Modeling of radiation effects to immune system: a review

Comparative in vivo toxicology of ATR inhibitors ceralasertib, elimusertib, and berzosertib alone and in combination with ionizing radiation

Ionizing radiation (IR) induces damage in the form of DNA strand breaks. As an apical initiator of the DNA damage response, Ataxia telangiectasia and Rad3-related (ATR) mitigates DNA damage, limiting therapeutic efficacy. Small molecule ATR inhibitors (ATRi) restrict this effect and sensitize cancer cells to radiation-induced damage. However, the impact of ATR inhibition in non-malignant tissues following IR is currently unknown. Here, we document the impact of ATRi on murine toxicity profiles following total body irradiation (TBI). Mice were stratified to receive single-dose ATRi (ceralasertib, elimusertib, or berzosertib), 6 Gy TBI, or the combination. Mice were euthanized 48 h post TBI. Blood and tissues were collected for analysis of complete blood counts and histopathology. To further distinguish toxicity profiles, IC50 values were compared between ATRi. Pharmacokinetics (PK) and pharmacodynamics (PD) were considered as potential explanatory factors of differences in toxicity profiles. Elimusertib was determined to be the most potent ATRi, and ceralasertib the least. We observed neutrophilia with all ATRi. We found that ATRi did not exacerbate any TBI-induced toxicities in mice. Berzosertib presented a unique profile among all ATRi across several toxicity endpoints, including modest amelioration of TBI-associated effects on spleen and lymphocyte and white blood cell counts. Cardiotoxicity was observed following single-dose ceralasertib, but no other ATRi, possibly due to high unbound plasma drug concentrations. Our results further support and guide clinical development of ATRi in clinic.

Radiation-Induced Tissue Regeneration: Pathways, Mechanisms, and Therapeutic Potential

This article explores the paradoxic nature of radiation as both a destructive and regenerative force. The article examines the interplay of signaling pathways, immune modulation, and stem cells in tissue regeneration post radiation, emphasizing the roles of key pathways like Wnt, Hedgehog, Notch, and p53. It highlights advancements in low-dose radiation therapy, extracellular vesicles, and stem cell-based interventions. Furthermore, the immune system's dual role in repair and damage is dissected, along with technologies such as artificial intelligence and bioengineered scaffolds that enhance therapeutic outcomes. The article offers a roadmap for integrating therapeutic innovation with regenerative medicine to improve patient outcomes.

Clinical study on changes of peripheral blood immune function indicators in adults with newly diagnosed glioblastoma during the peri-radiotherapy period

To analyze the changes of immune function-related indicators with newly diagnosed glioblastoma before and after radiotherapy and their clinical significance. Clinical data of 104 patients were analyzed. The independent samples t-test or chi-square test was used to compare changes in immune function indicators and to ascertain the differences between groups with different doses or volumes. The grading of the lowest lymphocyte count during radiotherapy was compared. The log-rank (Mantel - Cox) test of the Kaplan - Meier method was used to compare the survival rate, and the relationship of radiotherapy-related parameters, with the survival rate was evaluated by using the Spearman correlation coefficient. A Cox regression model was used to determine the relationship between various immune function indicators and prognosis. The percentages of total T lymphocytes and CD4+ T cells, the CD4-to-CD8 subset ratio, and the percentages of B cells and NKT cells showed an overall decreasing trend, whereas the percentages of CD8+ T cells and NK cells displayed an overall increasing trend. The lower CD4+ T cell percentage and CD4/CD8 ratio after radiotherapy were independent risk factors for OS. Short OS was observed in patients with grade 3 or 4 lymphopenia or with low levels of hemoglobin and serum albumin before radiotherapy. The percentage of CD4+ T cells and the CD4/CD8 ratio were higher in patients with the low tumor-irradiated volume and irradiated volume and dose of the OAR, than in patients from the corresponding high indicator group. Different irradiation dose or volume can differentially alter various immune function indicators.

Lymphocyte radiosensitivity: An extension to the linear-quadratic model?

BACKGROUND AND PURPOSE

The linear-quadratic (LQ) model has been pivotal for evaluating the effects of radiation on cells, but it is primarily characterized by linear responses, which has exhibited limitations when applied to lymphocyte data. The present research aims to address these limitations and to explore an alternative model extended from the conventional LQ model.

