Prognostic significance of alterations in peripheral cellular and humoral immune biomarkers during radiochemotherapy in head and neck cancer patients

Introduction

Head and neck cancer (HNC) is the seventh most common malignancy worldwide (1). Concurrent chemoradiotherapy (CCRT) with or without induction chemotherapy (ICT) for nasopharyngeal carcinoma and inoperable locally advanced head and neck squamous cell carcinoma is currently the standard of care. Adjuvant radiotherapy (RT) with or without concurrent chemotherapy (CCT) is also used for operated patients presented with high risk of local recurrence and distant metastasis (2). In recent years, immunotherapy has made evolutionary progress in HNC. Immune checkpoint inhibitors (ICIs) have been approved as second-line treatment, and ICIs plus chemotherapy now become first-line choice for recurrent and metastatic HNCs (3).

However, efforts to improve the clinical outcomes in locally advanced HNC with immunotherapy have not been successful so far. JAVELIN head & neck 100 study which explored the anti-programmed death ligand 1 (PD-L1) avelumab as concurrent and maintenance treatment with radiochemotherapy did not observe improved progression-free survival (PFS) and overall survival (OS) (4,5). GORTEC 2015-01 study which explored the anti-programmed death receptor 1 (PD-1) pembrolizumab combined with RT versus cetuximab concomitantly with RT did not reveal survival benefits from pembrolizumab (6). KEYNOTE-412 study that explored pembrolizumab combined with CCRT versus radiochemotherapy alone failed to achieve superior outcome with pembrolizumab (7). Although the underlying mechanisms remain incompletely understood, it is speculated that the potential detrimental effect of radiochemotherapy in the immune system might contribute to the failure of persistent immune activation.

For patients with head and neck squamous cell carcinoma, a large area of cervical lymphatic drainage area receives therapeutic and prophylactic radiation that greatly inhibits the quantity and function of immune cells, which might be one of the leading causes of the failure of RT combined with immunotherapy. Therefore, in patients with inoperable recurrent HNCs, local RT of tumor and avoiding irradiation of lymph node drainage area might protect the immune function to the greatest extent. An emerging study showed that re-irradiation with conventional fractionated intensity-modulated radiation therapy (IMRT) combined with anti-PD-L1 nivolumab therapy for loco-regionally recurrent or second primary HNC could improve patients’ prognosis, with one-year PFS rate up to 57.8%, and one-year OS rate being 81.7% (8).

Earlier studies shed light on the impact of RT on peripheral lymphocyte subpopulations. As early as 1985, Gray et al. and Wolf et al. noticed that RT resulted in significant and prolonged suppression in total lymphocytes, T cells, helper T cells, suppressor T cells, and a decreased ratio of helper T cell/cytotoxic T cell in HNC patients (9,10). Importantly, head and neck irradiation induced-lymphocytopenia could last as long as five years and is correlated to disease recurrence (11). Recently, it was demonstrated that conventionally fractionated RT in HNC patients induced an increase in both effector T cells and immune-suppressive cells, such as regulatory T cells, PD-1 positive T cells and myeloid-derived suppressor cells, suggesting that RT might create a disadvantageous environment for immunotherapy (12). However, the widespread application of new RT technologies such as IMRT and image-guided RT has led to increased dose deposition to tumor and better spare of adjacent organs at risk. The regulation of peripheral blood cells, lymphocyte subpopulations, complements and immunoglobulins by intensity-modulated RT, ICT and CCT has not been fully studied.

In this study, we investigated the alterations of peripheral immune biomarkers, with particular attention on blood cells, lymphocyte subpopulations, immunoglobulins and complements during the course of RT in HNC patients. We also determined the impacts of ICT and CCT on these biomarkers and their association with patients’ prognosis. We present this article in accordance with the STROBE reporting checklist (available at https://tcr.amegroups.com/article/view/10.21037/tcr-24-1510/rc).

Methods

Patient cohort

Patients with non-metastatic HNCs consecutively treated by conventional IMRT with or without induction or CCT in Zhongnan Hospital of Wuhan University from January 2019 to September 2019 were enrolled in this study. The inclusion criteria were: (I) patients of 18–85 years old; (II) histologically confirmed nasopharyngeal carcinoma or head and neck squamous cell carcinoma; (III) performance status 0–2; (IV) adequate hematological and organ functions; (V) completed prescribed RT doses. The exclusion criteria were: (I) other coexisting malignancies; (II) autoimmune status or autoimmune disease; (III) immunosuppressive status or immunosuppressive disease; (IV) use of corticosteroids or other immunosuppressive treatment; (V) use of immune modulatory treatment such as ICIs and immune-related cytokines; (VI) pregnancy or lactation status. The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013). This study was approved by the ethics committee of the Zhongnan Hospital of Wuhan University (No. 2019130) and informed consent was taken from all individual participants.

