Subgroup-specific predictive biomarkers in peripheral blood lymphocyte subsets for immune checkpoint inhibitor response in advanced esophageal squamous cell carcinoma: a prospective study

Abstract

Background

Immune checkpoint inhibitors (ICIs) significantly improve the survival of patients with advanced esophageal squamous cell carcinoma (ESCC). However, reliable biomarkers for predicting treatment response and prognosis have not yet been identified. This study investigated the relationship between specific lymphocytes in peripheral blood prior to treatment and the efficacy of ICIs, as well as prognosis, in patients with advanced ESCC.

Methods

Peripheral blood samples were prospectively collected from 97 patients with stage III–IVB ESCC before ICI treatment. Flow cytometry was used to detect and quantify peripheral blood lymphocyte subsets, including natural killer (NK) cells, B cells, T cells, CD4⁺ T cells, and CD8⁺ T cells, along with the CD4⁺/CD8⁺ T cells ratio. Treatment response was classified according to the Response Evaluation Criteria in Solid Tumors (RECIST, version 1.1). The patients with a complete response (CR) or partial response (PR) were allocated to the response group, while those with stable disease (SD) or progressive disease (PD) were allocated to the non-response group. The Chi-squared test and U test were used to assess the qualitative and quantitative differences between groups, and receiver operating characteristic (ROC) curves were used to evaluate the predictive efficacy of lymphocyte subpopulations for ICI response. Kaplan-Meier and log-rank tests were used to compare disease-free survival among the groups.

Results

Of the 97 patients, 42.3% (41/97) responded to ICI treatment. The baseline characteristics, including age, gender, and ICI drugs, were balanced between the response and non-response groups. The patients in the response group exhibited significantly higher baseline CD4⁺ T-cell counts (42.60 vs. 34.45, P=0.001) and CD4⁺/CD8⁺ ratios (2.02 vs. 1.54, P=0.01). The area under the curve (AUC) for the CD4⁺ T-cell count and the CD4⁺/CD8⁺ ratio were 0.701 and 0.648, respectively. Stratified analyses revealed variations in predictive efficacy based on staging and ICI drugs. In the stage III patients, higher AUC values were observed (0.883 for the CD4⁺ T-cell count and 0.833 for the CD4⁺/CD8⁺ ratio). Conversely, in the stage IV patients, a correlation was only observed between low B-cell counts and an improved response (6.40 vs. 8.65, P=0.02), with an AUC of only 0.510. Higher CD4⁺ T-cell counts were associated with improved responses in the patients receiving anti-programmed death-ligand 1 (PD-L1) therapy (40.00 vs. 30.30, P=0.03), with an AUC of 0.806. The results of the patients who received anti-programmed cell death protein 1 (PD-1) therapy were consistent with those of the overall population, but the corresponding AUC values were lower (0.693 and 0.638, respectively). The prognostic analysis revealed that lower NK cell counts before treatment were correlated with longer disease-free survival.

Conclusions

In patients with advanced ESCC, specific lymphocyte subsets in peripheral blood before treatment are closely associated with ICI efficacy and patient prognosis, and thus could potentially guide treatment decisions.

Highlight box.

Key findings

• The baseline peripheral blood high CD4⁺ T-cell count and CD4⁺/CD8⁺ ratio can predict responses to immune checkpoint inhibitor (ICI) therapy in advanced esophageal squamous cell carcinoma (ESCC).

• The predictive value of the baseline CD4⁺ T-cell count and CD4⁺/CD8⁺ ratio were higher in the patients with stage III disease or those receiving anti-programmed death-ligand 1 (PD-L1) inhibitor therapy.

• Peripheral blood CD4⁺ T-cell counts and CD4⁺/CD8⁺ ratios were not related to disease-free survival; however, lower natural killer (NK) cell counts were associated with longer disease-free survival.

What is known, and what is new?

• Baseline peripheral blood lymphocyte subsets can effectively predict the efficacy of immunotherapy for non-small cell lung cancer; however, their predictive value and prognostic significance in ICI treatment for advanced ESCC patients remain unclear.

