Intrinsic Radiosensitivity Research Articles

Inhibition of Phosphoglycerate Dehydrogenase Radiosensitizes Human Colorectal Cancer Cells under Hypoxic Conditions.

Simple SummaryColorectal cancer is the third most prevalent cancer worldwide. Treatment options for these patients consist of surgery combined with chemotherapy and/or radiotherapy. However, a subset of tumors will not respond to therapy or acquire resistance during the course of the treatment, leading to patient relapse. The interplay between reprogramming cancer metabolism and radiotherapy has become an appealing strategy to improve a patient’s outcome. Due to the overexpression of certain enzymes in a variety of cancer types, including colorectal cancer, the serine synthesis pathway has recently become an attractive metabolic target. We demonstrated that by inhibiting the first enzyme of this pathway, namely phosphoglycerate dehydrogenase (PHGDH), tumor cells that are deprived of oxygen (as is generally the case in solid tumors) respond better to radiation, leading to increased tumor cell killing in an experimental model of human colorectal cancer. Augmented de novo serine synthesis activity is increasingly apparent in distinct types of cancers and has mainly sparked interest by investigation of phosphoglycerate dehydrogenase (PHGDH). Overexpression of PHGDH has been associated with higher tumor grade, shorter relapse time and decreased overall survival. It is well known that therapeutic outcomes in cancer patients can be improved by reprogramming metabolic pathways in combination with standard treatment options, for example, radiotherapy. In this study, possible metabolic changes related to radioresponse were explored upon PHGDH inhibition. Additionally, we evaluated whether PHGDH inhibition could improve radioresponse in human colorectal cancer cell lines in both aerobic and radiobiological relevant hypoxic conditions. Dysregulation of reactive oxygen species (ROS) homeostasis and dysfunction in mitochondrial energy metabolism and oxygen consumption rate were indicative of potential radiomodulatory effects. We demonstrated that PHGDH inhibition radiosensitized hypoxic human colorectal cancer cells while leaving intrinsic radiosensitivity unaffected. In a xenograft model, the first hints of additive effects between PHGDH inhibition and radiotherapy were demonstrated. In conclusion, this study is the first to show that modulation of de novo serine biosynthesis enhances radioresponse in hypoxic colorectal cancer cells, mainly mediated by increased levels of intracellular ROS.

Radioimmunotherapy in HPV-Associated Head and Neck Squamous Cell Carcinoma.

HPV-associated head and neck squamous cell carcinoma (HNSCC) is a cancer entity with unique biological and clinical characteristics that requires more personalized treatment strategies. As the backbone of conventional therapeutics, radiation is now harnessed to synergize with immunotherapy in multiple malignancies. Accumulating preclinical and clinical data have suggested the potential of radioimmunotherapy in eliciting local and systemic anti-tumor response via direct killing of tumor cells and immunogenic cell death. However, this effect remains uncertain in HPV-associated HNSCC. Owing to its intrinsic radiosensitivity and distinct tumor microenvironment, HPV-associated HNSCC may represent a good candidate for radioimmunotherapy. In this review, we provide a detailed illustration of the biology, the genomic features, and immune landscapes of HPV-associated HNSCC that support the synergism between radiation and immune agents. The interaction between radiotherapy and immunotherapy is described. We also highlight the present evidence as well as ongoing trials using different combination strategies in the recurrent/metastatic or definitive settings. In addition, we have summarized the challenges and outlook for future trial design, with special emphasis on radiotherapy optimization and novel therapeutic options to incorporate.

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

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. 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. We performed clonogenic cell survival assays for eight cell lines exposed to 6 MV x-rays and 1.2, 2.6, or 9.9keV/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. 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. 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.

Epigenetic-Like Stimulation of Receptor Expression in SSTR2 Transfected HEK293 Cells as a New Therapeutic Strategy.

Simple SummaryNeuroendocrine tumors (NETs) expressing the somatostatin receptor subtype 2 (SSTR2) are promising targets for peptide receptor radionuclide therapy (PRRT) using the somatostatin analogue Lu-177-DOTATATE. Patients expressing low levels of SSTR2 do not benefit from PRRT. Therefore, an approach to increase the efficacy of PRRT utilizing the effects of 5-aza-2′-deoxycytidine (5-aza-dC) and valproic acid (VPA) on the SSTR2 expression levels is investigated. The cell lines HEKsst2 and PC3 are incubated with 5-aza-dC and VPA in different combinations. The drug pretreatment of HEKsst2 cells leads to increased Lu-177-DOTATATE uptake values (factor 28) and lower cell survival (factor 4) in comparison to unstimulated cells; in PC3 cells, the effects are negligible. Further, for the stimulated cell types, the maintenance of the intrinsic radiosensitivity in each cell type is confirmed by X-ray irradiation. The increased SSTR2 expression induced by VPA and 5-aza-dC stimulation in HEKsst2 cells might improve treatment strategies for patients with NETs.The aim of the study was to increase the uptake of the SSTR2-targeted radioligand Lu-177-DOTATATE using the DNA methyltransferase inhibitor (DNMTi) 5-aza-2′-deoxycytidine (5-aza-dC) and the histone deacetylase inhibitor (HDACi) valproic acid (VPA). The HEKsst2 and PC3 cells were incubated with variable concentrations of 5-aza-dC and VPA to investigate the uptake of Lu-177-DOTATATE. Cell survival, subsequent to external X-rays (0.6 or 1.2 Gy) and a 24 h incubation with 57.5 or 136 kBq/mL Lu-177-DOTATATE, was investigated via colony formation assay to examine the effect of the epidrugs. In the case of stimulated HEKsst2 cells, the uptake of Lu-177-DOTATATE increased by a factor of 28 in comparison to the unstimulated cells. Further, stimulated HEKsst2 cells demonstrated lower survival fractions (factor 4). The survival fractions of the PC3 cells remained almost unchanged. VPA and 5-aza-dC did not induce changes to the intrinsic radiosensitivity of the cells after X-ray irradiation. Clear stimulatory effects on HEKsst2 cells were demonstrated by increased cell uptake of the radioligand and enhanced SST2 receptor quantity. In conclusion, the investigated approach is suitable to stimulate the somatostatin receptor expression and thus the uptake of Lu-177-DOTATATE, enabling a more efficient treatment for patients with poor response to peptide radionuclide therapy (PRRT).

