Grams, Michael P.

Introduction Spleen tyrosine kinase (SYK) is a non-receptor tyrosine kinase involved in immune signaling and has been implicated in tumor-intrinsic resistance to DNA-damaging therapies. Although SYK activity has been associated with poor outcomes in triple-negative breast cancer (TNBC), its role in resistance to combined radiotherapy and immune checkpoint blockade remains unclear. Methods SYK expression and clinical relevance were assessed across multiple breast cancer cohorts, including radiotherapy-treated datasets. Integrated transcriptomic analyses were used to characterize SYK-associated immune states. The functional effects of pharmacologic SYK inhibition were evaluated using in vitro assays and an immunocompetent bilateral 4T1 tumor model in female BALB/c mice treated with radiotherapy and PD-1 blockade. Treatment-associated immune remodeling was assessed by flow cytometry and transcriptomic profiling. Results Across multiple cohorts, elevated SYK expression, particularly in TNBC, was associated with inferior clinical outcomes and immune dysregulation. Pharmacologic SYK inhibition enhanced tumor responses to radiotherapy and PD-1 blockade at both irradiated and distant tumor sites. These effects were accompanied by coordinated remodeling of the tumor immune microenvironment, including suppression of neutrophil-associated signatures and reductions in immunosuppressive myeloid populations, including M2-like macrophages and myeloid-derived suppressor cells. Discussion Pharmacologic SYK inhibition enhances responses to radiotherapy and PD-1 blockade in preclinical TNBC models and is accompanied by remodeling of the immunosuppressive myeloid compartment. These findings support further investigation of SYK-targeted strategies to improve responses to combined radiotherapy and immune checkpoint blockade.

Abstract Objective. Proton minibeam radiation therapy (pMBRT) is a novel spatially fractionated radiation therapy technique that offers improved tumor control and reduced normal tissue toxicity. However, its clinical translation has been hindered in part by limited field sizes, low dose rates, and complex manufacturing. This work describes the design, manufacturing, and commissioning of a novel divergent pMBRT collimator along with accessory components to maximize its versatility and facilitate clinical implementation. Approach. The dosimetric outcomes for pMBRT collimator geometry, including slit width, center-to-center (CTC) spacing, thickness, divergence, and field size, were evaluated using TOPAS Monte Carlo (MC) to maximize surface peak-to-valley dose ratio (PVDR) while maintaining uniform target coverage. The collimator was constructed using brass plates held by aluminum side holders. Commissioning measurements with a PTW Bragg peak chamber and EBT4 radiochromic film were compared to TOPAS and an in-house fast GPU-based MC simulation. Ancillary equipment consisting of lead foils, range shifters, custom apertures, and secondary pMBRT collimators were characterized in tandem. Main results. An optimized divergent pMBRT collimator with 0.5 mm slit width, 2.0 mm CTC distance, and 40 mm thickness produced a surface PVDR of 4.8 while preserving quasi-homogeneous dose in the 6–14 cm depth region. Measured dose profiles demonstrated valley dose agreement within 3% for both TOPAS and GPU-based MC predictions after the simulated collimator geometry was refined to match Bragg-peak chamber average dose measurements. The onset of the quasi-homogeneous dose region was shifted toward shallower depths by using thin lead foils, without significantly impacting entrance PVDR. Apertures sharpened penumbra and enhanced peripheral PVDR. A dual collimator approach produced 2D pinhole dose arrays that resulted in valley doses from MC simulations and film measurements agreeing within ∼5%. Significance. We demonstrated a practical low-cost, large-area divergent physical pMBRT collimation system with validated MC modeling. In addition, we introduce complementary accessories that substantially expand system versatility to facilitate clinical implementation.

Abstract Background There is a critical need for novel treatment strategies addressing key features of Alzheimer's disease (AD) pathogenesis. Therapies targeting individual hallmarks yield little benefit. Low‐dose whole brain radiation is a non‐pharmacological approach that has shown promise in AD animal models, reducing amyloid plaques and neuroinflammation, and improving cognitive performance. These findings have initiated small clinical trials. However, even low doses (2 Gray per treatment) can cause adverse effects like vascular damage and reduced neurogenesis in the hippocampus. Minibeam radiation therapy (MBRT) which delivers radiation in an alternating pattern of submillimeter‐wide high (“peak”) and low (“valley”) dose regions can potentially mitigate these negative effects. It has proven to reduce toxicity in a variety of normal tissues including the brain. Therefore, the objective of this study is to determine whether MBRT can safely and effectively address multiple AD mechanisms including amyloid deposition, neuroinflammation and brain energy metabolism while significantly reducing radiation exposure to the brain. Method The study aims to develop an MBRT treatment paradigm to investigate its efficacy in targeting biochemical and cognitive hallmarks of AD. This includes assessing amyloid plaque burden, cognitive function, optimal treatment age, radiation dose, and duration of effect. In a preliminary study, 6‐month‐old 5XFAD mice were irradiated with MBRT (2 Gy peak and 0.3 Gy valley) or conventional irradiation (2 Gy) for a total of 5 daily treatments. Tissue was collected 4 weeks later for analysis of soluble and insoluble amyloid beta by ELISA and microscopic assessment of plaques stained with thioflavin S. Spontaneous alternation in the Y‐maze was assessed 4 weeks post‐irradiation. Result Trends showing reductions in insoluble Aβ were observed in the brains of irradiated 5XFAD mice 4 weeks following MBRT. Although plaque burden is high in untreated 5XFAD mice, cognitive decline was not yet apparent at this age. Conclusion Given these preliminary results, we will define optimal treatment parameters and assess efficacy when MBRT is administered after the onset of cognitive deficits.

