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. 2026 Apr 6;16:16542. doi: 10.1038/s41598-026-47187-1

Prognostic significance and immune correlation of STING expression and promoter methylation in renal cell carcinoma

Shirong Ding 1,4, Mengge Ding 1, Ao’ran Hu 1, Yishu Guo 1, Qi Meng 4, Kun Ye 5, Min Lu 1, Chaoyuan Liu 1, Fang Ma 1, Qian Long 2,4,✉, Xianling Liu 1,3,✉
PMCID: PMC13216640  PMID: 41942521

Abstract

Renal cell carcinoma (RCC) typically shows resistance to immunotherapy and is associated with poor prognosis. Recent studies have revealed a role for DNA methylation in immune infiltration in different cancers, but its pattern in RCC is not well understood. In this study, we analyzed the relationships among STING promoter methylation, mRNA expression, overall survival, and immune cell infiltration in a TCGA cohort and validated the findings in an independent cohort. Additionally, we assessed these correlations in an RCC cohort from Sun Yat-sen University Cancer Center (SYSUCC) using immunohistochemistry and pyrosequencing. Our findings revealed significant hypomethylation of the STING promoter in RCC tumor tissues compared with normal tissues, which strongly correlated with increased STING mRNA expression across all three RCC cohorts. Additionally, hypomethylation of the STING promoter hypomethylation was associated with advanced clinicopathological features and poor overall survival. Moreover, we found a significant relationship between STING promoter methylation and both immune cell infiltration and the expression of immune checkpoint molecules. Our findings in the SYSUCC cohort confirmed that STING promoter methylation was related to CD4 and CD8 T-cell infiltration in RCC tumor tissues. These results suggest that methylation of the STING promoter plays a pivotal role in regulating its expression and influencing the tumor microenvironment. STING promoter methylation and expression are linked to clinicopathological characteristics, overall survival, and immune cell infiltration in RCC. We propose that further validation of STING promoter methylation represents a biomarker for predicting responses to immune checkpoint inhibitors in RCC.

Supplementary Information

The online version contains supplementary material available at 10.1038/s41598-026-47187-1.

Keywords: DNA methylation, Epigenetics, Biomarker, STING, Renal cell carcinoma, Tumor immune microenvironment

Subject terms: Cancer, Tumour biomarkers, Tumour immunology, Urological cancer

Introduction

Renal cell carcinoma (RCC) is the most prevalent form of kidney cancer, constituting 4.1% of all newly diagnosed cancer cases in the United States in 20221. RCC encompasses primarily clear-cell RCC (70–80%), along with papillary RCC and chromophobe RCC2. Although early‑stage RCC is typically managed surgically, nearly 30% of patients eventually develop recurrence or distant metastasis3,4. Historically perceived as a “hot” cancer, RCC displays notable immunogenicity coupled with significant infiltration of immune cells5. These biological characteristics support the clinical success of immunotherapy, particularly immune checkpoint blockade (ICB), in reshaping RCC treatment paradigms6,7. Current first-line approaches integrate immune checkpoint blockade (ICB) with tyrosine kinase inhibitors8,9. However, immune infiltration often induces compensatory upregulation of immune checkpoint molecules, reinforcing an immunosuppressive tumor microenvironment (TME) that limits sustained antitumor responses10. Although a subset of patients experience durable clinical benefits from ICB, primary and acquired resistance remains common, restricting its broader clinical impact11. Hence, identifying robust molecular biomarkers to predict responses to checkpoint blockade therapy is imperative for enhancing the clinical effectiveness of these interventions.

STING, formally known as a stimulator of interferon genes, is a pivotal intracellular molecule essential for regulating immune responses12. It is primarily located in the cytoplasm and acts as a receptor protein crucial for detecting DNA viruses and intracellular pathogens. Recent research has revealed its substantial involvement in tumor immunity13. Upon activation of the cyclic GMP–AMP synthase (cGAS)–STING pathway, cells produce type‑I interferons and inflammatory cytokines that stimulate natural killer (NK) cells, T cells, and macrophages, thereby enhancing antitumor immunity14,15. This activation enhances their ability to eliminate tumor cells, thereby restraining tumor growth and metastasis16. Nonetheless, tumor cells can exploit negative regulatory mechanisms within the STING pathway to evade immune surveillance, thereby promoting tumor progression17. Hence, the role of STING in tumors is intricate and multifaceted, contingent upon its interactions with other signaling pathways and the specific conditions of the tumor microenvironment18. Understanding the mechanisms underlying the involvement of STING in tumor initiation and progression has significant implications for the development of innovative tumor treatment strategies.

