Multi-scale geometric network analysis identifies melanoma immunotherapy response gene modules.

Melanoma response to immune-modulating therapy remains incompletely characterized at the molecular level. In this study, we assess melanoma immunotherapy response using a multi-scale network approach to identify gene modules with coordinated gene expression in response to treatment. Using gene expression data of melanoma before and after treatment with nivolumab, we modeled gene expression changes in a correlation network and measured a key network geometric property, dynamic Ollivier-Ricci curvature, to distinguish critical edges within the network and reveal multi-scale treatment-response gene communities. Analysis identified six distinct gene modules corresponding to sets of genes interacting in response to immunotherapy. One module alone, overlapping with the nuclear factor kappa-B pathway (NFkB), was associated with improved patient survival and a positive clinical response to immunotherapy. This analysis demonstrates the usefulness of dynamic Ollivier-Ricci curvature as a general method for identifying information-sharing gene modules in cancer.

Artificial intelligence-based automated segmentation and radiotherapy dose mapping for thoracic normal tissues.

Background and purpose: Objective assessment of delivered radiotherapy (RT) to thoracic organs requires fast and accurate deformable dose mapping. The aim of this study was to implement and evaluate an artificial intelligence (AI) deformable image registration (DIR) and organ segmentation-based AI dose mapping (AIDA) applied to the esophagus and the heart. Materials and methods: AIDA metrics were calculated for 72 locally advanced non-small cell lung cancer patients treated with concurrent chemo-RT to 60 Gy in 2 Gy fractions in an automated pipeline. The pipeline steps were: (i) automated rigid alignment and cropping of planning CT to week 1 and week 2 cone-beam CT (CBCT) field-of-views, (ii) AI segmentation on CBCTs, and (iii) AI-DIR-based dose mapping to compute dose metrics. AIDA dose metrics were compared to the planned dose and manual contour dose mapping (manual DA). Results: AIDA required âˆ¼2 min/patient. Esophagus and heart segmentations were generated with a mean Dice similarity coefficient (DSC) of 0.80±0.15 and 0.94±0.05, a Hausdorff distance at 95th percentile (HD95) of 3.9±3.4 mm and 14.1±8.3 mm, respectively. AIDA heart dose was significantly lower than the planned heart dose (p = 0.04). Larger dose deviations (>=1Gy) were more frequently observed between AIDA and the planned dose (N = 26) than with manual DA (N = 6). Conclusions: Rapid estimation of RT dose to thoracic tissues from CBCT is feasible with AIDA. AIDA-derived metrics and segmentations were similar to manual DA, thus motivating the use of AIDA for RT applications.

Spatially Fractionated Radiotherapy in the Era of Immunotherapy.

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

Auto-segmentation of neck nodal metastases using self-distilled masked image transformer on longitudinal MR images.

Objectives: Auto-segmentation promises greater speed and lower inter-reader variability than manual segmentations in radiation oncology clinical practice. This study aims to implement and evaluate the accuracy of the auto-segmentation algorithm, "Masked Image modeling using the vision Transformers (SMIT)," for neck nodal metastases on longitudinal T2-weighted (T2w) MR images in oropharyngeal squamous cell carcinoma (OPSCC) patients. Methods: This prospective clinical trial study included 123 human papillomaviruses (HPV-positive [+]) related OSPCC patients who received concurrent chemoradiotherapy. T2w MR images were acquired on 3 T at pre-treatment (Tx), week 0, and intra-Tx weeks (1-3). Manual delineations of metastatic neck nodes from 123 OPSCC patients were used for the SMIT auto-segmentation, and total tumor volumes were calculated. Standard statistical analyses compared contour volumes from SMIT vs manual segmentation (Wilcoxon signed-rank test [WSRT]), and Spearman's rank correlation coefficients (ρ) were computed. Segmentation accuracy was evaluated on the test data set using the dice similarity coefficient (DSC) metric value. P-values <0.05 were considered significant. Results: No significant difference in manual and SMIT delineated tumor volume at pre-Tx (8.68 ± 7.15 vs 8.38 ± 7.01 cm3, P = 0.26 [WSRT]), and the Bland-Altman method established the limits of agreement as -1.71 to 2.31 cm3, with a mean difference of 0.30 cm3. SMIT model and manually delineated tumor volume estimates were highly correlated (ρ = 0.84-0.96, P < 0.001). The mean DSC metric values were 0.86, 0.85, 0.77, and 0.79 at the pre-Tx and intra-Tx weeks (1-3), respectively. Conclusions: The SMIT algorithm provides sufficient segmentation accuracy for oncological applications in HPV+ OPSCC. Advances in knowledge: First evaluation of auto-segmentation with SMIT using longitudinal T2w MRI in HPV+ OPSCC.