Predicting acute severe toxicity for head and neck squamous cell carcinomas by combining dosimetry with a radiosensitivity biomarker: a pilot study.

Radiotherapy (RT) against head and neck squamous cell carcinomas (HNSCC) may lead to severe toxicity in 30-40% of patients. The normal tissue complication probability (NTCP) models, based on dosimetric data refined the normal tissue dose/volume tolerance guidelines. In parallel, the radiation-induced nucleoshuttling (RIANS) of the Ataxia-Telangiectasia Mutated protein (pATM) is a predictive approach of individual intrinsic radiosensitivity. Here, we combined NTCP with RADIODTECT©, a blood assay derived from the RIANS model, to predict RT toxicity in HNSCC patients. RADIODTECT© cutoff values (i.e. 57.8 ng/mL for grade⩾2 toxicity and 46 ng/mL for grade⩾3 toxicity) have been previously assessed. Validation was performed on a prospective cohort of 36 HNSCC patients treated with postoperative RT. Toxicity was graded with the Common Terminology Criteria for Adverse Events (CTCAE) scale and two criteria were considered: grade⩾2 oral mucositis (OM2), grade⩾3 mucositis (OM3) and grade⩾2 dysphagia (DY2), grade⩾3 dysphagia (DY3). pATM quantification was assessed in lymphocytes of HNSCC patients. The discrimination power of the pATM assay was evaluated through the Area Under the Receiver Operator Characteristics Curve (AUC-ROC). Two previously described NTCP models were considered, including the dose to the oral cavity and the mean dose to the parotid glands (OM2 and OM3) and the dose to the oral cavity, to the larynx and the volume of pharyngeal constrictor muscles (DY2 and DY3). Combining NTCP models with RADIODTECT© blood test improved the AUC-ROC. Considering the prediction of mucositis, AUC-ROCNTCP+RADIODTECT©=0.80 was for OM2, and AUC-ROCNTCP+RADIODTECT©=0.78 for OM3. Considering the prediction of acute dysphagia, AUC-ROCNTCP+RADIODTECT©=0.71 for DY2 and for DY3. Combining NTCP models with a radiosensitivity biomarker might significantly improve the prediction of toxicities for HNSCC patients.

SBRT for Localized Prostate Cancer: CyberKnife vs. VMAT-FFF, a Dosimetric Study.

In recent years, stereotactic body radiation therapy (SBRT) has gained popularity among clinical methods for the treatment of medium and low risk prostate cancer (PCa), mainly as an alternative to surgery. The hypo-fractionated regimen allows the administration of high doses of radiation in a small number of fractions; such a fractionation is possible by exploiting the different intrinsic prostate radiosensitivity compared with the surrounding healthy tissues. In addition, SBRT treatment guaranteed a better quality of life compared with surgery, avoiding risks, aftermaths, and possible complications. At present, most stereotactic prostate treatments are performed with the CyberKnife (CK) system, which is an accelerator exclusively dedicated for stereotaxis and it is not widely spread in every radiotherapy centre like a classic linear accelerator (LINAC). To be fair, a stereotactic treatment is achievable also by using a LINAC through Volumetric Modulated Arc Therapy (VMAT), but some precautions must be taken. The aim of this work is to carry out a dosimetric comparison between these two methodologies. In order to pursue such a goal, two groups of patients were selected at Instituto Nazionale Tumori—IRCCS Fondazione G. Pascale: the first group consisting of ten patients previously treated with a SBRT performed with CK; the second one was composed of ten patients who received a hypo-fractionated VMAT treatment and replanned in VMAT-SBRT flattening filter free mode (FFF). The two SBRT techniques were rescaled at the same target coverage and compared by normal tissue sparing, dose distribution parameters and delivery time. All organs at risk (OAR) constraints were achieved by both platforms. CK exhibits higher performances in terms of dose delivery; nevertheless, the general satisfying dosimetric results and the significantly shorter delivery time make VMAT-FFF an attractive and reasonable alternative SBRT technique for the treatment of localized prostate cancer.

