Single Cell Rnaseq Reveals Cell Heterogeneity and several gens as markers of High Fat Diet in C۵۷BL/۶ Mouse Model in cancer
- سال انتشار: 1403
- محل انتشار: دومین کنگره بین المللی کنسرژنومیکس
- کد COI اختصاصی: ICGCS02_521
- زبان مقاله: انگلیسی
- تعداد مشاهده: 112
نویسندگان
Department of Advanced Technologies in Medicine, School of Medicine, North Khorasan University of Medical Sciences, Bojnurd, Iran
Department of Biology, Faculty of Basic sciences, Qaemshahr Branch, Islamic Azad University, Mazandaran, Iran
Department of Biology, Islamic Azad University Mashhad Branch, Mashhad, Iran
Department of Advanced Technologies in Medicine, School of Medicine, North Khorasan University of Medical Sciences, Bojnurd, Iran
Department of Advanced Technologies in Medicine, School of Medicine, North Khorasan University of Medical Sciences, Bojnurd, Iran
چکیده
Despite obesity is an essential risk factor for cancer, it is unclear how variations in systemic metabolism promote alter the tumor microenvironment (TME) (۱), Moreover, while overall cancer incidence has decreased over the past ۱۰ years in the United States, rates are rising for several obesity-related cancers, such as liver, pancreatic, thyroid and uterine cancer, as well as for colorectal cancer in patients under ۵۵. The single-cell RNA-seq technique already enables single-cell population profiling of cancers and clarifies the molecular heterogeneity for all cell types (۲). With the goal to determine the immune cell's gene expression profile and the abundance of cells from different tissues, we performed a bioinformatics study on tissues from C۵۷BL/۶ mice fed a high-fat diet and a control diet. Material and method: Using the Seurat (۳), Celldex, and SingleCellExperiment packages, the ۱۰xGenomice scRNA-seq data (GSE۱۵۷۹۹۹) was analyzed in the R language (۴,۵). ۱۴,۰۷۹ cells from ۳ samples including: ۲ control diet and ۱ high fat diet. PCA and UMAP were applied to assess reductions in dimension and cell clustering. The singleR package (۴) was employed to automatically annotate clusters and determine various cell types. The DimPlot, FeaturePlot, VlnPlot and RidgePlot functions were used to create visualizations of the heterogeneity transcription and abundant of genes within every single cell subtype. Results and discussion: Abundance of Astrocyte, B Cells, Fibroblasts, Hepatocytes, Neuroepithelial Cells and Epithelial Cells was significantly increased in high fat diet tissue compared with control diet tissue. (Hmox۱, Mmp۱۲= Astrocyte), (Gzmc, Ikzf۲= B Cells), (Fabp۴, Ccr۷= Fibroblasts), (S۱۰۰a۹, S۱۰۰a۸= Hepatocytes), (Prdx۱, Mt۱= Epithelial Cells) and (Ccl۸, Wfdc۱۷= Neuroepithelial Cells) were highly expressed, respectively, as two markers that are present in high fat diet tissue and control diet tissue. Furthermore, interactions between Epithelial cells and Neuroepithelial cells, Hepatocytes and Astrocyte, Fibroblasts and B Cells appeared to be strong. Conclusion: Astrocytes, B cells, Fibroblasts, Hepatocytes, Neuroepithelial cells and Epithelial cells can infiltrate the tumor microenvironment (TME) and influence the metabolism of tumors associated with a high-fat diet.کلیدواژه ها
Single-Cell RNA-seq, Obesity Metabolism, NGS, Computational Biologمقالات مرتبط جدید
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