A series of studies suggest that aberrant DNA methylation is linked to numerous human diseases19,20. DNA methylation plays a pivotal role in regulating gene expression in both tumor cells and immune cells21,22. Methylation status at specific DNA sites may impact tumor progression and alter the tumor microenvironment. Studies indicate that abnormal DNA methylation is considered an epigenetic hallmark of cancer and can serve as a biomarker for predicting patient prognosis and treatment response23. Certain DNA CpG sites located on immune checkpoint molecule genes, such as PD-1, PD-L1, CTLA-4, and NLRP3 have been identified as reliable indicators for predicting response to immune checkpoint inhibitors24–27.

STING promotes the development of renal cell carcinoma. However, the precise regulatory role of STING promoter methylation in gene expression, as well as its influence on the tumor immune microenvironment, requires further elucidation. Our study aimed to investigate the relationships between STING promoter methylation and the development, clinical characteristics, immune relevance, and patient prognosis of renal cell carcinoma.

Materials and methods

Antibodies, reagents, and immunohistochemistry (IHC)

Anti‑STING (Abcam, ab239074), anti‑CD4 (Servicebio, GB11064), and anti‑CD8 (Servicebio, GB13429) antibodies were used in this study. SYSUCC samples were prepared in a tissue microarray. Briefly, a hollow needle was used to obtain tissue cores as small as 0.6 mm in diameter from paraffin-embedded surgical specimens of renal cancer patients. These tissue cores were then inserted into a recipient paraffin block in a precisely spaced, array pattern. Sections from this block were cut using a microtome, mounted on a microscope slide, and then analyzed by any method of immunohistochemistry (IHC). Immunohistochemistry (IHC) was performed on the paraffin-embedded tissue sections. Briefly, we deparaffinized and rehydrated the paraffin sections, followed by antigen retrieval procedures. Next, we incubated sections with primary antibodies against STING (dilution: 1:100), CD4 (dilution: 1:100), or CD8 (1:300) at 4 °C overnight in a humidified container (we chose the dilution ratio of different primary antibodies according to their recommended dilution ratio suggested in the manufacturer’s instructions). Additionally, we conducted a preliminary test for each primary antibody to determine the optimal dilution ratio. The tissues were subsequently at room temperature for 50 min. The IHC slides were then scanned and digitalized using 3DHISTECH (Hungary). The IHC data for STING, CD4, and CD8 are expressed as a density scores. Briefly, five random areas of each IHC image (1 mm2 each) were selected for each marker to count the number of positive cells per high power field (20X magnification), and the average of the five fields was taken; the data are expressed as a density score (total number of positive cells per 1 mm2 area).

Methylation analysis

Methylation data from the TCGA ccRCC cohort and CPTAC ccRCC cohort were obtained from the TCGA and CPTAC database, s respectively. The β value (beta value), defined as the ratio of methylated probe intensity to the sum of methylated and unmethylated intensities, is widely used as an approximation of percent DNA methylation.

Estimation of tumor microenvironment immune cell infiltration

To quantify to quantitate immune cell infiltration into the tumor microenvironment, an algorithm known as single-sample gene set enrichment analysis (ssGSEA) was used. A gene set corresponding to immune cell types was acquired from Zhou’s study28(Table S7). ssGSEA provided enrichment scores that represented the relative abundance of specific immune cells infiltrating the tumor microenvironment. In Tables S8 and S9, additional information was provided on the relative abundance of tumor microenvironment cells in each TCGA sample and each CPTAC sample is provided.

Gene set variation analysis (GSVA)

To analyze immune cell infiltration and biological pathways using GSVA enrichment, we used the R package ‘GSVA’. GSVA estimates the variation in pathway activity across a sample population in a nonparametric, unsupervised manner. It uses an enrichment scoring algorithm that bypasses the traditional approach of explicitly modeling phenotypes29. Detailed information on the GSVA of different pathways is provided in Table S10. From Powles’ study, gene sets representing other biological processes were obtained30.