MATERIALS AND METHODS

Literature providing lymphocyte counts from assays investigating apoptosis and survival after in vitro irradiation was selected. To address the nonlinearity in lymphocyte responses to radiation, we developed a saturation model characterized by a negative exponential relationship between radiation dose and cellular response. We compared the performance of this saturation model against that of conventional models, including the LQ model and its variants (linear model LM and linear-quadratic-cubic model LQC), as well as the repair-misrepair (RMR) model. The models were evaluated based on prediction-residual plots, residual standard errors, and the Akaike information criterion (AIC). We applied the saturation model to two additional datasets: (1) a dataset from the existing literature that assessed stimulated and unstimulated human lymphocytes exposed to gamma irradiation in vitro and (2) a novel dataset involving T lymphocytes from rodent spleens after exposure to various radiation types (X-rays and protons).

RESULTS

The literature (n = 15 out of 2342) showed that lymphocyte apoptosis varies with dose, time and experimental conditions. The saturation model had a lower AIC of 718 compared to the LM, LQ, LQC and RMR models (AIC of 728, 720, 720 and 734, respectively). The saturation model had a lower residual error and more consistent error distribution. Integrating time as a covariate, the saturation model also had a better AIC for demonstrating time-dependent variations in lymphocyte responses after irradiation. For datasets involving unstimulated lymphocytes before irradiation, the saturation model provided a more accurate fit than did the LM, LQ, and RMR models. In these cases, the fit of the saturation model was comparable to that of the LQC model but offered an advantage when extrapolating to higher doses, where the LQC model might underestimate survival. For stimulated lymphocytes, which are radioresistant, all the models approximated the LM. Both the LQ and saturation models indicated greater radiosensitivity to protons in vitro.

CONCLUSION

The new "saturation model" performed better than the LQ model in quantifying lymphocyte apoptosis and survival, estimating time dependency and assessing the role of radiation modalities or lymphocyte stimulation. Further experiments are warranted to experimentally explore the validity of the saturation model as a promising alternative in the clinical setting.

Early lymphocyte levels and low doses radiation exposure of lung predict lymphopenia in radiotherapy for lung cancer

Introduction

Radiation induced lymphopenia (RIL) deteriorate survival and diminishes the benefit of immune checkpoint inhibitors in combined treatment of lung cancer. Given the inconsistent data across various studies on the predictors of RIL, we aim to methodically elucidate these predictors and formulate a practical guide for clinicians.

Methods

We conducted observational cohort study in four tertiary cancer centers. Patients with non-small cell lung cancer and small cell lung cancer, without lymphopenia grade >1, who underwent standalone radiotherapy (RT) in minimum 15 fractions were eligible. Dose-volume parameters of structures and clinical factors were comprehensively analyzed using various predictors selection methods and statistical models (Linear Regressors, Elastic Net, Bayesian Regressors, Huber Regression, regression based on k-nearest neighbors, Gaussian Process Regressor, Decision Tree Regressor, Random Forest Regressor, eXtreme Gradient Boosting, Automated Machine Learning) and were ranked to predict lymphocytes count nadir (alc_nadir).

Results

Two hundred thirty eight patients (stage I-3.4%, II-17.6%, III-75.2%, IV-3.8%) who underwent RT to median dose of 60 Gy were analyzed. Median alc_nadir was 0.68K/mm3. The 60 feature sets were evaluated in 600 models (RMSE 0.27-0.41K/mm³). The most important features were baseline lymphocyte count (alc_1), mean lung_dose, lung v05, lung v10, heart v05 and effective dose to immune cells (edic). In patients with alc_1 ≤ 2.005K/mm3, median alc_nadir predictions were 0.54K/mm3 for lung_v05p > 51.8% and 0.76K/mm3 for lung_v05p ≤ 51.8%. Lymphopenia was rare in patients with alc_1 > 2.005K/mm3.

Discussion

RIL was most severe in patients with low early lymphocyte counts, primarily triggered by low RT doses in the heart and lungs.

A Novel Nomogram to Predict Prognosis of Advanced Hepatocellular Carcinoma Treated with Intensity-Modulated Radiotherapy Plus Anti-PD1

Purpose

The combination of radiotherapy and monoclonal antibody against programmed cell death 1 (anti-PD1) showed preliminary efficacy in hepatocellular carcinoma (HCC). This study aimed to identify the prognostic factors and construct a nomogram to predict the overall survival (OS) of patients with advanced HCC after treatment with intensity-modulated radiotherapy (IMRT) plus anti-PD1.

Patients and Methods

The OS and progression-free survival (PFS) of 102 patients with BCLC stage C HCC was analyzed using the Kaplan-Meier method. Potential independent prognostic factors were determined using univariate and multivariate Cox regression analyses. A nomogram was established to predict prognosis whose accuracy and reliability was verified by a calibration curve and area under the receiver operating characteristic curve (AUROC).

