Citations

Objective: The purpose of this study was to report the clinical characteristics and prognosis of spontaneous isolated abdominal aortic dissection (SIAAD) based on the dissection length. Methods: Between March 2012 and September 2023, 159 of 7572 patients with aortic dissection were diagnosed with SIAAD and enrolled in the retrospective study. We proposed a new morphologic classification: extensive SIAAD (e-SIAAD) and focal SIAAD (f-SIAAD), based on whether the dissection length exceeds 50 mm or not. The clinical baseline, computed tomography angiography (CTA) findings, and long-term follow-up of the two types were compared. Results: SIAAD prevalence was 2.1%. Patients with f-SIAAD were significantly older (63.74 ± 10.97 vs. 50.70 ± 10.10 years, p < 0.001), had more atherosclerosis risk factors, arteriosclerosis, and penetrating aortic ulcers compared to e-SIAAD patients. Conversely, e-SIAAD presented more acutely (72.97% vs. 34.12%, p = 0.001), exhibited more frequent symptoms (85.14% vs. 61.18%, p = 0.0037), larger dissection diameters (31.89 ± 10.99 vs. 24.41 ± 11.28 mm, p = 0.001), and greater involvement of the renal and iliac arteries. Treatment involved medical management (30%), endovascular repair (65%), or surgery (2.5%), without significant differences between groups. In-hospital mortality was higher in f-SIAAD (six deaths vs. one in e-SIAAD). During median follow-up of 48 months (range, 6–148 months), mortality was higher in f-SIAAD (70% vs. 90% estimated 10-year survival). Conclusions: SIAAD classification by dissection length revealed significant differences in clinical presentation, CTA characteristics, and prognosis. Focal dissections correlated with advanced age, severe arteriosclerosis, and poorer long-term outcomes, emphasizing the need for tailored management approaches.

Background: Cholestatic liver diseases, including primary sclerosing cholangitis, are characterized by biliary fibroinflammation. TGFβ-activated cholangiocytes release signals that recruit immune cells and activate myofibroblasts, promoting inflammation and extracellular matrix (ECM) deposition. TGFβ also regulates stearoyl-CoA desaturase (SCD), an enzyme involved in lipid signaling. Yet, the role of SCD or its inhibitor, Aramchol, in biliary fibroinflammation had not been studied. Methods and Results: Mdr2 -/- with established biliary fibrosis and 3,5-diethoxycarboncyl-1,4-dihydrocollidine (DDC) diet-fed mice were treated with Aramchol meglumine (12.5 mg/kg/day). Hepatic fibrosis was assessed by qPCR, Picrosirius red staining, immunofluorescence, and hydroxyproline content. Human H69 or murine large cholangiocyte cell lines stimulated with TGFβ, as well as PSC-derived cholangiocytes (PSC-C), were treated with Aramchol or SCD siRNA. RNA-seq, fibroinflammatory marker expression, peroxisome proliferator-activated receptor (PPAR) activity, and targeted fatty acid profiling were performed. Aramchol treatment significantly reduced hepatic ECM gene expression, inflammatory cytokines ( Il6 , Tnfa ), collagen content, and myofibroblast activation (aSMA staining) in both mouse models. In TGFβ-stimulated H69 cells, Aramchol suppressed hepatic fibrosis pathways and enhanced PPAR signaling. Aramchol also reduced the expression of fibrotic markers, myofibroblast-activating mediators ( VEGFA and PDGFB ), and IL6, mirroring the effects of SCD knockdown. In PSC-C, Aramchol significantly downregulated SCD, VEGFA and IL6 . Conversely, PPARα and -γ activity and fatty acid agonist, linoleic acid levels were increased in cholangiocyte cell lines. Conclusions: Aramchol attenuates and prevents biliary fibrosis in mouse models of cholestatic liver disease by inhibiting TGFβ-induced fibroinflammatory mediators and activating PPARa/γ in cholangiocytes. These findings, combined with its favorable clinical safety profile, support the potential of Aramchol as a therapeutic candidate for PSC.