Correlation between STING expression/promoter methylation and immune-related pathways

Previous studies constructed a gene set panel consisting of genes involved in various biological processes relevant to the tumor immune microenvironment28,30–32(Table S10). The relative pathway enrichment scores of each sample of the TCGA and CPTAC cohorts are listed in Tables S11 and S12, respectively. We then investigated the enrichment scores of each biological process in the groups with high and low STING expression and promoter methylation.

Statistics

Statistical analyses were conducted using SPSS (version 23.0), GraphPad Prism (version 8), and R (version 4.0.3). The correlation coefficients in our study were calculated using Spearman’s rank correlation. Student’s t test or the Mann–Whitney U test was used to compare differences between two groups. For survival analysis, the optimal cutoff values were calculated by the R package ‘Survminer’. Kaplan–Meier survival curves and log-rank tests were used to analyze the associations of STING expression and promoter methylation with overall survival in patients with RCC. All statistical P values were from a two-tailed t test, with P < 0.05 considered to indicate statistical significance. The significance levels are denoted as follows: *P < 0.05, **P < 0.01, ***P < 0.001, and ****P < 0.0001.

Results

High STING expression is correlated with poor outcomes in RCC patients

STING plays divergent roles as either an antitumoral factor or an oncogenic factor across various types of cancers. To investigate the impact of STING promoter methylation in renal cell carcinoma (RCC), our study commenced with an analysis of STING expression in tumor tissues and their corresponding normal adjacent tissues. Notably, we observed markedly elevated levels of STING expression in RCC tumor tissues compared with their normal counterparts (Fig. 1A–B). Additionally, although no statistically significant differences were observed, a trend toward increased STING expression with higher tumor grade was noted (Fig. 1C–F). Leveraging prognostic data sourced from the TCGA database, we discerned that heightened STING expression levels correlated with shortened overall survival and disease-free survival durations among RCC patients (Fig. 1G–H). These findings suggest that STING expression is upregulated in RCC and may be associated with adverse prognostic outcomes.

Fig. 1.

Fig. 1

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STING is highly expressed and associated with poor prognosis in RCC patients. (A) Relative mRNA expression of STING between tumor and adjacent normal tissues according to data from the TCGA cohort; (B) Relative expression of STING between tumor and adjacent normal tissues according to data from the CPTAC cohort; (C,D) The mRNA expression of STING in patients with different stages and pathological grades of patients in the TCGA cohort; (E,F) The protein expression of STING in patients in different stages and pathological grades in the TCGA cohort; (G,H) Kaplan–Meier survival analysis of the effect of STING expression on overall survival and disease-free survival in patients in the TCGA RCC cohort, respectively.

Aberrant methylation of the STING promoter in RCC

An increasing number of studies suggest that DNA promoter methylation plays a crucial role in determining the prognosis and grade of tumors. Hence, we further investigated into the role of STING promoter methylation in RCC. First, we utilized the relevant website (http://www.bioinfo-zs.com/smartapp/#) to assess the methylation status of STING and examined seven primary methylation sites: cg01938023, cg03317505, cg04232128, cg04560810, cg16532438, cg16983159, and cg23255964 (Fig. S2 and Table S1). To validate STING methylation in tumor tissues, we analyzed these seven methylation sites in the TCGA database, two additional GEO datasets, and various cell lines. Notably, compared with normal tissues and cell lines, RCC tumor tissues and cell lines exhibit significant hypermethylation at the cg16532438, cg16983159, and cg23255964 sites (Fig. 2A–D). Furthermore, we investigated the correlation between STING methylation and the clinical characteristics of RCC patients using data from the TCGA database. Our findings revealed variations in the promoter methylation level of STING across different pathological grades and stages of RCC. Specifically, higher grades were associated with lower methylation levels at the cg03317505, cg04560810, cg16532438, and cg16983159 sites (Fig. 3A–B). These results collectively indicate aberrant methylation of the STING promoter in RCC and suggest that differences in methylation levels are linked to RCC grade.

Fig. 2.