A Six-Gene Prognostic and Predictive Radiotherapy-Based Signature for Early and Locally Advanced Stages in Non-Small-Cell Lung Cancer.

Simple SummaryThe search for prognostic and/or predictive gene signatures of the response to radiotherapy treatment can significantly aid clinical decision making. These signatures can condition the fractionation, the total dose to be administered, and/or the combination of systemic treatments and radiation. The ultimate goal is to achieve better clinical results, as well as to minimize the adverse effects associated with current cancer therapies. To this end, we analyzed the intrinsic radiosensitivity of 15 NSCLC lines and found the differences in gene expression levels between radiosensitive and radioresistant lines, resulting in a potentially applicable six-gene signature in NSCLC patients. The six-gene signature had the ability to predict overall survival and progression-free survival (PFS), which could translate into a prediction of the response to the cancer treatment received.Non-small-cell lung cancer (NSCLC) is the leading cause of cancer death worldwide, generating an enormous economic and social impact that has not stopped growing in recent years. Cancer treatment for this neoplasm usually includes surgery, chemotherapy, molecular targeted treatments, and ionizing radiation. The prognosis in terms of overall survival (OS) and the disparate therapeutic responses among patients can be explained, to a great extent, by the existence of widely heterogeneous molecular profiles. The main objective of this study was to identify prognostic and predictive gene signatures of response to cancer treatment involving radiotherapy, which could help in making therapeutic decisions in patients with NSCLC. To achieve this, we took as a reference the differential gene expression pattern among commercial cell lines, differentiated by their response profile to ionizing radiation (radiosensitive versus radioresistant lines), and extrapolated these results to a cohort of 107 patients with NSCLC who had received radiotherapy (among other therapies). We obtained a six-gene signature (APOBEC3B, GOLM1, FAM117A, KCNQ1OT1, PCDHB2, and USP43) with the ability to predict overall survival and progression-free survival (PFS), which could translate into a prediction of the response to the cancer treatment received. Patients who had an unfavorable prognostic signature had a median OS of 24.13 months versus 71.47 months for those with a favorable signature, and the median PFS was 12.65 months versus 47.11 months, respectively. We also carried out a univariate analysis of multiple clinical and pathological variables and a bivariate analysis by Cox regression without any factors that substantially modified the HR value of the proposed gene signature.

RadSigBench: a framework for benchmarking functional genomics signatures of cancer cell radiosensitivity.

Multiple transcriptomic predictors of tumour cell radiosensitivity (RS) have been proposed, but they have not been benchmarked against one another or to control models. To address this, we present RadSigBench, a comprehensive benchmarking framework for RS signatures. The approach compares candidate models to those developed from randomly resampled control signatures and from cellular processes integral to the radiation response. Robust evaluation of signature accuracy, both overall and for individual tissues, is performed. The NCI60 and Cancer Cell Line Encyclopaedia datasets are integrated into our workflow. Prediction of two measures of RS is assessed: survival fraction after 2 Gy and mean inactivation dose. We apply the RadSigBench framework to seven prominent published signatures of radiation sensitivity and test for equivalence to control signatures. The mean out-of-sample R2 for the published models on test data was very poor at 0.01 (range: −0.05 to 0.09) for Cancer Cell Line Encyclopedia and 0.00 (range: −0.19 to 0.19) in the NCI60 data. The accuracy of both published and cellular process signatures investigated was equivalent to the resampled controls, suggesting that these signatures contain limited radiation-specific information. Enhanced modelling strategies are needed for effective prediction of intrinsic RS to inform clinical treatment regimes. We make recommendations for methodological improvements, for example the inclusion of perturbation data, multiomics, advanced machine learning and mechanistic modelling. Our validation framework provides for robust performance assessment of ongoing developments in intrinsic RS prediction.

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 in gene expression at the level of transcription and translation, including those regulated by microRNAs (miRNAs), play a role in the 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 that 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 in 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.

The Role of Patient- and Treatment-Related Factors and Early Functional Imaging in Late Radiation-Induced Xerostomia in Oropharyngeal Cancer Patients.