Abstract Aging increases the vulnerability of kidneys to injury and impairs their regenerative capacity. SIRT3 expression declines with aging and is associated with multiple age‐related pathologies. The expression profile and functional role of SIRT3 in renal aging remain unclear. Here, SIRT3 expression in aging kidneys is assessed and analyzed for its promoter methylation patterns using methylation‐specific PCR (MSP). It is found that aging exacerbates UUO‐induced renal fibrosis, associated with downregulated SIRT3 expression. Mechanistically, age‐related SIRT3 downregulation is mediated by hypermethylation of its promoter region. SIRT3 knockout exacerbated renal fibrosis in young mice subjected to UUO, whereas SIRT3 overexpression attenuated fibrosis in aged UUO mice. Integration of RNA‐seq and immunoprecipitation‐mass spectrometry (IP‐MS) analyses revealed that SIRT3 deficiency leads to hyperacetylation of GSK3β at lysine 15 (K15). This K15 hyperacetylation inhibited GSK3β activity, consequently stabilizing its substrate β‐catenin. Furthermore, self‐assembled PEG‐PCL‐PEG micelles are designed and synthesized to encapsulate hydrophobic honokiol (HKL). These micelles significantly enhanced the aqueous solubility and oral bioavailability of free HKL, maintained stable blood concentrations, and ultimately improved its anti‐fibrotic efficacy. These findings propose novel therapeutic strategies for managing renal fibrosis in the aging population and provide a foundation for developing new drugs and combination therapies.

Abstract Introduction: Radiotherapy (RT)-induced acute esophagitis (AE) is a common side effect in lung cancer patients receiving RT, which can significantly impact their quality of life. This highlights the need for a predictive model that can estimate AE risk in advance using pretreatment imaging data. However, collecting sufficient data for model development is often resource-intensive and costly. Additionally, acquiring a homogeneous training dataset (e.g., from a single center or modality) is not always feasible. This study aimed to develop an automated artificial intelligence-based 3D vision foundation model (VFM) combining standard-of-care planning computed tomography (pCT) and planned radiation dose maps to predict grade II or higher AE. Materials and methods: This study included 246 patients with non-small cell lung cancer who underwent either image-guided radiation treatment (IMRT) or proton-beam radiation therapy. The endpoint was grade two or higher AE (33% positive and 67% negative). The IMRT group consisted of 182 patients from a single center, whereas the proton therapy group included 64 patients from the Proton Collaborative Group trial from 11 different institutions. For each patient, pCT, dose maps, and radiotherapy segmentations were available. The VFM was created using a transformer pretrained using a large number of unlabeled volumetric 3D CTs from patients with varied diseases through a self-supervised learning approach, which extracts useful features directly from images. Next, the pretrained encoder was combined with fully connected classification layers and fine-tuned using stratified 5-fold cross-validation with 20 patients set aside for testing. We developed two models: a CT only and CT + dose model. Model performance was assessed using the area under the curve (AUC), specificity, and sensitivity. Results: In cross-validation, adding dose information to CT (CT+Dose) improved model performance, increasing AUC from 0.72 ± 0.08 to 0.76 ± 0.10 and specificity from 0.82 ± 0.09 to 0.87 ± 0.04, while sensitivity remained the same. On the independent test set, CT+Dose showed a marked improvement over CT only (AUC: 0.82 vs. 0.59; sensitivity: 0.57 vs. 0.14), with a slight decrease in specificity (0.77 vs. 1.00). Conclusion: A VFM model combining CT and radiation dose showed the capability to predict AE more accurately with higher specificity. Further studies on larger cohorts of testing patients are planned to assess model generalization. Citation Format: Chloe Min Seo Choi, Jue Jiang, Nikhil Mankuzhy, John Chang, Jing Zeng, Carlos Vargas, James Urbanic, Isabella Choi, Mark Mcdonald, James Gray, Joseph Deasy, Maria Thor, Charles Simone, Harini Veeraraghavan. Prediction of radiotherapy-Induced esophagitis in non-small cell lung cancer using a 3D vision foundation model [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Artificial Intelligence and Machine Learning; 2025 Jul 10-12; Montreal, QC, Canada. Philadelphia (PA): AACR; Clin Cancer Res 2025;31(13_Suppl):Abstract nr B022.

