# Effect of glioblastoma and brain radiotherapy on T-lymphocyte subpopulations in rodents

Thao-Nguyen Pham, Julie Coupey, Florian Yger, Serge M. Candéias, Juliette

Thariat, Samuel Valable

► To cite this version:

Thao-Nguyen Pham, Julie Coupey, Florian Yger, Serge M. Candéias, Juliette Thariat, et al.. Effect of glioblastoma and brain radiotherapy on T-lymphocyte subpopulations in rodents. Radiotherapy & Oncology, 2025, 206, pp.110801. 10.1016/j.radonc.2025.110801. hal-05151385

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Submitted on 11 Aug 2025

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Original Article

# Effect of glioblastoma and brain radiotherapy on T-lymphocyte subpopulations in rodents

<figure><img src="image_3.png" /></figure>

Thao-Nguyen Pham<sup>a,b</sup>, Julie Coupey<sup>a</sup>, Florian Yger<sup>c</sup>, Serge M. Candéias<sup>d</sup>,
Juliette Thariat<sup>b,e,* ,1</sup>, Samuel Valable<sup>a,* ,1 ID</sup>

ARTICLE INFO

Keywords:

Radiation-induced lymphopenia

Glioblastoma

Brain radiotherapy

T lymphocytes

Proton therapy

A B S T R A C T

**Introduction:** Although lymphopenia is linked to immune suppression favoring tumor growth, the effect of different radiation types on specific T-lymphocyte subsets remains unclear. Among the T-lymphocyte sub-populations, CD8⁺-lymphocytes serve as key effectors in cancer immunity. This study aimed to examine the changes in T-lymphocyte subpopulations in both tumor-free and glioblastoma-bearing mice following brain-irradiation.

**Methods:** The study was divided into two main phases. First, C57BL/6 mice, with or without glioblastoma (GL261 cells), received hemispheric brain-irradiation or no-treatment. T-lymphocyte subpopulations were analyzed using flow cytometry at various timepoint. The effect of tumor size and brain-irradiation on these cells was assessed using correlation analysis. Next, C57BL/6 mice were subjected to different brain-irradiation conditions. Blood samples were collected during and post-irradiation to analyze T-lymphocyte subpopulations, and tree-based modeling was used to determine radiation parameters impact on naïve CD8⁺-lymphocyte levels.

**Results:** Glioblastoma reduced all T-lymphocyte subpopulations by day 15 post-inoculation. Radiotherapy decreased regulatory and effector CD4⁺-lymphocytes in both tumor-free and glioblastoma-bearing mice, but not naïve or memory CD4⁺-lymphocytes, in both tumor-free and glioblastoma-bearing mice. In tumor-free mice, radiotherapy had no effect on CD8⁺-lymphocytes, but reduced all CD8⁺-lymphocyte types in glioblastoma-bearing mice. Glioblastoma size negatively affected CD8⁺-lymphocytes. Brain-irradiation persistently reduced naïve and memory CD8⁺-lymphocytes, but effector and regulatory T-lymphocytes recovered. Exposure of lymph nodes to radiation worsened CD8⁺-lymphocyte reduction.

**Conclusion:** These findings confirm that the presence of glioblastoma and brain-irradiation affect T-lymphocyte subpopulations in mice. The inclusion of lymph nodes in the irradiated area led to a long-term decrease in naïve CD8⁺-lymphocytes. Further mechanistic studies are needed to understand the molecular basis of radiation impact on T-lymphocyte subpopulations.

Introduction

The association between tumor-infiltrating lymphocytes and cancer prognosis is well documented. However, the specific effects of different radiation modalities on circulating T-lymphocyte subpopulations have not been reported. Low circulating lymphocyte concentration is negatively associated with patient survival during cancer treatment [1,2].

External beam radiotherapy has been linked to various immunological effects, including radiation-induced lymphopenia (RIL) [3,4]. In the context of brain tumors for which radiotherapy is the standard treatment, radiotherapy causes lymphopenia even though the brain has minimal bone marrow, blood, and lymphatic involvement [5]. T-lymphocytes include several functional subpopulations with different phenotypes that may have different or opposite effects on tumor growth.

<footnote><sup>a</sup> Université de Caen Normandie, CNRS, Normandie Université, ISTCT UMR6030, GIP CYCERON, F-14000 Caen, France</footnote>

<footnote><sup>b</sup> Laboratoire de Physique Corpusculaire UMR6534 IN2P3/ENSICAEN, France - Normandie Université, France</footnote>

<footnote><sup>c</sup> Univ. Paris-Dauphine, PSL Research Univ./CNRS, LAMSADE, Paris, France</footnote>

<footnote><sup>d</sup> Univ. Grenoble Alpes, CEA, CNRS, IRIG-LCBM-UMR5249, 38054 Grenoble, France</footnote>

<footnote><sup>e</sup> Department of Radiation Oncology, Centre François Baclesse, Caen, Normandy, France</footnote>

<footnote>* Corresponding authors at: ISTCT UMR6030, Boulevard Henri Becquerel, GIP CYCERON, 14000, Caen, France.</footnote>

<footnote>E-mail addresses: jthariat@gmail.com (J. Thariat), samuel.valable@cnrs.fr (S. Valable).</footnote>

<footnote n="1">¹ Authors equally contributed.</footnote>
Upon activation, naïve T-lymphocytes with the CD4⁺ or CD8⁺ phenotype undergo further differentiation in peripheral tissues into effector CD4⁺ (T helper) and CD8⁺ (cytotoxic T) cells. Subsequently, after antigenic activation, effector lymphocytes either undergo apoptosis or enter the circulation as memory cells or recirculating effector cells [6]. The variations in T-lymphocyte subpopulations before and after radiotherapy could provide valuable insights into treatment response [7,8]. Recently, immunosuppressive regulatory T CD4⁺ cells and T CD4⁺ helper 17 cells were shown to be involved in inflammation in cancer [9]. Regulatory T-lymphocytes, known for their ability to suppress immune responses, have been suggested to contribute to the resistance of tumors to radiotherapy [10]. Among T-lymphocyte subpopulations, CD8⁺ T-lymphocytes serve as key effectors in cancer immunity, and the most effective cancer immunotherapies involve the effector function of CD8⁺ T-lymphocytes [11]. Naïve CD8⁺ T-lymphocytes are the original source of effector CD8⁺ T-lymphocytes (cytotoxic T-lymphocytes) upon activation, and suppression of naïve CD8⁺ T-lymphocyte activity reflects an exhausted or hyporesponsive state within CD8⁺ T-lymphocyte populations [12].

Glioblastoma (GBM) is the most common aggressive brain tumor [13]. The standard treatment for glioblastoma includes surgical resection followed by radiotherapy and chemotherapy with temozolomide [14]. Despite these intensive treatments, the prognosis remains poor, with a median survival time of approximately one year after diagnosis [15]. T-lymphocyte-based immunotherapy has not yet been successful in treating GBM [16]. This ineffectiveness may be due to the tumor's ability to suppress the immune system [17]. Additionally, treatments for GBM such as radiation therapy can weaken the immune system by causing radiation-induced lymphopenia, a condition in which the number of lymphocytes is reduced [4,18,19].

