What Is RFC4? Replication Factor C Subunit 4 (RFC4) is a component of the RFC complex, which loads proliferating cell nuclear antigen (PCNA) onto DNA during DNA replication. RFC4 enables DNA polymerase delta and epsilon to extend primer templates, plays a role in S-phase checkpoint control, and is involved in mismatch and excision repair after DNA damage. Because RFC4 is central to cell cycle progression and DNA integrity maintenance, it is overexpressed in proliferating cancer cells.
The Immunotherapy Prediction Gap in LUAD Lung adenocarcinoma (LUAD) accounts for approximately 40-50% of all lung cancers, and while immune checkpoint inhibitors (ICIs) targeting PD-1/PD-L1 have transformed treatment, current effective response rates remain below 40%. Existing biomarkers - PD-L1 expression and tumor mutation burden - are insufficient to fully capture the heterogeneity of the tumor immune microenvironment (TIME). New biomarkers that reflect TIME composition and predict ICI response are urgently needed.
RFC4's Potential Link to Immune Evasion Emerging evidence suggests that DNA replication and repair genes do more than support proliferation; their expression shapes the genomic instability profile of tumors, which in turn affects how the immune system recognizes and attacks cancer cells. High RFC4 expression correlates with PD-L1 (CD274) positivity, suggesting RFC4 may be mechanistically connected to the PD-1/PD-L1 immune checkpoint pathway, though this connection requires experimental confirmation.
Study Approach This study analyzed RFC4 expression, survival association, immune cell infiltration, and immunotherapy response prediction using TCGA LUAD data (586 samples: 527 cancer, 59 normal), validated in three GEO expression datasets and one GEO survival dataset (GSE37745). Real-world immunohistochemical (IHC) staining in 31 LUAD patients from the Second Affiliated Hospital of Fujian Medical University provided protein-level clinical validation.
TCGA and GEO Data Sources The TCGA-LUAD dataset provided 527 cancer and 59 normal tissue RNA-seq samples for exploratory analysis. Differential RFC4 expression was validated in three GEO datasets (GSE116959, GSE32863, GSE118370). Prognostic analysis used GSE37745, which contains LUAD patients with survival follow-up. The best cutoff RFC4 expression value for survival dichotomization was determined separately in TCGA (cutoff 7.16) and GSE37745 (cutoff 9.31).
Immune Microenvironment Profiling Tools Three complementary immune analysis platforms were applied. CIBERSORT deconvolved bulk RNA-seq data to estimate infiltration levels of 22 specific immune cell types (T cell subsets, macrophage subtypes, NK cells, dendritic cells, mast cells) in RFC4-high versus RFC4-low tumors. ESTIMATE calculated stromal scores, immune scores, and tumor purity estimates from transcriptomic data. TIDE (Tumor Immune Dysfunction and Exclusion) predicted immune checkpoint inhibitor response probability, T cell dysfunction, and immune exclusion scores.
Functional Enrichment Analysis DEGs between RFC4-high and RFC4-low TCGA groups (1346 genes: 746 upregulated, 600 downregulated, using log fold-change threshold of 1 and P less than 0.05) were subjected to GO biological process, cellular component, and molecular function analysis, plus KEGG pathway enrichment. CancerSEA was used to predict RFC4's involvement in 14 cancer-relevant biological functions including cell cycle, DNA repair, invasion, and stemness.
Real-World IHC Validation RFC4 protein expression was first evaluated in IHC images from the Human Protein Atlas (HPA) database (30 LUAD and 9 normal lung tissue images). A prospective cohort of 31 LUAD patients who underwent surgery at the Second Affiliated Hospital of Fujian Medical University (January 2021 to May 2024) provided paired cancer and adjacent normal tissue specimens for IHC staining with a RFC4 rabbit polyclonal antibody. Results were scored by two independent pathologists.
Consistent Overexpression Across Datasets RFC4 mRNA expression was significantly elevated in LUAD compared to normal lung tissue in TCGA (P less than 0.001) and in all three GEO validation datasets (GSE116959, GSE32863, GSE118370). Protein-level confirmation came from HPA database IHC images: moderate-to-strong RFC4 protein expression was present in 83.33% (25/30) of LUAD tissues versus 22.22% (2/9) of normal lung tissues (P = 0.002). In the real-world 31-patient cohort, strong positive RFC4 expression was found in 77.42% (24/31) of LUAD tumors versus only 19.35% (6/31) of adjacent normal tissue (P less than 0.001).
Independent Prognostic Value In TCGA, RFC4-high patients (n = 344) had significantly worse overall survival than RFC4-low patients (n = 136): HR = 1.83 (95% CI 1.25-2.68, P = 0.002). Five-year survival rates were 54.95% in the RFC4-low group versus 41.25% in the RFC4-high group. GEO validation in GSE37745 confirmed this: HR = 1.52 (95% CI 1.09-2.13, P = 0.015), with 5-year survival of 50.00% (RFC4-low) versus 35.71% (RFC4-high). Multivariate Cox regression including clinical stage, cancer status, and residual tumor confirmed independent prognostic value of RFC4 (HR = 1.52, 95% CI 1.09-2.12, P = 0.015). Among all clinical characteristics tested, only survival status showed a significant association with RFC4 expression - stage, gender, age, and smoking status did not.
