Higher frequency of circulating regulatory T cells is associated with poor outcomes in patients with colorectal cancer.

Introduction
Colorectal cancer (CRC) is one of the most prevalent malignancies globally, exhibiting consistently high incidence and mortality rates among gastrointestinal cancers, and posing a significant threat to public health. According to recent global cancer statistics [1], there are over 1.9 million new cases of CRC annually, with projections indicating a rise to more than 3 million new cases and 1.6 million deaths by 2040. These trends underscore the importance of early diagnosis, effective therapeutic strategies, and accurate prognostic evaluation of CRC in both clinical practice and fundamental research.
The dynamic balance of the immune system plays a pivotal role in tumor progression, metastasis, and treatment response during the development of colorectal cancer [2]. Regulatory T cells (Tregs), which exert immunosuppressive functions by inhibiting effector T-cell activation and proliferation, have been linked to the prognosis of pancreatic cancer [3], prostate cancer [4], and other malignancies. In the context of CRC, tumor-infiltrating Tregs are often associated with an immunosuppressive tumor microenvironment and adverse clinical outcomes [5]. Follicular helper T cells (Tfhs) serve as central regulators of humoral immunity, facilitating B cell activation, proliferation, differentiation, and antibody class switching [6]. Conversely, follicular regulatory T cells (Tfrs) possess both immunosuppressive properties and follicular homing capacity, enabling them to suppress Tfh function, modulate B cell activity, and participate in humoral immune regulation [7]. Notably, an imbalance in the Tfh/Tfr ratio has been implicated in the pathogenesis of autoimmune diseases and is emerging as a potential factor in cancer immunology, with studies in other cancer types (e.g., hepatocellular carcinoma and non-small cell lung cancer [8, 9]) suggesting that a skewed ratio may influence tumor progression.
Peripheral blood circulating T-cell subsets, including circulating regulatory T cells (cTregs), circulating follicular helper T cells (cTfhs), and circulating follicular regulatory T cells (cTfrs), are easily measurable via flow cytometry, a standardized and widely available technique. These circulating immune cell levels have been identified as candidate biomarkers in several other cancer types. In non-small cell lung cancer, elevated cTregs and imbalanced cTfh/cTfr ratio are associated with poor prognosis [9, 10]. In thyroid cancer, higher circulating Tregs are linked to more aggressive disease [11]. Compared to tissue-based biomarkers, which require invasive biopsies and may not fully reflect systemic immune status, peripheral blood biomarkers offer the advantages of being minimally invasive, allowing for serial monitoring, and potentially providing a more accessible and reproducible measure for clinical use. However, no consensus has been reached regarding their levels, interrelationships, or associations with clinicopathological features or survival outcomes in patients with CRC. Although elevated levels of cTreg and cTfh cells have been reported in patients with CRC [12, 13], and cTregs are associated with disease progression [12], a lack of comprehensive survival data means the roles of cTreg subsets, cTfhs, and cTfrs, as well as the clinical significance of the cTfh/cTfr ratio, remain incompletely defined.
In this study, we aimed to comprehensively analyze the levels of cTregs and their subsets, cTfhs, cTfrs, and the cTfh/cTfr ratio in patients with CRC, and evaluate their correlation with clinicopathological parameters and survival outcomes. Our findings are expected to provide further insights​ into the immunobiology of CRC and may contribute to​ the development of​ prognostic biomarkers.

Materials and methods

Study population
Patients with histopathologically confirmed CRC, including all stages (I–IV), who were treated at the Affiliated Dongyang Hospital of Wenzhou Medical University between January 2021 and September 2022 were enrolled. The exclusion criteria included concomitant infectious diseases, other systemic malignancies, or autoimmune disorders. Peripheral blood samples were collected from all participants within 2 weeks prior to any surgical or therapeutic intervention. For the healthy control (HC) group, 91 sex- and age-matched volunteers were recruited from the hospital’s Health Examination Center. The study protocol was approved by the Medical Ethics Committee of the Affiliated Dongyang Hospital of Wenzhou Medical University (Approval No. 2022-YX-158), and written informed consent was obtained from all participants.