As secondary lymphoid organs, lymph nodes are sites of lymphocyte

storage and antigenic T-lymphocyte activation. We previously showed that lymph node exposure is a major determinant of radiotherapy-induced circulating T-lymphocyte lymphopenia after brain irradiation [4,20]. This lymphopenic effect was recovered by day 28 post irradiation [21]. The nature of the radiation beam is critical in the context of the RIL. Because of their penetrative power, X-ray doses not only affect the targeted brain tumor but also other organs on the beam path, including lymph nodes in the neck region [3,20], and lymph node irradiation contributes to RIL [4,23]. In contrast, proton radiotherapy is a promising alternative, as its ballistic reduces the volumes of irradiated normal tissues [22,24] and spares lymph nodes during brain exposure, thereby potentially mitigating RIL and other radiation effects [4].

With the increasing use of proton therapy in clinical settings, particularly for brain tumors, understanding the nuances of immune cell homeostasis responses and more especially of T lymphocyte subpopulations to various radiation modalities is crucial. Monitoring variations in T-lymphocyte subpopulations could offer valuable insights into the mechanisms underlying RIL [25]. The goal of this study was to investigate changes in the concentrations of T lymphocyte subpopulations, with a particular focus on naïve CD8⁺ T-lymphocytes following brain irradiation in tumor-free and glioblastoma-bearing rodents. Additionally, we applied proton beam therapy to reduce dose deposition to the cervical lymph nodes, aiming to determine the impact of lymph node radiation exposure on systemic T-lymphocyte levels.

## Materials and methods

### *Data*

### *Effects of X-ray brain irradiation in mice*

Data from preclinical cohorts of tumor-free or GL-261 glioma-

<figure><img src="image_4.png" /><figcaption>**Fig. 1.** Experimental design of T-lymphocyte subpopulation variations following brain irradiation in (A) glioblastoma and tumor-free mice; and (B) tumor-free mice under different radiation conditions.</figcaption></figure>
bearing C57BL/6 mice (Cohort 1–3, Fig. 1A) subjected to hemispheric brain irradiation (X-rays, 10 Gy in four 2.5 Gy fractions at a dose rate of 2 Gy/min in 2 consecutive days, thus 2 fractions per day) were used. The experimental protocol detailing tumor inoculation, mouse irradiation, blood collection, flow cytometry, and gating strategies has been previously described [26,27] (see **supplementary** for details regarding the animals and tumor volume quantification).

The concentrations of the blood T-lymphocyte subpopulations and their proportions were quantified using flow cytometry. Naïve T-CD4⁺ cells, effector T-CD4⁺ cells, memory T-CD4⁺ cells, naïve T-CD8⁺ cells, effector T-CD8⁺ cells, memory T-CD8⁺ cells, and regulatory T subpopulations were analyzed. T-lymphocyte levels were measured after radiation exposure on days 2 and 28. The markers used to identify different T-lymphocyte subpopulations are listed in Table S1.

### Effects of brain irradiation under different radiation conditions in tumor-free mice

X-ray or proton irradiation (2.5 Gy in 8 fractions) was delivered to the whole-brain or hemi-brain at a dose rate of 1–2 Gy/min (Cohort 4–5, Fig. 1B). For proton irradiation, the beam energy was set at 25 MeV to accurately target the brain, following a Gaussian distribution of 24.85 MeV with an energy spread of 127 keV. Proton irradiation was used as Spread-Out Bragg Peak (SOBP). Details of irradiation protocol was mentioned in the **supplementary**.

The experimental setup was identical for both X-ray and proton experiments. Each cohort comprised of 40 irradiated and 8 control mice. Blood samples were collected 12h after the fourth fraction (day 2, 10 Gy) and 25 days after treatment initiation (day 28). The concentration of T-lymphocyte subpopulations in the blood was quantified by flow cytometry, as described above. Our prior analysis indicated that the differences in radiation-induced changes in leukocyte subpopulations in the blood following brain irradiation were primarily due to the exposure of the cervical lymph node to radiation (which occurred with X-rays but not with protons) rather than the irradiated brain volume [4]. For the initial analysis, we merged all the data from the mice, regardless of the irradiated brain volume. The effects of these factors were analyzed using correlation and principal component analyses.

### T-lymphocyte subpopulation variations following brain irradiation in glioblastoma-bearing mice

Alterations in T-lymphocyte subpopulations after brain irradiation were assessed with respect to treatment-related factors using correlation analyses. Pairwise Spearman correlations among the 56 pairs of T-lymphocyte subpopulation concentrations across the T-lymphocyte subpopulations were calculated and illustrated in a correlation graph. Principal component analysis (PCA) was used to analyze the impact of glioblastoma volume and brain irradiation on T-lymphocyte subpopulations. Correlation analysis was performed to examine the relationship between glioblastoma volume and circulating naïve T-CD8⁺ T-lymphocyte concentration with or without brain irradiation. K-means clustering was subsequently used to categorize the mice into groups based on their glioblastoma volume and concentration of naïve CD8⁺ T-lymphocytes.

### T-lymphocyte subpopulation variations following brain irradiation under different radiation conditions in tumor-free mice

Alterations in the T-lymphocyte subpopulations after brain irradiation in relation to treatment-related factors were examined using correlation analysis and PCA.

### Assumptions

The uniform effect of X-ray and proton beams across all organs was considered. Based on our previous work [4], the differential effects of X-ray and proton beams in vivo could be attributed to the proton sparing of

the lymph nodes. The volume of blood exposed to radiation by X-ray or proton beams was considered similar, given the relatively small amount of blood in the arteries supplying the brain compared with the total cerebral blood volume [4].

### Treatment-related parameters

We identified the key parameters as treatment-related variables derived from radiation conditions and the aforementioned assumptions. These parameters included the proportion of brain volume irradiated (0 for control mice, 0.5 for hemispheric irradiation, and 1 for whole-brain irradiation), and the presence of mandibular and submandibular lymph nodes in the irradiation fields (0 for control or proton-irradiated mice and 1 for X-ray irradiation). The presence of mandibular and submandibular lymph nodes in the irradiated field following X-ray irradiation results from the vertical position of the beam delivered to the mouse brain, as previously explained [4].

### Effects of radiation condition on naïve CD8⁺ T-lymphocyte concentrations following brain irradiation

Random forest regression was performed to quantify the impact of radiation parameters, including lymph node exposure to radiation and irradiated brain volume on the circulating naïve T-CD8⁺ cell during or after brain irradiation. Then, decision tree regression was performed to determine the relationships between the radiation parameters and circulating naïve T-CD8⁺ T-lymphocyte concentration.