Fig. 2

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The STING promoter is hypomethylated in tumor versus normal adjacent tissues in RCC. (A) Relative methylation of seven differentially methylated CpG sites (cg01938023, cg03317505, cg04232128, cg04560810, cg16532438, cg16983159, and cg23255964) located in the STING promoter between tumor and adjacent normal tissues in the TCGA cohort; (B) Relative methylation of seven differentially methylated CpG sites between tumor and adjacent normal tissues in GSE70303; (C) Relative methylation of seven differentially methylated CpG sites between tumor and adjacent normal tissues in GSE105260; (D) Relative methylation of seven differentially methylated CpG sites between kidney epithelial cells and renal cancer cells.

Fig. 3.

Fig. 3

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Promoter methylation is associated with aggressive clinical phenotypes in RCC. (A) Relative methylation levels of cg01938023, cg03317505, cg04232128, cg04560810, cg16532438, cg16983159, and cg23255964 in patients with different stages of disease in the TCGA cohort. (B) Relative methylation levels of cg01938023, cg03317505, cg04232128, cg04560810, cg16532438, cg16983159, and cg23255964 in patients with different pathological grades in the TCGA cohort.

STING promoter methylation is correlated with STING expression in RCC

The methylation of gene promoters plays a critical role in regulating gene transcription. To explore how methylation of the STING promoter methylation influences STING expression, we investigated the relationship between the expression of seven differentially methylated sites and STING expression. With the exception of site cg01938023, all the other sites were significantly negatively correlated with STING expression (Fig. 4A). To further corroborate our findings, we assessed the correlation between these sites and STING expression using an independent cohort from the CPTAC database. These results were entirely consistent with our conclusions drawn from the TCGA data (Fig. 4B). These findings suggest that abnormal methylation of the STING promoter may contribute to the aberrant upregulation of STING expression in RCC.

Fig. 4.

Fig. 4

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Correlation of STING promoter methylation with STING expression in RCC. (A) Correlations of cg01938023, cg03317505, cg04232128, cg04560810, cg16532438, cg16983159, and cg23255964 methylation with STING expression in TCGA tumor tissues. (B) Correlations of cg01938023, cg03317505, cg04232128, cg04560810, cg16532438, cg16983159, and cg23255964 methylation with STING expression in CPTAC tumor tissues.

STING promoter methylation predicts overall survival in RCC

To investigate the prognostic significance of STING promoter methylation in RCC, we initially examined the correlation between seven differentially methylated CpG sites and patient prognosis in RCC. Our findings indicated that hypomethylation of these seven sites correlated with poor overall survival and disease-free survival outcomes (Figs. 5A–G and 6A–G). These results underscore the potential of STING expression and promoter methylation as biomarkers for predicting prognosis of RCC.

Fig. 5.

Fig. 5

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STING promoter methylation predicted overall survival in RCC. (A–G) Kaplan–Meier survival analysis of the overall survival of patients in the TCGA RCC cohort for cg01938023, cg03317505, cg04232128, cg04560810, cg16532438, cg16983159, and cg23255964.

Fig. 6.

Fig. 6

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STING promoter methylation predicts disease-free survival in RCC. (A–G) Kaplan–Meier survival analysis of the disease-free survival rates of patients in the TCGA RCC cohort for cg01938023, cg03317505, cg04232128, cg04560810, cg16532438, cg16983159, and cg23255964.

STING expression and promoter methylation are correlated with immune cell infiltration in RCC