Simple SummaryIn the present prospective study, we assessed the role of various Magnetic Resonance Imaging biomarkers combined with self-assessed xerostomia questionnaires and patient- and treatment-related factors, in predicting xerostomia at 12 months after chemoradiotherapy for oropharyngeal squamous cell carcinoma. We hypothesized that the integration of pre-treatment imaging biomarkers, which addresses the tissue heterogeneity and individual variations among patients, could improve the accuracy of conventional prediction models that are based only on dose information, ultimately providing a better understanding of the pathophysiological mechanisms underlying radiation induced salivary dysfunction. The implementation of multifactorial models, driven by machine learning algorithms, may improve prediction accuracy of radiation-induced toxicity and tailor individual treatment options for patients.The advent of quantitative imaging in personalized radiotherapy (RT) has offered the opportunity for a better understanding of individual variations in intrinsic radiosensitivity. We aimed to assess the role of magnetic resonance imaging (MRI) biomarkers, patient-related factors, and treatment-related factors in predicting xerostomia 12 months after RT (XER12) in patients affected by oropharyngeal squamous cell carcinoma (OSCC). Patients with locally advanced OSCC underwent diffusion-weighted imaging (DWI) and dynamic-contrast enhanced MRI at baseline; DWI was repeated at the 10th fraction of RT. The Radiation Therapy Oncology Group (RTOG) toxicity scale was used to evaluate salivary gland toxicity. Xerostomia-related questionnaires (XQs) were administered weekly during and after RT. RTOG toxicity ≥ grade 2 at XER12 was considered as endpoint to build prediction models. A Decision Tree classification learner was applied to build the prediction models following a five-fold cross-validation. Of the 89 patients enrolled, 63 were eligible for analysis. Thirty-six (57.1%) and 21 (33.3%) patients developed grade 1 and grade 2 XER12, respectively. Including only baseline variables, the model based on DCE-MRI and V65 (%) (volume of both glands receiving doses ≥ 65 Gy) had a fair accuracy (77%, 95% CI: 66.5–85.4%). The model based on V65 (%) and XQ-Intmid (integral of acute XQ scores from the start to the middle of RT) reached the best accuracy (81%, 95% CI: 71–88.7%). In conclusion, non-invasive biomarkers from DCE-MRI, in combination with dosimetric variables and self-assessed acute XQ scores during treatment may help predict grade 2 XER12 with a fair to good accuracy.

Normal tissue complication probability modeling to guide individual treatment planning in pediatric cranial proton and photon radiotherapy.

Proton therapy (PT) is broadly accepted as the gold standard of care for pediatric patients with cranial cancer. The superior dose distribution of PT compared to photon radiotherapy reduces normal tissue complication probability (NTCP) for organs at risk. As NTCPs for pediatric organs are not well understood, clinics generally base radiation response on adult data. However, there is evidence that radiation response strongly depends on the age and even sex of a patient. Furthermore, questions surround the influence of individual intrinsic radiosensitivity (α/β ratio) on pediatric NTCP. While the clinical pediatric NTCP data is scarce, radiobiological modeling and sensitivity analyses can be used to investigate the NTCP trends and its dependence on individual modeling parameters. The purpose of this study was to perform sensitivity analyses of NTCP models to ascertain the dependence of radiosensitivity, sex, and age of a child and predict cranial side-effects following intensity-modulated proton therapy (IMPT) and intensity-modulated radiotherapy (IMRT). Previously, six sex-matched pediatric cranial datasets (5, 9, and 13 years old) were planned in Varian Eclipse treatment planning system (13.7). Up to 108 scanning beam IMPT plans and 108 IMRT plans were retrospectively optimized for a range of simulated target volumes and locations. In this work, dose-volume histograms were extracted and imported into BioSuite Software for radiobiological modeling. Relative-Seriality and Lyman-Kutcher-Burman models were used to calculate NTCP values for toxicity endpoints, where TD50, (based on reported adult clinical data) was varied to simulate sex dependence of NTCP. Plausible parameter ranges, based on published literature for adults, were used in modeling. In addition to sensitivity analyses, a 20% difference in TD50 was used to represent the radiosensitivity between the sexes (with females considered more radiosensitive) for ease of data comparison as a function of parameters such as α/β ratio. IMPT plans resulted in lower NTCP compared to IMRT across all models (p<0.0001). For medulloblastoma treatment, the risk of brainstem necrosis (> 10%) and cochlea tinnitus (>20%) among females could potentially be underestimated considering a lower TD50 value for females. Sensitivity analyses show that the difference in NTCP between sexes was significant (p<0.0001). Similarly, both brainstem necrosis and cochlea tinnitus NTCP varied significantly (p<0.0001) across tested α/β as a function of TD50 values (assumption being that TD50 values are 20% lower in females). If the true α/β of these pediatric tissues is higher than expected (α/β ∼ 3), the risk of tinnitus for IMRT can significantly increase (p<0.0001). Due to the scarcity of pediatric NTCP data available, sensitivity analyses were performed using plausible ranges based on published adult data. In the clinical scenario where, if female pediatric patients were 20% more radiosensitive (lower TD50 value), they could be up to twice as likely to experience side-effects of brainstem necrosis and cochlea tinnitus compared to males, highlighting the need for considering the sex in NTCP models. Based on our sensitivity analyses, age and sex of a pediatric patient could significantly affect the resultant NTCP from cranial radiotherapy, especially at higher α/β values.

Opposite effects of the triple target (DNA-PK/PI3K/mTOR) inhibitor PI-103 on the radiation sensitivity of glioblastoma cell lines proficient and deficient in DNA-PKcs