Results

The median PFS and OS rates of the 102 patients with advanced HCC were 9.9 months and 14.3 months, respectively. Ninety-three patients were evaluated for efficacy, including five (5.38%) with complete response and 48 (51.61%) with partial response, with an overall response rate of 56.99%. Grade 3 and 4 adverse reactions (AEs) were observed in 32.35% of patients; no grade 5 AEs occurred. Multivariate Cox analysis revealed albumin and alpha-fetoprotein levels, neutrophil counts 3-4 weeks after IMRT initiation, and platelet-to-lymphocyte ratio 3-4 weeks after IMRT initiation to be independent prognostic factors. The nomogram model constructed using these factors had good consistency and accuracy with 1-3 years AUROC of 78.7, 78.6, and 93.5, respectively.

Conclusion

IMRT plus anti-PD1 showed promising efficacy and controllable adverse reactions in treating advanced HCC. The nomogram model demonstrated good reliability and clinical applicability.

LymphoDose: a lymphocyte dose estimation framework-application to brain radiotherapy

Objective. Severe radiation-induced lymphopenia occurs in 40% of patients treated for primary brain tumors and is an independent risk factor of poor survival outcomes. We developed anin-silicoframework that estimates the radiation doses received by lymphocytes during volumetric modulated arc therapy brain irradiation.Approach. We implemented a simulation consisting of two interconnected compartmental models describing the slow recirculation of lymphocytes between lymphoid organs (M1) and the bloodstream (M2). We used dosimetry data from 33 patients treated with chemo-radiation for glioblastoma to compare three cases of the model, corresponding to different physical and biological scenarios: (H1) lymphocytes circulation only in the bloodstream i.e. circulation inM2only; (H2) lymphocytes recirculation between lymphoid organs i.e. circulation inM1andM2interconnected; (H3) lymphocytes recirculation between lymphoid organs and deep-learning computed out-of-field (OOF) dose to head and neck (H&N) lymphoid structures. A sensitivity analysis of the model's parameters was also performed.Main results. For H1, H2 and H3 cases respectively, the irradiated fraction of lymphocytes was 99.8 ± 0.7%, 40.4 ± 10.2% et 97.6 ± 2.5%, and the average dose to irradiated pool was 309.9 ± 74.7 mGy, 52.6 ± 21.1 mGy and 265.6 ± 48.5 mGy. The recirculation process considered in the H2 case implied that irradiated lymphocytes were irradiated in the field only 1.58 ± 0.91 times on average after treatment. The OOF irradiation of H&N lymphoid structures considered in H3 was an important contribution to lymphocytes dose. In all cases, the estimated doses are low compared with lymphocytes radiosensitivity, and other mechanisms could explain high prevalence of RIL in patients with brain tumors.Significance. Our framework is the first to take into account OOF doses and recirculation in lymphocyte dose assessment during brain irradiation. Our results demonstrate the need to clarify the indirect effects of irradiation on lymphopenia, in order to potentiate the combination of radio-immunotherapy or the abscopal effect.

Designing combination therapies for cancer treatment: application of a mathematical framework combining CAR T-cell immunotherapy and targeted radionuclide therapy

Introduction

Cancer combination treatments involving immunotherapies with targeted radiation therapy are at the forefront of treating cancers. However, dosing and scheduling of these therapies pose a challenge. Mathematical models provide a unique way of optimizing these therapies.

Methods

Using a preclinical model of multiple myeloma as an example, we demonstrate the capability of a mathematical model to combine these therapies to achieve maximum response, defined as delay in tumor growth. Data from mice studies with targeted radionuclide therapy (TRT) and chimeric antigen receptor (CAR)-T cell monotherapies and combinations with different intervals between them was used to calibrate mathematical model parameters. The dependence of progression-free survival (PFS), overall survival (OS), and the time to minimum tumor burden on dosing and scheduling was evaluated. Different dosing and scheduling schemes were evaluated to maximize the PFS and optimize timings of TRT and CAR-T cell therapies.

Results

Therapy intervals that were too close or too far apart are shown to be detrimental to the therapeutic efficacy, as TRT too close to CAR-T cell therapy results in radiation related CAR-T cell killing while the therapies being too far apart result in tumor regrowth, negatively impacting tumor control and survival. We show that splitting a dose of TRT or CAR-T cells when administered in combination is advantageous only if the first therapy delivered can produce a significant benefit as a monotherapy.

Discussion

Mathematical models are crucial tools for optimizing the delivery of cancer combination therapy regimens with application along the lines of achieving cure, maximizing survival or minimizing toxicity.