Citations

ABSTRACT Background Radiotherapy is a cornerstone of treatment for pediatric central nervous system (CNS) tumors, but dose selection remains uniform despite interpatient variability in tumor radiosensitivity. This is consequential in children, for whom toxicity can have lifelong effects. Genomic-adjusted radiation dose (GARD) integrates tumor genomics with delivered radiation dose to quantify the biological effect of radiotherapy and has been validated across adult malignancies. Its relevance in pediatric CNS tumors is unknown. Methods We performed a cohort study using gene expression and data from 246 pediatric patients with high-grade glioma, medulloblastoma, or ependymoma from the Children’s Brain Tumor Network. GARD was calculated using a sequencing-adapted radiosensitivity index integrated with radiation dose through the linear–quadratic model. Associations of GARD and physical radiation dose with event-free and overall survival were evaluated using Cox proportional hazards models stratified by tumor type and anatomic location. Patients who did not receive radiotherapy comprised a negative control cohort (sham-GARD). Results Among patients receiving radiotherapy, physical dose was uniform, whereas GARD showed substantial interpatient variability in biological effect. Higher GARD was associated with improved event-free survival (hazard ratio [HR] 0·90, 95% CI 0·83–0·97; p=0·004) and overall survival (HR 0·90, 95% CI 0·83–0·99; p=0·018). Physical dose was not associated with either endpoint. Among patients who did not receive radiotherapy, sham-GARD was not associated with outcomes, supporting GARD as a treatment-specific predictor rather than a prognostic biomarker. Conclusions In pediatric CNS tumors, the biological effect of radiotherapy quantified by GARD was associated with outcomes, whereas physical dose was not. These findings challenge uniform radiotherapy dosing and support genomically informed dose individualization. Prospective evaluation of GARD-guided radiotherapy is warranted to optimize tumor control while minimizing long-term toxicity in children.

BACKGROUND: Although diabetes is a known driver of heart failure with preserved ejection fraction, whether antecedent hyperinsulinemia drives preclinical diastolic dysfunction (DD) progression before overt hyperglycemia remains unknown. Therefore, we investigated whether elevated endogenous insulin and insulin resistance independently predict longitudinal DD progression and adverse cardiovascular outcomes. METHODS: In a community-based cohort study, we evaluated 1191 participants from the Olmsted County Heart Function Study (median age, 58.7 [interquartile range, 52.4–66.6 years]) who underwent echocardiography at baseline and after 4 years. Fasting insulin and homeostatic model assessment of insulin resistance were assessed. The primary end point was DD progression. Secondary outcomes (mortality, heart failure) were assessed in 2030 participants followed for a median of 10.97 (95% CI, 10.90–11.05) years for heart failure and a median of 18.1 (95% CI, 18.0–18.2) years for mortality. RESULTS: DD progression occurred in 7.5% of participants. Baseline fasting insulin and homeostatic model assessment of insulin resistance strongly predicted progression ( P <0.001). In multivariable analysis, every 1-SD increase in log-transformed insulin was associated with 65% increased odds of progression (odds ratio, 1.65 [95% CI, 1.33–2.07]; P <0.001), adjusting for age, creatinine, and NT-proBNP (N-terminal pro-B-type natriuretic peptide). Similar results were observed for homeostatic model assessment of insulin resistance (odds ratio, 1.66 [95% CI, 1.34–2.08]; P <0.001). In secondary analyses, elevated insulin independently predicted all-cause (hazard ratio, 1.11 per 1-SD [95% CI, 1.02–1.21]) and cardiovascular mortality (hazard ratio, 1.16 [95% CI, 1.02–1.33]). Homeostatic model assessment of insulin resistance was similarly predictive of all-cause (hazard ratio, 1.11 [95% CI, 1.03–1.20]) and cardiovascular mortality (hazard ratio, 1.16 [95% CI, 1.02–1.32]). CONCLUSIONS: Elevated endogenous insulin and insulin resistance are predictors of progressive DD and long-term mortality, even after accounting for body mass index. Metabolic dysregulation may drive myocardial stiffening before diabetes onset, identifying a potential early therapeutic window for heart failure with preserved ejection fraction prevention.