• This study prospectively collected the peripheral blood of late-stage ESCC patients before ICI treatment, detected lymphocyte subsets, and found that: (I) the CD4⁺ T-cell count and CD4⁺/CD8⁺ ratio can be used to predict treatment efficacy, especially in phase III patients and those receiving PD-L1 inhibitors; and (II) there was a positive correlation between low NK cell counts and patient prognosis.

What is the implication, and what should change now?

• Peripheral blood CD4⁺ T-cell counts and CD4⁺/CD8⁺ ratios may help to identify patients with advanced ESCC, particularly those with stage III disease and those scheduled to receive PD-L1 inhibitor therapy, who are likely to benefit from ICI therapy and thus prevent ineffective treatment.

Introduction

The emergence of immune checkpoint inhibitors (ICIs) has significantly improved the prognosis of patients with advanced esophageal squamous cell carcinoma (ESCC) (1-6). Studies such as KEYNOTE-590 and CheckMate-648 have shown the efficacy and safety of combining programmed cell death protein 1 (PD-1) inhibitors with chemotherapy in the first-line treatment of advanced esophageal cancer. However, patients’ responses to ICI therapy vary significantly (7-11). Currently, no consensus has been reached as to the clinical use of predictive biomarkers, such as the programmed death-ligand 1 (PD-L1) expression level, tumor mutation burden, microsatellite instability, and the evaluation of tumor-infiltrating lymphocytes, all of which have limited predictive accuracy (7,12). Thus, more reliable predictive indicators urgently need to be identified to optimize patient selection for ICI therapy.

Due to their minimally invasive nature and real-time monitoring capacity, peripheral blood lymphocytes have attracted increasing attention as predictors of prognosis and therapeutic efficacy in patients with cancer (13-16). For instance, one study reported that a low percentage of peripheral blood B cells before treatment predicts poorer overall survival in patients with non-small cell lung cancer receiving ICI therapy (14). Additionally, the absolute number of natural killer (NK) cells and the CD4⁺/CD8⁺ ratio before treatment have been found to be associated with longer progression-free survival (PFS) and improved radiological responses in lung cancer patients treated with ICI combination therapy (16). However, the potential of peripheral blood immune cells and their subsets to predict therapeutic efficacy and prognosis in patients with advanced ESCC receiving immunotherapy requires further investigation.

Thus, this study aimed to prospectively evaluate the correlation between the percentage of peripheral blood lymphocyte subsets before immunotherapy in patients with advanced ESCC and the clinical efficacy and prognosis of ICI therapy. Stratified analyses based on disease stage and ICI therapeutic agents were also conducted to provide novel insights into their clinical application in specific patient populations. We present this article in accordance with the REMARK reporting checklist (available at https://jtd.amegroups.com/article/view/10.21037/jtd-2025-1843/rc).

Methods

Patient cohort

A total of 97 patients with advanced ESCC who received ICI therapy at Shandong Cancer Hospital from June 2020 to December 2022 were included in this prospective study. During the study period, patients who met the eligibility criteria were consecutively enrolled in the chronological order of their visits to avoid selective recruitment and to ensure a consecutive sample. Patients were included in the study if they had a histologically or pathologically confirmed diagnosis of advanced or recurrent ESCC, were aged between 18 and 75 years, had undergone at least two cycles of PD-1/L1 inhibitor therapy with evaluable efficacy, had an Eastern Cooperative Oncology Group performance status score of 0 or 1, and had tumors staged between III and IVB. Patients were excluded from the study if they had non-squamous cell carcinoma, were unable to tolerate immunotherapy, had severe autoimmune diseases, or had been diagnosed with any other malignancy within the past 5 years.

Of the 97 patients, 77 (79%) received ICI-based therapy as a first-line treatment, while 20 (21%) received it as a second- or later-line treatment. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the Ethical Review Committee of Shandong Cancer Hospital and Institute (No. SDTHEC2023011009). Written informed consent was obtained from each patient before their first treatment.