Dynamic network curvature analysis of gene expression reveals novel potential therapeutic targets in sarcoma.

Network properties account for the complex relationship between genes, making it easier to identify complex patterns in their interactions. In this work, we leveraged these network properties for dual purposes. First, we clustered pediatric sarcoma tumors using network information flow as a similarity metric, computed by the Wasserstein distance. We demonstrate that this approach yields the best concordance with histological subtypes, validated against three state-of-the-art methods. Second, to identify molecular targets that would be missed by more conventional methods of analysis, we applied a novel unsupervised method to cluster gene interactomes represented as networks in pediatric sarcoma. RNA-Seq data were mapped to protein-level interactomes to construct weighted networks that were then subjected to a non-Euclidean, multi-scale geometric approach centered on a discrete notion of curvature. This provides a measure of the functional association among genes in the context of their connectivity. In confirmation of the validity of this method, hierarchical clustering revealed the characteristic EWSR1-FLI1 fusion in Ewing sarcoma. Furthermore, assessing the effects of in silico edge perturbations and simulated gene knockouts as quantified by changes in curvature, we found non-trivial gene associations not previously identified.

A Simulation-Free Replacement Solution for Radiation Therapy Immobilization Devices Using Computer Numerical Control (CNC) -Milled Polystyrene Molds.

Purpose: In radiation therapy (RT), if an immobilization device is lost or damaged, the patient may need to be brought back for resimulation, device fabrication, and treatment planning, causing additional imaging radiation exposure, inconvenience, cost, and delay. We describe a simulation-free method for replacing lost or damaged RT immobilization devices. Methods and Materials: Replacement immobilization devices were fabricated using existing simulation scans as design templates by computer numerical control (CNC) milling of molds made from extruded polystyrene (XPS). XPS material attenuation and bolusing properties were evaluated, a standard workflow was established, and 12 patients were treated. Setup reproducibility was analyzed postfacto using Dice similarity coefficient (DSC) and mean distance to agreement (MDA) calculations comparing onboard treatment imaging with computed tomography (CT) simulations. Results: Results showed that XPS foam material had less dosimetric impact (attenuation and bolusing) than materials used for our standard immobilization devices. The average direct cost to produce each replacement mold was $242.17, compared with over $2000 for standard resimulation. Hands-on time to manufacture was 86.3 minutes, whereas molds were delivered in as little as 4 hours and mostly within 24 hours, compared with a week or more required for standard resimulation. Each mold was optically scanned after production and was measured to be within 2-mm tolerance (pointwise displacement) of design input. All patients were successfully treated using the CNC-milled foam mold replacements, and pretreatment imaging verified satisfactory clinical setup reproduction for each case. The external body contours from the setup cone beam CT and the original CT simulation with matching superior-inferior extent were compared by calculating the DSC and MDA. DSC average was 0.966 (SD, 0.011), and MDA average was 2.694 mm (SD, 0.986). Conclusions: CNC milling of XPS foam is a quicker and more convenient solution than traditional resimulation for replacing lost or damaged RT immobilization devices. Satisfactory patient immobilization, low dosimetric impact compared with standard immobilization devices, and strong correlation of onboard contours with CT simulations are shown. We share our clinical experience, workflow, and manufacturing guide to help other clinicians who may want to adopt this solution.