### Statistical analysis

Statistical analysis and modeling were performed using R version 4.1.2 with a significance level of 0.05 [28]. The cell concentration (cells/µL) was calculated from flow cytometry data using counting beads. Differences in cell concentration between treatment groups were analyzed using statistical *t*-test or a non-parametric Wilcoxon *t*-test, depending on data normality, which was assessed using the Shapiro-Wilk test.

The correlation map was processed using a *graph* package [29]. PCA was performed using the *FactoMineR* package (for analysis) and *factoextra* package (for data visualization) [30]. Correlations between parameters and relevant components were analyzed using one-way ANOVA. K-means clustering was performed using the *cluster* package version 2.1.2 [31]. Random forest regression was performed using the *caret* package version 6.0–94 [32]. Decision tree regression was performed using the *rpart* package version 4.1.19 [33].

## Results

Variations in T-lymphocyte subpopulation concentrations following hemibrain irradiation in glioblastoma-bearing and tumor-free mice are presented in Fig. 2A. In non-irradiated mice, no changes were observed in the T-lymphocyte population 9 days after glioblastoma implantation (average tumor volume was $6.36 \pm 2.48 \text{ mm}^3$) except an increase in naïve T CD4⁺ lymphocytes. In contrast a significant reduction occurred in all T-lymphocytes subpopulations (naïve, effector, memory CD4⁺ and CD8⁺, and Foxp3⁺CD4⁺T-lymphocytes) at day 15 after tumor implantation (at which the tumor volume was $123.51 \pm 78.80 \text{ mm}^3$, Fig. 2A).

Radiotherapy did not affect the concentrations of naïve and memory T CD4⁺ cells in either the tumor-free or glioblastoma-bearing mice (Fig. 2A). In contrast, radiotherapy resulted in significantly decreased concentrations of effector CD4⁺ and Foxp3⁺CD4⁺T-lymphocytes in both tumor-free and glioblastoma-bearing mice (Fig. 2A).

For CD8⁺ cells, the suppressive effect of radiotherapy on the concentrations of naïve, effector, and memory CD8⁺T-lymphocytes was not statistically significant in the tumor-free mice (Fig. 2A). However, in glioblastoma-bearing mice, radiotherapy resulted in reduced concentrations of these cells compared to those in control mice (Fig. 2A).
<figure><img src="image_5.png" /><figcaption>**Fig. 2.** Circulating T-lymphocyte concentration relative to that in control mice following brain irradiation in the context of glioblastoma. (A) T-lymphocyte sub-population concentration relative to that of control mice, stratified by the day after tumor implantation and brain irradiation. (B) Correlation network between T-lymphocyte subpopulation concentration, glioblastoma volume, and brain irradiation. The black dot represents the T-lymphocyte subpopulations and the white dot represents the tumor volume or X-ray irradiation. (C) Principal component analysis of T-lymphocyte subpopulation concentration, with glioblastoma volume and brain irradiation as additional variables.</figcaption></figure>

Correlation analysis revealed strong correlations between T-lymphocyte subpopulations, tumor volume, and radiation exposure (Fig. 2B). Glioblastoma volume is negatively correlated with all T-lymphocyte subpopulations, particularly naïve, effector, and memory CD8⁺ T-lymphocytes, whereas X-ray irradiation displayed a negative correlation across all T-lymphocyte subpopulations, particularly effector CD4⁺ T-lymphocytes and Foxp3⁺CD4⁺T-lymphocytes. PCA revealed that the first component had significant positive correlations with all T-lymphocyte subpopulations and was negatively correlated with both glioblastoma volume and X-ray irradiation (Fig. 2C, Table S2). There was no correlation between the glioblastoma volume and X-ray irradiation with the second component (Table S2).

Glioblastoma volume was negatively correlated with naïve and
memory T CD8⁺ cell proportions (out of the total T-lymphocyte

population) (Fig. S1). This decrease in the proportion of effector CD8⁺T-lymphocytes led to an increase in the ratio of Foxp3⁺CD4⁺T-lymphocytes to effector CD8⁺T-lymphocytes as the glioblastoma volume increased (Fig. 3). This increase was no longer visible after radiation. There was no significant correlation between X-rays and the T-lymphocyte subpopulation proportion (Fig. S1) and no significant change in the ratio of Foxp3⁺CD4⁺T-lymphocytes to effector CD4⁺T-lymphocytes as the glioblastoma volume increased (Fig. S2). Therefore, while glioblastoma affects CD8⁺T-lymphocytes and radiation therapy affects CD4⁺T-lymphocytes, radiation therapy in glioblastoma-bearing mice results in a composite effect without major changes in the effector T-lymphocyte to regulatory T-lymphocyte ratio.

A summary of the T-lymphocyte subpopulation variation during
brain irradiation in tumor-free mice is presented in Fig. 4A (for details,
<figure><img src="image_6.png" /><figcaption>Fig. 3. Ratio of Foxp3 + CD4 + T-lymphocytes to effector T CD8 + cells in glioblastoma-bearing mice and tumor-free mice following brain irradiation.</figcaption></figure>

see Fig. S3, Fig. S4). Two days after X-ray exposure, compared to control unirradiated mice, naïve and memory CD4⁺ T-lymphocyte concentrations were unchanged (>0.1). Effector CD4⁺ T-lymphocyte and regulatory T-lymphocyte concentrations were significantly lower (p = 0.03 and 0.04, respectively). Naïve CD8⁺ T-lymphocytes were not significantly reduced (p = 0.06), although more than 75 % of the mice exhibited lower concentrations than the control irradiated mice. The effector and memory CD8⁺ T-lymphocyte concentrations were significantly lower (p < 0.01). In contrast, proton irradiation did not significantly affect the concentration of the CD4⁺ subpopulations (p > 0.1). Only effector CD8⁺ T-lymphocytes were significantly reduced (p = 0.02). The naïve and memory CD8⁺ T-lymphocyte concentrations remained unchanged (p > 0.1). Analysis of the stratified data by irradiated brain volume showed no significant differences between the subgroups (Fig. S3). The use of either 1 Gy/min or 2 Gy/min yielded similar result (Fig. S8 and S9).

We then analyzed the interplay between the concentration changes for each T-lymphocyte subpopulation during irradiation (day 2) and radiation conditions (Fig. 4B.1). Correlation analysis revealed strong positive correlations among T-lymphocyte subpopulations. There was a negative correlation between the presence of lymph nodes in the irradiated area and the concentrations of all T-lymphocyte subpopulations, especially memory CD8⁺ T-lymphocytes. Irradiated brain volume and showed almost no correlation with variations in T-lymphocyte subpopulations (Fig. 4B.1).

The first three PCA components explained more than 10 % of the variance in the T-lymphocyte subpopulation concentrations (Fig. 4C.1). PCA highlighted a significant negative correlation between the presence of lymph nodes in the irradiated area and the first component, which was positively correlated with all T-lymphocyte subpopulations (Table S3). The correlation coefficient was > 0.5 for all cells except for effector CD8⁺ T-lymphocytes (R = 0.2). No significant correlation was found between irradiated brain volume or and the first three PCA components (Table S3).