Flow cytometry
Multicolor immunofluorescence combined with multiparametric flow cytometry was used to identify the phenotypes of Tregs, resting Tregs (rTregs), activated Tregs (aTregs), Tfhs, and Tfrs. The antibodies used were as follows: CD45RA-FITC (clone ALB11; Beckman Coulter), CD25-PE (clone B1.49.9; Beckman Coulter), CD127-PC7 (clone R34.34; Beckman Coulter), CCR4-APC (clone L291H4; BioLegend), CD4-AA750 (clone 13B8.2; Beckman Coulter), and CXCR5-BV421 (clone J252D4; BioLegend), and CD45-KO (clone J.33; Beckman Coulter).
The phenotypic characteristics of the cells were as follows: Tregs, CD4+CD25+CD127low; aTregs, CD4+CD25+CD127lowCD45RA−; rTregs, CD4+CD25+CD127lowCD45RA+; Tfhs, CD4+CD45RA−CXCR5+CD25−CD127+; and Tfrs, CD4+CD45RA−CXCR5+CD25+CD127low. The gating strategy is illustrated in Online Resource 1.
Fresh whole blood was incubated with the surface marker antibodies at room temperature for 15 min in the dark. Subsequently, 2 mL OptiLyse B (Beckman Coulter) was added and incubated for an additional 15-min to ensure complete erythrocyte lysis. After lysis, 2 mL of phosphate buffered saline (PBS) was added to the tube, followed by centrifugation at 300 ×g for 5 min. The supernatant was carefully removed, and the cell pellet was resuspended in 250 µL of PBS for flow cytometry analysis. Immunophenotyping of Tregs, rTregs, aTregs, Tfh, and Tfr was performed using a 10-color flow cytometer (Navios, Beckman Coulter). Data acquisition and analysis were conducted using the Kaluza Analysis Software (v2.1, Beckman Coulter).

Follow-up
Patients were regularly followed up through in-person clinic visits or telephone interviews at intervals of approximately 3–6 months, as per standard clinical practice, or more frequently if clinically indicated. The primary endpoint of the follow-up study was overall survival (OS), defined as the time from CRC diagnosis to death from any cause or the last follow-up. During each contact, survival status was confirmed, and date of death (if applicable) was recorded. For patients lost to follow-up, the date of last known contact was used for censoring. The final follow-up date for database lock was April 30, 2025. The median follow-up time for the entire cohort was 35 months, calculated using the reverse Kaplan–Meier method.

Statistical analysis
Statistical analyses and visualizations were performed using SPSS version 26.0 (IBM, Chicago, USA) and R version 4.4.1 (R Foundation for Statistical Computing, Vienna, Austria). Continuous variables are presented as mean ± standard deviation (SD) or median (interquartile range [IQR]) based on their distribution. Between-group differences were assessed using a two-tailed Student’s t-test or the Wilcoxon rank-sum test, as appropriate. Categorical variables were compared using the Pearson χ² test or Fisher’s exact test.
Univariable and multivariable Cox proportional hazards models were employed to identify significant prognostic factors for OS. For variables confirmed as significant prognostic factors in multivariate analysis, receiver operating characteristic (ROC) curve analysis was used to determine the optimal cutoff values for stratification. Survival curves were generated using the Kaplan–Meier method, and between-group differences were compared using the log-rank test. All tests were two-sided, and a P-value < 0.05 was considered statistically significant.

Results
A total of 120 patients with pathologically confirmed CRC and 91 HCs were enrolled in this study. As shown in Table 1, there were no significant differences in the sex or age distribution between the CRC and HC groups.

After a median follow-up of 35 months for patients with CRC, 22 deaths were recorded, with an overall mortality rate of 18.3%. Further comparative analysis revealed that non-survivors had a significantly higher age (60.8 ± 10.9 years vs. 68.8 ± 13.4 years, P = 0.015) and proportion of TNM stage III-IV (advanced stage) than survivors (survivors: 42.9% (42/98); non-survivors: 86.4% (19/22), P = 0.001).

