUPS OF COEXPRESSED GENES

2006 ◽  
Vol 04 (04) ◽  
pp. 853-864
Author(s):  
SERGEY I. ROGOV ◽  
KUVAT T. MOMYNALIEV ◽  
VADIM M. GOVORUN
Keyword(s):  
Gene Expression ◽  
Hierarchical Clustering ◽  
Parallel Execution ◽  
Expression Vectors ◽  
Dna Arrays ◽  
Java Application ◽  
Coordinated Expression ◽  
Series Of Experiments ◽  
Coexpressed Genes

Results: A new algorithm is developed which is intended to find groups of genes whose expression values change in a concordant manner in a series of experiments with DNA arrays. This algorithm is named as CoexpressionFinder. It can find more complete and internally coordinated groups of gene expression vectors than hierarchical clustering. Also, it finds more genes having coordinated expression. The algorithm's design allows parallel execution. Availability: The algorithm is implemented as a Java application which is freely available at: and .

scholarly journals Discovering Distinct Patterns in Gene Expression Profiles

2008 ◽  
Vol 5 (2) ◽  
Author(s):  
Li Teng ◽  
Laiwan Chan
Keyword(s):  
Gene Expression ◽  
Large Scale ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Gene Expression Profiles ◽  
Clustering Methods ◽  
Gene Expressions ◽  
Real Gene ◽  
Large Scale Dataset ◽  
Coexpressed Genes

SummaryTraditional analysis of gene expression profiles use clustering to find groups of coexpressed genes which have similar expression patterns. However clustering is time consuming and could be diffcult for very large scale dataset. We proposed the idea of Discovering Distinct Patterns (DDP) in gene expression profiles. Since patterns showing by the gene expressions reveal their regulate mechanisms. It is significant to find all different patterns existing in the dataset when there is little prior knowledge. It is also a helpful start before taking on further analysis. We propose an algorithm for DDP by iteratively picking out pairs of gene expression patterns which have the largest dissimilarities. This method can also be used as preprocessing to initialize centers for clustering methods, like K-means. Experiments on both synthetic dataset and real gene expression datasets show our method is very effective in finding distinct patterns which have gene functional significance and is also effcient.

scholarly journals BIOM-16. IMMUNOMIC ANALYSIS OF GLIOBLASTOMA (GBM) USING GENE EXPRESSION PROFILING

2020 ◽  
Vol 22 (Supplement_2) ◽  
pp. ii5-ii5
Author(s):  
Michael Castro ◽  
Nilofar Badra-Azar ◽  
Thomas Kessler ◽  
Moritz Schütte ◽  
Bodo Lange ◽  
...  
Keyword(s):  
Gene Expression ◽  
Antigen Presentation ◽  
Hierarchical Clustering ◽  
Immune Evasion ◽  
Human Cancer ◽  
Progression Free Survival ◽  
Immune Checkpoints ◽  
Successful Implementation ◽  
Cell Trafficking ◽  
Box Plots

Abstract BACKGROUND Despite the success of immunotherapy across the spectrum of human cancer, a successful strategy has not emerged for GBM. While PD-L1 IHC and TMB have demonstrated some utility as predictors of immunotherapy benefit, responsiveness is complexly determined by factors affecting T cell trafficking, antigen presentation, other immune checkpoints, and mediators of immune exhaustion. Thus, we set out to to characterize mediators of immune resistance and their diversity in a population of GBM patients utilizing quantitative gene expression. METHODS A set of 54 immunotherapy and checkpoint relevant genes and seven genes related to immune failure were selected from the literature. RNA gene counts for TCGA glioblastoma multiforme samples (N=163) were downloaded from https://portal.gdc.cancer.gov/. Annotation on subtypes and PFS values were obtained from PMID: 24120142. Gene expression normalization as FPKM, hierarchical clustering and box-plots were performed using R-3.6.0. Statistical differences of gene expression between subtypes were quantified using a TurkeyHSD test. RESULTS A heatmap with hierarchical clustering for immune related genes for the TCGA GBM cohort was generated including colored annotation for the subtype and progression free survival. The graph shows a rough separation into two groups, where one group of the genes is tentatively associated with mesenchymal subtype and shorter survival and showing higher expression for most immune evasion genes. However, a heterogeneity of immune evasion signatures was identified within and across subtypes. Transcripts related to antigen presentation, EZH2, and LDHA varied significantly between GBM subtypes (p < 0.05). CONCLUSION Gene expression analysis has utility to identify specific mediators of immune evasion and to inform the selection of combination therapies for discrete subsets of patients. A Bayesian approach to patient selection for specific immunotherapy strategies may enhance the likelihood of successful implementation of immunotherapy in the clinic.