Subsequently, we analyzed the concentration changes for each T-lymphocyte subpopulation on day 28 post-irradiation (Fig. 4A). X-ray exposure led to a significant increase in naïve CD4⁺ T-lymphocytes compared with that in the control group (p < 0.01). The effector CD4⁺ T-lymphocytes and Foxp3 + CD4 + T-lymphocytes recovered from their initial reduction on day 2 of irradiation. There were no significant concentration changes in memory T-lymphocytes (of both CD4⁺ and

CD8⁺) between the irradiated and control groups at day 28, but there was a significant difference in memory T-lymphocytes at day 28 compared to day 2 (p = 0.03, memory T CD4⁺ cells and p < 0.01, memory T CD8⁺ cells).

In proton-irradiated mice, no significant changes were noted in CD4⁺ subpopulations 28 days post-exposure when compared to those in the control or from day 2 (all p > 0.1). Compared to the controls, the naïve CD8⁺ T-lymphocyte concentration was greater (p < 0.01). The effector CD8⁺ T-lymphocyte reduction recovered after an initial decline (p < 0.01 compared to day 2). However, memory CD8⁺ T-lymphocytes remained unchanged.

We then analyzed the correlation between the change in the concentration of each T-lymphocyte subpopulation after irradiation (day 28) and the impact of radiation conditions on this change (Fig. 4B.2). Correlation analysis revealed a stronger negative correlation between the presence of lymph nodes in the irradiated area and the concentration of naïve and memory CD8⁺ T-lymphocytes than on day 2. Irradiated brain volume had almost no correlation with variation in T-lymphocyte subpopulations.

PCA focused on the first two components (Fig. 4C.2), which explained more than 10 % of the variance in the data. PCA revealed a negative correlation between the presence of lymph nodes in the irradiated area and the second component, strongly and positively correlated with naïve and memory CD8⁺ T-lymphocytes (R > 0.5, Table S4), and weakly negatively correlated with naïve CD4⁺ T-lymphocytes, effector CD4⁺ T-lymphocytes, and Foxp3 + CD4 + T-lymphocytes (R > −0.2, Table S4). No significant correlation emerged between irradiated brain volume, and the first two components (Table S4). Analysis of the stratified data by irradiated brain volume showed no significant differences between the subgroups (Fig. S4).

Lymph node exposure to irradiation led to an increase in the proportion of naïve CD4⁺ T-lymphocytes and a decrease in the proportion of the CD8⁺ T-lymphocyte subpopulation after irradiation on day 28 (Fig. S5). This was associated with a positive correlation between the ratio of Foxp3 + CD4 + T-lymphocytes to effector T CD8⁺ cells in the blood and the presence of lymph nodes in the irradiated area (Fig. S6).

Random forest regression analysis after brain irradiation using data from cohorts 4 and 5 (Fig. 1) showed that the presence of lymph nodes in the irradiated area was the most critical factor influencing changes in circulating naïve CD8⁺ T-lymphocyte concentrations. This effect was greater than that of either the irradiated brain volume (Fig. 5A.1). The
<figure><img src="image_7.png" /><figcaption>**Fig. 4.** Circulating T-lymphocyte concentrations following brain irradiation under different radiation conditions in tumor-free mice. (A) T-lymphocyte subpopulation concentration relative to that of control mice, stratified by the day after radiation initiation and beam type (X-rays or protons). (B) Correlation network between T-lymphocyte subpopulation concentrations and radiation conditions (lymph node exposure to radiation and irradiated brain volume) on days 2 (B.1) and 28 (B.2). Black dots represent the T-lymphocyte subpopulations, and white dots represent the radiation condition parameters. (C) Principal component analysis of T-lymphocyte subpopulation concentration, with radiation conditions (lymph node exposure to irradiation and irradiated brain volume) as additional variables on days 2 (C.1) and 28 (C.2).</figcaption></figure>

decision-tree model revealed that after X-ray exposure, where lymph nodes were included in the irradiation area, hemispheric irradiation resulted in a more significant reduction (38 %) in naïve CD8⁺ T-lymphocytes compared to whole-brain irradiation (11 %) (Fig. 5A.2). In contrast, in mice exposed to protons, where the lymph nodes were not irradiated, whole-brain irradiation led to an 11 % reduction in the naïve CD8⁺ T-lymphocyte concentration and hemispheric irradiation led to a 1.5-fold increase in the naïve CD8⁺ T-lymphocyte concentration compared to that in control mice (Fig. 5A.2).

At 28 days post-irradiation, random forest regression revealed that

naïve CD8⁺ T-lymphocyte concentrations, rather than the presence of lymph nodes in the irradiated area (Fig. 5B.1). In the decision tree analysis, the concentration of circulating naïve T-CD8⁺ cells in brain-irradiated mice were 4.5 times greater than that in the control mice. However, when lymph nodes were involved in the irradiated area, there was a 42 % reduction in naïve CD8⁺ T-lymphocyte concentration compared to that in the control mice (Fig. 5B.2).
C.1

<figure><img src="image_8.png" /></figure>

C.2

<figure><img src="image_9.png" /><figcaption>Fig. 4. (continued).</figcaption></figure>

<figure><img src="image_10.png" /></figure>

<figure><img src="image_11.png" /><figcaption>Fig. 5. Changes in the concentration of naïve T-CD8 + cells following brain irradiation using tree-based modeling. (A) Impact of radiation parameters on naïve T-CD8 + T-lymphocyte concentrations during brain irradiation on day 2; including (A.1) parameter importance according to the random forest and (A.2) decision tree models. (B) Impact of radiation parameters on naïve T-CD8 + lymphocyte concentrations after brain irradiation at day 28; including (B.1) parameter importance according to the random forest and (B.2) decision tree models. Legend: MSE: mean square error.</figcaption></figure>
<figure><img src="image_12.png" /></figure>

<figure><img src="image_13.png" /><figcaption>Fig. 5. (continued).</figcaption></figure>

**Discussion**

This study explored the effects of brain irradiation on circulating T-lymphocytes in the context of glioblastoma and compared the impact of various radiation conditions on brain irradiation in tumor-free mice.

Our results demonstrated that the concentrations of all T-lymphocyte subpopulations significantly decreased when glioblastoma volume increased. Glioblastomas are known for creating a highly immunosuppressive microenvironment that inhibits both the function and proliferation of T-lymphocytes. This suppression can be mediated by various mechanisms, such as the secretion of immunosuppressive cytokines or cell–cell contact-mediated inhibition [34]. Studies have reported that patients with glioblastoma experience both local and systemic immunosuppression characterized by reduced lymphocyte counts and impaired T-lymphocyte proliferation [35,36]. Specifically, blood concentrations of both CD4⁺ and CD8⁺ T-lymphocyte subpopulations are decreased in patients [37]. Cancer treatments, including radiotherapy, further contribute to the suppression of lymphocytes, as evidenced by RIL [1,6], which affect all lymphocyte subpopulations, including T-lymphocytes [4,38]. Adjusting the radiation parameters to mitigate the impact of radiotherapy on circulating T-lymphocytes may be important for improving treatment outcomes.