Abstract Although sequencing costs have steadily decreased with advances in technology, they remain high for large scale studies. The design of traditional individual-disease sequencing studies is either case only or cases with relatively few controls, resulting in potential loss of statistical power for discovery of disease associated genes. Here we show that for a given number of sequenced cases, a large control sample size is critical to maximize power for rare variant burden analysis. Furthermore, we have developed an end-to-end workflow based tool (CoCoRV-nf) to facilitate the use of external biobank sequence resources as controls. The modules include consistent variant QC, variant annotation, ancestry population prediction, and gene based burden analysis using summary genotype information, and combined analysis from multiple independent results. The tool supports exomes and genomes from gnomAD and All of Us as controls with preprocessed datasets. We apply the tool in two rare neurological diseases: amyotrophic lateral sclerosis and neuroblastoma. For each disease, two case cohorts are paired with gnomAD and All of Us data, respectively, followed by a combined analysis. Not only did we recapture known genes, but also, we identified new candidate genes for both diseases. By leveraging multiple large external biobank sequence data, we demonstrate the feasibility of using our tool to maximize statistical power to identify new disease predisposition genes.

DNA double-strand breaks (DSBs) that occur during mitosis are primarily repaired by Polθ-mediated microhomology-mediated end joining (MMEJ). The CIP2A–TOPBP1 complex has been shown to tether broken chromatin at mitotic DSBs, but whether it coordinates with or functions independently of Polθ remains unknown. Here, we show that the CIP2A–TOPBP1 complex is recruited to mitotic DSB sites, where it directly interacts with Polθ and corecruits Polθ to chromatin. CIP2A sustains Polθ phosphorylation by inhibiting PP2A, thereby prolonging Polθ chromatin retention and enabling efficient repair. Upon repair completion, the CIP2A–TOPBP1 complex dissociates, PP2A dephosphorylates Polθ, and Polθ is released from chromatin. Loss of CIP2A impairs tumor growth, while disruption of CIP2A–Polθ binding leads to persistent DNA damage, micronucleus formation, and synthetic lethality in BRCA1/2-deficient cells. These findings uncover a cooperative mechanism by which CIP2A–TOPBP1 dynamically regulates Polθ in mitotic DSB repair and provide insights into the synthetic lethal interaction of CIP2A with BRCA1/2 under radiotherapy.

Abstract Background While the radiation dose to left anterior descending (LAD) artery is associated with overall survival (OS) in NSCLC patients, manual segmentation is labor‐intensive. Several auto‐segmentation models were developed on average 4DCT with promising geometric agreement, yet their feasibility in clinical outcome analysis on lung CT remains unclear. Purpose This study evaluates whether automated LAD segmentation can reproduce, at the group level, the established dose‐survival association in a multi‐institutional clinical trial dataset. Methods Three deep learning‐based auto‐segmentation (DLAS) models for automatic segmentation of the LAD coronary artery were applied to 460 patients from the NRG Oncology/RTOG 0617 dataset. Kaplan–Meier curves and Cox proportional hazard ratio (HR) were calculated using each model's segmentation. The LAD V15 Gy was used to stratify patients into high‐and low‐risk groups, and the cut‐off values were determined by minimizing mean absolute error (MAE) between DLAS‐derived and manual OS curves. Results All three models demonstrated significantly different OS curves between the high risk and low risk groups ( p < 0.05). The HR was 1.40 (95% CI: 1.02–1.93; p = 0.0381; MAE = 7.1%), 1.32 (95% CI: 1.03–1.68; p = 0.0258; MAE = 9.6%), and 1.37 (95% CI: 1.03–1.84; p = 0.0331; MAE = 7.9%) for the three models using a common V15 Gy ≥ 10% cut‐off. After optimizing the cut‐off, one model aligned well with what was derived from manual segmentation (MAE = 4.3%). Conclusion Among the evaluated models, one DL model showed the strongest performance of survival groups separation and achieved group‐level overall survival stratification comparable to that previously reported using manual contours in the multi‐institutional cohort. Further validation with paired manual contours and pre‐specified cutoffs is warranted.

