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10 results for “EMT6”
CTLA-4 and PD-1 expressed in EMT6 mouse mammary carcinoma cell line acquired radio-resistance to gamma-ray irradiation.
<p>Supplementary File of manuscript entitled CTLA-4 and PD-1 expressed in EMT6 mouse mammary carcinoma cell line acquired radio-resistance to gamma-ray irradiation.</p>
Repository for Analysis of the Mined Dataset (RE: EMT6 Paper)
<p><strong>Table of Contents</strong></p><ol><li>Main Description</li><li>File Description</li></ol><p> </p><p><strong>1. Main Description</strong></p><p>---------------------------</p><p>This is a repository for the mined data and code used pertaining to the manuscript titled "A TCR β chain-directed antibody-fusion molecule that activates and expands subsets of T cells and promotes antitumor activity.".</p><p>The following libraries are required for script execution:</p><ul><li>Seurat</li><li>scReportoire</li><li>ggplot2</li><li>stringr</li><li>dplyr</li><li>ggridges</li><li>ggrepel</li><li>ComplexHeatmap</li></ul><p> </p><p> </p><p><strong>File Descriptions</strong></p><p>---------------------------</p><ul><li>The "Marengo_Code_Review.R" contains all the code needed to generate figures, and perform differential gene expression analysis for the mined datasets. </li><li>The "Cis_paper_EM_BetterEF.rds" file contains mined dataset sourced from DOI: 10.1038/s41586-022-05257-0. Whereas, the "combined_three_effectors.rds" file contains the mined dataset sourced from DOI: 10.1038/s41586-022-05257-0.</li></ul>
DNA barcoding reveals ongoing immunoediting of clonal cancer populations during metastatic progression and in response to immunotherapy [DNA barcodes: All_EMT6_BC5000]
GEO Series GSE210047. Mus musculus. 18 samples. Type: Other.
Gene expression profile at single cell level of CD4+ and CD8+ tumor infiltrating lymphocytes (TIL) originiating from the EMT6 tumor model from mSTAR1302 treatment
GEO Series GSE223311. Mus musculus. 2 samples. Type: Expression profiling by high throughput sequencing.
Gene expression changes in mouse breast cancer cells (EMT6) after anti-PD-L1 treatment
GEO Series GSE186034. Mus musculus. 6 samples. Type: Expression profiling by high throughput sequencing.
Gene expression changes in mouse breast tumor tissue (EMT6) after anti-PD-L1 resistance
GEO Series GSE186032. Mus musculus. 7 samples. Type: Expression profiling by high throughput sequencing.
Effect of depletion NEDD4 on gene expression on 4T1 and EMT6 tumor cells
GEO Series GSE283802. Mus musculus. 12 samples. Type: Expression profiling by high throughput sequencing.
RNA-seq tumor immunome analysis of murine breast cancer model EMT6-hHER2 responsive to novel antibody drug conjugate T-PNU
GEO Series GSE120888. Mus musculus. 24 samples. Type: Expression profiling by high throughput sequencing.
Repository for Single Cell RNA Sequencing Analysis of The EMT6 Dataset
<p><strong>Table of Contents</strong></p><ol><li>Main Description</li><li>File Descriptions</li><li>Linked Files</li><li>Installation and Instructions</li></ol><p> </p><p> </p><p> </p><p><strong>1. Main Description</strong></p><p>---------------------------</p><p>This is the Zenodo repository for the manuscript titled "A TCR β chain-directed antibody-fusion molecule that activates and expands subsets of T cells and promotes antitumor activity.". The code included in the file titled `marengo_code_for_paper_jan_2023.R` was used to generate the figures from the single-cell RNA sequencing data.</p><p>The following libraries are required for script execution:</p><ul><li>Seurat</li><li>scReportoire</li><li>ggplot2</li><li>stringr</li><li>dplyr</li><li>ggridges</li><li>ggrepel</li><li>ComplexHeatmap</li></ul><p> </p><p> </p><p><strong>File Descriptions</strong></p><p>---------------------------</p><ul><li>The code can be downloaded and opened in RStudios.</li><li>The "marengo_code_for_paper_jan_2023.R" contains all the code needed to reproduce the figues in the paper</li><li>The "Marengo_newID_March242023.rds" file is available at the following address: https://zenodo.org/badge/DOI/10.5281/zenodo.7566113.svg (Zenodo DOI: 10.5281/zenodo.7566113).</li><li>The "all_res_deg_for_heat_updated_march2023.txt" file contains the unfiltered results from DGE anlaysis, also used to create the heatmap with DGE and volcano plots.