RT

Radiotherapy was delivered to all patients according to institutional protocols. Conventionally fractionated IMRT with 68–70 Gy to gross tumor volumes, 60–66 Gy to high-risk cervical lymphatic draining areas, and 54 Gy to low-risk lymphatic draining areas was given using the simultaneous integrated boost technology in 30–31 fractions.

Chemotherapy

ICT

ICT included TP/TPF regimen (docetaxel 75 mg/m² on day 1 plus cisplatin or nedaplatin 75 mg/m² on day 1 with or without 5-FU 750 mg/m² from day 1 to day 5; every three weeks). Other regimens included GP regimen (gemcitabine 1 g/m² on day 1 and day 8 plus cisplatin or nedaplatin 75 mg/m² on day 1; every three weeks) according to patients’ disease, age, performance status and comorbidities.

CCT

CCT included cisplatin (tri-weekly 80 mg/m² or weekly fixed dose of 50 mg), nedaplatin (tri-weekly 80 mg/m² or weekly fixed dose of 50 mg), lobaplatin (tri-weekly fixed dose of 50 mg), weekly nimotuzumab (fixed dose of 200 mg) according to patients’ age, performance status and comorbidities.

Hematological examination

Peripheral blood cells, lymphocyte subpopulations, complements and immunoglobulins were detected before, at the middle (at the end of the third week of RT) and at the end of RT. Fasting whole blood from every patient was collected in an ethylenediaminetetraacetic acid (EDTA) anticoagulant-treated tube and analyzed within 30 minutes of collection. Peripheral blood cells were analyzed by Beckman Coulter DxH 800/AU5800 automated blood analyzer and related reagents (Beckman, CA, USA). Peripheral lymphocyte absolute counts and lymphocyte percentages were obtained by flow cytometry (BD) according to the manufacturer’s instructions. And anti-human CD45, anti-human CD3, anti-human CD56, anti-human CD19, fluorescein isothiocyanate (FITC) anti-human perforin, etc. were purchased from eBioscience (San Diego, CA, USA). The serum samples for immunoglobulins and complement concentrations were frozen the same day and were kept at −70 ℃ until they were analyzed. Serum concentrations of immunoglobulin A (IgA), immunoglobulin E (IgE), immunoglobulin G (IgG), immunoglobulin M (IgM), complement 3 (C3) and complement 4 (C4) were determined by turbidimetry using anti-human IgA, IgE, IgG, IgM, C3 and C4 antibodies (Behringwerke, Germany).

Patient follow-up

Patients were followed up once every three months within the first two years after RT, once every six months from two to five years and once every year thereafter. The last follow-up time was June 30, 2024. OS was defined as the duration from initial diagnosis until death from any cause or last follow-up.

Statistical analysis

R (MathSoft, 4.0.3) was used to analyze the changes of peripheral cells before, at the middle and at the end of RT, analyze the impacts of ICT and CCT during RT, and plot corresponding figures. Chi-squared test and Fisher’s exact test were used to analyze categorical variables. Mann-Whitney test (two skewed distributed groups) was used for continuous variables (with Bonferroni correction for pairwise comparisons among multiple groups). The impact of RT on cell counts at different time points was evaluated by the generalized linear model (GLM). GLM analysis was used to determine the impacts of RT, ICT and CCT with IBM SPSS Statistics (IBM, version 26.0). For items with large value fluctuations such as B cells, CD4⁺ T cells, CD8⁺ T cells, natural killer (NK) cells and IgE, we took logarithm 2 for them when using GLM analysis. Kaplan-Meier survival analysis was used to test the survival difference between different groups and a log-rank test was adopted to examine the statistical difference.