BackgroundRadiotherapy is routinely used to combat glioblastoma (GBM). However, the treatment efficacy is often limited by the radioresistance of GBM cells.MethodsTwo GBM lines MO59K and MO59J, differing in intrinsic radiosensitivity and mutational status of DNA-PK and ATM, were analyzed regarding their response to DNA-PK/PI3K/mTOR inhibition by PI-103 in combination with radiation. To this end we assessed colony-forming ability, induction and repair of DNA damage by γH2AX and 53BP1, expression of marker proteins, including those belonging to NHEJ and HR repair pathways, degree of apoptosis, autophagy, and cell cycle alterations.ResultsWe found that PI-103 radiosensitized MO59K cells but, surprisingly, it induced radiation resistance in MO59J cells. Treatment of MO59K cells with PI-103 lead to protraction of the DNA damage repair as compared to drug-free irradiated cells. In PI-103-treated and irradiated MO59J cells the foci numbers of both proteins was higher than in the drug-free samples, but a large portion of DNA damage was quickly repaired. Another cell line-specific difference includes diminished expression of p53 in MO59J cells, which was further reduced by PI-103. Additionally, PI-103-treated MO59K cells exhibited an increased expression of the apoptosis marker cleaved PARP and increased subG1 fraction. Moreover, irradiation induced a strong G2 arrest in MO59J cells (~ 80% vs. ~ 50% in MO59K), which was, however, partially reduced in the presence of PI-103. In contrast, treatment with PI-103 increased the G2 fraction in irradiated MO59K cells.ConclusionsThe triple-target inhibitor PI-103 exerted radiosensitization on MO59K cells, but, unexpectedly, caused radioresistance in the MO59J line, lacking DNA-PK. The difference is most likely due to low expression of the DNA-PK substrate p53 in MO59J cells, which was further reduced by PI-103. This led to less apoptosis as compared to drug-free MO59J cells and enhanced survival via partially abolished cell-cycle arrest. The findings suggest that the lack of DNA-PK-dependent NHEJ in MO59J line might be compensated by DNA-PK independent DSB repair via a yet unknown mechanism.

Stereotactic Body Radiotherapy in Oligomestatic/Oligoprogressive Sarcoma: Safety and Effectiveness Beyond Intrinsic Radiosensitivity.

Metastatic soft tissue sarcoma (STS) patients may benefit from local ablative treatments due to modest efficacy of systemic chemotherapy. However, use of stereotactic body radiotherapy (SBRT) is controversial because of presumed radioresistance of STS. Patients treated with SBRT for oligometastatic and oligoprogressive metastatic STS were retrospectively reviewed to assess results in terms of local control (LC), disease-free survival (DFS), and overall survival (OS). Incidence and grade of adverse events were reported. Statistical analysis was performed to identify variables correlated with outcome and toxicity. Forty patients were treated with SBRT to a median biologic effective dose (BED) of 105 (66-305) Gy5 to 77 metastases. Two-year LC, DFS, and OS were 67%, 23%, and 40%. Improved LC was shown in patients receiving a BED >150 Gy5 (hazard ratio [HR], 3.9; 95% confidence interval [CI], 1.6-9.7; P = 0.028). A delay >24 months between primary tumor diagnosis and onset of metastases was associated with improved DFS (HR, 0.46; 95% CI, 0.22-0.96; P = 0.01) and OS (HR, 0.48; 95% CI, 0.23-0.99; P = 0.03). No toxicity grade ≥3 was observed. Stereotactic body radiotherapy is effective in metastatic STS with a benign toxicity profile. A BED >150 Gy5 is required to maximize tumor control rates. Metastatic relapse >24 months after diagnosis is correlated to improved survival.

Radiosensitivity, Immune Activation, and Mutational Frequency of Melanoma Metastases Across Tissue Types

<h3>Purpose/Objective(s)</h3> Melanoma is a more radioresistant and immunogenic histology, associated with a higher mutational burden. However, the influence of metastasis tissue location is unknown. We hypothesize exploiting these differences may allow therapy personalization. <h3>Materials/Methods</h3> We identified metastatic melanoma samples across 6 tissues (brain, liver, lung, lymph node [LN], skin, soft tissue [ST]), which were profiled for gene expression by microarray chips. Intrinsic radiosensitivity was estimated by the radiosensitivity index (RSI), a rank-based gene expression signature, where a higher RSI (scale 0-1) indicates greater radioresistance, with a cut point of 0.375 in other histologies. Degree of inflammation in the microenvironment was calculated by an existing 12-gene chemokine signature (12CK) where a higher 12CK score indicates greater inflammation. A subset (n = 94) underwent targeted exome sequencing (1,327 cancer-associated genes) and somatic mutations (MF) were enriched after filtering known germline/silent mutations and artifacts. Differences by tissue were analyzed with the Kruskal-Wallis H test. Correlations between RSI, 12CK, and MF were tested using Spearman's rho. <h3>Results</h3> From 1995 to 2011, 337 metastatic samples were identified from unique patients. Median age at diagnosis was 61 (range 20-97). With a median follow-up of 162 months (95% CI 142.6-181.4), median survival was 59.8 months (95% CI 49.2-70.4). Median values for RSI, 12CK, and MB were 0.451 (interquartile range [IQR] 0.331-0.552), 8.700 (IQR 7.218-9.746), and 101.5 (IQR 73.75-137), respectively. Significant differences existed among tissues for both RSI (<i>P</i> = 0.003) and 12CK (<i>P</i> < 0.001), but not MF (<i>P</i> = 0.498) (Table 1). No pair-wise comparisons were significant after Bonferroni correction for RSI, but for 12CK, Brain-ST (<i>P</i> = 0.044), Brain-Lung (<i>P</i> = 0.013), Brain-LN (<i>P</i> = 0.000), and Liver-LN (<i>P</i> = 0.023) were significant. Correlation between RSI and 12CK was significant (rho = -0.661, <i>P</i> < 0.001), but correlations between MB and RSI/12CK were not significant. <h3>Conclusion</h3> In this novel composite genomic analysis of melanoma metastases, all were relatively radioresistant, but higher RSI values for liver and skin metastases may warrant radiotherapy dose escalation. Similarly, the lower inflammatory scores of liver and brain metastases may have implications for selection of patients for immunotherapy. More inflamed tumors may be more responsive to radiation. In contrast to current homogenous approaches to metastases, these results indicate personalized approaches to types/sequencing of therapy for melanoma metastases by tissue type may be warranted.

