Fen Zhao

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

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.

An Integrative Analysis Revealing ZFHX4-AS1 as a Novel Prognostic Biomarker Correlated with Immune Infiltrates in Ovarian Cancer

Ovarian cancer (OC) is the main cause of deaths worldwide in female reproductive system malignancies. Growing studies have indicated that eRNAs could regulate cellular activities in various tumors. Yet the potential roles of eRNAs in OC progression have not been elucidated. Thus, comprehensive assays were needed to screen the critical eRNAs and to explore their possible function in OC. We used Kaplan–Meier methods to identify survival-associated eRNAs in OC based on TCGA datasets. The levels of ZFHX4-AS1 were examined using TCGA datasets. Further exploration was carried out based on the following assays: clinical and survival assays, GO terms, and KEGG assays. TIMER was applied to delve into the relationships between ZFHX4-AS1 and tumor immune infiltration. In this research, we observed 71 survival-related eRNAs in OC patients. ZFHX4-AS1 was highly expressed in OC specimens and predicted a poor prognosis of OC patients. In addition, high ZFHX4-AS1 expression was positively related to the advanced stages of OC specimens. Multivariate assays revealed that ZFHX4-AS1 was an independent prognostic factor for overall survival of OC patients. KEGG analysis indicated that ZFHX4-AS1 may play a regulatory effect on TGF-beta signaling, PI3K-Akt signaling, and proteoglycans in cancer. The pan-cancer validation indicated that ZFHX4-AS1 was related to survival in eight tumors, namely, UCEC, STAD, SARC, OV, ACC, KICH, KIRC, and BLCA. The expression of ZFHX4-AS1 was correlated with the levels of B cells, T cell CD8+, neutrophil, macrophage, and myeloid dendritic cells. Simultaneously, ZFHX4-AS1 may be a prognostic biomarker and a distinctly immunotherapy-related eRNA in OC.