Blood collection and flow cytometry

Peripheral blood cells (2 mL) were collected from the patients before their first treatment with a PD-1 inhibitor. As previously described (17,18), the blood was treated with red blood cell lysis buffer to remove red blood cells, resulting in a suspension of white blood cells. The white blood cells were then stained with fluorescent-conjugated antibodies, which were obtained from Tongshengshidai (Z6410010, Z6410002; Beijing, China), Beckman (6607073; Brea, CA, USA), and BD (665343; Franklin Lakes, NJ, USA). Staining was performed in accordance with the manufacturers’ instructions. Post-staining, the proportions of various lymphocyte subsets, including CD3⁻CD56⁺ (NK cells), CD3⁻CD19⁺ (B cells), CD3⁺ (total T cells), CD3⁺CD4⁺ (helper T cells), and CD3⁺CD8⁺ (cytotoxic T cells), and the CD4⁺/CD8⁺ ratio, were determined by flow cytometry (Beckman Coulter dxFLEX, Brea, USA).

Clinical outcome assessment

For the patients receiving combination chemotherapy, the efficacy assessments were conducted after two treatment cycles. For those undergoing concurrent radiotherapy, the evaluations were performed one month after the completion of radiotherapy. In cases of monotherapy, the evaluations were conducted within the first four treatment cycles. Radiological response assessments were performed using the Response Evaluation Criteria in Solid Tumors (RECIST) version 1.1 (19). Additionally, since RECIST may underestimate the therapeutic effect of ICIs, the immune-related response criteria (irRC) were also used for evaluation (20,21). The best overall response during ICI treatment was recorded according to the following categories: complete response (CR), partial response (PR), stable disease (SD), and progressive disease (PD). The response group comprised the patients with CR or PR, while the non-response group comprised those with SD or PD. PFS was calculated from the start date of treatment to one of the following events, whichever occurred first: tumor progression as defined by RECIST or by irRC, the date of the last clinical examination, death from any cause before tumor progression, or the date of last contact (22,23). The median follow-up PFS time was 11.20 (range, 5.38–25.03) months.

Statistical analysis

The treatment efficacy of the patient cohort and subgroups was evaluated using the U test and Chi-squared test. Data are presented as median (lower quartile, upper quartile). A receiver operating characteristic (ROC) curve analysis was used to test the sensitivity of peripheral blood biomarkers in predicting immunotherapy efficacy. The optimal cut-off value was obtained using the pROC package in R language (version 4.1.2) (24). Multivariable logistic regression was performed to identify the independent factors associated with the treatment response. The median survival time was determined using the Kaplan-Meier method, and survival distributions were compared using the log-rank test. The analyses were two-sided, with a P value <0.05 indicating statistical significance. The data analysis was performed using R (version 4.1.0) software (https://www.r-project.org/), unless otherwise specified. The violin plots were created using GraphPad Prism Software 8.0 (San Diego, CA, USA).

Results

Patient characteristics

This study included a total of 97 patients diagnosed with advanced ESCC. Table 1 provides a summary of the patients’ basic clinical characteristics, including their gender, age, type of ICIs received, combination therapy methods, and clinical Tumor Node Metastasis (cTNM) staging. Following ICI treatment, 41 patients exhibited a clinical response, resulting in a response rate of 42.3%. The baseline characteristics were well-balanced between the patients who responded and those who did not.

Table 1. Baseline characteristics of 97 patients with advanced esophageal squamous cell carcinoma treated with immune checkpoint inhibitors.

