scholarly journals Rofecoxib modulates multiple gene expression pathways in a clinical model of acute inflammatory pain

Pain ◽  
2007 ◽  
Vol 128 (1) ◽  
pp. 136-147 ◽  
Author(s):  
Xiao-Min Wang ◽  
Tian-Xia Wu ◽  
May Hamza ◽  
Edward S. Ramsay ◽  
Sharon M. Wahl ◽  
...  
Keyword(s):  
Gene Expression ◽  
Inflammatory Pain ◽  
Multiple Gene ◽  
Clinical Model ◽  
Expression Pathways

Antioxidants increase number of progenitor endothelial cells through multiple gene expression pathways

2008 ◽  
Vol 42 (8) ◽  
pp. 754-762 ◽  
Author(s):  
Carmela Fiorito ◽  
Monica Rienzo ◽  
Ettore Crimi ◽  
Raffaele Rossiello ◽  
Maria Luisa Balestrieri ◽  
...  
Keyword(s):  
Gene Expression ◽  
Endothelial Cells ◽  
Multiple Gene ◽  
Expression Pathways

274 Tumoral and peripheral immunophenotype of refractory vs relapse to PD-(L)1 blockade in patients with advanced non-small cell lung cancer

2020 ◽  
Vol 8 (Suppl 3) ◽  
pp. A299-A299
Author(s):  
Maria Ascierto ◽  
Matthew Hellmann ◽  
Nathan Standifer ◽  
Song Wu ◽  
Han Si ◽  
...  
Keyword(s):  
Gene Expression ◽  
Informed Consent ◽  
Checkpoint Inhibitors ◽  
Patient Response ◽  
Calcium Dependent ◽  
Immune Exhaustion ◽  
Previously Treated ◽  
Expression Pathways ◽  
Relapsed Disease ◽  
Written Informed Consent

BackgroundDespite the encouraging successes of immune checkpoint inhibitors, many patients do not benefit and are either refractory or relapse. The mechanisms of refractory or relapsed disease following PD-(L)1 blockade are largely unknown. To identify characteristics associated with refractory or relapsed disease we explored the immune and genomic landscape of samples derived from NSCLC patients who previously received PD-(L)1 blockade and had blood and fresh tumor biopsies collected at the time of progression.MethodsPatient response categories were defined prospectively; ‘refractory’ defined as progression within 16 weeks of initiating PD-(L)1 and ‘relapse’ defined as initial clinical benefit (CR, PR, SD) followed by progression. RNAseq (n=52) and PD-L1 IHC (n=22) were performed on tumor tissue. Immune profiling of whole blood was assessed using flow cytometry or Biomark HD (Fluidigm) gene expression panel (n=54 and n=62, respectively). Differential gene expression was defined as unadjusted p<0.05 and fold-difference >1.5. Pathways analysis was conducted by David tool. Patient samples were collected during screening for clinical trial of second line immunotherapy. Written informed consent was obtained from the patients for publication of this abstract.ResultsIn patients with NSCLC previously treated with PD-(L)1 blockade, tumors of relapsed patients were characterized by increased expression of genes associated with interferon signaling (e.g. CXCL9, SPIC, IFNg), immune suppression (e.g. ARG1, TGFB), immune exhaustion (e.g. ADORA2A), and increased PD-L1 expression (by gene expression and IHC). Refractory disease was associated with increased cadherin signaling and calcium-dependent-cell-adhesion gene expression pathways. In the periphery, reduced quantities of B cells and activated (HLA-DR+ or CD38+) or proliferating (Ki67+) CD8+ T cells were observed in refractory patients.ConclusionsThe tumor and peripheral compartments of patients with NSCLC previously treated with PD-(L)1 blockade differ based on prior response. Relapsed patients tend to have signals of sturdy immune activation and chronic inflammation thus ultimately leading to immune exhaustion. These results may help inform rational therapeutic strategies to overcome resistance to PD-(L)1 blockade in NSCLC.Trial RegistrationNCT02000947Ethics ApprovalResearch on human samples here analyzed have been performed in accordance with the Declaration of Helsinki.ConsentWritten informed consent was obtained from the patient for publication of this abstract.

scholarly journals Artificial complementary chromatic acclimation gene expression system in Escherichia coli

