Cell lines of the same anatomic site and histologic type show large variability in intrinsic radiosensitivity and relative biological effectiveness to protons and carbon ions

Most DNA repair defects do not modify the relationship between relative biological effectiveness and linear energy transfer in CRISPR-edited cells

BACKGROUND

Cancer is a highly heterogeneous disease, driven by frequent genetic alterations which have significant effects on radiosensitivity. However, radiotherapy for a given cancer type is typically given with a standard dose determined from population-level trials. As a result, a proportion of patients are under- or over-dosed, reducing the clinical benefit of radiotherapy. Biological optimization would not only allow individual dose prescription but also a more efficient allocation of limited resources, such as proton and carbon ion therapy. Proton and ion radiotherapy offer an advantage over photons due to their elevated Relative Biological Effectiveness (RBE) resulting from their elevated Linear Energy Transfer (LET). Despite significant interest in optimizing LET by tailoring radiotherapy plans, RBE's genetic dependence remains unclear.

PURPOSE

The aim of this study is to better define the RBE/LET relationship in a panel of cell lines with different defects in DSB repair pathways, but otherwise identical biological features and genetic background to isolate these effects.

METHODS

Normal human cells (RPE1), genetically modified to introduce defects in DNA double-strand break (DSB) repair genes, ATM, BRCA1, DCLRE1C, LIG4, PRKDC and TP53, were used to map the RBE-LET relationship. Cell survival was measured with clonogenic assays after exposure to photons, protons (LET 1 and 12 keV/µm) and alpha particles (129 keV/µm). Gene knockout sensitizer enhancement ratio (SER) values were calculated as the ratio of the mean inactivation dose (MID) of wild-type cells to repair-deficient cells, and RBE values were calculated as the ratio of the MID of X-ray and particle irradiated cells. 53BP1 foci were used to quantify radiation-induced DSBs and their repair following irradiation.

RESULTS

Deletion of NHEJ genes had the greatest impact on photon sensitivity (ATM-/- SER = 2.0 and Lig4-/- SER = 1.8), with genes associated with HR having smaller effects (BRCA1-/- SER = 1.2). Wild-type cells showed RBEs of 1.1, 1.3, 5.0 for low- and high-LET protons and alpha particles respectively. SERs for different genes were independent of LET, apart from NHEJ knockouts which proved to be markedly hypersensitive across all tested LETs. Due to this hypersensitivity, the impact of high LET was reduced in cell models lacking the NHEJ repair pathway. HR-defective cells had moderately increased sensitivity across all tested LETs, but, notably, the contribution of HR pathway to survival appeared independent of LET. Analysis of 53BP1 foci shows that NHEJ-defective cells had the least DSB repair capacity after low LET exposure, and no visible repair after high LET exposure. HR-defective cells also had slower repair kinetics, but the impact of HR defects is not as severe as NHEJ defects.

CONCLUSIONS

DSB repair defects, particularly in NHEJ, conferred significant radiosensitivity across all LETs. This sensitization appeared independent of LET, suggesting that the contribution of different DNA repair pathways to survival does not depend on radiation quality.

Experimental Setups for In Vitro Studies on Radon Exposure in Mammalian Cells-A Critical Overview

Naturally occurring radon and its short lived progeny are the second leading cause of lung cancer after smoking, and the main risk factor for non-smokers. The radon progeny, mainly Polonium-218 (²¹⁸Po) and Polonium-214 (²¹⁴Po), are responsible for the highest dose deposition in the bronchial epithelium via alpha-decay. These alpha-particles release a large amount of energy over a short penetration range, which results in severe and complex DNA damage. In order to unravel the underlying biological mechanisms which are triggered by this complex DNA damage and eventually give rise to carcinogenesis, in vitro radiobiology experiments on mammalian cells have been performed using radon exposure setups, or radon analogues, which mimic alpha-particle exposure. This review provides an overview of the different experimental setups, which have been developed and used over the past decades for in vitro radon experiments. In order to guarantee reliable results, the design and dosimetry of these setups require careful consideration, which will be emphasized in this work. Results of these in vitro experiments, particularly on bronchial epithelial cells, can provide valuable information on biomarkers, which can assist to identify exposures, as well as to study the effects of localized high dose depositions and the heterogeneous dose distribution of radon.

Effects of spatial variation in dose delivery: what can we learn from radon-related lung cancer studies?

Exposure to radon progeny results in heterogeneous dose distributions in many different spatial scales. The aim of this review is to provide an overview on the state of the art in epidemiology, clinical observations, cell biology, dosimetry, and modelling related to radon exposure and its association with lung cancer, along with priorities for future research. Particular attention is paid on the effects of spatial variation in dose delivery within the organs, a factor not considered in radiation protection. It is concluded that a multidisciplinary approach is required to improve risk assessment and mechanistic understanding of carcinogenesis related to radon exposure. To achieve these goals, important steps would be to clarify whether radon can cause other diseases than lung cancer, and to investigate radon-related health risks in children or persons at young ages. Also, a better understanding of the combined effects of radon and smoking is needed, which can be achieved by integrating epidemiological, clinical, pathological, and molecular oncology data to obtain a radon-associated signature. While in vitro models derived from primary human bronchial epithelial cells can help to identify new and corroborate existing biomarkers, they also allow to study the effects of heterogeneous dose distributions including the effects of locally high doses. These novel approaches can provide valuable input and validation data for mathematical models for risk assessment. These models can be applied to quantitatively translate the knowledge obtained from radon exposure to other exposures resulting in heterogeneous dose distributions within an organ to support radiation protection in general.

