Citations

Abstract Despite aggressive therapy consisting of surgery followed by radio/chemotherapy Glioblastoma (GBM) recurs in almost all patients and, currently, there are no proven therapies to treat recurrent GBM (rGBM). Recent developments in nanomedicine provide new and promising opportunities to develop new targeted therapeutics to treat brain tumors. In this study we combine bioinformatics, forward-thinking understanding of miRNA biology and cutting-edge nucleic acid delivery vehicles to advance targeted therapeutics for rGBM. Bioinformatic analysis of RNA sequencing from GSCs and clinical rGBM specimens identified TGF-beta receptor II (TGFBR2) signaling as a targetable pathway in rGBM. Mechanistically, we show that alterations in chromatin state driven by stem-cell driving events are conducive to a therapy-resistant state induced by TGFBR2. We show that blocking TGFBR2 via molecular and pharmacological approaches decreases the stem cell capacity, cell viability and re-sensitizes clinical rGBM isolates to temozolomide (TMZ) in vitro. Network analysis of SMAD2/3 targets enriched in rGBM predicted a subset of miRNAs that can target multiple genes within this set. Notably, miR-590-3p was predicted to inhibit 37 SMAD 2/3 gene targets that are also enriched in rGBMs. Bioinformatics analysis also showed that expression of 24 of those 37 miR-590-3p targets are positively correlated with TGFBR2 expression in rGBM clinical specimens. Consistent with these predictions, miR-590-3p inhibited expression of 25 of the 37 targets across 3 distinct therapy-resistant GSC isolates. To translate these in vitro finding, we developed novel bioreducible Lipophilic poly(β-amino ester) nanoparticles (LiPBAEs) for in vivo miRNA delivery. Following direct intratumoral infusion, these nanomiRs efficiently distribute through the tumors and spatial transcriptomic analysis (STA) found a decrease in 34 out of the 37 miR- 590-3p targets in animals that received the active nanomiR compared to control miRNA. Furthermore, STA identified 3 cell populations with distinct transcriptomic profiles reflecting a gradient pharmacodynamic response within tumors that received miR-590-3p nanomiRs with decreasing target expression towards the core of the tumor closest to catheter tip placement. To test the effect of 590-3p nanomiR therapy on survival, animals bearing pre-established intracranial rGBM xenografts received three infusions of either control or miR-590-3p nanomiRs every other day beginning on post-implantation day 7. All 10 animals treated with control nanomiRs were either dead or premorbid requiring euthanasia by post-implantation day 23. In contrast, 3 of 10 animals treated with miR-590-3p nanomiRs remained alive and healthy by post-implantation day 45, at which time the experiment was terminated. These results show that miRNA-based targeted therapeutics provide new opportunities to treat rGBM and bypass the resistance that is developed to standard of care. Citation Format: Hernando Lopez-Bertoni, Jack Korleski, Sophie Sall, Kathryn Luly, Maya K Johnson, Amanda L Johnson, Harmon Khela, Bachchu Lal, TC Taylor, Jean Micheal Ashby, Hector Alonso, Alice Li, Stephany Tzeng, John Laterra, Jordan J Green. Multipronged SMAD Pathway Targeting by LiPBAE miR-590-3p NanomiRs Inhibits Recurrent Glioblastoma Growth and Prolongs Survival [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: RNAs as Drivers, Targets, and Therapeutics in Cancer; 2024 Nov 14-17; Bellevue, Washington. Philadelphia (PA): AACR; Mol Cancer Ther 2024;23(11_Suppl):Abstract nr PR011.