The responsiveness of embryonic stem cells to alpha and beta interferons provides the basis of an inducible expression system for analysis of developmental control genes

1993 ◽  
Vol 13 (12) ◽  
pp. 7971-7976
Author(s):  
L M Whyatt ◽  
A Düwel ◽  
A G Smith ◽  
P D Rathjen
Keyword(s):  
Gene Expression ◽  
Inner Cell Mass ◽  
Es Cells ◽  
Expression System ◽  
Cell Mass ◽  
Embryonic Stem ◽  
Expression Vectors ◽  
Developmental Control ◽  
Developmental Potential

Embryonic stem (ES) cells, derived from the inner cell mass of the preimplantation mouse embryo, are used increasingly as an experimental tool for the investigation of early mammalian development. The differentiation of these cells in vitro can be used as an assay for factors that regulate early developmental decisions in the embryo, while the effects of altered gene expression during early embryogenesis can be analyzed in chimeric mice generated from modified ES cells. The experimental versatility of ES cells would be significantly increased by the development of systems which allow precise control of heterologous gene expression. In this paper, we report that ES cells are responsive to alpha and beta interferons (IFNs). This property has been exploited for the development of inducible ES cell expression vectors, using the promoter of the human IFN-inducible gene, 6-16. The properties of these vectors have been analyzed in both transiently and stably transfected ES cells. Expression was minimal or absent in unstimulated ES cells, could be stimulated up to 100-fold by treatment of the cells with IFN, and increased in linear fashion with increasing levels of IFN. High levels of induced expression were maintained for extended periods of time in the continuous presence of the inducing signal or following a 12-h pulse with IFN. Treatment of ES cells with IFN did not affect their growth or differentiation in vitro or compromise their developmental potential. This combination of features makes the 6-16-based expression vectors suitable for the functional analysis of developmental control control genes in ES cells.

Angiogenic and T-effector subgroups identified by gene expression profiling (GEP) and propensity for PBRM1 and BAP1 alterations in clear cell renal cell carcinoma (ccRCC).

2021 ◽  
Vol 39 (6_suppl) ◽  
pp. 343-343
Author(s):  
Pedro C. Barata ◽  
Shuchi Gulati ◽  
Andrew Elliott ◽  
Arpit Rao ◽  
Hans J. Hammers ◽  
...  
Keyword(s):  
Gene Expression ◽  
Clinical Trials ◽  
Hierarchical Clustering ◽  
Immune Cell ◽  
Expression Profiles ◽  
Gene Expression Signature ◽  
Predictive Biomarkers ◽  
Primary Tumors ◽  
Metastatic Sites ◽  
Patient Subgroups

343 Background: With the emergence of multiple active treatment options in RCC, predictive biomarkers for optimal treatment selection are lacking. Gene expression data from IMmotion151 and Javelin Renal 101 clinical trials generated anti-angiogenic and immune signatures that warrant further validation. We aimed to describe the genomic and gene expression profiles in a multi-institutional database of patients with ccRCC, and its association with other biomarkers of interest. Methods: Whole transcriptome sequencing was performed for ccRCC patient samples submitted to a commercial CLIA-certified laboratory (Caris Life Sciences, Phoenix, AZ) from February 2019 to September 2020. Tumor GEP and hierarchical clustering based on the validated 66-gene signature (D’Costa et al, 2020) were used to identify patient subgroups. Samples from both primary tumors and metastatic sites were included. Results: A total of 316 patients with ccRCC, median age 62 (range 32-90), 71.8% men, were included. Tissue samples were obtained from primary tumor (46.5%), lung (12.3%), bone (9.5%), liver (4.7%) and other metastatic sites (27%). Gene expression analysis identified angiogenic, mixed and T-effector subgroups in 24.1%, 51.3% and 24.7%, respectively. Patients with angiogenic subgroup tumors compared to those with T-effector subgroup tumors were more likely to be older (63 versus 60 years, p=0.035), female (40.8% versus 16.7%, p=0.0009) and more frequently found in pancreatic/small bowel metastases (75% versus 12.5%, p=0.0103). Biomarkers of potential response to immunotherapy such as PD-L1 (p=0.0021), TMB (not significant), and dMMR/MSI-H status (not significant) were more frequent in the T-effector subgroup. PBRM1 mutations were more common in the angiogenic subgroup (62.0% vs 37.5%, p=0.0034) while BAP1 mutations were more common in the T-effector subgroup (18.6% versus 3.0%, p= 0.0035). Immune cell population abundance (e.g. NK cells, monocytes) and immune checkpoint gene expression (TIM-3, PD-L1, PD-L2, CTLA4) were also increased in the T-effector subgroup. Conclusions: Our hierarchical clustering results based on the 66-gene expression signature were concordant with results from prior studies. Patient subgroups identified by evaluation of angiogenic and T-effector signature scores exhibit significantly different mutations and immune profiles. These findings require prospective validation in future biomarker-selected clinical trials.