Results

Patient characteristics

From January 2019 to September 2019, a total of 126 patients of Zhongnan Hospital of Wuhan University of non-metastatic HNCs [nasopharyngeal carcinoma (n=47, 37.3%), head and neck squamous cell carcinoma (n=79, 62.7%] consecutively treated by conventional IMRT with or without induction or CCT were included in this study. The majority of patients were male (n=86, 68.3%). The median age was 54 (range, 24–82) years old. Nearly half of the patients (n=56, 44.4%) received CCT, and more than one-third of patients (n=44, 34.9%) received ICT. More than half of the patients (n=81, 64.3%) were with stage III–IVa diseases (based on the American Joint Committee on Cancer staging manual, 7^th edition) (13) (Table 1). One hundred and twenty-three patients had prognostic information, with 1 patient missing lymphocyte information before RT and 12 patients missing lymphocyte information after irradiation. Three patients missed immunoglobulin and complement information before RT, and 12 patients lacked immunoglobulin and complement information after irradiation. In addition, four patients lost their blood routine information after RT.

Changes in parameters of peripheral blood cells

Compared with the blood cell counts before and at the middle of RT, the absolute numbers of white blood cells, basophils and total lymphocytes significantly decreased at the end of RT. Moreover, platelets, basophils and total lymphocytes significantly decreased at the middle and end of RT compared with those before RT. Conversely, neutrophils increased at the middle of RT compared with that before RT. There were no significant changes of red blood cells, hemoglobin, eosinophils and monocytes during RT (Figure 1).

Figure 1 The varieties of blood cells before, during and after radiotherapy. *, P<0.05; ***, P<0.001. WBC, white blood cell; RBC, red blood cell; PLT, platelet; HGB, hemoglobin; LYM, lymphocytes; MO, monocyte; NEUT, neutrophils; ESO, eosinophils; BASO, basophils; Pre-RT, pre-radiation; Mid-RT, mid-radiation; End-RT, end of radiotherapy.

Patients treated with ICT had lower platelets than those without ICT before and during RT (Figure 2). And patients with CCT had lower levels of white blood cells, red blood cells, platelets, hemoglobin, total lymphocytes compared with patients without CCT during and after RT. Eosinophils and basophils declined in CCT patients from the beginning to the end of RT. And neutrophils decreased after RT in patients with CCT (Figure 3).

Figure 2 The changes of blood cells with and without ICT during radiotherapy. *, P<0.05. ICT, induction chemotherapy; WBC, white blood cell; RBC, red blood cell; PLT, platelet; HGB, hemoglobin; LYM, lymphocytes; MO, monocyte; NEUT, neutrophils; ESO, eosinophils; BASO, basophils; Pre-RT, pre-radiation; Mid-RT, mid-radiation; End-RT, end of radiotherapy.

Figure 3 The differences of blood cells with and without CCT during radiotherapy. **, P<0.01; ***, P<0.001. CCT, concurrent chemotherapy; WBC, white blood cell; RBC, red blood cell; PLT, platelet; HGB, hemoglobin; LYM, lymphocytes; MO, monocyte; NEUT, neutrophils; ESO, eosinophils; BASO, basophils; Pre-RT, pre-radiation; Mid-RT, mid-radiation; End-RT, end of radiotherapy.

Changes in lymphocyte subpopulations

Comparing the cell counts of lymphocyte subpopulations in pre-RT versus mid-RT, pre-RT versus post-RT, and mid-RT versus post-RT, we found that the number of B cells, CD4⁺ and CD8⁺ T cells, and NK cells significantly shrank. Accordingly, the proportions of B cells and CD4⁺ T cells decreased at the middle and end of RT. The ratio of helper T cell to suppressor T cell (Th/Ts) ratios also decreased at the middle and end of RT. Conversely, the proportion of NK cells increased at the middle and end of RT. While the percentage of CD8⁺ T cells had no significant difference during RT (Figure 4).

Figure 4 The varieties of lymphocyte subsets before, during and after radiotherapy. *, P<0.05; **, P<0.01; ***, P<0.001. NK, natural killer; Th/Ts, the ratio of helper T cell to suppressor T cell; Pre-RT, pre-radiation; Mid-RT, mid-radiation; End-RT, end of radiotherapy.

ICT and CCT caused different impacts on the different components of lymphocyte subpopulations. Specifically, patients treated with ICT had lower B cells than those without ICT before RT (Figure 5). As for patients receiving CCT, they had more profound reductions in B cells, CD3⁺ T cells, CD4⁺ T cells, CD8⁺ T cells, and NK cells than those without CCT at the middle and end of RT. However, Th/Ts ratios and the percentages of B cells, CD4⁺ T cells, CD8⁺ T cells, and NK cells had no statistical differences in patients with or without CCT (Figure 6). The numerical fluctuations of lymphocyte subpopulations during IMRT are detailed in Table 2.