An 18F-FDG PET/CT and Mean Lung Dose Model to Predict Early Radiation Pneumonitis in Stage III Non-Small Cell Lung Cancer Patients Treated with Chemoradiation and Immunotherapy.

Radiation pneumonitis (RP) that develops early (i.e., within 3 mo) (RPEarly) after completion of concurrent chemoradiation (cCRT) leads to treatment discontinuation and poorer survival for patients with stage III non-small cell lung cancer. Since no RPEarly risk model exists, we explored whether published RP models and pretreatment 18F-FDG PET/CT-derived features predict RPEarly Methods: One hundred sixty patients with stage III non-small cell lung cancer treated with cCRT and consolidative immunotherapy were analyzed for RPEarly Three published RP models that included the mean lung dose (MLD) and patient characteristics were examined. Pretreatment 18F-FDG PET/CT normal-lung SUV featured included the following: 10th percentile of SUV (SUVP10), 90th percentile of SUV (SUVP90), SUVmax, SUVmean, minimum SUV, and SD. Associations between models/features and RPEarly were assessed using area under the receiver-operating characteristic curve (AUC), P values, and the Hosmer-Lemeshow test (pHL). The cohort was randomly split, with similar RPEarly rates, into a 70%/30% derivation/internal validation subset. Results: Twenty (13%) patients developed RPEarly Predictors for RPEarly were MLD alone (AUC, 0.72; P = 0.02; pHL, 0.87), SUVP10, SUVP90, and SUVmean (AUC, 0.70-0.74; P = 0.003-0.006; pHL, 0.67-0.70). The combined MLD and SUVP90 model generalized in the validation subset and was deemed the final RPEarly model (RPEarly risk = 1/[1+e(- x )]; x = -6.08 + [0.17 × MLD] + [1.63 × SUVP90]). The final model refitted in the 160 patients indicated improvement over the published MLD-alone model (AUC, 0.77 vs. 0.72; P = 0.0001 vs. 0.02; pHL, 0.65 vs. 0.87). Conclusion: Patients at risk for RPEarly can be detected with high certainty by combining the normal lung's MLD and pretreatment 18F-FDG PET/CT SUVP90 This refined model can be used to identify patients at an elevated risk for premature immunotherapy discontinuation due to RPEarly and could allow for interventions to improve treatment outcomes.

Reduction of post-radiotherapy urinary toxicity via intrafractional MV-kV prostate location monitoring.

PURPOSE/OBJECTIVE(S): We hypothesized that an in-house developed system using MV and kV image guidance (MKIG) to ensure correct prostate positioning during SBRT could potentially avoid unwanted doses to non-target tissues, leading to reduced toxicities. MATERIALS/METHODS: We built a 3D MKIG platform that accurately tracks prostate implanted fiducials in real-time and clinically translated the system to replace a commercial approach, intrafraction motion review (IMR), which only tracks fiducials in the 2D kV views. From 2017 to 2019, 150 prostate cancer patients were treated with SBRT and monitored by MKIG. The motion trace of the fiducials alerts therapists to interrupt and reposition the prostate when displacement exceeds a 1.5 mm threshold. A comparison cohort of 121 patients was treated with the same dose regimen and treatment technique but managed by IMR. Statistics of intrafractional patient shifts and delivery time were collected to evaluate the workflow efficacy. The incidence of grade ≥2 urinary toxicities was analyzed to assess clinical complications. The median follow-up time was 3.7 years (0.2 to 8.2 years). RESULTS: MKIG treatments had more treatment shifts (1.09 vs. 0.28) and a longer average delivery time per fraction (579±205s vs. 357±117s) than IMR treatments. Three-quarters (75%) of shifts resulting from MKIG were ≤3mm, vs. 51% in IMR, indicating that MKIG detected and corrected smaller deviations. The incidence of grade ≥2 urinary toxicity was lower in the MKIG than IMR cohort: 10.7% vs. 19.8% (p=0.047). On multivariate analysis of late urinary toxicity, only high (>7) pre-RT IPSS (p<0.043) and the use of MKIG were selected (p< 0.029). CONCLUSIONS: Automated and quantitative MKIG introduced minimal workflow impact and was superior to IMR in localizing the prostate during SBRT, which correlated with a clinically significant reduction in late urinary toxicity. Further clinical testing via randomized trial will be required to validate the impact on outcomes.

