Citations

Abstract Glioblastoma (GBM) remains the most common and lethal adult malignant primary brain cancer with few treatment options. A significant issue hindering GBM therapeutic development is intratumor heterogeneity and plasticity. GBM tumors contain neoplastic cells within a fluid spectrum of diverse transcriptional states. Identifying effective therapeutics requires a platform that predicts the differential sensitivity and resistance of these states to various treatments. Here, we develop scFOCAL (Single-Cell Framework for -Omics Connectivity and Analysis via L1000), to quantify the cellular drug sensitivity and resistance landscape. Using single-cell RNA sequencing of newly diagnosed and recurrent GBM tumors, we identify compounds from the LINCS L1000 database with transcriptional response signatures selectively discordant with distinct GBM cell states, and leverage this capability to predict combination synergy. We validate the significance of these findings in vitro, ex vivo, and in vivo, and use the Olig2 inhibitor CT-179 as a reference drug to identify additional small molecules that would maximize the cell-drug discordance across the GBM transcriptional landscape. Our analysis leads to the combination of Olig2 inhibition with treatment with Depatux-M, of with which we demonstrate synergy in vivo. Our studies suggest that scFOCAL identifies cell states that are sensitive and resistant to targeted therapies in GBM using a measure of cell and drug connectivity, which can be applied to identify new synergistic combinations. Citation Format: Robert K. Suter, Anna M. Jermakowicz, Rithvik Veeramachaneni, Matthew D'Antuono, Longwei Zhang, Rishika Chowdary, Simon Kaeppeli, Madison Sharp, Pravallika Palwai, Vasileios Stathias, Grace Baker, Luz Ruiz, Winston Walters, Maria Cepero, Danielle Burgenske, Edward B. Reilly, Anatol Oleksijew, Mark G. Anderson, Sion Ll. Williams, Michael E. Ivan, Ricardo J. Komotar, Macarena I. De La Fuente, Gregory Stein, Alexandre Wojcinski, Santosh Kesari, Jann N. Sarkaria, Stephan C. Schürer, Nagi G. Ayad. Drug and single-cell gene expression integration identifies heterogeneity-aware synergistic combinations for glioblastoma [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Brain Cancer; 2026 Mar 23-25; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2026;86(6_Suppl):Abstract nr B032.

PURPOSE To compare mortality risk among long-term survivors of high-grade serous ovarian cancer (HGSOC) with that of the general US population and to examine how mortality and recurrence trends have evolved under changing treatment approaches. MATERIALS AND METHODS This is a retrospective cohort study including patients with histologically confirmed HGSOC treated at a single referral cancer center from 1991 to 2022. Mortality risk, expressed as standardized mortality ratios (SMRs, ratio of observed deaths in the study population to expected deaths in an age-matched US population), was assessed at diagnosis and yearly on patients without events (disease persistence, recurrence, or death from any cause). RESULTS A total of 2,074 consecutive patients were included. The median follow-up was 12.5 years (IQR, 11.7-13.8). Most patients were stage III (1,396, 69.2%), 1,299 (62.8%) underwent primary cytoreductive surgery, and 1,688 (87.4%) received platinum-taxane as first-line therapy. At diagnosis, the mortality rate was 7.40 times higher than that in the general population (95% CI, 7.04 to 7.77). By 7 event-free years, the 95% CI for the SMR included 1 for the first time, and at 10 years, the SMR was 1.05 (95% CI, 0.72 to 1.49), indicating no statistically significant excess mortality compared with the general population. In those event-free at 10 years, the 5-year cumulative incidence of ovarian cancer–related deaths (8.2% [95% CI, 4.2 to 16.0]) was comparable with that of non–ovarian cancer–related deaths (6.3% [95% CI, 2.9 to 13.8]). CONCLUSION In this cohort, mortality risk steadily declined for patients who remained event-free, approaching that of the general population by 7 years after diagnosis. These results emphasize the importance of individualized, long-term follow-up to address both recurrence risk and survivorship needs.