Comparison of cTreg subsets, cTfh, cTfr levels and cTfh/cTfr ratio between patients with CRC and HCs
Among cTreg subsets, the percentage of cTreg cells was significantly higher in patients with CRC than in HCs (7.43% [6.53–8.75] vs. 6.33% [5.53–7.07], P < 0.001; Fig. 1A). However, no significant differences were observed in the percentages of rTregs and aTregs between the two groups (Fig. 1B–C). Additionally, patients with CRC exhibited significantly higher percentages of Tfr cells (2.39% [1.96–2.98] vs. 2.20% [1.78–2.69], P = 0.019; Fig. 1D) and cTfh cells (15.8% [12.8–19.1] vs. 13.8% [10.1–16.6], P < 0.001; Fig. 1E) than HCs. By contrast, the cTfh/cTfr ratio did not differ significantly between groups (6.54% [5.44–7.61] vs. 6.37% [4.62–7.66], P = 0.263; Fig. 1F).

Comparison of cTreg subsets, cTfh, cTfr Levels and cTfh/cTfr ratio between patients with early- and advanced-stage CRC
Based on TNM staging, 59 patients were classified as having early stage (TNM I–II) CRC, and 61 as having advanced-stage (TNM III–IV) CRC. Advanced-stage patients exhibited significantly higher percentages of cTreg cells than early-stage patients (7.68% [6.76–9.42] vs. 7.10% [6.09–8.18], P = 0.006; Fig. 2A). However, no significant differences in the levels of rTregs, aTregs, cTfh, cTfr, or the cTfh/cTfr ratio were observed between the early- and advanced-stage groups (Fig. 2B–F).

Association of cTreg subsets, cTfh and cTfr levels, and the cTfh/cTfr ratio with prognosis in patients with CRC
Univariate and multivariate Cox regression analyses identified older age (hazard ratio (HR) = 1.06, 95% confidence interval (CI): 1.02–1.11; P = 0.003), advanced TNM stage (III–IV) (HR = 5.36, 95% CI: 1.55–18.52; P = 0.008), and a higher cTreg frequency (HR = 1.23, 95% CI: 1.03–1.47; P = 0.026) as significant factors associated with poor prognosis in CRC (Table 2).

ROC curve analysis determined the optimal prognostic cut-off value for cTreg frequency to be 8.295%, with an area under the curve (AUC) of 0.717 (95% CI: 0.596–0.838; Online Resource 2). Based on this cut-off, the patients were stratified into low cTreg (n = 79) and high cTreg (n = 41) groups. Kaplan–Meier analysis revealed that patients with higher cTreg levels had a significantly shorter OS (median OS: 32 vs. 37 months; P < 0.001) (Fig. 3).