Application of Hypoxia-Driven Dual-Reporter Model to Explore the Effect of Hypoxia on Radiosensitivity of Human Nasopharyngeal Carcinoma Cells

<h3>Purpose/Objective(s)</h3> hypoxia has been commonly observed in human nasopharyngeal carcinoma (NPC) which is associated with resistance to radiation and malignant phenotypes. The purpose of the study was to apply our build-in hypoxia-driven dual reporter model to explore the effect of hypoxia on radiosensitivity <b>in vitro</b> and <b>in vivo</b>. <h3>Materials/Methods</h3> The modalities to research the effect of hypoxia <b>in vitro</b> includes clonogenic survival assay and γH2AX foci formation. Tumor growth delay with radiation and/or cisplatin, imaging study on spatial biodistribution between blood perfusion (Hoechst 33342), endogenous (eGFP and CA9) and exogenous (pimonidazole) hypoxia markers were used to investigate the effect of hypoxia <b>in vivo</b>. <h3>Results</h3> The constructed hypoxia-driven dual-reporter model contains 9 repeats of hypoxia responsive element and fusion gene of 9xHRE-HSV1-TKeGFP in NPC cells (abbreviated as SUNE-1/HRE cells) in which hypoxia-induced molecular events can be visualized by fluorescence or nuclear imaging techniques. There is no difference in radiosensitivity between SUNE1/Parental and SUNE1/HRE cells, while cisplatin significantly increases radiosensitivity in both cell lines. γH2AX serves as a surrogate for unrepaired DSB. When the cells are exposed to 0.5% O₂, eGFP is observed only in SUNE1/HRE cells. DSB repair rate under hypoxia is similar in SUNE1/Parental and SUNE1/HRE cells. The number of γH2AX foci is dramatically higher in the presence of cisplatin compared to that given irradiation alone under the condition of normoxia or hypoxia. It indicates that the addition of cisplatin enhances radiosensitivity by compromising the ability of cells to repair DSB. Cisplatin alone shows modest whereas irradiation moderate effect on delayed tumor growth. Combined treatment of irradiation and cisplatin further enhances the effect on tumor growth delay. High expression of eGFP is observed in the nonperfused regions. The spatial biodistribution of hypoxia-induced expression of eGFP reporter gene is similar to other endogenous or exogenous hypoxia biomarkers, i.e., CA9 and pimonidazole. <h3>Conclusion</h3> The build-in hypoxia-driven dual reporter 9HRE-HSV1-TKeGFP hypoxia research model does not modify intrinsic radiosensitivity of SUNE1 cells under the condition of normoxia or hypoxia, suggesting it be used as preclinical model to explore the therapeutic efficacy of various treatment modalities to overcome hypoxia by fluorescence or nuclear imaging techniques.

Analysis of Soft Tissue Metastases Across Primary Histologies Comparing Radiosensitivity, Immune Infiltration, and Mutational Frequency

The soft tissues are a poorly studied subsite for metastases with unclear treatment paradigms. We hypothesize elucidating differences in these metastases by primary histology may allow for optimization of therapies.We isolated soft tissue metastases with microarray data. A subset also had data from a 1,327-gene targeted exome sequencing assay. An existing radiosensitivity index (RSI) was used to estimate intrinsic radiosensitivity, where higher values denote radioresistance (0-1), with a cutpoint of 0.375. An existing 12-gene chemokine signature (12CK) was used to measure the degree of microenvironment inflammation, where higher scores denote greater inflammation. Samples with exome data were enriched for somatic mutations by filtering out artifacts and known germline/silent mutations (MF). Differences by histology were evaluated by the Kruskal-Wallis H test. Correlations between RSI, 12CK, and MB were evaluated by Spearman's rho.Between 1986 and 2010, we found 202 soft tissue metastases from unique patients across 11 primary histologies (breast [B], colorectal [CR], endometrial [E], head and neck [HN], melanoma [M], non-small cell lung [NSC], ovarian [O], renal [R], sarcoma [S], thyroid [T], and urothelial [U]). With a median follow-up of 173.2 months (95% CI 156.7-189.8), median survival was 62.4 months (95% CI 47-77.9). 41 samples across 4 histologies had targeted exome data. Median values for RSI, 12CK, and MB were 0.415 (interquartile range [IQR] 0.306-0.515), 8.20 (IQR 7.16-9.24), and 89.5 (IQR 69.5-122.75), respectively. Significant differences existed among histologies in all metrics (Table 1). After Bonferroni correction, pairwise comparisons were significant for HN-M (P = 0.008) in RSI; T-HN (P = 0.013), U-HN (P = 0.023), O-HN (P = 0.000), B-HN (P = 0.023), CR-HN (P = 0.006) in 12CK; and T-M (P = 0.024) in MB. Correlation between RSI and 12CK was significant (rho = -0.403, P < 0.001), but correlations between MF and RSI/12CK were not.In this novel exploratory analysis of soft tissue metastases, a number of histologies demonstrated sufficient radiosensitivity (RSI < 0.375) to consider radiotherapy as a component of management. Significant differences across primary histologies also suggest an opportunity for dose personalization. Significant differences in microenvironment inflammation and mutational frequency across primary histologies also may inform personalization of immunotherapy and other targeted therapies.

