Similar Datasets
Project description:Exploitation of the immune system has emerged as an important therapeutic strategy for acute lymphoblastic leukemia (ALL). However, the mechanisms of immune evasion during leukemia progression remain poorly understood. We sought to understand the role of calcineurin in ALL and observed that knocking-down calcineurin B (CnB) in leukemia cells dramatically prolonged survival in immune-competent but not immune-deficient recipients. Furthermore, immune-competent recipients were protected from challenge with leukemia if they were first immunized with CnB-deficient leukemia, suggesting robust adaptive immunity. In the bone marrow, recipients of CnB-deficient leukemia had expansion of T cell populations as compared to controls. Gene expression analyses of leukemia cells extracted from bone marrow identified Cn-dependent significant changes in the expression of immuno-regulatory genes. We confirmed increased secretion of IL-12 from CnB-deficient leukemia cells, sufficient to induce T cell activation ex vivo, an effect that was abolished when IL-12 was neutralized. Strikingly, recombinant IL-12 prolonged survival of mice challenged with highly aggressive B-ALL. Moreover, gene expression analyses from children with ALL demonstrate prolonged survival in those with higher expression of either IL-12A or IL-12B. These data suggest that leukemia cells are dependent upon calcineurin for immune evasion by restricting the regulation of pro-inflammatory genes, particularly IL-12.
2019-04-25 | GSE130272 | GEO
Project description:BackgroundTriple-Negative Breast Cancer (TNBC) is an aggressive and complex subtype of breast cancer. The current biomarkers used in the context of breast cancer treatment are highly dependent on the targeting of oestrogen receptor, progesterone receptor, or HER2, resulting in treatment failure and disease recurrence and creating clinical challenges. Thus, there is still a crucial need for the improvement of TNBC treatment; the discovery of effective biomarkers that can be easily translated to the clinics is essential.MethodsWe report an approach for the discovery of biomarkers that can predict tumour relapse and pathologic complete response (pCR) in TNBC on the basis of mRNA expression quantified using the NanoString nCounter Immunology Panel. To overcome the limited sample size, prediction models based on random Forest were constructed using the differentially expressed genes (DEGs) as selected features. We also evaluated the differences between pre- and post-treatment groups aiming for the combinatorial assessment of pCR and relapse using additive models in edgeR.ResultsWe identify nine and 13 DEGs strongly associated with pCR and relapse, respectively, from 579 immune genes in a small number of samples (n = 55) using edgeR. An additive model for the comparison of pre- and post-treatment groups via the adjustment of the independent subject in the relapse group revealed associations for 41 genes. Comprehensive analysis indicated that our prediction models outperformed those constructed using features extracted from the existing feature selection model Elastic Net in terms of accuracy. The prediction models were assessed using a randomization test to validate the robustness (empirical P for the model of pCR = 0.015 and empirical P for the model of relapse = 0.018). Furthermore, three DEGs (FCER1A, EDNRB, and TGFBI) in the model of relapse showed prognostic significance for predicting the survival of patients with cancer through Cox proportional hazards regression model-based survival analysis.ConclusionGene expression quantified via the NanoString nCounter Immunology Panel can be seamlessly analysed using edgeR, even considering small sample sizes. Our approach provides a scalable framework that can easily be applied for the discovery of biomarkers based on the NanoString nCounter Immunology Panel.Data availabilityThe source code will be available from github at https://github.com/sungheep/nanostring .