Our results showed that an increase in glioblastoma volume led to an increase in the ratio of Foxp3 + CD4 + T-lymphocytes to effector T CD8⁺ cells in the blood. Foxp3 + is highly expressed and frequently used as a marker for regulatory T cells [39]. Regulatory T cells (Tregs) play a role

in maintaining immune tolerance and preventing autoimmune responses by suppressing effector T-lymphocyte functions [40]. In cancer, especially glioblastoma, an increase in Tregs has been associated with a more suppressive immune environment, which can facilitate tumor growth and metastasis. Multiple studies have shown that elevated Treg fractions are present in peripheral blood CD4⁺ T-lymphocytes in patients with glioblastoma [41]. Glioblastomas are capable of exerting distal effects on the immune system, including increasing the fraction of Tregs compared with effector T-lymphocytes in the tumor microenvironment [42]. Here, we observed a relative increase in Foxp3 + CD4 + T-lymphocytes vs. effector cytotoxic T-lymphocytes in the blood when the tumor grew, mainly due to the low CD8+ population ingliblastoma-bearing mice. This change could be mediated by various factors released by the tumor that circulate in the bloodstream, influencing the differentiation and/or proliferation of both Foxp3 + CD4 + T-lymphocytes and effector CD8⁺ T-lymphocytes [43]. In vitro studies have shown that Tregs can strongly suppress effector T-lymphocyte function by inducing responder T-lymphocyte senescence [44]. An imbalance in Foxp3 + CD4 + T-lymphocytes relative to CD8⁺ T-lymphocytes in the blood reflects an immunosuppressive environment at the systemic level. Generally, although lymphocytes are regarded as radiosensitive [45], Tregs are relatively resistant to radiotherapy, which is partly mediated by the downregulation of pro-apoptotic proteins and upregulation of anti-apoptotic proteins [46]. Interestingly, we observed that brain exposure rescued the effector CD8⁺ level to the level observed in control mice. Therefore, the Treg versus CD8⁺ balance was also restored,
suggesting that brain exposure could contribute to alleviating systemic glioblastoma-induced immunosuppression.

Our study revealed that naïve T-CD8⁺ cell concentrations decreased as glioblastoma volume increased. Tumor cells may express antigens recognizable by host CD8⁺ T-lymphocytes, facilitating immune recognition and responses [47]. T-lymphocytes undergo differentiation from naïve to effector and memory states in response to antigen exposure [12]. In patients with cancer, there is a pronounced shift in the T-lymphocyte population from naïve T CD8⁺ cells to effector memory T CD8⁺ cells [48]. This suggests the formation of antitumor T-lymphocyte memory, which plays a crucial role in the long-term immune response to cancer [48]. Alternatively, but not exclusively, the shift from naïve T CD8⁺ cells to effector memory T CD8⁺ cells may be similar to the phenomenon of age-related T-lymphocyte exhaustion, which results in T-lymphocytes with the phenotype of memory cells lacking functionality, potentially induced by the inflammatory context [49]. In addition, continual exposure to tumor antigens in the cancer environment can lead to exhaustion of both effector and memory CD8⁺ T-lymphocytes within the tumor microenvironment and at the systemic level [50,51]. Consequently, preserving naïve CD8⁺ T-lymphocytes is vital, because they constitute the foundational pool for generating active T-lymphocytes capable of infiltrating tumors. Naïve CD8⁺ T-lymphocytes are highly radiosensitive in irradiated tumor-bearing mice. Exposure to radiation during radiotherapy can result in lymphopenia in the periphery by direct T-lymphocyte killing [25]. Our results showed that the involvement of lymph nodes in the irradiated area resulted in a decrease in naïve T-CD8⁺ T-lymphocyte concentration. However, this cell population expanded to a greater extent than that in control mice after brain irradiation on day 28. The finding that naïve T-CD8⁺ T-lymphocyte populations expanded to greater levels than those in control mice by day 28 post irradiation suggests a compensatory mechanism. This rebound could be driven by homeostatic proliferation, where lymphocytes proliferate in response to reduced competition for survival signals, such as IL-7 and IL-15, which is typically observed after lymphodepletion events [6,52]. This phenomenon highlights the resilience and adaptive capacity of immune systems. After initial depletion, the immune system not only recovers, but can also potentially be hyperexpanded before homeostasis is reached [53]. This heightened immune response can be explained by the elastic regulation of the immune system, where a rebound effect can be observed following recovery after a perturbation before reaching the balanced state [54].

Our findings indicate that incidental radiation exposure to the lymph nodes during brain irradiation results in a decrease in several T-lymphocyte subpopulations in the blood including effector T CD4⁺, effector T CD8⁺, and memory T CD8⁺ cells. T-lymphocytes are particularly sensitive to radiation [25], which can cause direct T-lymphocyte death and disrupt their trafficking and function [55]. Given that lymph nodes are critical sites for lymphocyte homing, maturation and activation [6], avoiding their presence in the irradiated area is especially important for maintaining T-lymphocyte subpopulations in the blood. In our setting, proton therapy spares the cervical lymph node region when a vertical beam is delivered [4,22]. Clinical data have shown that substituting proton therapy for X-ray radiotherapy of glioblastoma can reduce the likelihood of RIL [56], likely due to the sparing of the lymph nodes. A simulation study demonstrated that including the cervical lymph nodes in the radiation field during brain radiotherapy increased the radiation dose delivered to lymphocytes [57]. By minimizing radiation exposure to the lymph nodes, particularly with proton therapy, it may be possible to better preserve peripheral T-lymphocyte subpopulations, as shown here, and therefore mitigate the adverse effects associated with lymphocyte depletion. Beyond the studied parameters, significant difference in dose rate could influence variations in T-cell subpopulations, as adjusting the dose rate inherently alters irradiation time [4]. Several simulation studies have suggested that prolonging irradiation time by modifying the dose rate could increase the proportion of circulating lymphocytes exposed to radiation [22,24,58],

potentially heightening lymphopenia.

In fact, X-rays and protons could produce different biological effects, which varied across different cell lines [59]. This raises the important question of whether the observed biological differences in our study can be attributed to the differing relative biological effectiveness (RBE) of the two types of beams. However, based on the work of Paganetti et al. (2002), the RBE of proton beams is estimated to be equal to or even greater than that of 250 kVp X-rays relative to ⁶⁰Co [59]. In vitro studies have demonstrated that protons induce higher rates of radiation-induced cell death in lymphocytes compared to X-rays [45,60]. Despite these in vitro results, our in vivo findings show a contrasting effect, with protons having a lesser impact on lymphocyte populations compared to X-rays. This discrepancy between in vitro and in vivo results suggests that the observed biological differences in our study are not due to the varying RBE of the two beams. Other factors, such as the interaction of radiation with different tissue environments or the specific conditions of in vivo studies, may contribute to these divergent outcomes. Therefore, the biological differences observed are likely not explained by RBE alone, and further investigation is needed to better understand the underlying mechanisms driving these effects.

