Differential Analysis Of Single-cell Transcriptome Sequencing For Microenvironment Between Muscle-invasive Bladder Cancer And Adjacent Tissue

Objective:The aim of this study is to depict the single-cell atlas of bladder cancer and adjacent tissue using single-cell transcriptome sequencing technology,identify cell types and differential genes between the samples,analyze the differences in the microenvironment between bladder cancer and adjacent normal tissue,and screen for key genes and transcriptional regulatory factors with differential expression.Methods:One bladder cancer tissue and one adjacent normal tissue were collected from a patient who underwent radical cystectomy in the Department of Urology at the First Hospital of Shanxi Medical University in July 2021.After tissue processing,single-cell transcriptome sequencing technology was used to depict the single-cell atlas of bladder cancer and adjacent normal tissue,explore the differences in cell composition between the two.In-depth bioinformatics analysis was performed on the sequencing data,including:(1)dimensionality reduction clustering and cell annotation of epithelial cells,fibroblasts,and T lymphocytes to clarify the composition and distribution differences of different cell subtypes in the two tissues;(2)marker gene identification,differential gene analysis,and GO,KEGG,and GSVA enrichment analysis to analyze the functions of different cell types and specifically focus on sample differences among subgroups;(3)pseudo-temporal analysis to describe the developmental trajectory of fibroblasts and T lymphocytes;(4)SCENIC transcription factor analysis to describe the transcriptional regulation features of the specifically focused subgroups,elucidating their impact on the tumor microenvironment;and(5)survival analysis of key genes and gene set correlation analysis using GEPIA online tool and TCGA public database.Results:(1)Cell type identification: There were a total of 10,684 valid cells in this sequencing,and 13 subgroups were generated by dimensionality reduction clustering,annotated as 6 types of cells: epithelial cells,fibroblasts,T cells,B cells,endothelial cells,and monocytes/macrophages.(2)In the study of fibroblasts,10 cell subgroups were identified and annotated as two cell types: inflammatory tumor-associated fibroblasts and myofibroblastic tumor-associated fibroblasts.Differential gene analysis between samples revealed that abnormal expression of MYC,EGFR,CYP1B1,SLIT2,DPYSL3,SFRP1,NAV3,PDGFRA,HSPA5 in the adjacent non-tumor tissue.These were significantly associated with poor patient prognosis.Subsequently,differential gene enrichment analysis was performed on subgroups 3 and 4 between samples.Compared with adjacent non-tumor tissue,subgroup 3 derived from tumor tissue showed expression of genes related to epithelial-mesenchymal transition,but no significant differences were found between samples in subgroup 4.In the pseudo-time analysis,a special fibroblast state(State2)was found to only consist of cells from adjacent non-tumor tissue,allowing for the determination of the starting point and direction of differentiation.Subsequently,the molecular dynamic changes during the pseudo-time process were explored,revealing changes in immune-related regulatory capabilities during the process.SCENIC analysis identified abnormal expression of transcription factors including STAT1,FOXF1,LEF1,STAT2,STAT3,HIF1 A,and ETS2 in tumor tissue.(3)In T lymphocyte research,8 cell subtypes were identified and annotated as 6 cell types.Among them,cytotoxic T cells have distinct characteristics,and based on pseudotime analysis results,subtype 7 was annotated as cytotoxic T cell memory cells.SCENIC analysis found that FOXP3,MAF,and SOX4 transcription factors were highly activated in regulatory T cells,with significantly higher activity than other transcription factors.(4)The study of epithelial cells identified three cell subgroups.Enrichment analysis revealed that subgroups 2 and 3,which have high copy number variations in tumor tissue,lack immune-related features.A small number of cells with a higher level of copy number variations were found in the adjacent non-tumor tissue.Conclusion:This study uses single-cell transcriptome sequencing to depict the single-cell transcriptome profile of the bladder urothelial carcinoma tumor microenvironment,proving the intratumoral heterogeneity of bladder cancer.(1)The fibroblasts in cancer adjacent tissue are in an abnormal regulatory state,with aberrantly activated MYC,EGFR,and PDGFRA genes,indicating that fibroblasts may regulate cellular proliferation and neovascularization in the microenvironment through abnormal activation of WNT/β-catenin,RAF-MEK-ERK signaling pathways,and overexpression of EGFR.Inflammatory tumor-associated fibroblasts(i CAFs)in cancer tissue exhibit stronger immunosuppressive abilities than those in adjacent normal tissue.Abnormally activated transcription factors in fibroblasts in cancer tissue include STAT1,FOXF1,LEF1,STAT2,STAT3,HIF1 A,and ETS2,indicating that CAFs may suppress anti-tumor immune response and regulate cell cycle and apoptosis through the JAK/STAT pathway,and promote bladder cancer tumor cell progression via the WNT signaling pathway.(2)T lymphocytes show significant intergroup differences,with Treg cells significantly increased in tumor tissues.FOXP3,MAF,and SOX4 are transcription factors that are abnormally activated in Treg cells and can regulate the growth and function of regulatory T cells in bladder cancer,leading to an immunosuppressive state in tumor tissues.(3)The loss of immune regulation ability in epithelial cells in tumor tissue was observed,Which may be attributed to the inhibition of dendritic cell differentiation.There are a few epithelial cells with high CNV levels in the cancer adjacent tissue.