Characteristics	Overall (n=97)	Non-response group (n=56)	Response group (n=41)	P
Gender				0.35
Male	86 (88.7)	48 (85.7)	38 (92.7)
Female	11 (11.3)	8 (14.3)	3 (7.3)
Age, years				0.41
>60	59 (60.8)	29 (51.8)	30 (73.2)
≤60	38 (39.2)	27 (48.2)	11 (26.8)
ICI				0.42
Anti-PD-L1	17 (17.5)	8 (14.3)	9 (22.0)
Anti-PD-1	80 (82.5)	48 (85.7)	32 (78.0)
Treatment				0.08
Single ICIs	9 (9.3)	9 (16.1)	0 (0.0)
With chemotherapy	60 (61.9)	33 (58.9)	27 (65.9)
With chemotherapy and targeted therapy	1 (1.0)	0 (0.0)	1 (2.4)
With radiochemotherapy	14 (14.4)	7 (12.5)	7 (17.1)
With radiochemotherapy and targeted therapy	9 (9.3)	5 (8.9)	4 (9.8)
With radiotherapy	2 (2.1)	1 (1.8)	1 (2.4)
With targeted therapy	2 (2.1)	1 (1.8)	1 (2.4)
cTNM				0.84
III	32 (33.0)	18 (32.1)	14 (34.1)
IVA	6 (6.2)	3 (5.4)	3 (7.3)
IVB	59 (60.8)	35 (62.5)	24 (58.5)
Treatment response				<0.001*
CR	0 (0.0)	0 (0.0)	0 (0.0)
PD	13 (13.4)	13 (23.2)	0 (0.0)
PR	41 (42.3)	0 (0.0)	41 (100.0)
SD	43 (44.3)	43 (76.8)	0 (0.0)

Data are presented as n (%). *, P<0.05. CR, complete response; cTNM, clinical Tumor Node Metastasis; ICI, immune checkpoint inhibitor; PD, progressive disease; PD-1, programmed cell death protein 1; PD-L1, programmed death-ligand 1; PR, partial response; SD, stable disease.

Correlations between lymphocyte subsets and the efficacy of ICIs

The study results revealed that a higher pre-treatment CD4⁺ T-cell count and elevated CD4⁺/CD8⁺ ratio were associated with improved immunotherapy efficacy [response vs. non-response: CD4⁺ T-cell count, median 42.60 (Q1, Q3: 35.70, 45.60) vs. median 34.45 (Q1, Q3: 25.55, 40.15), P=0.001; CD4⁺/CD8⁺ ratio: 2.02 (1.53, 2.74) vs. 1.54 (0.92, 2.06), P=0.01] as shown in Figure 1A,1B. However, in the overall analysis, no correlation was found between the other lymphocyte subsets (including the NK cells, B cells, total T cells, and CD8⁺ T cells) and immunotherapy efficacy (Table S1). Further, the ROC curve analysis demonstrated that the baseline CD4⁺ T-cell count and a high CD4⁺/CD8⁺ ratio could be used to predict immunotherapy outcomes, with area under the curve (AUC) values of 0.701 and 0.648, respectively (Figure 1C,1D). The multivariate logistic regression analysis incorporating gender, age, ICI treatment, and cTNM revealed that a high baseline peripheral blood CD4⁺ T-cell count [odds ratio (OR) =7.463, 95% confidence interval (CI): 2.857–21.277, P<0.001] and an elevated CD4⁺/CD8⁺ ratio (OR =6.494, 95% CI: 2.232–21.277, P=0.001) were independently associated with the objective response rate (Table S2).

Figure 1.

Correlations of the lymphocyte subsets with immune checkpoint inhibitor efficacy. (A,B) Relationship between the baseline CD4⁺ T-cell count, CD4⁺/CD8⁺ ratio, and immunotherapy response in 97 patients with esophageal squamous cell carcinoma. (C,D) The ROC curves of the CD4⁺ T-cell count and the CD4⁺/CD8⁺ ratio in overall efficacy prediction. AUC, area under the curve; ROC, receiver operating characteristic.

Correlations between clinical stage and lymphocyte subsets

Subgroup analyses were conducted on different clinical stages of ESCC, stages III and IV, to investigate the relationship between the lymphocyte subsets and treatment outcomes. In the patients with stage III ESCC, results consistent with those of the overall patient population were observed; that is, a higher CD4⁺ T-cell count and a higher CD4⁺/CD8⁺ ratios were associated with improved treatment responses [CD4⁺ T-cell count: 39.20 (35.00, 45.45) vs. 31.60 (24.90, 37.70), P=0.007; CD4⁺/CD8⁺ ratio: 2.05 (1.68, 2.57) vs. 1.21 (0.85, 1.60), P=0.02] (Figure 2A,2B and Table S3). However, in the patients with stage IV ESCC, no correlation was found between the aforementioned lymphocyte subset ratios and treatment outcomes. Instead, a lower B-cell count was associated with an improved response to ICIs [6.40 (3.90, 9.05) vs. 8.65 (6.20, 13.32), P=0.02] (Figure 2C and Table S3). The ROC curve analysis revealed that for the stage III ESCC patients, the AUC values for the baseline CD4⁺ T-cell count and the CD4⁺/CD8⁺ ratio were 0.883 and 0.833 (Figure 2D,2E). Conversely, the AUC value for the pre-treatment B-cell count in the stage IV ESCC patients was 0.510 (Figure 2F).