One of the limitations of this study is that only one tumor model was tested. It is important to expand testing to other GBM models to confirm the findings keeping in mind that the number of models in immunocompetent mice is restricted. In this context, sex differences are also a crucial consideration, as GBM is 1.6 times more prevalent in men [61], and functional differences in immune functions between males and females are well known. Given that the GL-261 cell line was originally derived from female mice, female animals were used in this study to avoid eventual sex-related biases in variations in immune cells composition and anti-tumor immune responses [62]. However, it is important to account for immunological differences between males and females when translating these findings to clinical practice. Since this study is limited to the GL261 glioma model and female subjects, further studies are necessary to confirm these findings across diverse glioma models and biological sexes. Nevertheless, these preliminary results provide insight into how both GBM volume and radiotherapy can affect changes in T cell subpopulations. Although adjustments in radiation condition sometimes show beneficial effects, they may not be sufficient to fully restore T cell subpopulations at the blood level. Moreover, it is necessary to test these results in additional mouse strains beyond C57BL/6 to ensure broader applicability. Furthermore, the relationship between the T cell subpopulations in the blood and the changes in the tumor microenvironment will need to be confirmed to evaluate the mechanistic impact of circulatory T cell subpopulation changes on the tumor evolution and prognosis.

## Conclusion

In conclusion, this study revealed the relationship between brain irradiation and variations in T-lymphocyte subpopulations in blood in various settings. The inclusion of lymph nodes in the irradiated area leads to a long-term decrease in naïve and memory CD8⁺ T-lymphocytes. Further studies are needed to explore the long-term consequences of these fluctuations in T-lymphocyte populations and their functions regarding how they affect patient susceptibility to cancer. Additional mechanistic studies to understand the cellular and molecular bases for radiation-induced changes and the subsequent recovery of T-lymphocyte populations could help devise strategies to mitigate negative effects while harnessing positive responses.

## Ethics statement

Animal experiments were performed in accordance with current European regulations, with permission from the Regional Committee on Animal Ethics.
### CRediT authorship contribution statement

**Thao-Nguyen Pham:** Writing - review & editing, Writing - original draft, Visualization, Validation, Software, Resources, Methodology, Investigation, Formal analysis, Data curation, Conceptualization. **Julie Coupey:** Writing - review & editing, Resources. **Florian Yger:** Writing - review & editing, Methodology, Formal analysis. **Serge M. Candéias:** Writing - review & editing, Methodology, Formal analysis, Data curation. **Juliette Thariat:** Writing - review & editing, Writing - original draft, Visualization, Validation, Supervision, Resources, Project administration, Investigation, Funding acquisition, Conceptualization. **Samuel Valable:** Writing - review & editing, Writing - original draft, Visualization, Validation, Supervision, Resources, Project administration, Investigation, Funding acquisition, Conceptualization.

### Data availability

The data generated in this study are available in the manuscript and supplementary files.

### Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

### Acknowledgments

This project received financial support from CNRS through the 80| Prime program and Ligue Contre le Cancer. The authors thank the French National Agency for Research ‘Investissements d’Avenir’ (n’ANR-10-EQPX1401) and all the facilities, including in vivo irradiation and imaging (Cyceron, CYRCé). SC work was funded in part by LABEX PRIMES (grant number ANR-11-LABX-0063).

### Appendix A. Supplementary material

Supplementary data to this article can be found online at https://doi.org/10.1016/j.radonc.2025.110801.

### References

[1] Damen PJJ, Kroese TE, Van Hillegersberg R, Schuit E, Peters M, Verhoeff JJC, et al. The influence of severe radiation-induced lymphopenia on overall survival in solid tumors: a systematic review and meta-analysis. Int J Radiat Oncol Biol Phys 2021; 111:936-48. https://doi.org/10.1016/j.ijrobp.2021.07.1695.

[2] Pham T-N, Coupey J, Thariat J, Valable S. Impact of circulating lymphocyte kinetics following radiotherapy on patient survival: a model-based meta-analysis. Comput Biol Med 2025;186:109702. https://doi.org/10.1016/j.combiomed.2025.109702.

[3] Zeng J, See AP, Phallen J, Jackson CM, Belcaid Z, Ruzevick J, et al. Anti-PD-1 blockade and stereotactic radiation produce long-term survival in mice with intracranial gliomas. Int J Radiat Oncol Biol Phys 2013;86:343-9. https://doi.org/10.1016/j.ijrobp.2012.12.025.

[4] Pham T-N, Coupey J, Toutain J, Candéias SM, Simonin G, Rousseau M, et al. Early effects of different brain radiotherapy modalities on circulating leucocyte subpopulations in rodents. Int J Radiat Biol 2024:1-12. https://doi.org/10.1080/09553002.2024.2324471.

[5] Maclennan ICM, Kay HEM. Analysis of treatment in childhood leukemia. IV. The critical association between dose fractionation and immunosuppression induced by cranial irradiation. Cancer. 1978; 41:108-111. 10.1002/1097-0142(197801)41:1<108::AID-CNCR2820410116>3.0.CO;2-Z.

[6] Pham T-N, Coupey J, Candées SM, Ivanova V, Valable S, Thariat J. Beyond lymphopenia, unraveling radiation-induced leucocyte subpopulation kinetics and mechanisms through modeling approaches. J Exp Clin Cancer Res 2023;42:50. https://doi.org/10.1186/s13046-023-02621-4.

[7] Hu X, Li Y-Q, Li Q-G, Ma Y-L, Peng J-J, Cai S-J. Baseline peripheral blood leukocytosis is negatively correlated with T-cell infiltration predicting worse outcome in colorectal cancers. Front Immunol 2018;9:2354. https://doi.org/10.3389/fimmu.2018.02354.

[8] Wang Q, Li S, Qiao S, Zheng Z, Duan X, Zhu X. Changes in T lymphocyte subsets in different tumors before and after radiotherapy: a meta-analysis. Front Immunol 2021;12:648652. https://doi.org/10.3389/fimmu.2021.648652.

[9] Marshall EA, Ng KW, Kung SHY, Conway EM, Martinez VD, Halvorsen EC, et al. Emerging roles of T helper 17 and regulatory T cells in lung cancer progression and metastasis. Mol Cancer 2016;15:67. https://doi.org/10.1186/s12943-016-0551-1.

[10] Persa E, Balogh A, Sáfrány G, Lumniczky K. The effect of ionizing radiation on regulatory T cells in health and disease. Cancer Lett 2015;368:252-61. https://doi.org/10.1016/j.canlet.2015.03.003.

[11] Giles JR, Globig A-M, Kaech SM, Wherry EJ. CD8+ T cells in the cancer-immunity cycle. Immunity 2023;56:2231-53. https://doi.org/10.1016/j.immuni.2023.09.005.

[12] Philip M, Schietinger A. CD8+ T cell differentiation and dysfunction in cancer. Nat Rev Immunol 2022;22:209-23. https://doi.org/10.1038/s41577-021-00574-3.