scholarly journals Tax induces the recruitment of NF-kB to unintegrated HIV-1 DNA to rescue viral gene expression and replication

2021 ◽  
Author(s):  
Ishak D. Irwan ◽  
Bryan R. Cullen
Keyword(s):  
Gene Expression ◽  
T Cells ◽  
Lentiviral Vectors ◽  
Expression Vectors ◽  
Viral Gene ◽  
Epigenetic Marks ◽  
Tax Protein ◽  
Human T Cell ◽  
Activation Of Transcription ◽  
Hiv 1

AbstractWe have previously reported that the normally essential step of integration of the HIV-1 proviral DNA intermediate into the host cell genome becomes dispensable in T cells that express the Human T cell leukemia virus 1 (HTLV-1) Tax protein. The rescue of integrase (IN) deficient HIV-1 replication by Tax results from the strong activation of transcription from the long terminal repeat (LTR) promoter on episomal HIV-1 DNA, an effect that is closely correlated with the recruitment of activating epigenetic marks, such as H3Ac, and depletion of repressive epigenetic marks, such as H3K9me3, from chromatinized unintegrated proviruses. In addition, activation of transcription from unintegrated HIV-1 DNA coincides with the recruitment of NF-kB to the two NF-kB binding sites found in the HIV-1 LTR enhancer. Here we report that the recruitment of NF-kB to unintegrated viral DNA precedes, and is a prerequisite for, Tax-induced changes in epigenetic marks, so that an IN-HIV-1 mutant lacking both LTR NF-kB sites is entirely non-responsive to Tax and fails to undergo the epigenetic changes listed above. We also report that heterologous promoters introduced into IN-HIV-1-based vectors are transcriptionally active even in the absence of Tax. Finally, we failed to reproduce a recent report arguing that heterologous promoters introduced into IN-vectors based on HIV-1 are more active if the HIV-1 promoter and enhancer, located in the LTR U3 region, are deleted, in a so-called self inactivating or SIN lentivector design.ImportanceIntegrase-deficient expression vectors based on HIV-1 are becoming increasingly popular as tools for gene therapy in vivo due to their inability to cause insertional mutagenesis. However, many IN-lentiviral vectors are able to achieve only low levels of gene expression and methods to increase this low level have not been extensively explored. Here we analyze how the HTLV-1 Tax protein is able to rescue the replication of IN-HIV-1 in T cells and describe IN-lentiviral vectors that are able to express a heterologous gene effectively.

Insect baculoviruses: Powerful gene expression vectors

BioEssays ◽  
1989 ◽  
Vol 11 (4) ◽  
pp. 91-95 ◽  
Author(s):  
Lois K. Miller
Keyword(s):  
Gene Expression ◽  
Expression Vectors

STK11/TP53 co-mutated non-small cell lung cancer (NSCLC) to display a unique tumor microenvironment (TME) and metabolic profile.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. 9087-9087
Author(s):  
Abdul Rafeh Naqash ◽  
Charalampos S. Floudas ◽  
Asaf Maoz ◽  
Joanne Xiu ◽  
Yasmine Baca ◽  
...  
Keyword(s):  
Gene Expression ◽  
Hierarchical Clustering ◽  
Immune Cell ◽  
Nk Cell ◽  
Checkpoint Inhibitors ◽  
Tp53 Gene ◽  
Suppressor Gene ◽  
Metabolic Reprogramming ◽  
Glutamine Metabolism ◽  
Cell Content