</li><li>The "genes_for_heatmap_fig5F.xlsx" contains the genes included in the heatmap in figure 5F.</li></ul><p> </p><p> </p><p><strong>Linked Files</strong></p><p>---------------------</p><p> </p><p>This repository contains code for the analysis of single cell RNA-seq dataset. The dataset contains raw FASTQ files, as well as, the aligned files that were deposited in GEO. The "Rdata" or "Rds" file was deposited in Zenodo. Provided below are descriptions of the linked datasets:</p><p> </p><p>Gene Expression Omnibus (GEO) ID: GSE223311(https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE223311)</p><ul><li><strong>Title</strong>: Gene expression profile at single cell level of CD4+ and CD8+ tumor infiltrating lymphocytes (TIL) originating from the EMT6 tumor model from mSTAR1302 treatment.</li><li><strong>Description</strong>: This submission contains the "matrix.mtx", "barcodes.tsv", and "genes.tsv" files for each replicate and condition, corresponding to the aligned files for single cell sequencing data.</li><li><strong> Submission type</strong>: Private. In order to gain access to the repository, you must use a reviewer token (https://www.ncbi.nlm.nih.gov/geo/info/reviewer.html).</li></ul><p> </p><p>Sequence read archive (SRA) repository ID: SRX19088718 and SRX19088719</p><ul><li><strong>Title</strong>: Gene expression profile at single cell level of CD4+ and CD8+ tumor infiltrating lymphocytes (TIL) originating from the EMT6 tumor model from mSTAR1302 treatment.</li><li><strong>Description</strong>: This submission contains the **raw sequencing** or `.fastq.gz` files, which are tab delimited text files.</li><li><strong>Submission type</strong>: Private. In order to gain access to the repository, you must use a reviewer token (https://www.ncbi.nlm.nih.gov/geo/info/reviewer.html).</li></ul><p> </p><p>Zenodo DOI: 10.5281/zenodo.7566113(https://zenodo.org/record/7566113#.ZCcmvC2cbrJ)</p><ul><li><strong> Title</strong>: A TCR β chain-directed antibody-fusion molecule that activates and expands subsets of T cells and promotes antitumor activity.</li><li><strong>Description</strong>: This submission contains the "Rdata" or ".Rds" file, which is an R object file. This is a necessary file to use the code.</li><li><strong>Submission type</strong>: Restricted Acess. In order to gain access to the repository, you must contact the author.</li></ul><p> </p><p> </p><p> </p><p><strong>Installation and Instructions</strong></p><p>--------------------------------------</p><p>The code included in this submission requires several essential packages, as listed above. Please follow these instructions for installation:</p><p> </p><p>> Ensure you have R version 4.1.2 or higher for compatibility.</p><p> </p><p>> Although it is not essential, you can use R-Studios (Version 2022.12.0+353 (2022.12.0+353)) for accessing and executing the code.</p><p> </p><p>1. Download the *"Rdata" or ".Rds" file from Zenodo (https://zenodo.org/record/7566113#.ZCcmvC2cbrJ) (Zenodo DOI: 10.5281/zenodo.7566113).</p><p>2. Open R-Studios (https://www.rstudio.com/tags/rstudio-ide/) or a similar integrated development environment (IDE) for R.</p><p>3. Set your working directory to where the following files are located:</p><ul><li>marengo_code_for_paper_jan_2023.R</li><li>Install_Packages.R</li><li>Marengo_newID_March242023.rds</li><li>genes_for_heatmap_fig5F.xlsx</li><li>all_res_deg_for_heat_updated_march2023.txt</li></ul><p> </p><p>You can use the following code to set the working directory in R:</p><p>> setwd(directory)</p><p> </p><p>4. Open the file titled "Install_Packages.R" and execute it in R IDE. This script will attempt to install all the necessary pacakges, and its dependencies in order to set up an environment where the code in "marengo_code_for_paper_jan_2023.R" can be executed.</p><p>5. Once the "Install_Packages.R" script has been successfully executed, re-start R-Studios or your IDE of choice.</p><p>6. Open the file "marengo_code_for_paper_jan_2023.R" file in R-studios or your IDE of choice.</p><p>7. Execute commands in the file titled "marengo_code_for_paper_jan_2023.R" in R-Studios or your IDE of choice to generate the plots.</p>
Effect of depletion of ISG20 on gene expression in EMT6 mouse breast cancer cells with RNA-Seq.
GEO Series GSE287164. Mus musculus. 12 samples. Type: Expression profiling by high throughput sequencing.
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