Discussion
Recently, the role of circulating immune cells in antitumor immune responses has garnered increasing research attention [14–17]. These cells not only serve as key mediators of immune surveillance but also dynamically reflect the interactions between the tumor and the immune system. In this study, we systematically analyzed the levels of cTreg subsets, cTfh and cTfr, in the peripheral blood of patients with CRC and investigated their associations with clinicopathological features and prognosis. Our results showed a significantly higher proportion of cTregs, Tfh, and Tfr cells in patients with CRC than in HCs. Notably, cTreg levels were elevated in patients with advanced-stage CRC and were identified as a significant prognostic factor for OS in multivariate Cox regression analysis.
Treg cells are pivotal suppressors mediating tumor immune escape, primarily through the secretion of immunosuppressive cytokines such as IL-10 and TGF-β [18, 19], or via immune checkpoint molecules including CTLA-4 and PD-1, which directly inhibit the activation and proliferation of effector T cells [20, 21]. Collectively, these mechanisms foster an immunosuppressive microenvironment that is conducive to tumor growth. Consistent with previous reports [12, 22], we observed a significant increase in cTreg frequency in patients with CRC, underscoring the link between CRC progression and systemic immunosuppression. In contrast, the proportions of the rTreg and aTreg subsets remained unchanged, suggesting that the elevation in cTregs may reflect systemic upregulation rather than clonal expansion of specific subpopulations. This phenomenon may be driven by tumor-derived chemokines, such as CCL22 and CCL17, which recruit cTregs to the tumor site [23–25]. However, the exact mechanism requires further functional validation, for example, through in vitro migration assays, in vivo functional studies in animal models, and detailed characterization of the immunosuppressive phenotype of patient-derived cTregs.
In addition, we found that the proportions of cTfh and cTfr in the peripheral blood of patients with CRC were significantly higher than those in HCs; however, there was no significant difference in the cTfh/cTfr ratio between the two groups. As central regulators of humoral immunity, cTfh cells facilitate B-cell differentiation into plasma cells and antibody production via IL-21 secretion [26]. This increase in CRC may represent an adaptive immune response to tumor antigens. Conversely, cTfr cells maintain immune homeostasis by suppressing cTfh activity and preventing excessive humoral activation [27]. The concurrent increase in cTfr may represent a compensatory mechanism to preserve the immune balance, ultimately stabilizing the cTfh/cTfr ratio. Consequently, the stability of the cTfh/cTfr ratio, in stark contrast to the significantly elevated cTreg frequency, might indicate that the dominant immune dysregulation in the patients with CRC that we studied stems from the cellular immune arm rather than the humoral arm. This interpretation is further supported by the lack of prognostic value for the cTfh/cTfr ratio in both our group comparisons and survival analysis, whereas cTreg frequency consistently demonstrated clinical significance.
One of the key findings of this study was that an increase in cTregs was associated with poor prognosis in patients with CRC. The core mechanism underlying this association may involve the potent immunosuppressive effects of Tregs. High cTreg activity dampens effector T-cell–mediated tumor clearance, facilitating disease progression, recurrence, or metastasis, thereby shortening survival [28]. These findings highlight the potential of targeting cTregs as a novel immunotherapeutic strategy for CRC treatment. Currently, relevant strategies have entered the clinical trial stage, and include clearing Tregs with anti-CTLA-4 antibodies and inhibiting cTreg proliferation with IL-2 receptor antagonists, and preliminary exploratory results have been obtained for CRC treatment [29, 30].
Several limitations of this study should be considered when interpreting the results. First, the single-center design and modest sample size (120 patients with 22 death events) limited the statistical power of the Cox models, yielding unstable hazard ratios and precluding subgroup analyses. The cut‑off value of cTreg was derived and tested in the same cohort, potentially overstating its prognostic performance. Hence, the threshold (8.295%) and associated metrics are exploratory and await external validation. Second, although all disease stages were included, pooling them in a unified survival analysis may obscure stage-specific tumor–immune biology and treatment effects. Third, the single baseline immune measurement, without longitudinal or paired tissue data, restricts insight into dynamic changes or local microenvironmental interactions. Fourth, our models could not adjust for several established prognostic variables, including detailed tumor location, microsatellite instability/mismatch repair status, and crucially, the type and sequence of systemic therapies received, which themselves can influence immune cell levels and survival, leaving substantial potential for residual confounding. Furthermore, the use of all-cause mortality without excluding early postoperative deaths may introduce bias from non-cancer-related events. Finally, although the number of patients lost to follow-up was limited, their exclusion may slightly affect the completeness of survival data. Future studies with larger, prospectively stratified cohorts, integrated multi-omics profiling, and longitudinal sampling are needed to validate these findings. Further incorporation of spatial transcriptomics or multiplex immunohistochemistry of tumor tissues, alongside longitudinal immune profiling, will be crucial for elucidating the local tumor-immune landscape and the dynamic role of circulating immune subsets in CRC progression.
In conclusion, we confirmed that the levels of cTregs, cTfh, and cTfr were significantly increased in the peripheral blood of patients with CRC. In particular, cTregs were closely associated with advanced tumor stage and poor prognosis, suggesting their potential as prognostic biomarkers. Future prospective studies integrating multi‑omics and longitudinal sampling are warranted to validate these findings.

Supplementary Information
Below is the link to the electronic supplementary material.