Figure 2.

Correlations between the lymphocyte subsets and the efficacy of immune checkpoint inhibitors in the cTNM subgroups. (A,B) The relationship between the baseline CD4⁺ T-cell count, CD4⁺/CD8⁺ ratio, and immunotherapy response in patients with stage III esophageal squamous cell carcinoma. (C) Relationship between the pre-treatment B-cell count and therapeutic efficacy response in stage IV patients. (D,E) ROC curve of the CD4⁺ T-cell count and CD4⁺/CD8⁺ ratio for predicting treatment efficacy in stage III patients. (F) ROC curve of the B-cell count for predicting treatment efficacy in stage IV patients. AUC, area under the curve; cTNM, clinical Tumor Node Metastasis; ROC, receiver operating characteristic.

Relationship between lymphocytes and treatment efficacy in the anti-PD-1/PD-L1 subgroup

We further examined the relationship between the pre-treatment lymphocyte subpopulations and treatment responses in the ICI drug subgroups. Among the patients, 17.5% (17/97) received anti-PD-L1 therapy, while 82.5% (80/97) received anti-PD-1 therapy. In the patients undergoing anti-PD-L1 therapy, treatment efficacy was significantly associated with a higher baseline CD4⁺ T-cell count [40.00 (39.00, 42.60) vs. 30.30 (27.30, 34.33), P=0.03] (Figure 3A). However, no significant relationship was observed between treatment efficacy and the levels of NK cells, B cells, CD8⁺ T cells, or the CD4⁺/CD8⁺ ratio (Table S4). For the patients receiving anti-PD-1 therapy, the findings were consistent with those for the overall patient cohort. Specifically, an elevated CD4⁺ T-cell count and a higher CD4⁺/CD8⁺ ratio were associated with an improved treatment response [CD4⁺ T-cell count: 43.50 (35.35, 47.90) vs. 35.40 (25.55, 41.45), P=0.004; CD4⁺/CD8⁺ ratio: 2.14 (1.49, 2.89) vs. 1.58 (1.00, 2.14), P=0.04] (Figure 3B,3C). The other lymphocyte subpopulations did not exhibit any significant correlations with treatment efficacy (Table S4). The ROC curve analysis demonstrated that in the patients treated with anti-PD-L1, the AUC value for the CD4⁺ T-cell count was 0.806 (Figure 3D). Further, in the ESCC patients receiving anti-PD-1 treatment, the AUC values of the CD4⁺ T-cell count and the CD4⁺/CD8⁺ ratio were 0.693 and 0.638, respectively (Figure 3E,3F).

Figure 3.

Relationship between the lymphocyte subsets and immune checkpoint inhibitor efficacy in the anti-PD-L1 and anti-PD-1 subgroups. (A) Relationship between the pre-treatment CD4⁺ T-cell count and treatment response in patients receiving anti-PD-L1 therapy. (B,C) Relationship between the pre-treatment CD4⁺ T-cell count, CD4⁺/CD8⁺ ratio, and treatment efficacy in patients receiving anti-PD-1 therapy. (D) ROC curve of the baseline CD4⁺ T-cell count in patients receiving anti-PD-L1 therapy. (E,F) ROC curves of the baseline CD4⁺ T-cell count and CD4⁺/CD8⁺ ratio in patients receiving anti-PD-1 therapy. AUC, area under the curve; PD-1, programmed cell death protein 1; PD-L1, programmed death-ligand 1; ROC, receiver operating characteristic.

