Single Cell RNA-Seq Study Of Differentiation Of Regulatory T Cells In Tumor Infiltrating Lymphocytes

Since the discovery of a subset of Foxp3 producing T-cell,this regulatory T cell(Treg)cell lineage has been a focus of great research interest.Treg cells have been shown to play an important role in autoimmune diseases and inflammation.Meanwhile,Treg cells can affect the growth and evolution of cancerous cells.In recent years,in both early and late-phase trails,CTLA-4 blockade has shown consistent activity against melanoma,non-small cell lung cancer and colorectal cancer.A RNA-Seq experiment provides a snapshot of RNA content within a cell population.Gene expression profiling using RNA-Seq is a powerful technique for screening RNA species’landscapes and their dynamics in an unbiased way.In this study,we used RNA-Seq to measure gene expression during the early Treg cells differentiation and T-cell activation(Th0).Analysis of differentiation efficiencies revealed the significant differentiation expression genes at 5h,12h and 48h and.We then searched shared functions among genes at different time points by clusterProfiler.Several significant pathways were obtained by enrichment analysis,such as Jak-STAT signaling pathway,TNF signaling pathway and PI3K-Akt signaling pathway.The tumor microenvironment(TME)is the cellular environment in which the tumor exists,surrounded by immune cells,bone marrow-derived inflammatory cells,fibroblasts,signaling molecules and the extracellular matrix.Tumors can influence the microenvironment by releasing extracellular signals,promoting tumor angiogenesis,while the immune cells in the microenvironment can affect the growth and evolution of cancerous cells.Single cell RNA seq(scRNA-seq)is a new and rapidly upcoming method in the field of single cell genomics and are predicted to replace bulk RNA-Seq eventually.By analyzing the transcriptome at single cell level,scRNA-seq generates new insights into the complex biological systems that give rise to a cell’s identity in living organisms.This allows us to address scientific questions that were evaded in the past years such as deconvolving the heterogeneity in cell populations,studying dynamic processes like cell state transitions and constructing gene regulatory networks.In this study,we first constructed a scRNA-seq analysis pipeline and then applied this pipeline in a melanoma dataset from a recent published paper.And we could reproduce and improve their results.Then we calculated the correlation values of tumor genes with the percentages of several immune cells,including Tregs,B cells and CD8+ T cells,by a mixed-effect linear model.The significant genes were selected as clusterProfiler input.After analyzing,we found several significant biological process pathways.Tregs associated genes mainly participate in nitric oxide biosynthetic process.B cells associated genes mainly participate in type I interferon signaling pathway.CD8+ T cells associated genes mainly participate in positive regulation of response to stimulus.