Abstract Background Spatially fractionated radiation therapy (SFRT) is a technique that delivers heterogenous dose distributions consisting of alternating regions of high dose “peaks” and low dose “valleys”. Current delivery methods for SFRT using megavoltage x‐rays usually treat large and bulky tumors with brass grid or volumetric modulated arc therapy (VMAT) lattice techniques. The size and spacing of high dose regions in these approaches are typically on the order of centimeters. However, multiple studies have suggested that decreasing these dimensions may improve the therapeutic ratio. Furthermore, a more compact approach to SFRT would allow for a greater number of high dose regions within the tumor, as well as application to smaller and more irregularly shaped targets thereby increasing the number of patients that could benefit from SFRT. Purpose This study describes the commissioning and first patient treatment using mini‐lattice radiation therapy (MLRT). MLRT uses a clinical linear accelerator and decreases the size and spacing of standard lattice SFRT by using individual multileaf collimator (MLC) leaves to deliver 5 mm wide high dose regions. Methods MLRT plans were created in the Varian Eclipse treatment planning system for a Varian Truebeam equipped with Millennium 120 MLCs. MLRT uses 6 MV Flattening Filter Free high dose rate and the width of individual MLCs to define 5 mm by 5 mm openings separated by closed MLCs to deliver alternating opened and blocked regions. Dynamic conformal arcs were used to conform MLCs to 4 mm spherical mini‐lattice structures in the gross tumor volume (GTV). A MLRT‐specific beam model was commissioned to accurately model the small MLRT fields. Film measurements were performed to assess the accuracy of MLRT plans calculations. Plans for seven treatment sites in different parts of the body for retrospective patient candidates were created with varying numbers of mini‐lattices and separation distances to assess the impact of varying these parameters on treatment dose metrics. MLRT was used for the first time to treat a patient with two fractions of MLRT. Results The AcurosXB calculation algorithm with modified x and y spot sizes, dosimetric leaf gap, transmission factor, and output factor table was used to generate a beam model for accurate MLRT calculations. The MLRT‐specific beam model resulted in gamma passing rates (1%/0.5 mm criteria) of 90%–99% for retrospective patient MLRT film measurements. Dose volume histogram statistics, equivalent uniform dose, and mean dose showed a higher number of mini‐lattices with smaller separation increased the dose to the GTV and surrounding tissue. Separation distances between mini‐lattices did not impact plan heterogeneity as measured by D10%/D90%. The first patient treated with the MLRT technique reported pain relief, had stable disease, and no acute toxicities following both fractions. Conclusions MLRT is feasible using clinical linear accelerators and existing radiation oncology infrastructure. It enables targeting smaller tumors with SFRT, allows for a greater number of high dose regions within the target compared to standard VMAT lattice techniques, and may be a useful technique for challenging treatment scenarios.