Background: We previously developed deep-learning algorithms that identify coronary artery disease (CAD) risk based on (i) coronary artery calcium (CAC), (ii) obstructive CAD by angiography, and (iii) left ventricular akinesis in ≥1 segment by echocardiogram, using a 12-lead electrocardiogram (CAD ECG-AI). We tested the hypothesis that those with increased probability of CAD by CAD ECG-AI algorithms will have an increased risk of atherosclerotic cardiovascular disease (ASCVD) events and would refine the AHA Predicting Risk of Cardiovascular Disease Events (PREVENT TM ) equations’ predictive capabilities. Methods: We assessed a group of consecutive patients who sought primary care in Olmsted County, MN, between 1997 and 2003. Passive follow-up was conducted using the Rochester Epidemiology Project's record linkage system. Patients included met the same criteria of the original PREVENT TM equations. The probability output of each CAD ECG-AI algorithm was used to predict ASCVD (fatal and non-fatal myocardial infarction and ischemic stroke) and ASCVD-Plus [further including percutaneous coronary intervention (PCI), coronary artery bypass grafting (CABG), and all-cause mortality]. Events were validated in duplicate. Cox proportional hazard models adjusted for age, sex, and risk factors while modeling each CAD ECG-AI algorithm as an individual and additive predictor (see footnote). PREVENT TM risk categories stratified analysis to evaluate the effect of the CAD ECG-AI models on predicted ASCVD risk. Results: We included 21,193 patients, with mean ± SD age 51.6 ± 12.0, 54% women and 95% white. After 14.2±12.4 years follow-up, 1,351 (6.4%) developed ASCVD, and 2,808 (13.2%) had ASCVD-Plus. The risk of ASCVD and ASCVD-Plus increased with positivity for the CAD ECG-AI algorithms after adjustments for age, sex, and PREVENT TM equations factors, all p for trend <0.001 (data not shown). In additive analyses, the risk of ASCVD and ASCVD-Plus increased with increased CAD ECG-AI factors, all p for trend <0.001 ( Fig. A-B ). Furthermore, the CAD ECG-AI algorithm enhanced the predictive capabilities of PREVENT TM equations across most risk subgroups ( Fig. C-E ). Conclusions: The deep-learning CAD ECG-AI algorithms displayed an independent and additive association with long-term ASCVD and ASCVD-Plus events in the community and improved the PREVENT TM predicted ASCVD risk. The CAD ECG-AI algorithms could help identify individuals at risk in primary prevention of cardiovascular events.

Background: Our team recently developed an Artificial Intelligence model that enables the identification of increased left ventricular filling pressures using a single-lead electrocardiogram (AI-ECG) with excellent performance (AUC 0.91). However, its ability to predict incident heart failure (HF) in the community is yet to be evaluated. Hypothesis: We tested the hypothesis that the output from the AI-ECG will predict the long-term incidence of heart failure (HF) and HF with preserved ejection fraction (HFpEF), and would refine the HF predictive capabilities of the AHA Predicting Risk of Cardiovascular Disease EVENTs (PREVENT TM ) Equations. Methods: Leveraging the resources of the Rochester Epidemiology Project (REP) we analyzed data from patients who sought primary care in Olmsted County, MN, between 1997-2003 with passive follow-up until April 2024. We included those with a digital ECG at baseline and excluded those who were part of the original algorithm development or history of heart failure. The diagnosis of heart failure was ascertained by using ICD codes (ICD9-428,ICD10-I.50) and a word search for the terms related to heart failure. HFpEF was ascertained using the Ejection Fraction (EF) data closest to the heart failure diagnosis date, using EF more than 40% as the criterion. We tested the association between AI-ECG predicted probabilities and new-onset HF and HFpEF using Cox proportional hazard models. These models were also adjusted for cardiovascular risk factors and were stratified to evaluate the effect of the AI-ECG output on PREVENT TM -predicted HF at 10 years. Results: We included 20,276 subjects, mean age 55±14.03, 52% women, 92% non-Hispanic white. After 18.2±8.5 years of follow-up, 4,008 (19.76%) were diagnosed with HF and 3,812 (18.8%) HFpEF. Risks of HF and HFpEF significantly increased in patients with increased left ventricular filling pressures by AI-ECG, independent of risk factors, all p for trend <0.001, see Fig A-B , respectively. AI-ECG enhanced the prediction capabilities of the PREVENT TM score across all risk groups, see Fig-C. Conclusions: AI-ECG-Derived increased left ventricular filling pressure is associated with new-onset HF and HFpEF in the community and was associated with incidental heart failure at any PREVENT TM risk category. Those results suggest a potential role of AI ECG in predicting heart failure.