Baseline lymphocyte subsets and treatment efficacy in ICI combined therapy subgroups

Among the 61 patients who received ICI with chemotherapy, treatment response showed no significant association with the baseline NK cells, B cells, CD4⁺ T cells, CD8⁺ T cells, or CD4⁺/CD8⁺ ratio (Table S5). In the 25 patients who received ICI with radiotherapy, a higher baseline CD4⁺ T-cell count was associated with an improved treatment response [39.65 (38.17, 43.08) vs. 34.20 (28.40, 35.60), P=0.01], while no significant correlations were observed with the other lymphocyte subsets (Table S5). The ROC curve analysis revealed an AUC of 0.674 (Figure S1).

Lower peripheral blood NK cells before ICI treatment is positively associated with longer PFS

The prognostic significance of various lymphocyte subsets, as determined by peripheral blood lymphocyte analysis, was evaluated in the advanced ESCC patients receiving ICI treatment. The Kaplan-Meier survival curves revealed that the patients with lower levels of peripheral blood NK cells before treatment had significantly prolonged PFS (Figure 4A), while B cells, T cells, CD4⁺ T cells, CD8⁺ T cells, and the CD4⁺/CD8⁺ ratio were not significantly associated with PFS (Figure 4B-4F).

Figure 4.

Kaplan-Meier survival curves of peripheral blood lymphocytes. (A) NK cells. (B) B cells. (C) T cells. (D) CD4⁺ T cells. (E) CD8⁺ T cells. (F) CD4⁺/CD8⁺ ratio. NK, natural killer; PFS, progression-free survival.

Discussion

This study explored the relationship between peripheral blood lymphocyte subsets before ICI therapy and the treatment efficacy and prognosis of patients with advanced ESCC. We found that a high CD4⁺ T-cell count and a high CD4⁺/CD8⁺ ratio were associated with improved immunotherapy outcomes, and thus could serve as biomarkers for patient selection.

Xu et al. reported that the CD4⁺/CD8⁺ ratio was significantly associated with the efficacy of combination therapy based on PD-1 inhibitors in advanced ESCC patients (25). Similarly, another study reported that a high CD4⁺ T-cell count and a high CD4⁺/CD8⁺ ratio in baseline peripheral blood lymphocytes were associated with improved ICI efficacy and prognosis in advanced non-small cell lung cancer (26). We observed similar results in advanced ESCC. The predictive value of the CD4⁺ T-cell count and the CD4⁺/CD8⁺ ratio was particularly significant in the stage III ESCC patients. This suggests that these indicators may have greater sensitivity and specificity in earlier clinical stages of the disease, enabling the more effective identification of the patient groups likely to benefit from ICI therapy. This observation may be related to the relative integrity of the immune system in the early stages of the disease, which becomes significantly suppressed by the tumor in later stages (27,28). Collectively, these findings suggest that an elevated pre-treatment CD4⁺ T-cell count and a higher CD4⁺/CD8⁺ ratio in peripheral blood may serve as promising immune biomarkers for predicting which patients are likely to benefit from ICI therapy across various cancer types.

Beyond the total CD4⁺ T cells, specific functional subsets of CD4⁺ T cells may play a more critical role. For instance, naive CD4⁺ T cells (typically identified by markers such as CD45RA⁺) are considered crucial for maintaining T-cell repertoire diversity and long-term immune memory. One study suggested that a high density of CD4⁺ naive T cells at the invasive margin may be associated with a more favorable prognosis in ESCC (29). Future research should investigate the dynamic changes and prognostic significance of different CD4⁺ T-cell subsets (e.g., naive T cells, central memory T cells, and effector memory T cells) in ESCC patients undergoing immunotherapy. This will help to more precisely identify the specific immune cell types driving treatment efficacy.