Abstract Purpose: Navtemadlin is a potent small-molecule inhibitor of MDM2, which has completed a phase 0 window-of-opportunity study in glioblastoma (GBM). To optimally interpret the clinical data, a detailed analysis of navtemadlin pharmacokinetics (PK), pharmacodynamics, and efficacy was performed in GBM patient-derived xenografts (PDX). Experimental Design: Response to navtemadlin was characterized in vitro and in vivo in GBM PDXs with and without MDM2 amplification. Efficacy in vivo was integrated with measured plasma and intra-tumoral drug levels to develop a translational PK/efficacy model comparing exposure effective in PDX to exposure achieved in phase 0 patient samples. Results: In vitro, navtemadlin showed robust on-target activity in TP53–wild-type GBM. In vivo efficacy strongly correlated with MDM2 amplification status. In subcutaneous PDXs, navtemadlin significantly extended survival when dosed at 25 mg/kg in an MDM2-amplified PDX compared with 100 mg/kg in a non-amplified PDX. Central nervous system distribution was limited by blood–brain barrier efflux (Kp_brain = 0.009). In an MDM2-amplified orthotopic PDX model, navtemadlin was ineffective at 100 mg/kg; when established in mice with deficient blood–brain barrier efflux (Rag−/−Abcb1a−/−Abcg2−/−), 25 mg/kg doubled survival. A tumor PK/efficacy model was built to define target exposure for efficacy in GBM, using the effective 25 mg/kg dose. Modeled exposures exceeded this threshold in three (of 16) tumor samples from phase 0 study patients at the 240 mg dose level. Conclusions: Navtemadlin efficacy was highly dependent on adequate brain penetration. Our translational PK/efficacy model suggests that the minimum effective tumor exposures were achieved only in a minority of patients with GBM.

Triple-negative breast cancer (TNBC) represents the most malignant subtype of breast cancer. The clinical application of PARP inhibitors (PARPi) is limited by the low frequency of BRCA1/2 mutations in TNBC. Here, we identified that MTAP deletion sensitized genotoxic agents in our clinical cohort of metastatic TNBC. Further study demonstrated that MTAP deficiency or inhibition rendered TNBC susceptibility to chemotherapeutic agents, particularly PARPi. Mechanistically, targeting MTAP that synergized with PARPi by disrupting the METTL16-MAT2A axis involved in methionine metabolism and depleting in vivo s-adenosylmethionine (SAM) levels. Exhausted SAM in turn impaired PARPi-induced DNA damage repair through attenuation of MRE11 recruitment and end resection by diminishing MRE11 methylation. Notably, brain metastatic TNBC markedly benefited from a lower dose of PARPi and MTAP deficiency/inhibition synergy due to the inherently limited methionine environment in the brain. Collectively, our findings revealed a feed-forward loop between methionine metabolism and DNA repair through SAM, highlighting a therapeutic strategy of PARPi combined with MTAP deficiency/inhibition for TNBC.

e23345 Background: Telemedicine enables patients to attend visits remotely and is associated with shorter wait times (i.e. scheduling-to-appointment duration). However, its impact on patient–clinic distance and wait times for new patients in high-volume surgical oncology centers remains unclear. In these centers, where appointment availability and travel distance significantly influence care decisions, understanding telemedicine’s impact on access is essential as federal policies supporting telemedicine continue to be under legislative review. To address this, we examined the relationship between new patient visit modality, distance, and wait time across demographics, providing insights to guide policy makers, and clinical practice. Methods: We extracted visit data from a multispecialty surgical oncology center in Northern California from 2019 to 2023 and used linear models with fixed effects for clinician and patient characteristics to assess the association of NPV modality with distance and wait times. We calculated distance using geodesic measurements between residential ZIP codes and care sites and derived median household income and education levels from the American Community Survey. Results: There were 10596 NPVs in 2019, and 13982 in 2023, conducted by 78 and 100 clinicians respectively. The proportion of NPV visits conducted by telemedicine increased from 0% to 28% during this period. From 2021–2023, NPVs conducted by telemedicine were more likely to fall outside the center’s 2019 catchment area (80th percentile of distance) with an adjusted odds ratio of 1.89 (95% CI 1.62, 2.21). Wait times for telemedicine NPVs was 3.0 days shorter (95% CI [2.0, 3.9]) than in-person visits. Compared to the reduction in wait times for patients aged 45–65 (2.8 days, 95% CI [1.8, 3.8]), those 80 and older had a smaller reduction (1.9 days, 95% CI [0.9, 2.8]), while patients aged 65–79 had a greater reduction (3.4 days, 95% CI [2.4, 4.5]). This effect did not significantly vary by sex, race, ethnicity, education, income, or insurance status. Conclusions: At this multispecialty surgical oncology center, new patients seen via telemedicine were more likely to reside outside the center’s traditional catchment area and had shorter wait times, with these differences varying by demographic characteristics. Strategic telemedicine integration tailored to patient needs could enhance access by reducing wait times and expanding specialized surgical oncology care to patients across broader geographic distances.