Single‐Cell RNA Sequencing Analysis Reveals Correlation Between Immune Cell Composition and Gene Expression in Cervical Cancer

TL;DR

This study uses single-cell RNA sequencing to explore immune cell diversity and gene expression patterns in cervical cancer, revealing how immune cells and genes interact in the tumor environment.

Contribution

The study provides new insights into immune cell composition and gene expression correlations in cervical cancer using single-cell RNA sequencing.

Findings

Twelve unique cell populations were identified, including epithelial cells, T cells, and macrophages.

Genes like FOXP3 and CD8A showed distinct expression patterns across immune cell subsets.

TNFRSF18 expression correlated with immune cell proportions and inversely with some lymphocyte subsets.

Abstract

Cervical 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 single‐cell 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.

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