The tumor microenvironment harbors not only tumor cells but also a diverse array of stromal and immune cells, all of which play pivotal roles in the progression of tumors. Given the significant involvement of STING in immune cell functions and immune regulation, we hypothesized that STING expression is correlated with immune cell infiltration in the tumor microenvironment. To test this hypothesis, we analyzed the RNA-seq signatures of 23 immune cells, including CD4 and CD8 T cells, and correlated them with STING expression and promoter methylation. Our analysis revealed that high STING expression and promoter hypomethylation were associated with increased immune infiltration. Among the examined sites, hypomethylation at cg23255964, cg16983159, cg04232128, and cg01938023 was most significantly correlated with immune cell infiltration (Fig. 7A and Additional Figs. S3-4). To validate our findings, we assessed the correlation of STING expression and promoter methylation with immune cell infiltration using an independent cohort from the CPTAC database, and our results were consistent with those from the TCGA cohort (Fig. 7B). Furthermore, we investigated the role of STING expression and promoter methylation in key immune-related pathways by analyzing their relationships with 17 biological pathways, respectively. Our analysis revealed that high STING expression was associated with high angiogenesis scores, suggesting that patients with high STING expression may be more responsive to antiangiogenesis therapy. Additionally, elevated STING expression was significantly correlated with increased scores for EMT1, EMT2, EMT3, PAN-F-TBRS, and the IFN response, indicating that STING is involved in signaling pathways that respond to the tumor microenvironment and contribute to tumor immune evasion. Similarly, hypomethylation at cg16983159 and cg23255964 was associated with higher scores for EMT and PAN-F-TBRS. Moreover, cg16983159 hypomethylation was linked to increased CD8 T‑effector, co‑inhibition T cell, costimulation T cell, cytolytic activity, immune checkpoint, and MHC‑II HLA pathway scores. cg23255964 hypomethylation is also positively correlated with CD8 T effector activity, costimulation, and cytolytic activity. Together, these findings indicate that STING promoter hypomethylation is strongly associated with increased immune cell infiltration and elevated immune checkpoint signatures, potentially sensitizing tumors to immune checkpoint inhibitor therapy. Consistent results from the CPTAC cohort further support the robustness of these associations. Thus, STING expression and promoter methylation represent suggestive biomarkers for predicting responsiveness to immunotherapy in RCC.

Fig. 7.

Fig. 7

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STING expression and promoter methylation are correlated with immune cell infiltration in RCC. (A) The correlation heatmap of STING expression and its differentially methylated sites with 23 types of immune cells in the TCGA RCC cohort; only statistically significant (P < 0.05) correlation coefficients are shown. (B) The correlation heatmap of STING expression and its differentially methylated sites with 23 types of immune cells in the CPTAC RCC cohort; only statistically significant (P < 0.05) correlation coefficients are shown.

STING expression and promoter methylation are associated with the expression of key immunomodulators in RCC

The tumor immune microenvironment is intricately regulated by a myriad of membrane proteins and cytokines. To elucidate the relationship between STING regulation and immune signaling, we assessed the correlation between STING expression, STING promoter methylation, and 74 key immunomodulators in the TCGA cohort. Our analysis revealed that high STING expression and hypomethylation at cg16983159 and cg23255964 were associated with upregulation of the majority of immunomodulatory genes (Fig. 8A). Considering the promising therapeutic potential of immune checkpoint inhibitors (ICIs) across various tumor types, we further investigated the association of STING expression and cg16983159/cg23255964 methylation with immune checkpoint molecules (BLTA, TGFB1, MICB, and CD276) using expression data from the TCGA cohort. We observed a significant positive correlation between STING expression and the expression of BLTA, TGFB1, MICB, and CD276 (Fig. S5A). Conversely, methylation at cg16983159 was significantly negatively associated with the expression of BLTA, TGFB1, MICB, and CD276 (Fig. S5B). Additionally, methylation at cg23255964 was significantly negatively associated with the expression of BLTA and TGFB1 (Fig. S5C). Our analysis of data from the CPTAC cohort confirmed these findings from the TCGA cohort (Fig. 8B). Collectively, these results indicate that STING expression and promoter hypomethylation are closely associated with enhanced immunomodulatory and immune checkpoint–related signaling, suggesting a potentially regulated or inhibitory immune context in RCC.

Fig. 8.

Fig. 8

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STING expression and promoter methylation are associated with the expression of key immunomodulators in RCC. (A) Correlation heatmap of STING expression and the seven methylated CpG sites with the key immunomodulators in the TCGA RCC cohort; only statistically significant (P < 0.05) correlation coefficients are shown. (B) Correlation heatmap of STING expression and the seven methylated CpG sites with the key immunomodulators in the CPTAC RCC cohort; only statistically significant (P < 0.05) correlation coefficients are shown.