Background: Papillary fibroelastomas (PFE) arising between the left upper pulmonary vein and left atrial appendage, commonly referred to as the coumadin ridge or Q-tip, are extremely rare and best detected by transesophageal echocardiography (TEE). Although PFEs are benign, they have been associated with a range of serious embolic events. Objective: To analyze the characteristics, clinical findings, and diagnostic techniques of PFEs originating from the coumadin ridge. Methods: We describe 13 cases of pathology proven papillary fibroelastomas uniquely attached to the Q-tip. Patient data, including demographics, mass characteristics and diagnostic imaging were collected and analyzed. Results: Thirteen patients with pathology-proven PFEs attached to the coumadin ridge were included in the study. The median age of the cohort is 73 (IQR 67-77), and 54% of the patients were male. Tumor sizes ranged from 2mm to 20mm with a median of 5mm (IQR 3.5-8.5). Twelve (92%) of the PFEs were initially visualized on TEE, and one case was diagnosed postoperatively by pathologists after the excision of the left atrial appendage. The majority of cases were incidental diagnoses, with 46% of cases incidentally discovered intraoperatively by routine TEE, and 30% visualized on TEE done for diverse reasons including valvular assessment, exclusion of infective endocarditis, and coronary artery disease (CAD) assessment. One case was incidentally detected on CMR performed as part of a metastatic tumor workup. Four (30%) patients presented with symptoms of stroke/TIA, of which 2 had a previous history of stroke. One patient had symptoms of both TIA and angina pectoris. Cardiovascular disease risk factors were prevalent: 69% had hyperlipidemia, 46% had atrial fibrillation (Afib), 31% had CAD, 54% had hypertension, and 46% were former smokers. Conclusions: Masses on the Q-tip are rare but significant intracardiac sources of embolism. Accurate identification and categorization of these masses are challenging, yet critical, to guide appropriate surgical intervention and improve patient outcomes. Further studies are needed to establish standardized diagnostic and treatment protocols for this unique presentation of PFEs.

IMPORTANCEYoung adults aged 18 to 39 years represent the minority of breast cancer diagnoses but are particularly vulnerable to financial hardship. Factors contributing to sustained financial hardship are unknown.OBJECTIVESTo identify financial hardship patterns over time and characterize factors associated with discrete trajectories; it was hypothesized that treatment-related arm morbidity, a key source of expense, would be associated with long-term financial difficulty.DESIGN, SETTING, AND PARTICIPANTSThis cohort study included US young adults aged 40 years or younger treated between 2006 and 2016. Eligible patients were treated for stage 0 to stage III breast cancer at institutions participating in the Young Women’s Breast Cancer Study, which included a specialized cancer institute and 12 other academic and community hospitals. Patients who responded at baseline and returned a 1-year survey were included in analysis. Data were analyzed in March 2024.MAIN OUTCOMES AND MEASURESTrajectory modeling classified patterns of financial difficulty from baseline through 10 years postdiagnosis using the Cancer Rehabilitation Evaluation System (CARES) scale. Multinomial regression examined characteristics, including treatment-related arm morbidity, associated with each trajectory.RESULTSA total 1008 patients were included (median [IQR] age at diagnosis, 36 [33-39] years; 60 Asian [6.0%], 35 Black [3.5%], 47 Hispanic [4.7%], 884 White [87.7%]); 840 patients were college graduates (83.3%), 764 were partnered at baseline (75.8%), 649 were nulliparous (64.4%), and 908 were without comorbidities at enrollment (90.1%). Patients’ tumors were primarily stage I-II (778 [77.2%]), estrogen receptor/progesterone receptor–positive (754 [74.8%]), and ERBB2-negative (formerly HER2) (686 [68.1%]). Patients were more frequently treated with mastectomy than breast conservation (771 [76.5%] vs 297 [29.5%]; P &amp;lt; .001). A majority of patients received radiation therapy (627 [62.2%]), chemotherapy (760 [75.4%]), and endocrine therapy (610 [60.6%]). A total of 727 patients (72.1%) reported arm symptoms within 2 years of surgery. Three distinct trajectories of experiences with finances emerged: 551 patients (54.7%) had low financial difficulty (trajectory 1), 293 (29.1%) had mild difficulty that improved (trajectory 2), and 164 (16.3%) had moderate to severe difficulty peaking several years after diagnosis before improving (trajectory 3). Hispanic ethnicity (OR, 3.71; 95% CI, 1.47-9.36), unemployment at baseline and 1 year (OR, 2.66; 95% CI, 1.63-4.33), and arm symptoms (OR, 1.77; 95% CI, 1.06-2.96) were associated with increased odds of experiencing trajectory 3. Having a college degree (OR, 0.20; 95% CI, 0.12-0.34) or being partnered (OR, 0.24; 95% CI, 0.15-0.38) were associated with increased odds of experiencing trajectory 1.CONCLUSIONIn this cohort study of young adults with breast cancer, we identified a subset of patients who experienced a high degree of financial difficulty persisting into early survivorship. Targeted interventions to mitigate financial toxicity—modifiable factors that include support for the employability or return to work support for those experiencing arm symptoms after treatment—are needed.