Radiosensitivity-Specific Proteomic and Signaling Pathway Network of Non-Small Cell Lung Cancer (NSCLC)

An unmet clinical need in non-small cell lung cancer (NSCLC) management is the accurate prediction of radiation response in patients receiving radical radiation therapy. We explored the intrinsic radiosensitivity of NSCLC from the proteomic profiles of NSCLC cell lines and paraffin-embedded human samples. To uncover radiosensitivity-specific proteomic and signaling pathways, we performed quantitative proteomics by data-independent acquisition mass spectrometry assay on 29 human NSCLC cell lines and 13 paraffin-embedded human NSCLC samples. We validated closely interacting radioresistant proteins by western blotting, immunofluorescence, real-time quantitative polymerase chain reaction in NSCLC cell lines, and immunohistochemistry in paraffin-embedded human samples. We validated the functions of 3 key hub proteins by lentivirus transfection, clonogenic survival assay, and flow cytometry. The proteomic profiling of NSCLC showed that the intrinsic radiosensitivity of NSCLC is mainly modulated by signaling pathways of proteoglycans in cancer, focal adhesion, and regulation of the actin cytoskeleton. We identified 71 differentially expressed proteins and validated 8 closely interacting proteins as radioresistant proteins of NSCLC. Moreover, we also validated the functionality of integrin-linked protein kinase, p21-activated kinase 1, and Ras GTPase-activating-like protein IQGAP1 in the radiation response of NSCLC cell lines. Finally, with the NSCLC radiosensitivity-specific proteins, we delineated the atlas network of NSCLC radiosensitivity-related signaling pathways. Radiosensitivity-specific proteins could guide individualized radiation therapy in clinical practice by predicting the radiation response of patients with NSCLC. Moreover, the NSCLC radiosensitivity-related signaling pathway atlas could guide further exploration of the underlying mechanism.

Genomic-adjusted radiation dose to personalise radiotherapy.

In The Lancet Oncology, Jacob Scott and colleagues 1 Scott JG Sedor G Ellswroth P et al. Pan-cancer prediction of radiotherapy benefit using genomic-adjusted radiation dose (GARD): a cohort-based pooled analysis. Lancet Oncol. 2021; (published Aug 4.)https://doi.org/10.1016/S1470-2045(21)00347-8 Summary Full Text Full Text PDF Scopus (17) Google Scholar describe an algorithm using the genomic-adjusted radiation dose (GARD) to personalise radiotherapy dose prescription on the basis of the biological effect of the dose rather than on physical dose alone. GARD is a preclinically and clinically validated combination of a gene expression assay, which assumes pan-tissue biological networks of radiosensitivity and radioresistance, with a linear quadratic model for estimation of total radiation dose in tissues. In previous work, the investigators identified a tumour molecular signature based on the expression of ten genes (AR, cJun [JUN], STAT1, PKC-β [PRKCB], RelA [RELA], cABL [ABL], SUMO1, PAK2, HDAC1, and IRF1) that correlated with radiosensitivity (expressed as tumour cell survival fraction per 2 Gy fraction) in a number of cancer cell lines, called the radiosensitivity index (RSI). 2 Eschrich S Zhang H Zhao H et al. Systems biology modeling of the radiation sensitivity network: a biomarker discovery platform. Int J Radiat Oncol Biol Phys. 2009; 75: 497-505 Summary Full Text Full Text PDF PubMed Scopus (157) Google Scholar , 3 Eschrich SA Pramana J Zhang H et al. A gene expression model of intrinsic tumor radiosensitivity: prediction of response and prognosis after chemoradiation. Int J Radiat Oncol Biol Phys. 2009; 75: 489-496 Summary Full Text Full Text PDF PubMed Scopus (191) Google Scholar , 4 Scott JG Berglund A Schell MJ et al. A genome-based model for adjusting radiotherapy dose (GARD): a retrospective, cohort-based study. Lancet Oncol. 2017; 18: 202-211 Summary Full Text Full Text PDF PubMed Scopus (219) Google Scholar Later, RSI was validated on various tumour types that led to the GARD algorithm. 4 Scott JG Berglund A Schell MJ et al. A genome-based model for adjusting radiotherapy dose (GARD): a retrospective, cohort-based study. Lancet Oncol. 2017; 18: 202-211 Summary Full Text Full Text PDF PubMed Scopus (219) Google Scholar In the current publication, 1 Scott JG Sedor G Ellswroth P et al. Pan-cancer prediction of radiotherapy benefit using genomic-adjusted radiation dose (GARD): a cohort-based pooled analysis. Lancet Oncol. 2021; (published Aug 4.)https://doi.org/10.1016/S1470-2045(21)00347-8 Summary Full Text Full Text PDF Scopus (17) Google Scholar Scott and colleagues validated GARD in 1615 patients with seven cancer types from 11 study cohorts. They found that GARD was associated with time to first recurrence and overall survival for patients receiving radiotherapy and that, by contrast with physical dose, it predicted radiotherapy benefit. Consequently, GARD is a model that can potentially serve as a tool to individualise prescribed radiation doses in clinical practice. The efforts of Scott and colleagues need to be applauded worldwide, because radiotherapy is considerably lagging compared with the enormous progress done in the field of personalised medicine that currently mainly applies to decisions on the use of systemic therapy or targeted agents. Pan-cancer prediction of radiotherapy benefit using genomic-adjusted radiation dose (GARD): a cohort-based pooled analysisThe biological effect of radiotherapy, as quantified by GARD, is significantly associated with time to first recurrence and overall survival for patients with cancer treated with radiation. It is predictive of radiotherapy benefit, and physical dose of radiation is not. We propose integration of genomics into radiation dosing decisions, using a GARD-based framework, as the new paradigm for personalising radiotherapy prescription dose. Full-Text PDF