STING promoter methylation is correlated with overall survival and CD4/CD8 T-cell tumor infiltration

Our earlier findings from the TCGA and CPTAC cohorts indicated that the STING promoter is hypomethylated in tumor tissues and that this hypomethylation is linked to poor survival outcomes, advanced TNM stage, and high pathological grade. Additionally, hypomethylation of the STING promoter was associated with immune cell infiltration and the expression of immune checkpoint molecules. Given that cg16983159 was one of the most significant prognostic factors and was notably associated with TNM stage, pathological grade, and immune cell infiltration, we chose to validate this site in the SYSUCC validation cohort. We used pyrosequencing to assess the methylation status of cg16983159. Our results demonstrated a significant decrease in methylation at cg16983159 in tumor tissues compared with adjacent normal tissues (Fig. 9A). This hypomethylation was also associated with poor overall survival (Fig. 9B). CD4 and CD8 T cells play a central role in antitumor immune responses and are the primary immune cells involved in antitumor immunity. To confirm the relationship between STING promoter methylation and immune cell infiltration, we examined the expression of CD4, CD8, and STING in tumor tissues. We found that cg16983159 methylation was negatively correlated with the expression of CD4, CD8, and STING (Fig. 9C–F), consistent with our previous findings from the TCGA and CPTAC cohorts. These findings further support that STING promoter methylation is associated with overall survival and immune cell infiltration in RCC.

Fig. 9.

Fig. 9

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STING promoter methylation is associated with overall survival and tumor infiltration of CD4/CD8 T cells in the SYSUCC validation cohort. (A) Relative cg16983159 methylation between tumor and normal adjacent tissues in the SYSUCC cohort; (B) Kaplan–Meier survival analysis of cg16983159 methylation in SYSUCC cohort; (C–E) Correlations of cg16983159 methylation with CD4, CD8, and STING expression in the SYSUCC cohort, respectively. (F) Representative IHC images of CD4, CD8, and STING expression in the high and low cg16983159 methylation groups of the SYSUCC cohort.

Discussion

Aberrant DNA methylation is a hallmark of many cancers and typically manifests early in carcinogenesis33,34. DNA methylation profiling has become increasingly important for in cancer diagnosis, prognosis prediction, and therapeutic outcomes monitoring because of its high stability and reliability35,36. In this study, we discovered that compared with that in normal tissues, the STING promoter in RCC tumor tissues was widely hypomethylated. We identified seven significantly differentially methylated CpG sites (cg01938023, cg03317505, cg04232128, cg04560810, cg16532438, cg16983159, and cg23255964) that were substantially hypomethylated in tumor tissues (Fig. 2A–D). Typically, hypermethylation of specific gene promoters leads to gene silencing, whereas hypomethylation is often associated with gene activation because of an open chromatin structure37,38. Among these sites, cg16983159 and cg23255964 displayed the strongest negative correlations with STING expression, whereas cg01938023 did not demonstrate such a relationship, suggesting functional heterogeneity among the CpG sites within the STING promoter. Survival analysis further revealed that high STING expression is associated with poor overall survival, which aligns with previous findings39,40. Similarly, promoter hypomethylation across all the analyzed CpG sites predicted poor overall survival, which is consistent with the negative relationship between promoter hypomethylation and STING expression. Notably, cg16983159 demonstrated stage- and grade-dependent hypomethylation, indicating that it is a particularly strong prognostic indicator for RCC patients.