Abstract Safe delivery of mRNA to the brain will revolutionize the treatment of brain tumors. While lipid nanoparticles (LNPs) are clinically most advanced non-viral delivery vehicles for therapeutic mRNA, LNP-mediated mRNA delivery to the brain remains challenging. We hypothesized that rationally designed LNPs based on extracellular vesicle mimicry would enable efficient delivery of RNA therapeutics to brain cells without undue toxicity. We engineered LNPs consisting of four components similar to the formulation used in the mRNA COVID-19 vaccines (Moderna and Pfizer-BioNTech): ionizable lipid, cholesterol, helper lipid and polyethylene glycol (PEG)-lipid. We screened ten classes of helper lipids based on lipids enriched in extracellular vesicles to engineer biomimetic LNPs and tested their GFP mRNA delivery efficacy in SIM-A9 mouse microglia cell line. Several unique LNP formulations with potent delivery efficacy (&gt;90% cells transfected) and stable GFP expression kinetics (5 days) were identified. LNP formulations with high transfection efficacy were then tested in vivo for luciferase mRNA delivery via intrathecal injection in C57BL/6 mice. Luciferase expression in vivo confirmed widespread mRNA delivery in the brain. We then tested Cre recombinase mRNA delivery in Ai9 mouse to identify LNP-targeted cells via flow cytometry and histology. Flow cytometry and expansion microscopy confirmed Cre recombinase mRNA delivery to a variety of brain cells, including microglia (75-90%), neurons (31-40%), neural stem cells (39-62%), oligodendrocytes (70-90%), and astrocytes (44-76%). LNPs were further evaluated for Cas9 mRNA and CD81 sgRNA delivery in C57BL/6 mouse brains to assess brain-targeted gene editing. Sanger sequencing showed that CRISPR-Cas9 editing was successful in ~40% of cells in the mouse brain. In summary, we engineered extracellular vesicle-based LNP library that can deliver RNA therapeutics to a variety of brain cells in vivo. With further development, this technology could potentially enable genetic and epigenetic therapies targeting drivers of brain tumors.

PURPOSE Pharmacologic therapies for neurofibromatosis type 1-associated plexiform neurofibromas (NF1-PNs) are limited; currently, none are US Food and Drug Administration–approved for adults. METHODS ReNeu is an open-label, multicenter, pivotal, phase IIb trial of mirdametinib in 58 adults (≥18 years of age) and 56 children (2 to 17 years of age) with NF1-PN causing significant morbidities. Patients received mirdametinib capsules or tablets for oral suspension (2 mg/m 2 twice daily, maximum 4 mg twice daily), regardless of food intake, in 3 weeks on/1 week off 28-day cycles. The primary end point was confirmed objective response rate (ORR; proportion of patients with a ≥20% reduction of target PN volume from baseline on consecutive scans during the 24-cycle treatment phase) assessed by blinded independent central review (BICR) of volumetric magnetic resonance imaging. RESULTS Twenty-four of 58 adults (41%) and 29 of 56 children (52%) had a BICR-confirmed objective response during the 24-cycle treatment phase; in addition, two adults and one child had confirmed responses during long-term follow-up. Median (range) target PN volumetric best response was –41% (−90 to 13) in adults and –42% (−91 to 48) in children. Both cohorts reported significant and clinically meaningful improvement in patient- or parent proxy-reported outcome measures of worst tumor pain severity, pain interference, and health-related quality of life (HRQOL) that began early and were sustained during treatment. The most commonly reported treatment-related adverse events were dermatitis acneiform, diarrhea, and nausea in adults and dermatitis acneiform, diarrhea, and paronychia in children. CONCLUSION In ReNeu, the largest multicenter NF1-PN trial reported to date, mirdametinib treatment demonstrated significant confirmed ORRs by BICR, deep and durable PN volume reductions, and early, sustained, and clinically meaningful improvement in pain and HRQOL. Mirdametinib was well-tolerated in adults and children.