Abstract Purpose Lattice radiation therapy (LRT) is a form of spatially fractionated radiation therapy that allows increased total dose delivery aiming for improved treatment response without an increase in toxicities, commonly utilized for palliation of bulky tumors. The LRT treatment planning process is complex, while eligible patients often have an urgent need for expedited treatment start. In this study, we aimed to develop a simulation‐free workflow for volumetric modulated arc therapy (VMAT)‐based LRT planning via deep learning‐predicted synthetic CT (sCT) to expedite treatment initiation. Methods Two deep learning models were initially trained using 3D U‐Net architecture to generate sCT from diagnostic CTs (dCT) of the thoracic and abdomen regions using a training dataset of 50 patients. The models were then tested on an independent dataset of 15 patients using image similarity analysis assessing mean absolute error (MAE) and structural similarity index measure (SSIM) as metrics. VMAT‐based LRT plans were generated based on sCT and recalculated on the planning CT (pCT) for dosimetric accuracy comparison. Differences in dose volume histogram (DVH) metrics between pCT and sCT plans were assessed using the Wilcoxon signed‐rank test. Results The final sCT prediction model demonstrated high image similarity to pCT, with a MAE and SSIM of 38.93 ± 14.79 Hounsfield Units (HU) and 0.92 ± 0.05 for the thoracic region, and 73.60 ± 22.90 HU and 0.90 ± 0.03 for the abdominal region, respectively. There were no statistically significant differences between sCT and pCT plans in terms of organ‐at‐risk and target volume DVH parameters, including maximum dose (Dmax), mean dose (Dmean), dose delivered to 90% (D90%) and 50% (D50%) of target volume, except for minimum dose (Dmin) and (D10%). Conclusion With demonstrated high image similarity and adequate dose agreement between sCT and pCT, our study is a proof‐of‐concept for using deep learning predicted sCT for a simulation‐free treatment planning workflow for VMAT‐based LRT.

Abstract Background Most oncology therapeutics have limited distribution into the brain, and developing strategies to overcome this limitation would be clinically impactful. While therapeutic radiation is often cited as a strategy to accomplish this, there are no published studies demonstrating the effect of radiation on drug distribution into the brain or brain tumors. Methods Mice were treated with brain radiation (6 Gy × 5, 4 Gy × 10; 40 Gy × 1) and dosed with drugs (levetiracetam, cefazolin, nedisertib, brigimadlin, apitolisib, or GNE-317) at times ranging from just prior to months after radiation. Plasma and tissue drug concentrations were measured by LC-MS/MS. Results Radiation did not significantly enhance drug delivery into brain tissue for levetiracetam, cefazolin, GNE-317, apitolisib, or nedisertib at any time post-radiation. Even a single, supra-therapeutic dose of radiation (40 Gy) did not significantly affect brain distribution of GNE-317 or apitolisib (P ≥ .07) from 16 to 160 hours post-radiation. For brigimadlin, radiation (6 Gy × 5) was associated with a modest but significant increase in drug accumulation only at 72 hours post-radiation (brain-to-plasma ratio 0.014 ± 0.006 vs. 0.025 ± 0.010, respectively; P = .04), but not at any other timepoint (24 hours, 15, 28, 94, 133, 183 days; P > .05). Similarly, radiation (6 Gy × 5) of orthotopic tumors did not increase levels of brigimadlin in GBM10 or GBM108 or nedisertib in GBM108 (P > .05). Conclusions Radiation had no meaningful impact on drug delivery into brain or brain tumors for the drugs tested.

Abstract Ataxia Telangiectasia–mutated (ATM) inhibitors are being developed as radiosensitizers to improve the antitumor effects of radiotherapy, but ATM inhibition can also radiosensitize normal tissues. Therefore, understanding the elevated risk of normal tissue toxicities is critical for radiosensitizer development. This study focused on modeling the relationship between acute mucosal toxicity, radiation dose, fractionation schedule, and radiosensitizer exposure. The ATM inhibitor WSD0628 was combined with single or fractionated doses of radiation delivered to the oral cavity or esophagus of Friend Leukemia virus B (FVB) mice. The potentiation by WSD0628 was quantified by a sensitizer enhancement ratio (SER), which describes the changes in radiation tolerance for radiation combined with WSD0628 relative to radiation-only regimens. WSD0628 profoundly enhanced radiation-induced acute oral and esophageal toxicities. For oral mucosal toxicity, the enhancement by WSD0628 with 3 fractions of radiation resulted in an SER ranging from 1.3 (0.25 mg/kg) to 3.1 (7.5 mg/kg). For the 7.5 mg/kg combination, the SER increased with increasing number of fractions from 2.2 (1 fraction) to 4.3 (7 fractions) for oral toxicity and from 2.2 (1 fraction) to 3.6 (3 fractions) for esophageal toxicity, which reflects a loss of the normal tissue sparing benefit of fractionated radiation. These findings were used to develop a modified biologically effective dose model to determine alternative radiation schedules with or without WSD0628 that result in similar levels of toxicity. Successful radiosensitizer dose escalation to a maximally effective therapeutic dose will require careful deliberation of tumor site and reduction of radiation dose volume limits for organs at risk.