Immune Cell Infiltration Patterns CIBERSORT analysis showed that RFC4-high tumors had significantly greater infiltration of CD8+ T cells, CD4+ memory activated T cells, follicular helper T cells, gamma-delta T cells, M0 and M1 macrophages, and activated mast cells - all cell types associated with active immune responses. Conversely, RFC4-low tumors had more M2 macrophages, resting dendritic cells, plasma cells, and resting mast cells. ESTIMATE analysis confirmed that RFC4-high tumors had lower stromal scores, lower immune scores, lower ESTIMATE scores, and higher tumor purity - indicating that RFC4-high tumors are more cellular and immunologically active despite having higher RFC4-driven proliferation.
TIDE Predicts Better ICI Response in RFC4-High Patients TIDE analysis predicted that RFC4-high patients would have lower TIDE scores - indicating higher immune sensitivity and greater predicted benefit from ICI treatment. RFC4-high tumors showed lower T cell dysfunction scores and higher T cell exclusion scores, along with higher MDSC, CAF, and CD8 scores, and lower M2 macrophage and IFNG scores. Lower TIDE scores and the specific immune infiltration pattern collectively indicate that RFC4-high LUAD tumors have a TIME that is immunologically primed but with active immune suppression mechanisms that ICIs could overcome.
Core Biological Functions CancerSEA functional prediction analysis showed RFC4 was positively involved in 12 of 14 cancer biological functions, with the strongest correlations for cell cycle (RFC4 drives mitotic division), DNA repair (RFC4 is directly required for PCNA loading and DNA polymerase extension), and DNA damage response. This confirms the known mechanistic role of RFC4 in DNA replication machinery while revealing broader involvement in cancer biology.
RFC4/NOTCH1 Signaling Feedback Loop Prior research identified an RFC4/NOTCH1 signaling feedback loop that promotes NSCLC metastasis and stemness. In this loop, RFC4 activates NOTCH1 signaling, which in turn maintains cancer stem cell properties and facilitates metastatic seeding. The RFC4/NOTCH1 axis represents a specific mechanistic pathway by which RFC4 overexpression drives disease progression beyond its canonical DNA replication function.
Immunostimulator Suppression as Primary TIME Mechanism Correlation analysis between RFC4 and 43 immunostimulatory factors showed mixed results - positive correlation with 14 and negative correlation with 13. However, GSVA meta-analysis of the entire immunostimulator gene set showed RFC4 is negatively correlated with immunostimulator activity overall (rho = -0.164, P less than 0.001). This suggests RFC4 primarily acts to suppress immune stimulatory signaling, reducing the overall immunostimulatory tone of the tumor microenvironment. A similar analysis of 23 immunoinhibitors showed no significant net correlation, indicating the TIME remodeling effect is asymmetric - suppressing stimulation while not significantly altering inhibition.
RFC4-PD-L1 Connection Among individual immunoinhibitor correlations, RFC4 expression showed positive correlation with PD-L1 (CD274) expression. This finding is consistent with a possible mechanism where RFC4-driven genomic instability activates PD-L1 upregulation as an immune escape strategy, but the causal direction remains unconfirmed. The study authors identified this as a priority for experimental investigation via RFC4 overexpression and knockdown experiments.
No Experimental Validation of Immune Mechanisms While the bioinformatics analysis identifies RFC4's association with immune cell infiltration and TIDE-predicted ICI response, the study provides no experimental evidence that RFC4 directly causes the observed immune changes. The critical experiments needed include RFC4 knockdown (shRNA/CRISPR) and overexpression in LUAD cell lines measuring downstream effects on PD-L1 expression, cytokine secretion, T cell killing efficiency, and immune checkpoint pathway activation. In vivo syngeneic mouse models are required to test whether RFC4 modulation changes tumor immune infiltration and ICI treatment outcomes.
TIDE-Based ICI Prediction Needs Clinical Validation TIDE provides a computational prediction of immunotherapy response based on gene expression patterns, but it is not a direct clinical outcome measurement. The study lacks a real-world patient cohort with documented ICI treatment and response data to confirm that RFC4-high patients actually respond better to anti-PD-1/PD-L1 therapy. A prospective or retrospective cohort of ICI-treated LUAD patients stratified by RFC4 expression is the next essential validation step.
Incremental Value Over Established Biomarkers Unknown PD-L1 expression and tumor mutation burden are the current clinical standard biomarkers for ICI selection in LUAD. The study did not assess whether RFC4 provides additional predictive value when combined with these established biomarkers, or whether RFC4-high/PD-L1-low patients represent a distinct subgroup with differential ICI benefit. Multi-biomarker modeling studies incorporating RFC4 alongside PD-L1 and TMB are needed.
Upstream Regulation and Therapeutic Targeting The study identifies RFC4 as a therapeutic target but does not characterize its upstream regulators or identify druggable nodes in its regulatory network. Understanding which transcription factors or signaling pathways drive RFC4 overexpression in LUAD could reveal pharmacologically tractable intervention points. Whether direct RFC4 inhibition is feasible - given that RFC4 is also expressed in normal proliferating cells - raises selectivity and toxicity questions that pre-clinical studies must address before RFC4 inhibition can be considered as a therapy.