Abstract Purpose: To determine the relationship between germline pathogenic variants (PV) in cancer predisposition genes and the risk of ductal carcinoma in situ (DCIS). Experimental Design: Germline PV frequencies in breast cancer predisposition genes (ATM, BARD1, BRCA1, BRCA2, CDH1, CHEK2, PALB2, RAD51C, and RAD51D) were compared between DCIS cases and unaffected controls and between DCIS and invasive ductal breast cancer (IDC) cases from a clinical testing cohort (n = 9,887), a population-based cohort (n = 3,876), and the UK Biobank (n = 2,421). The risk of contralateral breast cancer (CBC) for DCIS cases with PV was estimated in the population-based cohort. Results: Germline PV were observed in 6.5% and 4.6% of women with DCIS in the clinical testing and population-based cohorts, respectively. BRCA1, BRCA2, and PALB2 PV frequencies were significantly lower among women with DCIS than those with IDC (clinical cohort: 2.8% vs. 5.7%; population-based cohort: 1.7% vs. 3.7%), whereas the PV frequencies for ATM and CHEK2 were similar. ATM, BRCA1, BRCA2, CHEK2, and PALB2 PV were significantly associated with an increased risk of DCIS (OR &gt; 2.0), but only BRCA2 PV were associated with high risk (OR &gt; 4) in both cohorts. The cumulative incidence of CBC among carriers of PV in high-penetrance genes with DCIS was 23% over 15 years. Conclusions: The enrichment of PV in ATM, BRCA1, BRCA2, CHEK2, and PALB2 among women with DCIS suggests that multigene panel testing may be appropriate for women with DCIS. Elevated risks of CBC in carriers of PV in high-penetrance genes with DCIS confirmed the utility of testing for surgical decision-making.

Background Early detection of left and right ventricular systolic dysfunction (LVSD and RVSD respectively) in children can lead to intervention to reduce morbidity and death. Existing artificial intelligence algorithms can identify LVSD and RVSD in adults using a 12‐lead ECG; however, its efficacy in children is uncertain. We aimed to develop novel artificial intelligence–enabled ECG algorithms for LVSD and RVSD detection in pediatric patients. Methods and Results We identified 10 142 unique pediatric patients (age≤18) with a 10‐second, 12‐lead surface ECG within 14 days of a transthoracic echocardiogram, performed between 2002 and 2022. LVSD was defined quantitatively by left ventricular ejection fraction (LVEF). RVSD was defined semiquantitatively. Novel pediatric models for LVEF ≤35% and LVEF <50% achieved excellent test areas under the curve of 0.93 (95% CI, 0.89–0.98) and 0.88 (95% CI, 0.83–0.94) respectively. The model to detect LVEF <50% had a sensitivity of 0.85, specificity of 0.80, positive predictive value of 0.095, and negative predictive value of 0.995. In comparison, the previously validated adult data‐derived model for LVEF <35% achieved an area under the curve of 0.87 (95% CI, 0.84–0.90) for LVEF ≤35% in children. A novel pediatric model for any RVSD detection reached a test area under the curve of 0.90 (0.87–0.94). Conclusions An artificial intelligence–enabled ECG demonstrates accurate detection of both LVSD and RVSD in pediatric patients. While adult‐trained models offer good performance, improvements are seen when training pediatric‐specific models.

Abstract Females likely experience larger performance benefits from androgenic‐anabolic steroids than males. We set out to determine if there were temporal differences in select athletics (track and field) records between females and males. Exploratory aims included: (1) evaluating the improvements in female and male world records over time, and (2) investigating the influence of doping programs on male and female world records before and after 1990, when sports governing bodies began to implement random out‐of‐competition and systematic in‐competition drug testing. We collected the top 500 performances of all time for both sexes from an online database (worldathletics.org) in four running events (100, 200, 400 and 800 m) and two throwing events (discus throw and shot‐put). Data were stratified into quintiles based on world record ranking (1st to 100th, 101st to 200th, etc.). The temporal distribution of the top 100 female performers was significantly earlier than the top 100 male performers (year: 2000 ± 1 vs. 2005 ± 1, respectively; P < 0.0001). Within the event, the top performances occurred significantly earlier for females in the 800 m (year: 1995 ± 15 vs. 2003 ± 12; P = 0.0007) and shot‐put (year: 1992 ± 14 vs. 2003 ± 17; P = 0.0004). Among females, world records rapidly improved through the 1980s, but following 1990, the world records ceased to improve. Geographically, there was a greater representation of countries with state‐sponsored doping programs, specifically among female performances. We postulate these sex differences in the temporal distribution of top performances are likely associated with enhanced effectiveness of exogenous androgens (steroid doping) among female athletes with lower endogenous androgen hormones compared to males.