Abstract BACKGROUND Glioma radiotherapy planning requires accurate tumor delineation. While T1- contrast-enhanced-MRI (T1-CE-MRI) is the standard, due to blood-brain-barrier breakdown dependencies, T1-CE-MRI fails to reflect the extent of glioma. Studies using amino acid PET tracers report glioma uptake up to 3cm-4cm beyond T1-CE. In this study, amino acid tracer 18F-fluoro-dihydroxyphenylalanine (18F-DOPA) uptake was correlated with histopathological features to determine tumor thresholds. METHODS Using registered 18F-DOPA-PET and T1-CE-MRI images in the Stealth Neuronavigation system targeting concordant and discordant regions, 181 stereotactic biopsy samples (newly-diagnosed=74; recurrent=107) were obtained from 59 enrolled astrocytoma patients across two prospective phase II clinical trials between 2010-2019. An experienced neuropathologist reviewed each sample with hematoxylin and eosin stain and assigned an alphanumeric score: mitotic activity (0=no tumor; 1=no mitosis; 2=few/scattered mitosis; 3=frequent mitosis) and cellular density (A=<25%; B=25%-50%; C=50%-75%; D=>75%). Samples assigned 1C-1D, 2B-2D, or 3A-3D were categorized as histopathological high-score (aggressive disease), remaining samples as low-score. Relative mean (rFDOPA_mean) tumor-to-background uptake ratios were computed for 5mm uniformly expanded volumes from each Stealth biopsy coordinate using the crescent and wedge normalization methods. Relative uptake was compared overall and separately within newly-diagnosed/recurrent disease subgroups. An optimal rFDOPA_mean threshold to delineate high- from low-score was determined using the maximal Youden index of ROC curves. RESULTS Overall, high-score samples (n=116) had higher median (IQR) rFDOPA_mean uptake than low-score samples (n=65): high-score rFDOPA:mean=1.70(1.16-2.26), low-score rFDOPA:mean=1.16(0.83-1.49), Kruskal-Wallis p<0.001. The uptake difference between high- vs. low-score samples was observed within newly-diagnosed and recurrent subgroups, but was only significant for newly-diagnosed (p<0.001). For newly-diagnosed, an rFDOPA:mean=1.49 cutoff between high- and low-score groups shows 69% accuracy, 63% sensitivity, 80% specificity (AUC=0.782). Using the wedge normalization method, rFDOPA_mean values were 0.2 higher than crescent method values. CONCLUSIONS This work presents histologically verified 18F-DOPA-PET thresholds for aggressive disease in newly-diagnosed astrocytoma patients. Separate thresholds will need to be determined for recurrent glioma patients.

Abstract Spatially fractionated radiation therapy (SFRT) is a therapeutic approach with the potential to disrupt the classical paradigms of conventional radiation therapy. The high spatial dose modulation in SFRT activates distinct radiobiological mechanisms which lead to a remarkable increase in normal tissue tolerances. Several decades of clinical use and numerous preclinical experiments suggest that SFRT has the potential to increase the therapeutic index, especially in bulky and radioresistant tumors. To unleash the full potential of SFRT a deeper understanding of the underlying biology and its relationship with the complex dosimetry of SFRT is needed. This review provides a critical analysis of the field, discussing not only the main clinical and preclinical findings but also analyzing the main knowledge gaps in a holistic way.

Abstract Objective . An algorithm was developed for automated positioning of lattice points within volumetric modulated arc lattice radiation therapy (VMAT LRT) planning. These points are strategically placed within the gross tumor volume (GTV) to receive high doses, adhering to specific separation rules from adjacent organs at risk (OARs). The study goals included enhancing planning safety, consistency, and efficiency while emulating human performance. Approach . A Monte Carlo-based algorithm was designed to optimize the number and arrangement of lattice points within the GTV while considering placement constraints and objectives. These constraints encompassed minimum spacing between points, distance from OARs, and longitudinal separation along the z -axis. Additionally, the algorithm included an objective to permit, at the user’s discretion, solutions with more centrally placed lattice points within the GTV. To validate its effectiveness, the automated approach was compared with manually planned treatments for 24 previous patients. Prior to clinical implementation, a failure mode and effects analysis (FMEA) was conducted to identify potential shortcomings. Main results. The automated program successfully met all placement constraints with an average execution time (over 24 plans) of 0.29 ±0.07 min per lattice point. The average lattice point density (# points per 100 c.c. of GTV) was similar for automated (0.725) compared to manual placement (0.704). The dosimetric differences between the automated and manual plans were minimal, with statistically significant differences in certain metrics like minimum dose (1.9% versus 1.4%), D5% (52.8% versus 49.4%), D95% (7.1% versus 6.2%), and Body-GTV V30% (20.7 c.c. versus 19.7 c.c.). Significance. This study underscores the feasibility of employing a straightforward Monte Carlo-based algorithm to automate the creation of spherical target structures for VMAT LRT planning. The automated method yields similar dose metrics, enhances inter-planner consistency for larger targets, and requires fewer resources and less time compared to manual placement. This approach holds promise for standardizing treatment planning in prospective patient trials and facilitating its adoption across centers seeking to implement VMAT LRT techniques.