Abstract Background Replication factor C subunit 4 (RFC4) plays a critical role in the initiation and progression of some cancers; however, its relationship with tumor-infiltrating immune cells in cervical cancer (CC) has not been comprehensively analyzed. This study aimed to determine whether RFC4 overexpression affects overall survival in CC and to explore its impact and potential mechanisms on the tumor immune microenvironment. Methods Data from Genotype-Tissue Expression database (GTEx) and Cancer Genome Atlas (TCGA) database were used as the exploration set. Datasets from the Gene Expression Omnibus (GEO) were used as the validation set. We also validated the expression of the RFC4 protein in the Human Protein Atlas (HPA) database and a real cohort. Clinical data on CC were evaluated for their association with RFC4 using TCGA and GEO databases. Possible relationships amongst RFC4, immune cells, and related genes were investigated using Cell-type Identification by Estimating Relative Subsets of RNA Transcripts (CIBERSORT) and Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression (ESTIMATE). GO and KEGG pathway enrichment analyses were used to explore potential mechanisms. Tumor immune dysfunction and exclusion (TIDE) scores were used to predict the immunotherapeutic response to RFC4. Results In the exploration, validation, and real cohort datasets, RFC4 expression was significantly elevated in CC tissues compared to that in normal tissues. Survival analysis based on TCGA and GEO datasets showed that CC patients with high RFC4 expression had a better prognosis than those with low expression. RFC4 expression was strongly correlated with some immunostimulators and immunoinhibitors. RFC4 expression was significantly negatively correlated with activated mast cell immune infiltration, activated CD4 memory T cells, M0 macrophages, and resting natural killer (NK) cells and significantly positively associated with activated dendritic cells, resting dendritic cells, and plasma cells. Conclusion RFC4 is highly expressed in CC tissues. However, patients with high RFC4 expression in CC have a better prognosis, possibly because RFC4 exerts antitumor effects by affecting the immunostimulatory tumor microenvironment, such as immunostimulatory and dendritic cell infiltration. Keywords: cervical cancer, replication factor C subunit 4 (RFC4), tumor immune microenvironment, immune-related genes, immunochemistry, pan-cancer analysis 1 Introduction Cervical cancer (CC) is one of the most common gynecological malignancies and life-threatening health issue worldwide. Its incidence rate and mortality remain high, especially in developing countries ([34]Siegel et al., 2021; [35]Buskwofie et al., 2020; [36]Bray et al., 2024; [37]Arbyn et al., 2020; [38]Zhang et al., 2020). Despite significant progress in screening and prevention measures for CC in recent years, a deep understanding of the molecular mechanisms underlying CC remains key to improving treatment efficacy and patient survival ([39]Balasubramaniam et al., 2019). In recent years, significant progress has been made in the treatment of CC, resulting in a significant reduction in patient mortality ([40]Sharma et al., 2020). The implementation of targeted therapies has benefited patients with advanced CC, as these treatments have been effective and significantly reduce the mortality rate of advanced CC ([41]Liontos et al., 2019). In addition to targeted treatment, the use of immune checkpoint inhibitors (ICIs) has greatly improved CC prognosis ([42]Ferrall et al., 2021). However, the overall effectiveness of ICIs is poor, and depends on the sensitivity and expression of driver genes in cancer tissues ([43]Volkova et al., 2021). It is important to understand the genetic mechanism of immunotherapy resistance, which is currently a cutting-edge oncology topic attracting the interest of many scholars. Human replication factor C (RFC) is a multimeric protein composed of five distinct subunits that have been highly conserved throughout evolution ([44]Yao and O'Donnell, 2012). The function of the RFC family (RFCs) is to load proliferating cell nuclear antigen (PCNA) onto DNA as ATP dependent clamp loaders during DNA synthesis ([45]Chen et al., 2021). In addition, the RFC family plays an important role in DNA repair after DNA damage. The enhanced activity of RFC family members is