Despite the growing significance of DNA methylation in cancer diagnosis and prognosis prediction, DNA methylation markers also show promise as reliable indicators of patient outcomes across various therapies, including immunotherapy41,42. Several studies have identified several DNA methylation biomarkers in the promoter regions of immune-related genes that can predict immune cell infiltration and responses to immune checkpoint inhibitors in different cancer types26,43,44. Given the key role of STING in immune regulation, we explored whether STING expression and promoter methylation could also predict immune cell infiltration in RCC. We analyzed the correlation between STING expression and promoter methylation in 23 immune cell types in the tumor microenvironment, which was quantified using the ssGSEA algorithm with transcriptome data. We observed that high STING expression and promoter hypomethylation were significantly positively correlated with immune cells, including CD4 T cells, CD8 T cells, macrophages and natural killer T cells (Fig. 7). Interestingly, unlike other solid tumors that respond to immunotherapy, high CD8 T-cell infiltration is associated with poor outcomes in RCC patients45, which is consistent with our earlier results, indicating that high STING expression and promoter hypomethylation are linked to immune cell infiltration but also predict poor survival. A possible explanation is that increased immune cell infiltration may be accompanied by elevated expression of inhibitory immune checkpoint molecules, which can attenuate effective antitumor immune responses and reflect a functionally exhausted or regulated immune state46,47. In support of this hypothesis, STING expression and promoter hypomethylation were strongly correlated with key immunomodulators and immune checkpoint molecules, including BLTA, TGFB1, MICB, and CD276 (Fig. 8 and Fig. S5). To further validate these findings, we focused on cg16983159—the most prognostic and immunologically relevant site—and confirmed in the SYSUCC cohort that cg16983159 hypomethylation was associated with poor survival and reduced CD4⁺/CD8⁺ T-cell infiltration (Fig. 9A–B). Moreover, our IHC data indicated that cg16983159 methylation was negatively correlated with the expression of CD4, CD8, and STING (Fig. 9C–F). Taken together, these findings suggest that STING promoter methylation may influence tumor immunity in RCC by shaping a complex immune microenvironment characterized by both immune activation and concurrent immunoregulatory signals.

Notably, our data from the TCGA were sourced from the Infinium HumanMethylation450 BeadChip, which does not encompass all the CpG sites in the human genome. Thus, beyond cg16983159, other identified CpG sites may provide better predictions for survival and immune cell infiltration in RCC. Additionally, our study did not include a validation cohort of patients who received immune checkpoint inhibitor therapy, despite demonstrating that STING methylation was associated with immune cell infiltration in RCC. Moreover, the regulation of tumor immunity by genetic and epigenetic mechanisms is highly complex, and the findings of this study are primarily based on correlative analyses. Therefore, further experimental validation, particularly in vivo studies, is warranted to elucidate the underlying biological mechanisms. Future studies incorporating immunotherapy-treated cohorts and functional experiments will be important to further validate the clinical and biological relevance of STING promoter methylation in RCC.

The cGAS–STING pathway plays a dual role in regulating tumor progression48,49. Activation of the cGAS-STING signaling pathway can trigger a robust antitumor immune response17,50. In antigen-presenting cells, particularly in tumor-resident dendritic cells within the tumor microenvironment, activation of the cGAS-STING pathway provides the foundation for T-cell activation and proliferation, promoting CD8 T-cell infiltration and the development of antitumor immunity51–53. Natural killer cells, which can recognize tumor cells lacking MHC class molecules, also rely heavily on the activation of the cGAS–STING pathway for sustained antitumor immune activity54,55. Additionally, chromosomal instability in tumor cells can cause persistent activation of the cGAS–STING pathway, leading to chronic inflammation, desensitization to inflammatory responses, and a potentially immunosuppressive tumor microenvironment, thereby aiding tumor cells in immune evasion56,57. Although many STING agonists are currently in clinical trials, their safety and efficacy still require further improvement. Given the significant positive correlation between STING and multiple immune checkpoint molecules (BLTA, TGFB1, MICB, and CD276), it would be of interest to further investigate whether STING signaling is involved in the regulation of these immune checkpoint molecules. If validated, the combined use of STING-targeting strategies and immune checkpoint inhibitors may represent a potential therapeutic approach in solid tumors.

Overall, our study revealed that STING promoter methylation is associated with STING expression, clinicopathological characteristics, survival outcomes, immune cell infiltration, and immune checkpoint molecule expression in RCC. Importantly, STING promoter hypomethylation emerges as a suggestive biomarker for predicting prognosis and potential responsiveness to immune checkpoint blockade, although further validation in independent immunotherapy-treated cohorts is required. These insights may contribute to the development of more personalized immunotherapeutic strategies for RCC patients.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary Material 1 (343.5KB, xlsx)
Supplementary Material 2 (1.1MB, docx)

Acknowledgements

We thank all members of Liu’s laboratory for their advice and assistance.

Author contributions

X.L., Q.L., and S.D. conceived and designed the project. S.D., Q.L., M.D., A.H., Y.G., K.Y., and Q.M. analyzed and interpreted the data. S.D., M.L., C.L., and F.M. wrote the main manuscript text. S.D. and Q.L. prepared figures. All authors contributed to the article and approved the submitted version.