Figure 5 The changes of lymphocyte subsets with and without ICT during radiotherapy. *, P<0.05. ICT, induction chemotherapy; NK, natural killer; Th/Ts, the ratio of helper T cell to suppressor T cell; Pre-RT, pre-radiation; Mid-RT, mid-radiation; End-RT, end of radiotherapy.

Figure 6 The differences of lymphocyte subsets with and without CCT during radiotherapy. *, P<0.05; **, P<0.01; ***, P<0.001. CCT, induction chemotherapy; NK, natural killer; Th/Ts, the ratio of helper T cell to suppressor T cell; Pre-RT, pre-radiation; Mid-RT, mid-radiation; End-RT, end of radiotherapy.

The impact of RT on cell counts at different time points was evaluated by the GLM, and the results showed mid-term or post-RT could cause decreases in total lymphocytes, B cells, CD4⁺ and CD8⁺ T cells, NK cells, Th/Ts ratios (P≤0.001), and the percentages of B cells and CD4⁺ T cells (P<0.01). While the percentage of CD8⁺ T cells showed no statistical difference during RT (P>0.05). On the contrary, the percentage of NK cells was increased at the middle and end of RT (P<0.001). In our study, B cells [odds ratio (OR): 0.043, P<0.001] were most severely affected by RT, followed by CD4⁺ T cells (OR: 0.113, P<0.001), CD8⁺ T cells (OR: 0.174, P<0.001) and NK cells (OR: 0.266, P<0.001), which might indicate that B cells were more radiosensitive than CD3⁺ T cells, while NK cells were most radioresistant (Table 3).

ICT mainly caused a decrease in Th/Ts ratios (OR: 0.849, 95% confidence interval (CI): 0.738–0.977, P=0.02). And patients with CCT had higher risks of lymphocyte (OR: 0.861, 95% CI: 0.764–0.970, P=0.01), B cell (OR: 0.614, 95% CI: 0.436–0.863, P=0.005), CD4⁺ T cell (OR: 0.676, 95% CI: 0.529–0.864, P=0.002), CD8⁺ T cell (OR: 0.659, 95% CI: 0.517–0.840, P=0.001) and NK cell (OR: 0.749, 95% CI: 0.590–0.951, P=0.01) decrease than those without CCT. However, the percentages of B cells, CD4⁺ T cells, CD8⁺ T cells, and NK cells were not significantly influenced by ICT and CCT (Table 4).

Changes in immunoglobulins and complements

In terms of immunoglobulins and complements, the level of C4 was higher at end of RT than that before and at the middle of RT (Figure 7). Similarly, patients who received ICT or CCT had higher C4 level than those without ICT or CCT at the middle or end of RT. By contrast, IgA level was lower in patients with ICT before RT and IgG level decreased in patients with CCT from the beginning to the end of RT (Figures 8,9). While C3 was not significantly affected by RT, ICT and CCT. Besides, there was also no significant difference in the levels of IgE and IgM in radiochemotherapy.

Figure 7 The varieties of complements and immunoglobulins before, during and after radiotherapy. **, P<0.01; ***, P<0.001. C3, complement 3; C4, complement 4; IgA, immunoglobulin A; IgE, immunoglobulin E; IgG, immunoglobulin G; IgM, immunoglobulin M; Pre-RT, pre-radiation; Mid-RT, mid-radiation; End-RT, end of radiotherapy.

Figure 8 The differences of complements and immunoglobulins with and without ICT during radiotherapy. *, P<0.05; **, P<0.01. ICT, induction chemotherapy; C3, complement 3; C4, complement 4; IgA, immunoglobulin A; IgE, immunoglobulin E; IgG, immunoglobulin G; IgM, immunoglobulin M; Pre-RT, pre-radiation; Mid-RT, mid-radiation; End-RT, end of radiotherapy.

Figure 9 The differences of complements and immunoglobulins with and without CCT during radiotherapy. *, P<0.05; **, P<0.01. CCT, concurrent chemotherapy; C3, complement 3; C4, complement 4; IgA, immunoglobulin A; IgE, immunoglobulin E; IgG, immunoglobulin G; IgM, immunoglobulin M; Pre-RT, pre-radiation; Mid-RT, mid-radiation; End-RT, end of radiotherapy.

