A Model of Indirect Cell Death Caused by Tumor Vascular Damage after High-Dose Radiotherapy

Spatially Fractionated Radiotherapy in the Era of Immunotherapy

Spatially fractionated radiotherapy (SFRT) includes historical grid therapy approaches but more recently encompasses the controlled introduction of one or more cold dose regions using intensity modulation delivery techniques. The driving hypothesis behind SFRT is that it may allow for an increased immune response that is otherwise suppressed by radiation effects. With both two- and three-dimensional SFRT approaches, SFRT dose distributions typically include multiple dose cold spots or valleys. Despite its unconventional methods, reported clinical experience shows that SFRT can sometimes induce marked tumor regressions, even in patients with large hypoxic tumors. Preclinical models using extreme dose distributions (i.e., half-sparing) have been shown to nevertheless result in full tumor eradications, a more robust immune response, and systemic anti-tumor immunity. SFRT takes advantage of the complementary immunomodulatory features of low- and high-dose radiotherapy to integrate the delivery of both into a single target. Clinical trials using three-dimensional SFRT (i.e., lattice-like dose distributions) have reported both promising tumor and toxicity results, and ongoing clinical trials are investigating synergy between SFRT and immunotherapies.

Simulating tumor volume dynamics in response to radiotherapy: Implications of model selection

From the beginning of the usage of radiotherapy (RT) for cancer treatment, mathematical modeling has been integral to understanding radiobiology and for designing treatment approaches and schedules. There has been extensive modeling of response to RT with the inclusion of various degrees of biological complexity. In this study, we compare three models of tumor volume dynamics: (1) exponential growth with RT directly reducing tumor volume, (2) logistic growth with direct tumor volume reduction, and (3) logistic growth with RT reducing the tumor carrying capacity with the objective of understanding the implications of model selection and informing the process of model calibration and parameterization. For all three models, we: examined the rates of change in tumor volume during and RT treatment course; performed parameter sensitivity and identifiability analyses; and investigated the impact of the parameter sensitivity on the tumor volume trajectories. In examining the tumor volume dynamics trends, we coined a new metric - the point of maximum reduction of tumor volume (MRV) - to quantify the magnitude and timing of the expected largest impact of RT during a treatment course. We found distinct timing differences in MRV, dependent on model selection. The parameter identifiability and sensitivity analyses revealed the interdependence of the different model parameters and that it is only possible to independently identify tumor growth and radiation response parameters if the underlying tumor growth rate is sufficiently large. Ultimately, the results of these analyses help us to better understand the implications of model selection while simultaneously generating falsifiable hypotheses about MRV timing that can be tested on longitudinal measurements of tumor volume from pre-clinical or clinical data with high acquisition frequency. Although, our study only compares three particular models, the results demonstrate that caution is necessary in selecting models of response to RT, given the artifacts imposed by each model.

Radiobiological Meta-Analysis of the Response of Prostate Cancer to Different Fractionations: Evaluation of the Linear-Quadratic Response at Large Doses and the Effect of Risk and ADT

The purpose of this work was to investigate the response of prostate cancer to different radiotherapy schedules, including hypofractionation, to evaluate potential departures from the linear-quadratic (LQ) response, to obtain the best-fitting parameters for low-(LR), intermediate-(IR), and high-risk (HR) prostate cancer and to investigate the effect of ADT on the radiobiological response. We constructed a dataset of the dose-response containing 87 entries/16,536 patients (35/5181 LR, 32/8146 IR, 20/3209 HR), with doses per fraction ranging from 1.8 to 10 Gy. These data were fit to tumour control probability models based on the LQ model, linear-quadratic-linear (LQL) model, and a modification of the LQ (LQmod) model accounting for increasing radiosensitivity at large doses. Fits were performed with the maximum likelihood expectation methodology, and the Akaike information criterion (AIC) was used to compare the models. The AIC showed that the LQ model was superior to the LQL and LQmod models for all risks, except for IR, where the LQL model outperformed the other models. The analysis showed a low α/β for all risks: 2.0 Gy for LR (95% confidence interval: 1.7-2.3), 3.4 Gy for IR (3.0-4.0), and 2.8 Gy for HR (1.4-4.2). The best fits did not show proliferation for LR and showed moderate proliferation for IR/HR. The addition of ADT was consistent with a suppression of proliferation. In conclusion, the LQ model described the response of prostate cancer better than the alternative models. Only for IR, the LQL model outperformed the LQ model, pointing out a possible saturation of radiation damage with increasing dose. This study confirmed a low α/β for all risks.

A Biomathematical Model of Tumor Response to Radioimmunotherapy With αPDL1 and αCTLA4

There is evidence of synergy between radiotherapy and immunotherapy. Radiotherapy can increase liberation of tumor antigens, causing activation of antitumor T-cells. This effect can be boosted with immunotherapy. Radioimmunotherapy has potential to increase tumor control rates. Biomathematical models of response to radioimmunotherapy may help on understanding of the mechanisms affecting response, and assist clinicians on the design of optimal treatment strategies. In this work we present a biomathematical model of tumor response to radioimmunotherapy. The model uses the linear-quadratic response of tumor cells to radiation (or variation of it), and builds on previous developments to include the radiation-induced immune effect. We have focused this study on the combined effect of radiotherapy and αPDL1/ αCTLA4 therapies. The model can fit preclinical data of volume dynamics and control obtained with different dose fractionations and αPDL1/ αCTLA4. A biomathematical study of optimal combination strategies suggests that a good understanding of the involved biological delays, the biokinetics of the immunotherapy drug, and the interplay between them, may be of paramount importance to design optimal radioimmunotherapy schedules. Biomathematical models like the one we present can help to interpret experimental data on the synergy between radiotherapy and immunotherapy, and to assist in the design of more effective treatments.