also an important characteristic of cancer occurrence and development. Among the RFCs, the RFC4 gene encodes the fourth subunit of the RFC complex and is involved in DNA replication as a clamp loader. RFC4 is exhibited highly expressed and has significantly increased activity in various malignant tumors, including prostate, cervical, and colorectal cancers ([46]Krause et al., 2001; [47]Kang et al., 2009; [48]Misbah et al., 2024). However, the role of RFC4 in CC initiation and progression remains unclear. In this study, we investigated the expression of RFC4 in CC and determined its potential biological function and impact on CC prognosis and immunoregulation. 2 Materials and methods 2.1 Study protocol The current study consisted of two parts: one explored the different expression of RFC4 and determined its potential biological function and impact on CC prognosis and immunoregulation using bioinformatics analysis, and the other explored different levels of RFC4 expression using immunohistochemistry (IHC) of 15 patients with CC recruited from the Second Affiliated Hospital of Fujian Medical University. This study was approved by the ethics committee of the Second Affiliated Hospital of Fujian Medical University (2020-06). The study flowchart is shown in [49]Figure 1. FIGURE 1. [50]FIGURE 1 [51]Open in a new tab Study design flowchart. 2.2 Analysis of RFC4 mRNA and protein expression in CC tissues and adjacent tissues Pan-cancer expression data were downloaded from Genotype-Tissue Expression database (GTEx; [52]https://www.gtexportal.org/home/) and Cancer Genome Atlas (TCGA; [53]https://www.cancer.gov/ccg/research/genome-sequencing/tcga) databases in May 2024. The RFC4 expression was examined using GTEx and TCGA datasets and verified using Gene Expression Omnibus (GEO; [54]https://www.ncbi.nlm.nih.gov/geo/) and Human Protein Atlas (HPA; [55]https://www.proteinatlas.org/). Differential expression analysis of RFC4 mRNA was conducted using the TCGA dataset for preliminary analysis, and the GTEx and GEO datasets for validation. RFC4 and CC-associated genes were identified using log fold change (|log2FC|) values >1 and P < 0.05. 2.3 Relationship between RFC4 and clinicopathological characteristics and prognosis of CC patients The clinicopathological data for survival analysis were identified using the TCGA and GEO ([56]GSE44001) datasets. The relationship between RFC4 mRNA and different clinicopathological characteristics, such as age, pathological type, and clinical stage, was explored using data from the TCGA database. The surv_cutpoint function in the survminer package was used to determine the best cutoff value of RFC4 mRNA expression in the samples. Using the best cutoff value, patients with CC were divided into high-expression (RFC4^High) and low-expression (RFC4^Low) groups. The Kaplan-Meier method was used to plot the overall survival (OS) curves of the two groups, and the log rank test was used for comparisons. The relationship between the RFC4 expression and OS was verified using the [57]GSE44001 dataset. Differences were considered statistically significant at P < 0.05. 2.4 Screening and functional enrichment analysis of RFC4-related differentially expressed genes (DEGs) in CC We used the “limma” package to identify DEGs in CC tissues, and then correlation analysis was used to identify RFC4-associated DEGs. The correlation between different gene expression levels was analyzed using Pearson’s correlation coefficient, with P < 0.05 indicating statistical significance. The top 50 common DEGs closest to RFC4 were selected, and a heatmap was plotted. RFC4-related DEGs with Pearson correlation coefficient >0.5 and P < 0.05 were selected to enrichment analysis. Gene ontology (GO) functional enrichment analysis of the cell composition, biological processes, and molecular function and Kyoto Encyclopedia of Genes and Genomes (KEGG) were conducted for pathway enrichment analysis. 2.5 Analysis of the relationship between RFC4 and tumor immune cell infiltration and immunoregulatory factors Using the Spearman correlation analysis, the correlation between RFC4 expression and various infiltrating immune cells in the tumor microenvironment was explored and analyzed, with P < 0.05 considered statistically significant. The immune regulatory factors gene set was selected from previously reported references ([58]Zhang et al., 2021;