GLM analysis showed that C3 (OR: 1.055, 95% CI: 1.003–1.110, P=0.03) and C4 (OR: 1.051, 95% CI: 1.031–1.071, P<0.001) were more likely to increase after RT (Table 3). C4 (OR: 1.024, 95% CI: 1.007–1.041, P=0.006) also increased, while IgA (OR: 0.778, 95% CI: 0.671–0.902, P =0.001) and IgM levels (OR: 0.804, 95% CI: 0.703–0.919, P=0.001) decreased in patients with ICT. For patients with CCT, C3 (OR: 1.055, 95% CI: 1.012–1.100, P=0.01) and C4 (OR: 1.020, 95% CI: 1.003–1.036, P=0.01) were elevated, while IgG (OR: 0.271, 95% CI: 0.156–0.471, P<0.001) was declined compared with those without CCT (Table 4).

Changes in peripheral blood cells, lymphocytes, immunoglobulins and complements under different treatments

We further assessed the impacts of RT, ICT plus RT, CCRT, and ICT plus CCRT on peripheral blood cells, lymphocytes, immunoglobulins and complements, we detected that ICRT did not cause changes in peripheral blood cells, immunoglobulins and complements compared with RT alone. On the other hand, CCRT could lead to a decrease in the numbers of white blood cells, red blood cells, hemoglobin, platelets, and CD4⁺ T cells, but had no effect on other biomarkers. Moreover, compared to RT alone, ICT plus CCRT resulted the reduction in most of peripheral blood cells, immunoglobulins and complements, but had no effect on lymphocyte percentages (Figures S1-S3).

The prognostic characteristic of different levels of peripheral blood cells, complements and immunoglobulins

We further acquired 123 HNC patients with information of survival and peripheral blood cells, immunoglobulins, or complements before, during and after radiation. The 123 patients were classified as high- and low-lever groups based on the best cut off value of each item. We found that RT caused a decrease in B cells, leading to poor prognosis. Lower percentage of CD3⁺ T cell before and after RT was also associated with poor prognosis, while higher CD4⁺ T cells before RT and higher CD8⁺ T cells after RT showed good prognoses. On the contrary, higher Th/Ts ratios before and after RT were associated with poor prognosis. And an increase in NK cells and NK cell percentage before RT was associated with a worse prognosis. Moreover, changes of lymphocyte ratio of post-radiation to pre-radiation, such as CD8⁺ T cell percentage, NK cells, and Th/Ts, were also related to patient’s prognosis. In addition, higher levels of C3 and C4 before and after RT were also associated with a favorable prognosis. However, higher levels of immunoglobulins like IgA, IgE, IgG, and IgM before RT were with adverse prognosis. Higher white blood cells and neutrophil counts before radiation were positively relevant to a good outcome, yet the growing counts of these markers after RT led to a poor prognosis. Also, the increased monocyte ratio of post-radiation to pre-radiation was associated with poor prognosis in HNC patients (Figures 10-12).

Figure 10 The survival characteristics of each item of lymphocytes. post-/pre-treatment, the ratio of post-treatment value to pre-treatment value; NK, natural killer; Th/Ts, the ratio of helper T cell to suppressor T cell.

Figure 11 The survival characteristics of each item of immunoglobulins and complements. C3, complement 3; C4, complement 4; post-/pre-treatment, the ratio of post-treatment value to pre-treatment value; IgA, immunoglobulin A; IgE, immunoglobulin E; IgG, immunoglobulin G; IgM, immunoglobulin M.

Figure 12 The survival characteristics of each item of other peripheral blood cells. WBC, white blood cell; Neut, neutrophils; LYM, lymphocytes; Mo, monocyte; post-/pre-treatment, the ratio of post-treatment value to pre-treatment value.

Discussion

In this study, we demonstrated that RT in HNC patients caused a significant decrease in peripheral white blood cells, platelets, basophils, total lymphocytes, CD4⁺ T cells, CD8⁺ T cells, NK cells, B cells, Th/Ts ratios, and the percentages of CD4⁺ T cells and B cells. On the contrary, there was an increase in neutrophils, C4 level and the percentage of NK cells. The proportion of CD8⁺ T cells had no obvious change. The levels of immunoglobulins were not clearly impacted by RT. We also revealed that ICT caused reductions of platelets, B cells, IgA level, and led to increased level of C4. CCT suppressed most peripheral blood cells and lymphocytes. Furthermore, CCT resulted in lower IgG level but higher C4 level. These results indicated that there were profound alterations in peripheral blood cells, especially peripheral immune cells during RT combined with CCT.