Funding

This study was supported by the funds from the National Natural Science Foundation of China (grant number: 82303526 and 82403073), the Natural Science Foundation of the Hunan Province of China (grant number: 2024JJ6590, 2023JJ40842 and 2022JJ40704), the Education and Teaching Reform Research Project of Central South University (grant number: 2022JY197), the China Postdoctoral Science Foundation (grant number: 2023M743946 and 2023M733955), the Open Funds of State Key Laboratory of Oncology in South China (grant number: HN2024-04 and NH2024-07) and the Scientific Research Launch Project for new employees of the Second Xiangya Hospital of Central South University (grant number: QH20230256 and QH20230268).

Data availability

TCGA cohort: The datasets analyzed during the current study are available in The Cancer Genome Atlas (TCGA) repository (http://cancergenome.nih.gov/). Gene expression, DNA methylation (Infinium HumanMethylation450 BeadChip), and related clinical data for clear‑cell renal cell carcinoma (ccRCC) were obtained from TCGA and processed using the ChAMP R package. The clinicopathological characteristics of the patients are summarized in Table S1. An overview of the study workflow is presented in Figure S1. CPTAC cohort and GEO datasets: The datasets generated and analyzed during the current study are available in the following repositories: gene expression and methylation data of 100 RCC samples from the CPTAC repository (https://proteomics.cancer.gov/data-portal); methylation datasets GSE70303 and GSE105260 are available in the GEO repository (https://www.ncbi.nlm.nih.gov/geo/) under accession numbers GSE70303 and GSE105260, respectively. The processed data used in this study are provided in Supplementary Tables S2, S3, S4, and S5. SYSUCC cohort: For validation of cg16983159 methylation in RCC, a total of 98 samples including 14 adjacent normal tissues and 84 tumor tissues were collected from Sun Yat-sen University Cancer Center (SYSUCC). The patients underwent surgery from 2009 to 2015 at SYSUCC, and clinical follow-up information was collected for analysis. The basic information of all the datasets included in our study is provided in Table S6.

Declarations

Competing interests

The authors declare no competing interests.

Ethics statement

Public data was obtained from the TCGA and CPTAC were used. Clinical specimens were obtained from the Tumor Bio-bank of Sun Yat-sen University Cancer Center. The study protocol for the SYSUCC cohort was approved by the Institutional Research Ethics Committee of Sun Yat-sen University Cancer Center (B2020-310-01). All methods were conducted in accordance with relevant guidelines and regulations.

Footnotes

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Contributor Information

Qian Long, Email: dr_longqian@csu.edu.cn.

Xianling Liu, Email: liuxianling@csu.edu.cn.

References

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplementary Material 1 (343.5KB, xlsx)
Supplementary Material 2 (1.1MB, docx)

Data Availability Statement

TCGA cohort: The datasets analyzed during the current study are available in The Cancer Genome Atlas (TCGA) repository (http://cancergenome.nih.gov/). Gene expression, DNA methylation (Infinium HumanMethylation450 BeadChip), and related clinical data for clear‑cell renal cell carcinoma (ccRCC) were obtained from TCGA and processed using the ChAMP R package. The clinicopathological characteristics of the patients are summarized in Table S1. An overview of the study workflow is presented in Figure S1. CPTAC cohort and GEO datasets: The datasets generated and analyzed during the current study are available in the following repositories: gene expression and methylation data of 100 RCC samples from the CPTAC repository (https://proteomics.cancer.gov/data-portal); methylation datasets GSE70303 and GSE105260 are available in the GEO repository (https://www.ncbi.nlm.nih.gov/geo/) under accession numbers GSE70303 and GSE105260, respectively. The processed data used in this study are provided in Supplementary Tables S2, S3, S4, and S5. SYSUCC cohort: For validation of cg16983159 methylation in RCC, a total of 98 samples including 14 adjacent normal tissues and 84 tumor tissues were collected from Sun Yat-sen University Cancer Center (SYSUCC). The patients underwent surgery from 2009 to 2015 at SYSUCC, and clinical follow-up information was collected for analysis. The basic information of all the datasets included in our study is provided in Table S6.

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