Connecting radiation-induced bystander effects and senescence to improve radiation response prediction

Alpha Particle-Emitting Radiopharmaceuticals as Cancer Therapy: Biological Basis, Current Status, and Future Outlook for Therapeutics Discovery

Critical advances in radionuclide therapy have led to encouraging new options for cancer treatment through the pairing of clinically useful radiation-emitting radionuclides and innovative pharmaceutical discovery. Of the various subatomic particles used in therapeutic radiopharmaceuticals, alpha (α) particles show great promise owing to their relatively large size, delivered energy, finite pathlength, and resulting ionization density. This review discusses the therapeutic benefits of α-emitting radiopharmaceuticals and their pairing with appropriate diagnostics, resulting in innovative "theranostic" platforms. Herein, the current landscape of α particle-emitting radionuclides is described with an emphasis on their use in theranostic development for cancer treatment. Commonly studied radionuclides are introduced and recent efforts towards their production for research and clinical use are described. The growing popularity of these radionuclides is explained through summarizing the biological effects of α radiation on cancer cells, which include DNA damage, activation of discrete cell death programs, and downstream immune responses. Examples of efficient α-theranostic design are described with an emphasis on strategies that lead to cellular internalization and the targeting of proteins involved in therapeutic resistance. Historical barriers to the clinical deployment of α-theranostic radiopharmaceuticals are also discussed. Recent progress towards addressing these challenges is presented along with examples of incorporating α-particle therapy in pharmaceutical platforms that can be easily converted into diagnostic counterparts.

Involvement of miRNAs in cellular responses to radiation

PURPOSE

Exposure of living cells to ionizing radiation has different consequences, depending on the dose and cell type. Changes of gene expression at the level of transcription and translation, including those regulated by microRNAs (miRNAs), play a role in intrinsic radiosensitivity of different cells and define their fate, survival or death. The aim of our work was to examine how ionizing radiation may influence the expression of genes regulated by different miRNAs and miRNA biogenesis.

MATERIALS AND METHODS

The work was performed on cultured human melanoma Me45 cells, transiently transfected with plasmids containing Renilla luciferase reporter gene targeted by miRNAs Let-7, miR-21 or miR-24. The levels of reporter mRNAs and mRNAs coding for proteins participating in miRNA biogenesis were assayed at different time points in irradiated and non-irradiated cells using RT-qPCR, and reporter protein by luciferase activity assays. MiRNA-targeted motifs in mRNAs coding for proteins engaged in miRNA biogenesis were extracted from the miRTarBase database.

RESULTS

Messenger RNA and protein levels of transfected luciferase genes fluctuated in time in patterns which depended on the type of miRNA regulation and changed upon irradiation of the cells. The average levels of reporter mRNAs were higher in irradiated cells, whereas the levels of proteins changed in either direction. Radiation also influenced the levels of miRNAs and the expression of genes engaged in their biogenesis suggesting that the changes in gene expression following ionizing radiation result mainly from these changes in expression of genes regulating miRNA biogenesis and the influence of miRNA on mRNA translation.

CONCLUSIONS

Currently, the responses of cells to ionizing radiation are mainly ascribed to changes of their redox conditions and increased intracellular levels of ROS, but the experiments described here suggest that a further important factor is modulation of translation through changes in biogenesis and levels of miRNAs.

Forecasting Individual Patient Response to Radiation Therapy in Head and Neck Cancer With a Dynamic Carrying Capacity Model

Purpose:

To model and predict individual patient responses to radiation therapy.

Methods and Materials:

We modeled tumor dynamics as logistic growth and the effect of radiation as a reduction in the tumor carrying capacity, motivated by the effect of radiation on the tumor microenvironment. The model was assessed on weekly tumor volume data collected for 2 independent cohorts of patients with head and neck cancer from the H. Lee Moffitt Cancer Center (MCC) and the MD Anderson Cancer Center (MDACC) who received 66 to 70 Gy in standard daily fractions or with accelerated fractionation. To predict response to radiation therapy for individual patients, we developed a new forecasting framework that combined the learned tumor growth rate and carrying capacity reduction fraction (δ) distribution with weekly measurements of tumor volume reduction for a given test patient to estimate δ, which was used to predict patient-specific outcomes.