Biomarkers associated with pulmonary exacerbations in a randomized trial of nintedanib for radiation pneumonitis.

BACKGROUND AND PURPOSE: Radiation pneumonitis (RP) is a common side effect of thoracic radiotherapy and often has a long course characterized by acute exacerbations and progression to permanent lung fibrosis. There are no validated biomarkers of prognosis in patients diagnosed with RP. MATERIALS AND METHODS: We analyzed a time course of serum chemokines, cytokines, and other proteins from patients with grade 2+ RP in a randomized clinical trial of a steroid taper plus nintedanib, a multiple tyrosine kinase inhibitor, versus placebo plus a steroid taper for the treatment of RP. Weighted gene correlation network analysis (WGCNA) and univariable zero inflated Poisson models were used to identify groups of correlated analytes and their associations with clinical outcomes. RESULTS: Thirty enrolled patients had biomarker data available, and 17 patients had enough analytes tested for network analysis. WGNCA identified ten analytes, including transforming growth factor beta-1 (TGF-ß1), monocyte chemoattractant protein-1 (MCP-1), and platelet-derived growth factor (PDGF), that in aggregate were correlated with the occurrence of pulmonary exacerbations (p = 0.008), the total number of acute pulmonary exacerbations (p = 0.002), and treatment arm (p = 0.036). By univariable analysis, an increase in rate of change of two components of the RP module were associated with an increased incidence rate of pulmonary exacerbations: interleukin 5 (IL-5, incidence rate ratio (IRR) 1.02, 95% CI 1.01-1.04, p = 0.002), and tumor necrosis factor superfamily 12 (TNFSF12, IRR 1.06, CI 1-1.11, p = 0.036). An increased slope of epidermal growth factor (EGF) was associated with a decreased incidence rate of exacerbations (IRR 0.94, CI 0.89-1, p = 0.036). CONCLUSION: We identified a panel of serum biomarkers that showed association with nintedanib treatment and acute pulmonary exacerbations in patients with RP. A confirmatory study will be needed to validate this panel for use as a prognostic tool in patients with RP.

Multi-modality imaging parameters that predict rapid tumor regression in head and neck radiotherapy.

Background and purpose: Volume regression during radiotherapy can indicate patient-specific treatment response. We aimed to identify pre-treatment multimodality imaging (MMI) metrics from positron emission tomography (PET), magnetic resonance imaging (MRI), and computed tomography (CT) that predict rapid tumor regression during radiotherapy in human papilloma virus (HPV) associated oropharyngeal carcinoma. Materials and methods: Pre-treatment FDG PET-CT, diffusion-weighted MRI (DW-MRI), and intra-treatment (at 1, 2, and 3 weeks) MRI were acquired in 72 patients undergoing chemoradiation therapy for HPV+ oropharyngeal carcinoma. Nodal gross tumor volumes were delineated on longitudinal images to measure intra-treatment volume changes. Pre-treatment PET standardized uptake value (SUV), CT Hounsfield Unit (HU), and non-gaussian intravoxel incoherent motion DW-MRI metrics were computed and correlated with volume changes. Intercorrelations between MMI metrics were also assessed using network analysis. Validation was carried out on a separate cohort (N = 64) for FDG PET-CT. Results: Significant correlations with volume loss were observed for baseline FDG SUVmean (Spearman ρ = 0.46, p < 0.001), CT HUmean (ρ = 0.38, p = 0.001), and DW-MRI diffusion coefficient, Dmean (ρ = -0.39, p < 0.001). Network analysis revealed 41 intercorrelations between MMI and volume loss metrics, but SUVmean remained a statistically significant predictor of volume loss in multivariate linear regression (p = 0.01). Significant correlations were also observed for SUVmean in the validation cohort in both primary (ρ = 0.30, p = 0.02) and nodal (ρ = 0.31, p = 0.02) tumors. Conclusions: Multiple pre-treatment imaging metrics were correlated with rapid nodal gross tumor volume loss during radiotherapy. FDG-PET SUV in particular exhibited significant correlations with volume regression across the two cohorts and in multivariate analysis.