Notably, our study found that lower levels of NK cells were associated with prolonged disease-free survival. Previous studies have reported inconsistent results. For example, Choi et al. found that a higher absolute number of NK cells before treatment was associated with longer PFS in lung cancer patients receiving ICI combination therapy (30). The inconsistencies in the study results may be related to the different activation states of NK cells (31), which could affect their effectiveness in modulating immune responses during cancer treatment. PD-1/PD-L1 inhibitors kill tumor cells expressing human leukocyte antigen 1 (HLA-1) by increasing T-cell activity. However, HLA-1 negative tumor cells can escape immune therapy via a “self-missing” mechanism, which prevents T-cell-mediated killing, but enables NK cell-mediated recognition and elimination (32). In mouse models, NK cells expressing PD-1 have been identified as the primary responders to HLA-1 negative tumors (33), while exhausted NK cells have been shown to be poor responders to immunotherapy (34,35). Future research needs to be conducted to explore the levels of NK cells with upregulated ICIs, such as PD-1, T-cell immunoglobulin and mucin domain-containing protein 3, and lymphocyte activation gene-3, in the baseline peripheral blood of ESCC patients to more accurately assess their prognostic value.

Previous studies have reported associations between peripheral blood lymphocyte subsets and immunotherapy outcomes in ESCC; however, most of these studies were retrospective and did not adequately account for differences in disease stage and ICI drug types (36-38). Conversely, this prospective study systematically evaluated multiple lymphocyte subsets in 97 patients with advanced ESCC, and found that the CD4⁺ T-cell count and CD4⁺/CD8⁺ ratio better predicted treatment efficacy in the stage III patients and those receiving anti-PD-L1 therapy, while B cells were more predictive in the stage IV patients, reflecting the heterogeneity of immune responses. Further, we emphasized the predictive value of baseline lymphocyte profiles for immunotherapy response and PFS, which distinguishes our work from previous studies that have primarily focused on post-treatment immune changes. Additionally, we observed that lower NK cell levels were associated with longer PFS, suggesting a complex immune regulatory mechanism. These differentiated findings offer new perspectives for personalized immunotherapy and the development of multi-parameter biomarkers.

Despite the novel insights of this study on the correlation between peripheral blood lymphocyte subsets and the efficacy and prognosis of ICI therapy in patients with advanced ESCC, several limitations need to be noted. First, the sample size of this study, which comprised only 97 patients, was relatively small, which might limit the generalizability and statistical power of the results. A smaller sample size might have led to statistical insignificance in certain subgroup analyses; thus, larger-scale studies need to be conducted to validate these findings. Second, this study was designed as a single-center study, which might have introduced selection bias. Patient populations from different centers may yield different results due to varying baseline characteristics or treatment protocols; thus, multi-center studies need to be conducted to enhance the generalizability of the results. Third, the absence of overall survival data, a more robust endpoint for assessing long-term therapeutic benefit, limited our ability to evaluate the ultimate survival effect associated with the identified lymphocyte subsets. Fourth, while we analyzed the relationship between several lymphocyte subsets and the ICI treatment response, we did not explore other potential immune-related biomarkers or mechanisms in depth. Additionally, the potential association between lymphocyte subpopulations and immune-related adverse events (irAEs) was not investigated, as detailed toxicity data—particularly regarding the specific grading, timing, and management of irAEs—were not systematically collected. Additionally, further investigation is needed into the dynamic changes in lymphocyte subsets and their effect on treatment response. Finally, as this was an observational study, causality cannot be established. While certain lymphocyte subsets associated with treatment response were identified, prospective interventional studies need to be conducted to verify their validity as markers for treatment selection. These limitations suggest that future research should consider larger multi-center designs and integrate other biomarkers or genomic data to further explore the role of peripheral blood immune cells in cancer immunotherapy.

Conclusions

The results of this study indicate that the CD4⁺ T-cell count and CD4⁺/CD8⁺ ratio in peripheral blood before treatment may serve as potential biomarkers for predicting the response to ICI therapy, providing an important basis for further stratified treatment.

Supplementary

The article’s supplementary files as

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the Ethical Review Committee of Shandong Cancer Hospital and Institute (No. SDTHEC2023011009). Written Informed consent was obtained from each participant.

Data Sharing Statement

Available at https://jtd.amegroups.com/article/view/10.21037/jtd-2025-1843/dss

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DOI: 10.21037/jtd-2025-1843