Results:

The model fit data from MCC with high accuracy with patient-specific δ and a fixed tumor growth rate across all patients. The model fit data from an independent cohort from MDACC with comparable accuracy using the tumor growth rate learned from the MCC cohort, showing transferability of the growth rate. The forecasting framework predicted patient-specific outcomes with 76% sensitivity and 83% specificity for locoregional control and 68% sensitivity and 85% specificity for disease-free survival with the inclusion of 4 on-treatment tumor volume measurements.

Conclusions:

These results demonstrate that our simple mathematical model can describe a variety of tumor volume dynamics. Furthermore, combining historically observed patient responses with a few patient-specific tumor volume measurements allowed for the accurate prediction of patient outcomes, which may inform treatment adaptation and personalization.

Targets for protection and mitigation of radiation injury

Protection of normal tissues against toxic effects of ionizing radiation is a critical issue in clinical and environmental radiobiology. Investigations in recent decades have suggested potential targets that are involved in the protection against radiation-induced damages to normal tissues and can be proposed for mitigation of radiation injury. Emerging evidences have been shown to be in contrast to an old dogma in radiation biology; a major amount of reactive oxygen species (ROS) production and cell toxicity occur during some hours to years after exposure to ionizing radiation. This can be attributed to upregulation of inflammatory and fibrosis mediators, epigenetic changes and disruption of the normal metabolism of oxygen. In the current review, we explain the cellular and molecular changes following exposure of normal tissues to ionizing radiation. Furthermore, we review potential targets that can be proposed for protection and mitigation of radiation toxicity.

Blackboard to Bedside: A Mathematical Modeling Bottom-Up Approach Toward Personalized Cancer Treatments

Cancers present with high variability across patients and tumors; thus, cancer care, in terms of disease prevention, detection, and control, can highly benefit from a personalized approach. For a comprehensive personalized oncology practice, this personalization should ideally consider data gathered from various information levels, which range from the macroscale population level down to the microscale tumor level, without omission of the central patient level. Appropriate data mined from each of these levels can significantly contribute in devising personalized treatment plans tailored to the individual patient and tumor. Mathematical models of solid tumors, combined with patient-specific tumor profiles, present a unique opportunity to personalize cancer treatments after detection using a bottom-up approach. Here, we discuss how information harvested from mathematical models and from corresponding in silico experiments can be implemented in preclinical and clinical applications. To conceptually illustrate the power of these models, one such model is presented, and various pertinent tumor and treatment scenarios are demonstrated in silico. The presented model, specifically a multiscale, hybrid cellular automaton, has been fully validated in vitro using multiple cell-line-specific data. We discuss various insights provided by this model and other models like it and their role in designing predictive tools that are both patient, and tumor specific. After refinement and parametrization with appropriate data, such in silico tools have the potential to be used in a clinical setting to aid in treatment protocols and decision making.

Drugs That Modify Cholesterol Metabolism Alter the p38/JNK-Mediated Targeted and Nontargeted Response to Alpha and Auger Radioimmunotherapy

PURPOSE

For the development of new anticancer therapeutic radiopharmaceuticals, including alpha particle emitters, it is important to determine the contribution of targeted effects in irradiated cells, and also of nontargeted effects in nonirradiated neighboring cells, because they may affect the therapeutic efficacy and contribute to side effects.

EXPERIMENTAL DESIGN

Here, we investigated the contribution of nontargeted cytotoxic and genotoxic effects in vitro and in vivo (in xenografted mice) during alpha (²¹²Pb/²¹²Bi, ²¹³Bi) and Auger (¹²⁵I) radioimmunotherapy (RIT).

RESULTS

Between 67% and 94% (alpha RIT) and 8% and 15% (Auger RIT) of cancer cells were killed by targeted effects, whereas 7% to 36% (alpha RIT) and 27% to 29% (Auger RIT) of cells were killed by nontargeted effects. We then demonstrated that the nontargeted cell response to alpha and Auger RIT was partly driven by lipid raft-mediated activation of p38 kinase and JNK. Reactive oxygen species also played a significant role in these nontargeted effects, as demonstrated by NF-κB activation and the inhibitory effects of antioxidant enzymes and radical scavengers. Compared with RIT alone, the use of RIT with ASMase inhibitor (imipramine) or with a lipid raft disruptor (e.g., methyl-beta-cyclodextrin or filipin) led to an increase in clonogenic cell survival in vitro and to larger tumors and less tissue DNA damage in vivo. These results were supported by an inhibitory effect of pravastatin on Auger RIT.