Mapping the Single-Cell Differentiation Landscape of Osteosarcoma.

PURPOSE: The genetic intratumoral heterogeneity observed in human osteosarcomas poses challenges for drug development and the study of cell fate, plasticity, and differentiation, which are processes linked to tumor grade, cell metastasis, and survival. EXPERIMENTAL DESIGN: To pinpoint errors in osteosarcoma differentiation, we transcriptionally profiled 31,527 cells from a tissue-engineered model that directs mesenchymal stem cells toward adipogenic and osteoblastic fates. Incorporating preexisting chondrocyte data, we applied trajectory analysis and non-negative matrix factorization to generate the first human mesenchymal differentiation atlas. RESULTS: This "roadmap" served as a reference to delineate the cellular composition of morphologically complex osteosarcoma tumors and quantify each cell's lineage commitment. Projecting a bulk RNA-sequencing osteosarcoma dataset onto this roadmap unveiled a correlation between a stem-like transcriptomic phenotype and poorer survival outcomes. CONCLUSIONS: Our study quantifies osteosarcoma differentiation and lineage, a prerequisite to better understanding lineage-specific differentiation bottlenecks that might someday be targeted therapeutically.

Stereotactic Body Radiation Therapy for Stage IIA to IIIA Inoperable Non-Small Cell Lung Cancer: A Phase 1 Dose-Escalation Trial.

PURPOSE: Larger tumors are underrepresented in most prospective trials on stereotactic body radiation therapy (SBRT) for inoperable non-small cell lung cancer (NSCLC). We performed this phase 1 trial to specifically study the maximum tolerated dose (MTD) of SBRT for NSCLC >3 cm. METHODS AND MATERIALS: A 3 + 3 dose-escalation design (cohort A) with an expansion cohort at the MTD (cohort B) was used. Patients with inoperable NSCLC >3 cm (T2-4) were eligible. Select ipsilateral hilar and single-station mediastinal nodes were permitted. The initial SBRT dose was 40 Gy in 5 fractions, with planned escalation to 50 and 60 Gy in 5 fractions. Adjuvant chemotherapy was mandatory for cohort A and optional for cohort B, but no patients in cohort B received chemotherapy. The primary endpoint was SBRT-related acute grade (G) 4+ or persistent G3 toxicities (Common Terminology Criteria for Adverse Events version 4.03). Secondary endpoints included local failure (LF), distant metastases, disease progression, and overall survival. RESULTS: The median age was 80 years; tumor size was >3 cm and ≤5 cm in 20 (59%) and >5 cm in 14 patients (41%). In cohort A (n = 9), 3 patients treated to 50 Gy experienced G3 radiation pneumonitis (RP), thus defining the MTD. In the larger dose-expansion cohort B (n = 25), no radiation therapy-related G4+ toxicities and no G3 RP occurred; only 2 patients experienced G2 RP. The 2-year cumulative incidence of LF was 20.2%, distant failure was 34.7%, and disease progression was 54.4%. Two-year overall survival was 53%. A biologically effective dose (BED) <100 Gy was associated with higher LF (P = .006); advanced stage and higher neutrophil/lymphocyte ratio were associated with greater disease progression (both P = .004). CONCLUSIONS: Fifty Gy in 5 fractions is the MTD for SBRT to tumors >3 cm. A higher BED is associated with fewer LFs even in larger tumors. Cohort B appears to have had less toxicity, possibly due to the omission of chemotherapy.