9087 Background: Recent data suggest inferior responses to immune checkpoint inhibitors (ICIs) in STK11-mt NSCLC. TP53 is a critical tumor suppressor gene regulating DNA repair by arresting cells in the G1 phase in response to critical double strand breaks. We hypothesized that accumulated DNA damage from mutations in the TP53 gene might increase immunogenicity and potentially enhance benefit of ICIs in STK11-mt NSCLC. Methods: A total of 16,896 NSCLC tumors submitted to Caris Life Sciences (Phoenix, AZ) for targeted NGS (DNA-Seq, 592 genes) were analyzed. A subset (N = 5034 tumors) had gene expression profiling (RNA-Seq, whole transcriptome). PD-L1 (TPS) was tested with 22c3 antibody (Dako). Exome-level neoantigen load for STK11-mt NSCLC was obtained from published TCGA Pan-immune analysis (Thorsson et al. 2018). Non-parametric tests were used for comparing differences in tumor mutational burden (TMB) and neoantigen load. Transcriptomic analysis included differential gene expression and hierarchical clustering. Tumor immune cell content was obtained from transcriptome using Microenvironment Cell Population-counter (MCP). Publicly available data from the POPLAR/OAK trials of atezolizumab in advanced NSCLC were used to model PFS and OS for STK11-mt with TP53-mt (n = 14) and without TP53-mt (n = 20). Results: Of 16,896 NSCLC samples, 12.6% had an STK11-mt with the proportions of TMB-high (≥10 Mut/Mb), PD-L1 ≥ 50% and MSI-high being 55.9%, 11.8%, and 0.72%, respectively. STK11-mt vs. STK11-wt NSCLC did not differ in median TMB (Caris:10 vs. 10 Mut/Mb; p > 0.1) or neoantigen load (TCGA: 154.5 vs. 165; p > 0.1). Median TMB (13 vs. 9 Mut/Mb; p < 0.001) and neoantigen load (263 vs. 134; p < 0.001) were higher in STK11-mt/ TP53-mt vs. STK11-mt/ TP53-wt. MCP analysis showed higher CD8, NK-cell and lower myeloid dendritic cell infiltration in STK11-mt/ TP53-mt vs. STK11-mt/ TP53-wt (p < 0.01). Expression of MYC and HIF-α were increased in the STK11-mt/ TP53-mt vs. STK11-mt/ TP53-wt (p < 0.01) along with higher expression (p < 0.01) of genes associated with both glycolysis ( HK2, LDHA, ALDOA) and glutamine metabolism ( GOT2, PPAT2). Hierarchical clustering of STK11-mt adenocarcinomas (n = 463) for STING pathway genes (CCL5, CXCL10, cGAS) identified a STING-high and a STING low cluster. The STING high cluster was significantly enriched in TP53-mt (48 vs. 32%; p < 0.01).In the OAK/POPLAR cohort, median OS (HR is 1.14, 95% CI 0.53 - 2.48); p > 0.1) and PFS (HR 1.88, 95% CI 0.89-3.97, p = 0.098) were not statistically different between STK11-mt/ TP53-mt vs. STK-mt/ TP53-wt. However, the 15-months PFS was 21% in the STK11-mt/ TP53-mt vs 0% in the STK11-mt/ TP53-wt. Conclusions: STK11-mt NSCLC with TP53-mt are associated with an immunologically active TME with metabolic reprogramming. These intrinsic properties could be exploited to improve outcomes to ICIs in combination with metabolically directed agents.

Combined transcriptome sequencing and prokaryotic expression to investigate the key enzyme in the 2-C-methylerythritol-4-phosphate pathway of Osmanthus fragrans

2020 ◽  
Vol 47 (10) ◽  
pp. 945
Author(s):  
Rui Xiong ◽  
Zhu Chen ◽  
Weiyu Wang ◽  
Li Jiang ◽  
Yan Xiang ◽  
...  
Keyword(s):  
Prokaryotic Expression ◽  
Expression Vectors ◽  
Pcr Analysis ◽  
Subcellular Localisation ◽  
Reaction Products ◽  
Osmanthus Fragrans ◽  
Qrt Pcr ◽  
Key Enzyme ◽  
Series Of Experiments ◽  
Main Components

Terpenoids are one of the main components of plant aromas. In the present study we investigated these compounds in Osmanthus fragrans Lour., which is a fragrant plant widely used for the production of essential oils. Quantitative real-time PCR (qRT-PCR) results of enzymes associated with the 2-C-methylerythritol-4-phosphate pathway confirmed that the TPS is a key enzyme for terpenoid synthesis in O. fragrans. In a series of experiments, we identified the TPS candidate genes in O. fragrans and revealed the underlying catalytic activity and subcellular localisation of the encoded proteins. Because there is no available O. fragrans reference genome, we sequenced and analysed its transcriptome and identified two putative TPS genes, OfTPS1 and OfTPS2. According to qRT-PCR analysis, both genes were most highly expressed at the full-bloom stage, suggesting that OfTPS1 and OfTPS2 contribute to O. fragrans terpenoid synthesis. To verify this hypothesis, we constructed prokaryotic expression vectors to obtain protein. In order to study the function of OfTPS1 and OfTPS2 in the synthesis of monoterpenes, the obtained proteins were reacted with geranyl pyrophosphate. As a result, two kinds of monoterpenes, (E)-β-ocimene and linalool, were detected from reaction products, respectively. In conclusion, OfTPS1 and OfTPS2 are both monoterpene synthases.

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