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Single-cell RNA sequencing (scRNA-seq) enables detailed profiling of cellular heterogeneity and the tumour microenvironment (TME) immune landscape. The study evaluates immune cell subset distribution and correlates these patterns with gene expression using quality control plots, highly variable gene selection, and UMAP/t-SNE clustering. Cell populations are annotated with flow cytometry and immunohistochemistry, followed by GO enrichment and single-cell expression pattern analysis, including TNFRSF18-related immune proportions.",{"@graph":69,"@context":122},[70,84,105],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":40,"@type":76,"position":81},"https://docshare.wps.com/document/research-report/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/single-cell-rna-sequencing-analysis-reveals-correlation-between-immune-cell-composition-and-gene-expression-in-cervical-cancer/352286/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/single-cell-rna-sequencing-analysis-reveals-correlation-between-immune-cell-composition-and-gene-expression-in-cervical-cancer/352286.png","ImageObject",300,407,{"name":92,"@type":93},"Olivia Brown","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-09-23","2026-09-22",true,{"@type":102,"interactionType":103,"userInteractionCount":8},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"What is the main goal of the study in cervical cancer?","Question",{"text":112,"@type":113},"To characterize immune cell subset distribution in the tumour microenvironment using scRNA-seq and determine how immune cell composition correlates with gene expression.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"How were single-cell clusters and immune cell populations identified?",{"text":117,"@type":113},"Cells were clustered using UMAP and t-SNE, then cell populations were labelled using flow cytometry and immunohistochemistry validation.",{"name":119,"@type":110,"acceptedAnswer":120},"Which analysis approaches were used to link genes to immune microenvironment biology?",{"text":121,"@type":113},"Gene functions were assessed with GO enrichment, and individual gene expression patterns were examined at the single-cell level, including correlations involving TNFRSF18.","https://schema.org",{"og:url":83,"og:type":124,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":126,"canonical":83},"index,follow",{"doc_id":128,"site_id":62},352286,1790130969,{"code":4,"msg":5,"data":131},{"doc_id":128,"user_id":132,"nickname":92,"user_avatar":133,"doc_module":4,"category_id":39,"category_name":40,"doc_title":65,"doc_description":67,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":8,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":139,"language":140,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":141,"faqs":142,"seo_title":143,"seo_description":67,"update_tm":144,"read_time":145},16904993612988,"https://ap-avatar.wpscdn.com/davatar_a8503ba1806abce46bf441b54a3ca4cd","Journal of Cellular and Molecular Medicine   \n ORIGINAL ARTICLE  OPEN ACCESS   \nUnveiling the Tumour Microenvironment by Machine Learning to Develop New Immunotherapeutic Strategies  \nSingle-Cell RNA Sequencing Analysis Reveals Correlation Between Immune Cell Composition and Gene Expression in Cervical Cancer  \nChangchang Huang1 | Guosha Pang2 | Xiaolin Lang1 | Jingjing Zhang1 | Fen Zhao1   \n1Department of Gynecology, First People's Hospital of Linping District, Hangzhou, Zhejiang, China | 2Department of Gynecology, Xingqiao Community  \nHealth Service Center, Hangzhou, Zhejiang, China Correspondence: Fen Zhao ([zhaof0508@163.com](zhaof0508@163.com))  \nReceived: 23 July 2025 | Revised: 30 October 2025 | Accepted: 24 November 2025  \nKeywords: cervical cancer | gene expression | immune cells | single-cell RNA sequencing | tumour microenvironment  \nABSTRACT  \nCervical cancer has become a glaring concern for women's health globally. The use of single-cell RNA sequencing (scRNA-seq) contributes to a comprehensive understanding of cellular heterogeneity and the immune cell landscape in the TME of cervical cancer. This study is to investigate the distribution pattern of immune cell subsets and their correlation with some gene expression based on single-cell RNA sequencing (scRNA-seq) data in patients with cervical cancer. We collected cervical cancer singlecell RNA sequencing data and explored the quality of the data using the violin plots, scatter plots, variance plots and elbow plots, as well as a search for highly variable genes. We clustered cells with UMAP and t-SNE clustering analyses and then labelled cell populations via flow cytometry and immunohistochemistry. We also analysed the biological functions of critical genes using GO enrichment analysis, and the expression patterns of individual genes at the single-cell level. Lastly, we calculated the shift of immune cell proportion and explored the relationship between key genes like TNFRSF18 and immune cell subgroups. We identified 12 unique cell populations in cervical cancer samples and stained positive for epithelial cells, T cells and macrophages. Functional enrichment analysis revealed the gene expression pattern associated with multiple biological processes and molecular interactions in the tumour microenvironment. Certain genes, such as 16 FOXP3 and CD8A, displayed different expression patterns across the immune cell subsets. Additionally, the expression of TNFRSF18 was directly related to the proportions of most of the immune cells and inversely related to a few T and B lymphocyte subsets. This study offers a comprehensive landscape of immune cell proportions within the cervical cancer TME and uncovers a complexity in the relationships between gene expression and tumour-infiltrating immune cell subsets. These results will provide valuable clues for the study of the immune microenvironment in cervical cancer and will shed some light into novel therapeutic approaches.  \n1 | Introduction  \nCervical cancer (CC), one of the most common gynaecologic tumours, exhibits diverse clinical behaviour and urgently requires accurate prognostic modelling for the improvement of patient care [1–3]. Although substantial progress has been achieved in treatment regimens, it is urgent to elucidate the molecular pathogenesis of cervical cancer for better risk stratification and treatment.  \nThe tumour microenvironment (TME), including immune cell infiltration, is critical to cancer prognosis and response to treatment. Research on the correlation between gene expression and immune cell infiltration profile in the tumour microenvironment might help to unveil the potential mechanism of cervical cancer [4–7].  \nSingle-cell sequencing is an indispensable tool for the study of cervical cancer. It may unveil the intricate tumour  \nThis is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the ori","cbCaij2kWcQC58AT","https://ap.wps.com/l/cbCaij2kWcQC58AT","pdf",9024781,14,"English","# Introduction\n# Methods\n## Data Source\n## Clustering and Cell Annotation\n## Functional Enrichment and Gene Expression Analysis\n# Results\n## Immune Cell Populations and Validation\n## Gene-Immune Correlations and Immune Proportion Shifts\n# Conclusion\n## Therapeutic Implications","[{\"question\":\"What is the main goal of the study in cervical cancer?\",\"answer\":\"To characterize immune cell subset distribution in the tumour microenvironment using scRNA-seq and determine how immune cell composition correlates with gene expression.\"},{\"question\":\"How were single-cell clusters and immune cell populations identified?\",\"answer\":\"Cells were clustered using UMAP and t-SNE, then cell populations were labelled using flow cytometry and immunohistochemistry validation.\"},{\"question\":\"Which analysis approaches were used to link genes to immune microenvironment biology?\",\"answer\":\"Gene functions were assessed with GO enrichment, and individual gene expression patterns were examined at the single-cell level, including correlations involving TNFRSF18.\"}]","Single-Cell RNA Sequencing Analysis Reveals Correlation Between Immune Cell Composition and Gene Expression in Cervical Cancer | PDF",1790098762,35]