HNCs are characterized by high immune infiltration, and increased infiltration of CD8⁺ T cells and CD56⁺ NK cells is associated with a better prognosis (14). As it is well known, CD8⁺ T cells and NK cells are the most important components of lymphocyte subpopulations in eliminating cancer cells, and play central roles in adaptive and innate antitumor immunity. Infiltration of these lymphocytes and other myeloid-derived cells constitute complex immune microenvironment in tumors (15). Furthermore, most of tumor-infiltrating immune cells derived from peripheral circulation. There are abundant immune cells in peripheral blood, and changes in the level of peripheral immune cells reflect the body’s response to malignant tumors, as well as the interaction between the host and the tumor after anti-tumor treatment.

The number of immune cell subpopulations in the peripheral blood of tumor patients varies compared to healthy individuals. Multiple studies have shown that the number of regulatory T cells in the peripheral blood of tumor patients is significantly higher than that of healthy individuals (16-20). A study on peripheral blood cellular immunity of breast cancer found that compared with healthy people, the function of peripheral blood immune cells such as dendritic cells and T cell subtypes in breast cancer patients changed, mainly manifested in the decreased secretion of various cytokines, and this trend was more obvious in the disease progression stage (21). The number and function of peripheral CD4⁺ and CD8⁺ T cells were negatively correlated with the number of circulating tumor cells (CTCs) which play an important role in tumor metastasis (22-24). Li et al. found that a decreased level of peripheral CD8⁺ T cells was associated with lymph node metastasis in patients with breast cancer (25). Moreover, several studies have shown that peripheral blood neutrophil/lymphocyte ratios were relevant to lymph node metastasis and associated with patients’ prognosis (26,27). Thus, screening for immune biomarkers with therapeutic and prognostic value in peripheral blood will greatly promote individualized treatment of tumor patients.

Since peripheral lymphocytes of different subsets play important roles in anti-tumor. In the current situations where no clear synergy between RT and immunotherapy in locally advanced HNC could be detected, it is urgent to explore the regulation of peripheral immune biomarkers by RT (28). Only by combining systemic immune modification and local tumor immune adaptation can we understand better the effect of radiochemotherapy on anti-tumor immunity. Accumulating studies showed that RT accompanied with or without chemotherapy could profoundly impact on peripheral lymphocyte subpopulations in a variety of cancers. As early as 1984, Job et al. reported that RT resulted in concomitant reduction of B lymphocytes, T lymphocytes and total lymphocytes in breast and uterus cancer patients (29). Bachtiary et al. confirmed that RT with or without CCT induced comparably significant and enduring decrease in total lymphocytes, Th cells and cytotoxic T cells in cervical cancer patients (30). RT in prostate cancer patients caused decrease in T cells, NK cells and B cells (31). The proportion of peripheral blood T lymphocytes was proved to be closely related to the efficacy of RT and chemotherapy and the prognosis of patients, and CD8⁺CD28⁺ T lymphocyte ratio was a significant independent predictor of PFS (32). RT in patients with esophageal cancer also caused decrease in lymphocytes and CD4/CD8 ratios, as well as a decline of the percentages of NK cells and B cells (33). In lung cancers, stereotactic body RT (SBRT) for early-stage non-small cell lung cancer induced significant reductions in CD4⁺ T cells, CD8⁺ T cells, B cells, and NK cells (34). A meta-analysis involving a variety of cancers showed that RT induced a significant reduction in CD4⁺ T cells, while CD8⁺ T cells showed an increase in a number of studies. However, in the subgroup analysis for HNCs in that meta-analysis, there was a decline of CD4⁺ and CD8⁺ T cells (35). On the other hand, Ts cells were more resistant to RT and recovered rapidly during RT, leading to a decrease in Th/Ts ratio, which potentially suppressed immunity (29). The diverse results seen in these studies may be explained by different cancer types, RT techniques and fractionations, irradiated sites, irradiation doses, use of surgery or CCT, and time of detection.