[13] Brown NF, Carter TJ, Ottaviani D, Mulholland P. Harnessing the immune system in glioblastoma. Br J Cancer 2018;119:1171-81. https://doi.org/10.1038/s41416-018-0258-8.

[14] Stupp R, Mason WP, Van Den Bent MJ, Weller M, Fisher B, Taphoorn MJB, et al. Radiotherapy plus concomitant and adjuvant temozolomide for glioblastoma. N Engl J Med 2005;352:987-96. https://doi.org/10.1056/NEJMoa043330.

[15] Tesileanu CMS, Sanson M, Wick W, Brandes AA, Clement PM, Erridge SC, et al. Temozolomide and radiotherapy versus radiotherapy alone in patients with glioblastoma, *IDH* -wildtype: *Post Hoc* analysis of the EORTC randomized phase III CATNON trial. Clin Cancer Res 2022;28:2527-35. https://doi.org/10.1158/1078-0432.CCR-21-4283.

[16] Yu MW, Quail DF. Immunotherapy for glioblastoma: current progress and challenges. Front Immunol 2021;12:676301. https://doi.org/10.3389/fimmu.2021.676301.

[17] Wang H, Zhou H, Xu J, Lu Y, Ji X, Yao Y, et al. Different T-cell subsets in glioblastoma multiforme and targeted immunotherapy. Cancer Lett 2021;496:134-43. https://doi.org/10.1016/j.canlet.2020.09.028.

[18] Ghosh S, Huang J, Inkman M, Zhang J, Thotala S, Tikhonova E, et al. Radiation-induced circulating myeloid-derived suppressor cells induce systemic lymphopenia after chemoradiotherapy in patients with glioblastoma. Sci Transl Med 2023;15:eabn6758. https://doi.org/10.1126/scitranslmed.abn6758.

[19] Kim J, Choi H, Jeun S-S, Ahn S. From lymphopenia to restoration: IL-7 immunotherapy for lymphocyte recovery in glioblastoma. Cancer Lett 2024;588:216714. https://doi.org/10.1016/j.canlet.2024.216714.

[20] Pham T-N, Coupey J, Thariat J, Valable S. Bayesian networks in modeling leucocyte interplay following brain irradiation: a comprehensive framework. Comput Methods Programs Biomed 2024;257:108421. https://doi.org/10.1016/j.cmpb.2024.108421.

[21] Pham T-N, Coupey J, Rousseau M, Thariat J, Valable S. Revealing the effect of X-ray or proton brain irradiation on systemic inflammation and leucocyte subpopulation interplay in rodents. *Journal of Leukocyte Biology*. 2024;qiae156. 10.1093/jeuko/qiae156.

[22] Hammi A, Paganetti H, Grassberger C. 4D blood flow model for dose calculation to circulating blood and lymphocytes. Phys Med Biol 2020;65:055008. https://doi.org/10.1088/1361-6560/ab6c14.

[23] De Kermenguy F, Benzazon N, Maury P, Vauclin R, M'hamdi C, Mifliku V, Limkin E, et al. LymphoDose: a lymphocyte dose estimation framework—application to brain radiotherapy. *Phys. Med. Biol.* 2024; 69:105009. 10.1088/1361-6560/ad3c8d.

[24] Yovino S, Kleinberg L, Grossman SA, Narayanan M, Ford E. The etiology of treatment-related lymphopenia in patients with malignant gliomas: modeling radiation dose to circulating lymphocytes explains clinical observations and suggests methods of modifying the impact of radiation on immune cells. Cancer Invest 2013;31:140-4. https://doi.org/10.3109/07357907.2012.762780.

[25] Paganetti H. A review on lymphocyte radiosensitivity and its impact on radiotherapy. Front Oncol 2023;13:1201500. https://doi.org/10.3389/fonc.2023.1201500.

[26] Coupey J, Pham TN, Toutain J, Ivanova V, HUE E, Helaine C, Ismail A, et al. Investigating the effects of protons versus x-rays on radiation-induced lymphopenia after brain irradiation. *bioRxiv*. 2024. Available at: https://www.biorxiv.org/content/early/2024/03/06/2024.03.02.583088. 10.1101/2024.03.02.583088.

[27] Coupey J, Leblond MM, Hue ES, Valable S. Flow cytometry detection and quantification of circulating leucocyte subpopulations in mice after brain irradiation. In: *Methods in Cell Biology*. Elsevier; 2024: S0091679X24001705. Available at: https://linkinghub.elsevier.com/retrieve/pii/S0091679X24001705 [Accessed July 19, 2024]. 10.1016/bs.mcb.2024.06.004.

[28] **R Core Team.** R: A Language and Environment for Statistical Computing. 2021. Available at: https://www.R-project.org/.

[29] Pedersen TL. ggraph: An Implementation of Grammar of Graphics for Graphs and Networks. 2022. Available at: https://CRAN.R-project.org/package=ggraph.

[30] Le S, Josse J, Husson F. FactoMineR: An R Package for Multivariate Analysis. *J. Stat. Soft.* 2008; 25. Available at: http://www.jstatsoft.org/v25/i01/ [Accessed June 20, 2023]. 10.18637/jss.v025.i01.

[31] Maechler M, Rousseewu P, Struyf A, Hubert M, Hornik K. cluster: Cluster Analysis Basics and Extensions. 2021. Available at: https://CRAN.R-project.org/package=cluster.

[32] Kuhn, Max. Building Predictive Models in R Using the caret Package. *Journal of Statistical Software*. 2008; 28:1-26. 10.18637/jss.v028.i05.

[33] Therneau T, Atkinson B. rpart: Recursive Partitioning and Regression Trees. 2022. Available at: https://CRAN.R-project.org/package=rpart.

[34] Chongsathidkiet P, Jackson C, Koyama S, Loebel F, Cui X, Farber SH, et al. Sequestration of T cells in bone marrow in the setting of glioblastoma and other intracranial tumors. Nat Med 2018;24:1459-68. https://doi.org/10.1038/s41591-018-0135-2.
[35] Domenis R, Cesselli D, Toffoletto B, Bourkoula E, Caponnetto F, Manini I, Beltrami AP, et al. Systemic T Cells Immunosuppression of Glioma Stem Cell-Derived Exosomes Is Mediated by Monocytic Myeloid-Derived Suppressor Cells Federico M, ed. PLoS ONE. 2017; 12:e0169932. 10.1371/journal.pone.0169932.

[36] Waziri A. Glioblastoma-Derived Mechanisms of Systemic Immunosuppression. Neurosurg Clin N Am 2010;21:31-42. https://doi.org/10.1016/j.nec.2009.08.005.

[37] Gousias K, Markou M, Arzoglou V, Voulgaris S, Vartholomatos G, Kostoula A, et al. Frequent abnormalities of the immune system in gliomas and correlation with the WHO grading system of malignancy. J Neuroimmunol 2010;226:136-42. https://doi.org/10.1016/j.jneuroim.2010.05.027.