CONCLUSIONS

Cell membrane-mediated nontargeted effects play a significant role during Auger and alpha RIT, and drugs that modulate cholesterol level, such as statins, could interfere with RIT efficacy.

Targeted and Off-Target (Bystander and Abscopal) Effects of Radiation Therapy: Redox Mechanisms and Risk/Benefit Analysis

SIGNIFICANCE

Radiation therapy (from external beams to unsealed and sealed radionuclide sources) takes advantage of the detrimental effects of the clustered production of radicals and reactive oxygen species (ROS). Research has mainly focused on the interaction of radiation with water, which is the major constituent of living beings, and with nuclear DNA, which contains the genetic information. This led to the so-called target theory according to which cells have to be hit by ionizing particles to elicit an important biological response, including cell death. In cancer therapy, the Poisson law and linear quadratic mathematical models have been used to describe the probability of hits per cell as a function of the radiation dose. Recent Advances: However, in the last 20 years, many studies have shown that radiation generates "danger" signals that propagate from irradiated to nonirradiated cells, leading to bystander and other off-target effects.

CRITICAL ISSUES

Like for targeted effects, redox mechanisms play a key role also in off-target effects through transmission of ROS and reactive nitrogen species (RNS), and also of cytokines, ATP, and extracellular DNA. Particularly, nuclear factor kappa B is essential for triggering self-sustained production of ROS and RNS, thus making the bystander response similar to inflammation. In some therapeutic cases, this phenomenon is associated with recruitment of immune cells that are involved in distant irradiation effects (called "away-from-target" i.e., abscopal effects).

FUTURE DIRECTIONS

Determining the contribution of targeted and off-target effects in the clinic is still challenging. This has important consequences not only in radiotherapy but also possibly in diagnostic procedures and in radiation protection.

The Optimal Radiation Dose to Induce Robust Systemic Anti-Tumor Immunity

The synergy of radiation and the immune system is currently receiving significant attention in oncology as numerous studies have shown that cancer irradiation can induce strong anti-tumor immune responses. It remains unclear, however, what are the best radiation fractionation protocols to maximize the therapeutic benefits of this synergy. Here, we present a novel mathematical model that can be used to predict and dissect the complexity of the immune-mediated response at multiple tumor sites after applying focal irradiation and systemic immunotherapy. We successfully calibrate the proposed framework with published experimental data, in which two tumors were grown in mice at two spatially-separated sites from which only one was irradiated using various radiation fractionation protocols with and without concurrent systemic immunotherapy. The proposed model is calibrated to fit the temporal dynamics of tumor volume at both sites and can predict changes in immune infiltration in the non-irradiated tumors. The model was then used to investigate additional radiation fractionation protocols. Model simulations suggest that the optimal radiation doses per fraction to maximize anti-tumor immunity are between 10 and 13 Gy, at least for the experimental setting used for model calibration. This work provides the framework for evaluating radiation fractionation protocols for radiation-induced immune-mediated systemic anti-tumor responses.

DNA damage response (DDR) and senescence: shuttled inflamma-miRNAs on the stage of inflamm-aging

A major issue in aging research is how cellular phenomena affect aging at the systemic level. Emerging evidence suggests that DNA damage response (DDR) signaling is a key mechanism linking DNA damage accumulation, cell senescence, and organism aging. DDR activation in senescent cells promotes acquisition of a proinflammatory secretory phenotype (SASP), which in turn elicits DDR and SASP activation in neighboring cells, thereby creating a proinflammatory environment extending at the local and eventually the systemic level. DDR activation is triggered by genomic lesions as well as emerging bacterial and viral metagenomes. Therefore, the buildup of cells with an activated DDR probably fuels inflamm-aging and predisposes to the development of the major age-related diseases (ARDs). Micro (mi)-RNAs - non-coding RNAs involved in gene expression modulation - are released locally and systemically by a variety of shuttles (exosomes, lipoproteins, proteins) that likely affect the efficiency of their biological effects. Here we suggest that some miRNAs, previously found to be associated with inflammation and senescence - miR-146, miR-155, and miR-21 - play a central role in the interplay among DDR, cell senescence and inflamm-aging. The identification of the functions of shuttled senescence-associated miRNAs is expected to shed light on the aging process and on how to delay ARD development.