Noninvasive optoacoustic imaging of breast tumor microvasculature in response to radiotherapy

Detailed insight into the radiation-induced changes in tumor microvasculature is crucial to maximize the efficacy of radiotherapy against breast cancer. Recent advances in imaging have enabled precise targeting of solid lesions. However, intratumoral heterogeneity makes treatment planning and monitoring more challenging. Conventional imaging cannot provide high-resolution observation and longitudinal monitoring of large-scale microvascular in response to radiotherapy directly in deep tissues. Herein, we report on an emerging non-invasive imaging assessment method of morphological and functional tumor microvasculature responses with high spatio-temporal resolution by means of optoacoustic imaging (OAI). In vivo imaging of 4T1 breast tumor response to a conventional fractionated radiotherapy at varying dose (14 × 2 Gy and 3 × 8 Gy) has been performed after 2 weeks following treatment. Remarkably, optoacoustic images can generate richful contrast for the tumor microvascular architecture. Besides, the functional status of tumor microvasculature and tumor oxygenation levels were further estimated using OAI. The results revealed the differential (size-dependent) nature of vascular responses to radiation treatments at varying doses. The vessels exhibited an decrease in their density accompanied by a decline in the number of vascular segments following irradiation, compared to the control group. The measurements further revealed an increase of tumor oxygenation levels for 14 × 2 Gy and 3 × 8 Gy irradiations. Our results suggest that OAI could be used to assess the response to radiotherapy based on changes in the functional and morphological status of tumor microvasculature, which are closely linked to the intratumor microenvironment. OAI assessment of the tumor microenvironment such as oxygenation status has the potential to be applied to precise radiotherapy strategy.

Angiogenesis and immune checkpoint dual blockade in combination with radiotherapy for treatment of solid cancers: opportunities and challenges

Several immune checkpoint blockades (ICBs) capable of overcoming the immunosuppressive roles of the tumor immune microenvironment have been approved by the US Food and Drug Administration as front-line treatments of various tumor types. However, due to the considerable heterogeneity of solid tumor cells, inhibiting one target will only influence a portion of the tumor cells. One way to enhance the tumor-killing efficiency is to develop a multiagent therapeutic strategy targeting different aspects of tumor biology and the microenvironment to provide the maximal clinical benefit for patients with late-stage disease. One such strategy is the administration of anti-PD1, an ICB, in combination with the humanized monoclonal antibody bevacizumab, an anti-angiogenic therapy, to patients with recurrent/metastatic malignancies, including hepatocellular carcinoma, metastatic renal cell carcinoma, non-small cell lung cancer, and uterine cancer. Radiotherapy (RT), a critical component of solid cancer management, has the capacity to prime the immune system for an adaptive antitumor response. Here, we present an overview of the most recent published data in preclinical and clinical studies elucidating that RT could further potentiate the antitumor effects of immune checkpoint and angiogenesis dual blockade. In addition, we explore opportunities of triple combinational treatment, as well as discuss the challenges of validating biomarkers and the management of associated toxicity.

Evaluation of indirect damage and damage saturation effects in dose-response curves of hypofractionated radiotherapy of early-stage NSCLC and brain metastases

BACKGROUND AND PURPOSE

To investigate the possible contribution of indirect damage and damage saturation to tumour control obtained with SBRT/SRS treatments for early-stage NSCLC and brain metastases.

METHODS AND MATERIALS

We have constructed a dataset of early-stage NSCLC and brain metastases dose-response. These data were fitted to models based on the linear-quadratic (LQ), the linear-quadratic-linear (LQL), and phenomenological modifications of the LQ-model to account for indirect cell damage. We use the Akaike-Information-Criterion formalism to compare performance, and studied the stability of the results with changes in fitting parameters and perturbations on dose/TCP values.

RESULTS

In NSCLC, a modified LQ-model with a beta-term increasing with dose yields the best-fits for α/β = 10 Gy. Only the inclusion of very fast accelerated proliferation or low α/β values can eliminate such superiority. In brain, the LQL model yields the best-fits, and the ranking is not affected by variations of fitting parameters or dose/TCP perturbations.

CONCLUSIONS

For α/β = 10 Gy, a modified LQ-model with a beta-term increasing with dose provides better fits to NSCLC dose-response curves. For brain metastases, the LQL provides the best fit. This might be interpreted as a hint of indirect damage in NSCLC, and damage saturation in brain metastases. The results for NSCLC are strongly dependent on the value of α/β and may require further investigation, while those for brain seem to be clearly significant. Our results can assist in the design of improved radiotherapy for NSCLC and brain metastases, aiming at avoiding over/under-treatment.

Translating the Immunobiology of SBRT to Novel Therapeutic Combinations for Advanced Prostate Cancer

Stereotactic body radiotherapy (SBRT) is an increasingly used radiation modality for the treatment of both localized and metastatic prostate cancer. Substantial data suggests that prostate cancer may be more sensitive to higher doses of radiation per fraction due to its low α/β ratio. This increased sensitivity raises important questions as to how SBRT should be combined with systemic therapy for clinically significant prostate cancer, including whether androgen deprivation therapy retains its beneficial effects when combined with SBRT. Furthermore, pre-clinical and clinical data suggest pronounced immunomodulatory effects of SBRT, including observed improvements in T cell priming and trafficking. These data support investigational strategies combining SBRT with immunotherapy. Here we aim to review the data for the use of SBRT in both the local and metastatic disease settings as well as ongoing translational and clinical research examining combinations with ADT, immunotherapy and other targeted agents.