[38] Piotrowski AF, Nirschl TR, Velarde E, Blosser L, Ganguly S, Burns KH, et al. Systemic depletion of lymphocytes following focal radiation to the brain in a murine model. OncolImmunol 2018;7:e1445951. https://doi.org/10.1080/2162402X.2018.1445951.

[39] Saleh R, Elkord E. FoxP3+ T regulatory cells in cancer: prognostic biomarkers and therapeutic targets. Cancer Lett 2020;490:174-85. https://doi.org/10.1016/j.canlet.2020.07.022.

[40] Mempel TR, Pittet MJ, Khazaie K, Weninger W, Weissleder R, Von Boehmer H, et al. Regulatory T cells reversibly suppress cytotoxic T cell function independent of effector differentiation. Immunity 2006;25:129-41. https://doi.org/10.1016/j.immuni.2006.04.015.

[41] Fecci PE, Mitchell DA, Whitesides JF, Xie W, Friedman AH, Archer GE, et al. Increased regulatory T-cell fraction amidst a diminished CD4 compartment explains cellular immune defects in patients with malignant glioma. Cancer Res 2006;66:3294-302. https://doi.org/10.1158/0008-5472.CAN-05-3773.

[42] Andaloussi AE, Lesniak MS. An increase in CD4+CD25+FOXP3+ regulatory T cells in tumor-infiltrating lymphocytes of human glioblastoma multiforme1. Neuro Oncol 2006;8:234-43. https://doi.org/10.1215/15228517-2006-006.

[43] Fecci PE, Ochiai H, Mitchell DA, Grossi PM, Sweeney AE, Archer GE, et al. Systemic CTLA-4 blockade ameliorates glioma-induced changes to the CD4+ T cell compartment without affecting regulatory T-cell function. Clin Cancer Res 2007; 13:2158-67. https://doi.org/10.1158/1078-0432.CCR-06-2070.

[44] Ye J, Huang X, Hsueh EC, Zhang Q, Ma C, Zhang Y, et al. Human regulatory T cells induce T-lymphocyte senescence. Blood 2012;120:2021-31. https://doi.org/10.1182/blood-2012-03-416040.

[45] Pham T-N, Coupey J, Thariat J, Valable S. Lymphocyte radiosensitivity: an extension to the linear-quadratic model? Radiother Oncol 2024;198:110406. https://doi.org/10.1016/j.radonc.2024.110406.

[46] Liu S, Sun X, Luo J, Zhu H, Yang X, Guo Q, et al. Effects of radiation on T regulatory cells in normal states and cancer: mechanisms and clinical implications. Am J Cancer Res 2015;5:3276-85.

[47] Gajewski TF, Schreiber H, Fu Y-X. Innate and adaptive immune cells in the tumor microenvironment. Nat Immunol 2013;14:1014-22. https://doi.org/10.1038/ni.2703.

[48] Takahashi H, Sakakura K, Ida S, Kawabata-Iwakawa R, Matsuyama T, Tada H, et al. Circulating naïve and effector memory T cells correlate with prognosis in head and neck squamous cell carcinoma. Cancer Sci 2022;113:53-64. https://doi.org/10.1111/cas.15195.

[49] Quinn KM, Vicencio DM, La Gruta NL. The paradox of aging: aging-related shifts in T cell function and metabolism. Semin Immunol 2023;70:101834. https://doi.org/10.1016/j.ssim.2023.101834.

[50] Dolina JS, Van Braeckel-Budimir N, Thomas GD, Salek-Ardakani S. CD8+ T cell exhaustion in cancer. Front Immunol 2021;12:715234. https://doi.org/10.3389/fimmu.2021.715234.

[51] Gebhardt T, Park SL, Parish IA. Stem-like exhausted and memory CD8+ T cells in cancer. Nat Rev Cancer 2023;23:780-98. https://doi.org/10.1038/s41568-023-00615-0.

[52] Almeida ARM, Borghans JAM, Freitas AA. T cell homeostasis. J Exp Med 2001;194: 591-600. https://doi.org/10.1084/jem.194.5.591.

[53] Kawabe T, Yi J, Sprent J. Homeostasis of naïve and memory T lymphocytes. Cold Spring Harb Perspect Biol 2021;13:a037879. https://doi.org/10.1101/cshperspect.a037879.

[54] Brodin P, Davis MM. Human immune system variation. Nat Rev Immunol 2017;17: 21-9. https://doi.org/10.1038/nri.2016.125.

[55] Lumniczky K, Sáfrány G. The impact of radiation therapy on the antitumor immunity: local effects and systemic consequences. Cancer Lett 2015;356:114-25. https://doi.org/10.1016/j.canlet.2013.08.024.

[56] Mohan R, Liu AY, Brown PD, Mahajan A, Dinh J, Chung C, et al. Proton therapy reduces the likelihood of high-grade radiation-induced lymphopenia in glioblastoma patients: phase II randomized study of protons vs photons. Neuro Oncol 2021;23:284-94. https://doi.org/10.1093/neuonc/noaa182.

[57] de Kermenguy F, Meziani L, Mondini M, Clémenson C, Morel D, Deutsch E, Robert C. Radio-induced lymphopenia in the era of anti-cancer immunotherapy. In: *International Review of Cell and Molecular Biology*. Elsevier; 2023: S1937644823000229. Available at: https://linkinghub.elsevier.com/retrieve/pii/S1937644823000229 [Accessed April 9, 2023]. 10.1016/bs.icmb.2023.03.002.

[58] Hammi A. 4D dosimetric-blood flow model: impact of prolonged fraction delivery times of IMRT on the dose to the circulating lymphocytes. Phys Med Biol 2023;68: 145017. https://doi.org/10.1088/1361-6560/acdcdc.

[59] Paganetti H, Niemierko A, Ancukiewicz M, Gerweck LE, Goitein M, Loeffler JS, et al. Relative biological effectiveness (RBE) values for proton beam therapy. Int J Radiat Oncol Biol Phys 2002;53:407-21. https://doi.org/10.1016/S0360-3016 (02)02754-2.

[60] Miszczyk J, Rawojć K, Panek A, Borkowska A, Prasanna PGS, Ahmed MM, et al. Do protons and X-rays induce cell-killing in human peripheral blood lymphocytes by different mechanisms? Clin Translational Radiat Oncol 2018;9:23-9. https://doi.org/10.1016/j.ctr-o.2018.01.004.

[61] Weller M, Van Den Bent M, Preusser M, Le Rhun E, Tonn JC, Minniti G, et al. EANO guidelines on the diagnosis and treatment of diffuse gliomas of adulthood. Nat Rev Clin Oncol 2021;18:170-86. https://doi.org/10.1038/s41571-020-00447-z.

[62] Forsyth KS, Jiwrajka N, Lovell CD, Toothacre NE, Anguera MC. The conneXion between sex and immune responses. Nat Rev Immunol 2024;24:487-502. https://doi.org/10.1038/s41577-024-00996-9.