Targeted Inhibition of DNA-PKcs, ATM, ATR, PARP, and Rad51 Modulate Response to X Rays and Protons

Small molecule inhibitors are currently in preclinical and clinical development for the treatment of selected cancers, particularly those with existing genetic alterations in DNA repair and DNA damage response (DDR) pathways. Keen interest has also been expressed in combining such agents with other targeted antitumor strategies such as radiotherapy. Radiotherapy exerts its cytotoxic effects primarily through DNA damage-induced cell death; therefore, inhibiting DNA repair and the DDR should lead to additive and/or synergistic radiosensitizing effects. In this study we screened the response to X-ray or proton radiation in cell lines treated with DDR inhibitors (DDRis) targeting ATM, ATR, DNA-PKcs, Rad51, and PARP, with survival metrics established using clonogenic assays. We observed that DDRis generate significant radiosensitization in cancer and primary cells derived from normal tissue. Existing genetic defects in cancer cells appear to be an important consideration when determining the optimal inhibitor to use for synergistic combination with radiation. We also show that while greater radiosensitization can be achieved with protons (9.9 keV/µm) combined with DDRis, the relative biological effectiveness is unchanged or in some cases reduced. Our results indicate that while targeting the DDR can significantly radiosensitize cancer cells to such combinations, normal cells may also be equally or more severely affected, depending on the DDRi used. These data highlight the importance of identifying genetic defects as predictive biomarkers of response for combination treatment.

Effect of boron compounds on the biological effectiveness of proton therapy

PURPOSE

We assessed whether adding sodium borocaptate (BSH) or 4-borono-l-phenylalanine (BPA) to cells irradiated with proton beams influenced the biological effectiveness of those beams against prostate cancer cells to investigate if the alpha particles generated through proton-boron nuclear reactions would be sufficient to enhance the biological effectiveness of the proton beams.

METHODS

We measured clonogenic survival in DU145 cells treated with 80.4-ppm BSH or 86.9-ppm BPA, or their respective vehicles, after irradiation with 6-MV X-rays, 1.2-keV/μm (low linear energy transfer [LET]) protons, or 9.9-keV/μm (high-LET) protons. We also measured γH2AX and 53BP1 foci in treated cells at 1 and 24 h after irradiation with the same conditions.

RESULTS

We found that BSH radiosensitized DU145 cells across all radiation types. However, no difference was found in relative radiosensitization, characterized by the sensitization enhancement ratio or the relative biological effectiveness, for vehicle- versus BSH-treated cells. No differences were found in numbers of γH2AX or 53BP1 foci or γH2AX/53BP1 colocalized foci for vehicle- versus BSH-treated cells across radiation types. BPA did not radiosensitize DU145 cells nor induced any significant differences when comparing vehicle- versus BPA-treated cells for clonogenic cell survival or γH2AX and 53BP1 foci or γH2AX/53BP1 colocalized foci.

CONCLUSIONS

Treatment with 11 B, at concentrations of 80.4 ppm from BSH or 86.9 ppm from BPA, had no effect on the biological effectiveness of proton beams in DU145 prostate cancer cells. Our results agree with published theoretical calculations indicating that the contribution of alpha particles from such reactions to the total absorbed dose and biological effectiveness is negligible. We also found that BSH radiosensitized DU145 cells to X-rays, low-LET protons, and high-LET protons but that the radiosensitization was not related to DNA damage.

An empirical model of proton RBE based on the linear correlation between x-ray and proton radiosensitivity

BACKGROUND

Proton relative biological effectiveness (RBE) is known to depend on physical factors of the proton beam, such as its linear energy transfer (LET), as well as on cell-line specific biological factors, such as their ability to repair DNA damage. However, in a clinical setting, proton RBE is still considered to have a fixed value of 1.1 despite the existence of several empirical models that can predict proton RBE based on how a cell's survival curve (linear-quadratic model [LQM]) parameters α and β vary with the LET of the proton beam. Part of the hesitation to incorporate variable RBE models in the clinic is due to the great noise in the biological datasets on which these models are trained, often making it unclear which model, if any, provides sufficiently accurate RBE predictions to warrant a departure from RBE = 1.1.

PURPOSE

Here, we introduce a novel model of proton RBE based on how a cell's intrinsic radiosensitivity varies with LET, rather than its LQM parameters.

METHODS AND MATERIALS

We performed clonogenic cell survival assays for eight cell lines exposed to 6 MV x-rays and 1.2, 2.6, or 9.9 keV/µm protons, and combined our measurements with published survival data (n = 397 total cell line/LET combinations). We characterized how radiosensitivity metrics of the form DSF% , (the dose required to achieve survival fraction [SF], e.g., D10% ) varied with proton LET, and calculated the Bayesian information criteria associated with different LET-dependent functions to determine which functions best described the underlying trends. This allowed us to construct a six-parameter model that predicts cells' proton survival curves based on the LET dependence of their radiosensitivity, rather than the LET dependence of the LQM parameters themselves. We compared the accuracy of our model to previously established empirical proton RBE models, and implemented our model within a clinical treatment plan evaluation workflow to demonstrate its feasibility in a clinical setting.

RESULTS

Our analyses of the trends in the data show that DSF% is linearly correlated between x-rays and protons, regardless of the choice of the survival level (e.g., D10% , D37% , or D50% are similarly correlated), and that the slope and intercept of these correlations vary with proton LET. The model we constructed based on these trends predicts proton RBE within 15%-30% at the 68.3% confidence level and offers a more accurate general description of the experimental data than previously published empirical models. In the context of a clinical treatment plan, our model generally predicted higher RBE-weighted doses than the other empirical models, with RBE-weighted doses in the distal portion of the field being up to 50.7% higher than the planned RBE-weighted doses (RBE = 1.1) to the tumor.

CONCLUSIONS

We established a new empirical proton RBE model that is more accurate than previous empirical models, and that predicts much higher RBE values in the distal edge of clinical proton beams.