Abstract Invasive lobular breast carcinoma (ILC) is the most common special histological subtype of breast cancer, which accounts for 10-15% of all cases. To study the phenotype characteristics, metastatic growth kinetic and immune microenvironment of ILC, we developed an orthotopically transplantable cell line model from the spontaneous mammary fat pad tumor of CDH1-PTEN dual knockout C57BL/6 mouse with Cre-loxP system, designated CPT6. CPT6 recapitulates single-file growth pattern of human ILC, with pleomorphic features and a high mitotic index. RNA sequencing together with whole exome sequencing reveals a luminal A subtype with targetable driver mutations such as Kras G12C. As a novel orthotopically transplantable ILC model in immune competent mice, CPT6 shows robust in vivo growth and metastatic rate, and has moderate immunogenicity which appears to be T-cell independent. We also profiled the immune microenvironment of CPT6, revealing a myeloid-rich environment with dominant M2-macrophage population, which is concordant with human ILC. In summary, this model recapitulates human ILC phenotype and represents a valuable preclinical platform for evaluating immunotherapy and other therapeutic strategies for invasive lobular breast carcinoma.

Urinary urea is a key biomarker for tracking protein oxidation and nitrogen balance. A persistent analytical limitation is that conventional total-nitrogen assays do not deconvolute urinary urea from urinary ammonia, and direct measurement still requires capital-intensive clinical analyzers. Here, we implement and independently validate two cost-effective methods that resolve urinary urea by pairing the presence and absence of urease: Method 1 is a urease-coupled potentiometric assay using an ammonium ion-selective electrode (ISE method); Method 2 is a microplate Berthelot–salicylate colorimetric assay employing a repurposed consumer-grade aquarium ammonia test kit (API®) (API method). Each method was validated against the Roche Cobas C311 clinical analyzer (ISE for urinary ammonia and API for urinary urea) in healthy adult volunteers (n = 10 each), and API–ISE were then compared head-to-head for urinary urea. ISE vs. Cobas yielded R2 = 0.967, slope 95% CI [0.867, 1.173], and Bland–Altman bias of −1.02 mM (95% LoA [−7.40, +5.36] mM). API vs. Cobas yielded R2 = 0.973, slope 95% CI [0.790, 1.039], and bias of −1.55 mM (95% LoA [−11.56, +8.46] mM). API–ISE urinary urea comparison confirmed mutual agreement (R2 = 0.9976, slope 95% CI [0.946, 1.024]; bias of +3.47 mM; 95% LoA [−14.60, +21.53] mM), with mean recoveries near 100% (API: 100.7 ± 2.9%; ISE: 100.6 ± 5.4%; 20–350 mM). Both methods agreed with the clinical analyzer, supporting their potential for decentralized, resource-limited testing; clinical and point-of-care validations are needed.

BMT CTN 1506 ("MORPHO") was a phase 3 study of post-hematopoietic cell transplantation (HCT) maintenance with gilteritinib versus placebo for patients with FLT3-ITD-mutated acute myeloid leukemia (AML) in first remission. Subgroup analysis indicated a significant benefit of post-HCT gilteritinib for participants in North America, but no benefit for those in Europe or Asia. We conducted a post-hoc analysis of the data focusing on days from AML diagnosis to HCT, pre-HCT FLT3 inhibitor use, and FLT3-ITD measurable residual disease (MRD). Participants transplanted &lt; 120 days from AML diagnosis and/or those treated with FLT3 inhibition pre-HCT were more likely to have improved survival from post-HCT gilteritinib. Pre-HCT MRD levels were higher (P = 0.001) in participants transplanted within 120 days from diagnosis and in those treated with a FLT3 inhibitor pre-HCT and transplanted within 120 days (P = 0.008). Pre-HCT MRD was dependent on both FLT3 inhibitor use and time to HCT, as participants treated with successive courses of chemotherapy + FLT3 inhibition had successively lower MRD by the time of HCT. Time from AML diagnosis to HCT and pre-HCT FLT3 inhibitor use both appeared to impact MRD levels immediately prior to HCT, and geographic differences in these two practice patterns likely accounted for the observed regional differences in benefit from post-HCT gilteritinib. Increasing the number of courses of treatment pre-HCT may lower MRD sufficiently to eliminate the need for post-HCT inhibition, but with a presumed risk of some patients experiencing early progression. This trial was registered at www.clinicaltrials.gov as #NCT02997202.