A Novel Approach for the Discovery of Biomarkers of Radiotherapy Response in Breast Cancer

Radiotherapy (RT) is an important treatment modality for the local control of breast cancer (BC). Unfortunately, not all patients that receive RT will obtain a therapeutic benefit, as cancer cells that either possess intrinsic radioresistance or develop resistance during treatment can reduce its efficacy. For RT treatment regimens to become personalised, there is a need to identify biomarkers that can predict and/or monitor a tumour’s response to radiation. Here we describe a novel method to identify such biomarkers. Liquid chromatography-mass spectrometry (LC-MS) was used on conditioned media (CM) samples from a radiosensitive oestrogen receptor positive (ER+) BC cell line (MCF-7) to identify cancer-secreted biomarkers which reflected a response to radiation. A total of 33 radiation-induced secreted proteins that had higher (up to 12-fold) secretion levels at 24 h post-2 Gy radiation were identified. Secretomic results were combined with whole-transcriptome gene expression experiments, using both radiosensitive and radioresistant cells, to identify a signature related to intrinsic radiosensitivity. Gene expression analysis assessing the levels of the 33 proteins showed that 5 (YBX3, EIF4EBP2, DKK1, GNPNAT1 and TK1) had higher expression levels in the radiosensitive cells compared to their radioresistant derivatives; 3 of these proteins (DKK1, GNPNAT1 and TK1) underwent in-lab and initial clinical validation. Western blot analysis using CM samples from cell lines confirmed a significant increase in the release of each candidate biomarker from radiosensitive cells 24 h after treatment with a 2 Gy dose of radiation; no significant increase in secretion was observed in the radioresistant cells after radiation. Immunohistochemistry showed that higher intracellular protein levels of the biomarkers were associated with greater radiosensitivity. Intracellular levels were further assessed in pre-treatment biopsy tissues from patients diagnosed with ER+ BC that were subsequently treated with breast-conserving surgery and RT. High DKK1 and GNPNAT1 intracellular levels were associated with significantly increased recurrence-free survival times, indicating that these two candidate biomarkers have the potential to predict sensitivity to RT. We suggest that the methods highlighted in this study could be utilised for the identification of biomarkers that may have a potential clinical role in personalising and optimising RT dosing regimens, whilst limiting the administration of RT to patients who are unlikely to benefit.

Integrating Intrinsic Radiosensitivity and Immune Status for Predicting Benefits of Radiotherapy in Head and Neck Squamous Cell Carcinoma.

BackgroundHNSCC (head and neck squamous cell carcinoma) is a heterogeneous disease for which radiotherapy is a main treatment. As intrinsic radiosensitivity and immune status affect the initial and effective stage of the radiation-induced cancer immunity cycle, respectively, it is important to consider both of them when we select patients who can benefit from radiotherapy.Material/MethodsOur study included all HNSCC patients with complete survival and radiotherapy information in TCGA database. Patients were divided into RS (radiosensitive), RR (radioresistant), immune, and non-immune groups according to their RSI (radiosensitivity index) and immune score calculated by the ESTIMATE algorithm. Survival analysis was performed to compare OS (overall survival) between patients receiving and not receiving radiotherapy. GO and KEGG pathway enrichment analysis was performed for functional analysis. Univariate Cox and ridge regression analysis were performed to construct a predictive gene signature based on the combined stratification.ResultsOnly patients in the RS-immune group could benefit from radiotherapy, and the survival analysis results remained consistent after we performed propensity score matching between patients receiving and not receiving radiotherapy. The differentially expressed genes between the RS-immune and non-RS-immune groups were mainly enriched in pathways related to immune process. The 3-gene signature we built exhibited predictive value in training and validation cohorts when treated as a binary or continuous variable.ConclusionsThe combined stratification of intrinsic radiosensitivity and immune status was superior to considering intrinsic radiosensitivity or immune status alone and could be used in preclinical evaluation to select patients or to decide whether radiotherapy sensitizers and immunotherapy should be used at the same time.