Like the above-mentioned studies on other cancers, RT of oral cavity cancers led to prolonged (one year after RT) reductions in most lymphocyte subpopulations like B cells, naïve and memory T cells, CD4⁺ and CD8⁺ T cells, while only NK cells recovered to pre-treatment level (36). Similar results were obtained for CD4⁺ T cells, CD8⁺ T cells, and NK cells in other HNCs, where a substantial decrease was noted following RT (37). Similarly, in our study, we observed significant reductions in the absolute number of peripheral CD4⁺ T cells, CD8⁺ T cells, B cells, NK cells, and the percentages of CD4⁺ T cells and B cells in HNC patients treated with RT.

Importantly, we found that alongside a general decrease of most kinds of lymphocytes, there was an increase in the percentage of NK cells but a decreased ratio of Th/Ts. However, another study suggested that adjuvant RT accompanied with adjuvant chemotherapy reduced peripheral CD4⁺ T cells in HNC patients while enduringly increased the proportion of regulatory T cells, which might contribute to immunosuppression (38). These results suggested that while the total number of lymphocytes declined during RT, differential radiosensitivity of lymphocyte subpopulations might shift the immune balance. Therefore, it is still necessary to identify determinant factors associated with enhanced or suppressed systemic immunity during RT in HNCs. Surgery, chemotherapy regimens, and even nutrition status might play certain roles in immunity.

To determine the roles of ICT and CCT in the regulation of lymphocyte subpopulations, we found that ICT mainly impacted on B cells and Th/Ts ratios, while CCT impacted significantly on lymphocytes of various subtypes including CD4⁺ T cells, CD8⁺ T cells, NK cells and B cells. CCT was a risk factor for reduced lymphocytes, CD4⁺ T cells, CD8⁺ T cells, B cells and NK cells. Previous extensive research has shown that ICT might have critical impact on lymphocyte populations in multiple cancers. In breast cancer, ICT resulted in a dramatic drop in B cells and NK cells (39). In lung cancer, ICT using paclitaxel, carboplatin and bevacizumab (PCB) induced a proliferation of peripheral blood CD8⁺ T cells more highly expressing the PD-1 and CTLA-4, which might provide a rationale for combining PCB with checkpoint inhibition in lung cancer (40). In follicular lymphoma (FL) patients, rituximab-chemotherapy-based regimen (R-CHOP) before RT caused a decrease of the percentages of peripheral T cells expressing the immune checkpoint molecules such as PD-1 and TIGIT. Moreover, the amount of peripheral CD4⁺ and CD8⁺ T cells expressing both HLA-DR and CD38 also decreased during treatment. These observations suggest that the profound alterations observed in T-cell subsets and blood T-cell phenotyping in FL patients could provide a certain clinical implication about the combination of chemotherapy with immunotherapy (41). In terms of CCT, Huang et al. observed that it increased the percentages of regulatory T cells, NK cells, and CD8⁺ T cells, while it declined the proportions of naïve T cell and CD4⁺ T cells in HNCs (42). Li et al. found that the proportions of CD4⁺ and PD-1⁺ T cells in peripheral blood mononuclear cells decreased after CCT, whereas inhibitory regulatory T cells increased and the Tc/Treg ratios decreased in cervical cancer, which were involved in the efficacy of ICIs (43). Given that chemotherapy delivered cytotoxic drug into circulation that can also get access into the bone marrow, it is not surprising that chemotherapy would have marked immune modulatory effect, especially when used concurrently or sequentially with RT.

Currently, it is still unclear how radiochemotherapy impacts on lymphocytes of various types. Emerging evidence pointed out that differential radiosensitivity of lymphocyte subpopulations might play critical roles. For example, in vitro and in vivo studies suggested B cells were more radiosensitive than T cells, while NK cells were most radioresistant (31,44,45). This was consistent with our observations. However, no significant difference in radiosensitivity was observed between helper T cells and cytotoxic T cells (45,46). Conversely, another study found that B cells were more resistant to RT than T cells in case of pelvic irradiation (47). CD95 might play a critical role in both spontaneous apoptosis of circulating CD8⁺ T cells and RT-induced T cell and NK cell depletion in HNCs (37,48). In addition, there was an increased expression of the pro-apoptotic protein BAX on CD4⁺ T cells, contributing to their radiosensitivity (38).

Few studies have focused on the modulation of humoral immune response by RT. However, it is becoming clear that humoral immunity also contributes to cancer development and cancer control (49). C3 and C4 and immunoglobulins like IgG play important roles in antitumor. When complement system is activated, membrane attack complex (MAC) is formed on the surface of tumor cells, which leads to imbalance of osmotic pressure inside and outside cells, finally resulting in cell dissolution. In addition, C3b and C4b directly combine with the surface of bacteria or other particulate matter and promote the phagocytosis by binding to corresponding complement receptors of phagocytes. As well known, IgG can kill cancer cells by opsonization and antibody-dependent cell-mediated cytotoxicity (ADCC). Thus, further exploring the changes of peripheral complements and immunoglobulins during RT is necessary.