| S-EPMC7607642 | biostudies-literature
Project description:We undertook to determine whether carcinoma cells residing in the epithelial or quasi-mesenchymal phenotypic states differ in their expression of immunomodulatory markers.To demonstrate a direct association between activation of the EMT program and immunosuppression, we induced EMT programs in vitro in an array of cultured BrCa cell lines via the doxycycline-induced expression of various EMT-inducing transcription factors (EMT-TFs) and proceeded to determine whether activation of the EMT program also alters cell-intrinisc immuno-modulatory markers To do so, we used the nCounter PanCancer Immune Profiling Panel (Nanostring Technologies)to perform transcriptomic analyses of control E cells or those induced to undergo an EMT
2021-09-15 | GSE161747 | GEO
Project description:The gene expression analysis of the RNA samples were analyzed with NanoString Non Human Primate immunology panel comprised of 754 immune related gene
2021-12-25 | GSE192584 | GEO
Project description:mRNA expression in human bronchial epithelial cells unstimulated was compared with mRNA expression of cells stimulated with poly (I:C) (viral mimic) and poly (I:C) in combination with imiquimod (TLR7 agonist; Treatment). The aim was to assess the effect of imiquimod treatment on poly (I:C)-dependent changes in bronchial epithelium from asthmatics.
2021-08-02 | GSE181281 | GEO
Project description:SummaryThe NanoTube is an open-source pipeline that simplifies the processing, quality control, normalization and analysis of NanoString nCounter gene expression data. It is implemented in an extensible R library, which performs a variety of gene expression analysis techniques and contains additional functions for integration with other R libraries performing advanced NanoString analysis techniques. Additionally, the NanoTube web application is available as a simple tool for researchers without programming expertise.Availability and implementationThe NanoTube R package is available on Bioconductor under the GPL-3 license (https://www.bioconductor.org/packages/NanoTube/). The R-Shiny application can be downloaded at https://github.com/calebclass/Shiny-NanoTube, or a simplified version of this application can be run on all major browsers, at https://research.butler.edu/nanotube/.Supplementary informationSupplementary data are available at Bioinformatics online.
| S-EPMC9805552 | biostudies-literature
Project description:The Nanostring nCounter gene expression assay uses molecular barcodes and single molecule imaging to detect and count hundreds of unique transcripts in a single reaction. These counts need to be normalized to adjust for the amount of sample, variations in assay efficiency and other factors. Most users adopt the normalization approach described in the nSolver analysis software, which involves background correction based on the observed values of negative control probes, a within-sample normalization using the observed values of positive control probes and normalization across samples using reference (housekeeping) genes. Here we present a new normalization method, Removing Unwanted Variation-III (RUV-III), which makes vital use of technical replicates and suitable control genes. We also propose an approach using pseudo-replicates when technical replicates are not available. The effectiveness of RUV-III is illustrated on four different datasets. We also offer suggestions on the design and analysis of studies involving this technology.
| S-EPMC6614807 | biostudies-literature
Project description:The NanoString nCounter System has been widely used in basic science and translational science research for the past decade. The System consists of two instruments: the PrepStation and the Digital Analyzer, and both have been continuously improved with evolving technologies. A great amount of research data have been generated at multiple research laboratories with the employment of different generations of the System. With the need of integrating multiple datasets, researchers are interested to know whether signals are comparable between different generations of the System. Toward this end, we designed a profiling study to compare performance of two generations of the NanoString nCounter System using a common set of biological samples. Using graphical tools and statistical models, we found that two different generations of NanoString nCounter System produced equivalent signals and signal deviations are in the range of random background noises for the medium-high expression levels.
| S-EPMC6874068 | biostudies-literature
Project description:The objective of this study was to corroborate the findings of previous BRD-associated transcriptome experiments, utilizing multiple independent populations of high-risk beef cattle.
2022-03-02 | GSE179536 | GEO
Project description:The goal of this study was to investigate the roles of Butyrophilin Subfamily 1 Member A1 (BTN1A1) in terms of the signaling pathway after overexpression of BTN1A1A1 gene. To this end, we conducted NanoString analysis. From NanoString analysis with BTN1A1-overexpressing PC3 cells, we concluded that BTN1A1 play a pivotal role in the regulation of several signaling pathway including Jak-STAT pathway that is involved in processes such as immunity, cell division, cell death and tumor formation.
2021-10-19 | GSE186060 | GEO