| BackgroundCervical cancer(CC)is the fourth most common type of cancer in the world’s female population.More than 500,000 women are diagnosed with cervical cancer every year,and the disease causes more than 300,000 deaths worldwide.It has become a global public health problem.In the development of cervical cancer,accompanied with the emergence of a series of cell lineages and mutant genes,however,in the cervical tissues of precancerous lesions and malignant lesions,the full spectrum of various cell types and their molecular characteristics remains not to be clearly defined.Therefore,it is impossible to clarify their role in the pathogenesis of CC.The screening of CC is mainly based on the combination of Thinprep cytologic test(TCT)and Human papillomavirus DNA(HPV-DNA).Although this method may be useful for early detection of cervical lesions and reduce the incidence and mortality of cervical cancer,it is also easy to miss some patients.Colposcopy biopsy and pathological examination can be confirmed,but invasive examination also greatly limits the clinical application of colposcopy.Therefore,screening tumor-related genes is necessary for early diagnosis and detection of therapeutic targets of cervical cancer.Previous studies using large sample-based experiments or mathematical models to explore the molecular characteristics of cervical cancer mask the characteristics of different cell groups or other studies that rely on predetermined markers to purify cell populations are also limited to several specific cell types,which can’t distinguish cell types completely and detect of rare cell populations or cells with specific states.This requires a systematic and comprehensive understanding of the different cell populations in malignant tissues.RNA analysis of individual cells is needed to better characterize the cellular heterogeneity of cervical malignancies,thus providing more information on the characteristics and heterogeneity of single cells.Single-cell RNA-sequencing(sc RNA-seq)distinguishes different cell populations in the tumor microenvironment and captures changes in rare cell subsets,better defining the heterogeneity of tumor cells.At the same time,the differential genes obtained by sc RNA-seq analysis of cervical cancer may provide a new direction for the screening of specific markers and accurate treatment.ObjectiveThe data of the target population were obtained by single cell transcriptome sequencing of population cells derived from cervical cancer and adjacent cancer tissue samples to realize the classification of high throughput single cell data and the differential analysis of gene expression among cell populations,to explore the heterogeneity of cervical malignant tumor cells,and to screen out the differentially expressed genes.MethodsA single cell suspension was prepared by collecting fresh samples of cervical squamous cell carcinoma and corresponding adjacent carcinoma.Sc RNA-seq of tens of thousands of cells passing the quality inspection apply 10 x genomics and illumina novaseq 6000 platform.Principal component analysis(PCA)was performed to reduce the dimensionality on the log transformed gene-barcode matrices of top variable genes.Cells were clustered based on a graph-based clustering approach,and were visualized in 2-dimension using t SNE.Likelihood ratio test that simultaneously test for changes in mean expression and in the percentage of expressed cells was used to identify significantly differentially expressed genes between clusters.Here,we use the R package Single R,a novel computational method for unbiased cell type recognition of sc RNA-seq to infer the cell of origin of each of the single cells independently and identify cell types.Differentially expressed genes(DEGs)were identified using the Seurat package.P value < 0.05 and |log2foldchange| > 1(or |log2foldchange| > 0.58)was set as the threshold for strongly differential expression.KEGG pathway enrichment and GO enrichment analysis of DEGs were respectively performed using R based on the hypergeometric distribution.Trajectory Analysis was used to describe the dynamic trajectory of tumor cell differentiation by Monocle.Finely,cancer tissues and adjacent tissues from patients with cervical cancer diagnosed by pathology between August 2020 and March 2021 were collected according to the exclusion criteria.The expression levels of seven cluster specific genes were verified by RT-qPCR experiments.Results1.Cell type identification: 12,037 single cells obtained from cervical squamous cell carcinoma were analyzed.The cells were clustered into six major clusters,including NK and T cells;Fibroblasts cells;Epithelial cells;Endothelial cells;B cells;Macrophage cells.2.Differential expression gene screening: Compared to adjacent tissues,117 differentially expressed genes were selected in cancer samples,including 29up-regulated and 1 down-regulated differentially expressed genes.The differentially expressed genes were mostly expressed in fibroblasts cells and epithelial cells.Furthermore,7 distinct expression genes specific to each cluster were obtained by screening the differences between groups: HSPA6、KRT19、TACSTD2、CLDN4、WFDC2、S100A2、SLPI.3.Differential gene enrichment analysis: GO analysis showed that the function of differential genes was mostly focused on protein folding(heat shock protein family),cytokine and chemokine mediated signaling pathway,cell response to tumor necrosis factor,receptor mediated endocytosis and other biological processes.KEGG analysis showed that differentially expressed genes were concentrated in the immune system,related to infectious diseases,and related pathways to signal transduction.4.The immune microenvironment of cervical malignant tumors: It is composed of NK cells,T cells,macrophages,monocytes,and B cells,and contains multiple subtypes.At the same time,KEGG pathway analysis shows that chemokines CCL2,CCL3,and CXCL1 play key roles in the involvement of immune cells in the progression of cervical cance by regulating the immune microenvironment.5.Pseudotime: Two cell sub-clusters,type 1 and type 2 epithelial cells were obtained by further analysis of epithelial cells clusters.Epithelial cells of cervical cancer tend to progress from type 1 to type 2 differentiation.Type 1 highly expresses PIK3R3 and CENPF genes,type 2 highly expresses KLK5 and CEACAM1 genes.6.Verification of gene expression levels: The seven genes specific to each cluster were screened and confirmed by RT-q PCR experiments that there are significant differences in cervical cancer and adjacent tissues: HSPA6(p=0.0013)、KRT19(p=0.016)、TACSTD2(p=0.0182)、CLDN4(p<0.001)、WFDC2(p=0.0321)、S100A2(p=0.0027)、SLPI(p=0.0172).Conclusion1.A single-cell map of the tumor microenvironment of squamous cell carcinoma of the cervix described in this study through sc RNA-seq.For the first time,the heterogeneity of cervical malignant tumors was proved.The 6 types of cells that make up cervical cancer tissue were systematically analyzed,5 types of immune cells and their subtypes in the tumor microenvironment,and two different subtypes of cervical cancer epithelial cells have been discovered.2.Fibroblasts cells and epithelial cells have significant inter-group differences,and almost all of the differential genes come from these two types of cells,demonstrating that fibroblasts may be closely involved in cervical cancer progression.3.The complex immune microenvironment of cervical cancer provides a basis for studying the mechanism of the occurrence and development of CC.At the same time,chemokines CCL2,CCL3 and CXCL1 play an important role in regulating the immune microenvironment.4.Two types of cancer epithelial cell differentiation trajectories were explored,and tumor epithelial cells were transformed from type 1 to type 2 cells.Type 2 has a more obvious malignant phenotype.It can be speculated that CENPF with high expression of type 1 promotes cell proliferation by activating the PI3K/AKT pathway as an early cancer event.Type 2 highly expressed KLK5 and CEACAM1 genes may be targets for the treatment effect and prognosis of advanced CC.5.The differentially expressed genes of cervical cancer were explored from single cell level,and the significant enrichment genes(HSPA6、KRT19、TACSTD2、CLDN4、WFDC2、S100A2、SLPI)unique to each cluster in cervical cancer tissue may play an key role in the progression of CC. |
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