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Dwi Ariyanti ◽  
Kazunori Ikebukuro ◽  
Koji Sode
Keyword(s):  
Gene Expression ◽  
Escherichia Coli ◽  
Light Exposure ◽  
Expression System ◽  
Red Light ◽  
Green Light ◽  
Light Illumination ◽  
Multiple Gene ◽  
Gene Expression System ◽  
Chromatic Acclimation

Abstract Background The development of multiple gene expression systems, especially those based on the physical signals, such as multiple color light irradiations, is challenging. Complementary chromatic acclimation (CCA), a photoreversible process that facilitates the control of cellular expression using light of different wavelengths in cyanobacteria, is one example. In this study, an artificial CCA systems, inspired by type III CCA light-regulated gene expression, was designed by employing a single photosensor system, the CcaS/CcaR green light gene expression system derived from Synechocystis sp. PCC6803, combined with G-box (the regulator recognized by activated CcaR), the cognate cpcG2 promoter, and the constitutively transcribed promoter, the PtrcΔLacO promoter. Results One G-box was inserted upstream of the cpcG2 promoter and a reporter gene, the rfp gene (green light-induced gene expression), and the other G-box was inserted between the PtrcΔLacO promoter and a reporter gene, the bfp gene (red light-induced gene expression). The Escherichia coli transformants with plasmid-encoded genes were evaluated at the transcriptional and translational levels under red or green light illumination. Under green light illumination, the transcription and translation of the rfp gene were observed, whereas the expression of the bfp gene was repressed. Under red light illumination, the transcription and translation of the bfp gene were observed, whereas the expression of the rfp gene was repressed. During the red and green light exposure cycles at every 6 h, BFP expression increased under red light exposure while RFP expression was repressed, and RFP expression increased under green light exposure while BFP expression was repressed. Conclusion An artificial CCA system was developed to realize a multiple gene expression system, which was regulated by two colors, red and green lights, using a single photosensor system, the CcaS/CcaR system derived from Synechocystis sp. PCC6803, in E. coli. The artificial CCA system functioned repeatedly during red and green light exposure cycles. These results demonstrate the potential application of this CCA gene expression system for the production of multiple metabolites in a variety of microorganisms, such as cyanobacteria.

scholarly journals Detection of Nonlinear Effects in Gene Expression Pathways

2010 ◽  
Author(s):  
Andreas Mayr ◽  
Djork-Arne Clevert ◽  
Sepp Hochreiter
Keyword(s):  
Gene Expression ◽  
Nonlinear Effects ◽  
Expression Pathways

scholarly journals Integrative machine learning analysis of multiple gene expression profiles in cervical cancer

PeerJ ◽  
2018 ◽  
Vol 6 ◽  
pp. e5285 ◽  
Author(s):  
Mei Sze Tan ◽  
Siow-Wee Chang ◽  
Phaik Leng Cheah ◽  
Hwa Jen Yap
Keyword(s):  
Gene Expression ◽  
Machine Learning ◽  
Cervical Cancer ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Hpv Infection ◽  
Gene Set Enrichment Analysis ◽  
Multiple Gene ◽  
Cervical Cancers ◽  
Learning Analysis

Although most of the cervical cancer cases are reported to be closely related to the Human Papillomavirus (HPV) infection, there is a need to study genes that stand up differentially in the final actualization of cervical cancers following HPV infection. In this study, we proposed an integrative machine learning approach to analyse multiple gene expression profiles in cervical cancer in order to identify a set of genetic markers that are associated with and may eventually aid in the diagnosis or prognosis of cervical cancers. The proposed integrative analysis is composed of three steps: namely, (i) gene expression analysis of individual dataset; (ii) meta-analysis of multiple datasets; and (iii) feature selection and machine learning analysis. As a result, 21 gene expressions were identified through the integrative machine learning analysis which including seven supervised and one unsupervised methods. A functional analysis with GSEA (Gene Set Enrichment Analysis) was performed on the selected 21-gene expression set and showed significant enrichment in a nine-potential gene expression signature, namely PEG3, SPON1, BTD and RPLP2 (upregulated genes) and PRDX3, COPB2, LSM3, SLC5A3 and AS1B (downregulated genes).

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