In an effort to determine whether and how radiochemotherapy impacted on humoral immunity represented by peripheral complements and immunoglobulins, we found that C3 and C4 increased in RT, ICT or CCT, while immunoglobulins like IgA, IgM decreased in ICT and IgG decreased in CCT. Consistently, Huang et al. reported that both ICT and CCT induced reductions in the levels of IgA, IgG and IgM, while C3 or C4 was increased in HNCs (42). Yang et al. observed that high expression of cancer IgG was associated with poor prognosis and radiation resistance (50). Although currently we still do not fully know the significance and application of these results, we speculate that they might provide valuable information when designing monoclonal antibodies as anticancer treatments.

It was demonstrated that lymphocytopenia was a prominent negative prognostic factor in many cancers (51). For example, the percentages of CD3⁺ T cells before RT and the lymphocyte counts after RT were associated with patients’ survival in esophageal cancer (33). Pelvic RT for gynecological cancers induced marked reductions in total T cells, CD4⁺ cells, CD8⁺ T cells, and NK cells. Lymphocytopenia was significantly greater in patients who had no tumor regression in response to RT. This study proved that pelvic RT may lead to severe lymphocytopenia which could negatively impact the efficacy of RT (52). Kuss et al. found that head and neck squamous cell carcinoma (HNSCC) patients had significantly lower absolute numbers of peripheral CD4⁺ and CD8⁺ T cells than normal controls and patients with the lowest CD4⁺ T cell counts tended to have recurrent disease (53). Consistently, RT caused a decrease in B cells, leading to poor prognosis and the decrease in CD3⁺ T cell percentage before and after RT was associated with poor prognosis. Furthermore, the higher the CD4⁺ T cells before RT and higher CD8⁺ T cells after RT, the better the prognosis of the HNC patients.

There are several limitations in this study. Firstly, this is a retrospective observational study and there was inevitable selection bias of patients. Secondly, we only analyzed the existent laboratory data of patients. A more detailed investigation into the profiles of other subsets of lymphocytes such as PD-1 positive T cells, regulatory T cells, and memory T cells is not available and warrants further study. Thirdly, the optimal prognostic cutoff value of each item based on which we grouped still needs to be precisely set in clinical practice. Finally, prospective studies with larger sample sizes need to be further conducted, and the determination of the optimal peripheral blood cutoff value still needs to explore.

Conclusions

In conclusion, our results suggested that RT induced significant alterations in peripheral blood cells, lymphocyte subpopulations, immunoglobulins and complements in head and neck patients which in turn impacted the patient’s prognosis. ICT and CCT could also impact specific lymphocyte subpopulations, immunoglobulins and complements.

Acknowledgments

We would like to acknowledge all the participants for their participation and their contribution to this study. We would like to thank Lin-lin Bu for his assistance in English editing.

Footnote

Reporting Checklist: The authors have completed the STROBE reporting checklist. Available at https://tcr.amegroups.com/article/view/10.21037/tcr-24-1510/rc

Data Sharing Statement: Available at https://tcr.amegroups.com/article/view/10.21037/tcr-24-1510/dss

Peer Review File: Available at https://tcr.amegroups.com/article/view/10.21037/tcr-24-1510/prf

Funding: This study was supported by Health Commission of Hubei Province Scientific Research Project (No. WJ2023M068), Leading Discipline of Oncology Construction Project of Zhongnan Hospital of Wuhan University (No. XKJS202005), Youth Interdisciplinary Special Fund of Zhongnan Hospital of Wuhan University (No. ZNQNJC2022003), Translational Medicine and Interdisciplinary Research Joint Fund of Zhongnan Hospital of Wuhan University (No. ZNJC202322) and Knowledge Innovation Program of Wuhan-Shuguang Project (No. 2023020201020510).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tcr.amegroups.com/article/view/10.21037/tcr-24-1510/coif). The authors have no conflicts of interest to declare.

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 (as revised in 2013). This study was approved by the ethics committee of the Zhongnan Hospital of Wuhan University (No. 2019130) and informed consent was taken from all individual participants.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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