Introduction Neurological post-acute sequelae of COVID-19 (neuroPASC) are associated with persistent cognitive dysfunction and quality-of-life decline. We aimed to identify clinical, behavioral and sociodemographic factors associated with neuroPASC symptom burden two years after COVID-19 among individuals without prior neurological disease. Methods In this prospective, observational study, individuals with neuroPASC ( n = 102) and controls without symptomatic COVID-19 ( n = 74), all without prior neurological, psychiatric, or post-viral conditions, were enrolled between February 2022 and June 2024 across five academic sites. An unsupervised algorithm identified clusters with differing self-reported neurological symptom burden within the neuroPASC group. Functional differences between clusters were evaluated using quality-of-life, neurological and cognitive evaluations. Demographics, behavioral history, comorbidities, and blood biomarkers were compared across clusters and controls. Multivariable logistic regression assessed predictors of neuroPASC severity, including demographics, body-mass-index, Charlson Comorbidity Index, Framingham Risk Score, pre-existing endocrine/metabolic and/or gastrointestinal/hepatobiliary conditions, COVID-19 vaccination prior to infection, hospitalization during acute infection, and cumulative alcohol use. Results Two clusters emerged based on neurological symptom burden, labeled “high-burden” and “low-burden” neuroPASC, reflecting differences in the number and frequency of symptoms. Both clusters had deficits in quality-of-life and cognitive function compared to controls, with greater impairment in high-burden than low-burden neuroPASC. The clusters did not differ by sex, education, tobacco and cannabis use, blood pressure, body-mass-index, HbA1C, days since infection, hospitalization during COVID-19, pre-COVID vaccination rate, antibody-positivity, inflammation, and neurodegeneration biomarkers. The high-burden cluster was older and exhibited higher comorbidity burden and greater cumulative alcohol use compared with the low-burden cluster and controls. Pre-existing endocrine/metabolic and gastrointestinal/hepatobiliary conditions were more common in high-burden (63%) than in low-burden neuroPASC (35%). After adjusting for clinical and demographic factors, these pre-existing conditions remained the only independent predictor of severity, conferring a 3.5-fold increase in the odds of high-burden versus low-burden neuroPASC. Discussion Older age, higher comorbidity burden, greater cumulative alcohol use, and endocrine/metabolic and gastrointestinal conditions, rather than acute COVID-19 severity, were observed in the high-burden neuroPASC cluster. After multivariable adjustment, only pre-existing endocrine/metabolic and/or gastrointestinal/hepatobiliary conditions remained independently associated with high-burden neuroPASC, conferring a 3.5-fold increase in odds and highlighting the need for targeted post-infection monitoring in at-risk patients.

Invasive lobular breast carcinoma (ILC), the most common special histological subtype of breast cancer, is characterized by nearly universal expression of estrogen receptor alpha (ER) and unique sites of metastases, neither of which is fully recapitulated by genetically engineered mouse models. Using reporter-labeled ILC mouse xenografts, herein we used mammary fat pad, tail vein and intracardiac orthotopic growth to analyze spontaneous and experimental metastasis and gene expression. We observed ER-positive primary tumors with single-file histology and collagen deposition, and spontaneous metastasis from the mammary fat pad to bones, ovaries, and brain including the leptomeninges, thereby closely mirroring the growth and metastatic spread of human ILC. Brain metastases showed strong ER staining, confirmed by sequencing analyses which identified estrogen signaling as top activated pathway, and the lesions exhibited robust response to endocrine therapy. In summary, we report endocrine responsive mammary fat pad, tail vein and intracardiac xenografts that faithfully demonstrate unique ILC features and can serve as invaluable pre-clinical translational platforms for validating candidate ILC genetic drivers and testing novel therapeutics.

ABSTRACT Background There is limited data regarding the surgical outcomes of urosymphyseal fistula (USF) repair with primary repair or autologous tissue transfer. We performed a study to compare outcomes of USF repair with primary repair, VRAM flap, and omental flap. Methods We retrospectively identified patients with a diagnosis of USF who underwent fistula decompression and urinary tract reconstruction. The minimal follow‐up was 3 months. Patients with distal urethral obstruction, radiation cystitis, or a non‐viable sphincter underwent anterior exenteration and flap transfer. Results Fifty‐six patients were included. Eleven patients underwent surgical management for USF using primary repair (19.6%), 34 had omental flap‐based reconstruction (60.8%), and a VRAM flap was used in 11 patients (19.6%). The 90‐day rate of sepsis was lower with omentum flap transposition (3%) compared with VRAM flap (27%) or primary repair (18%, p = 0.041). The rate of fistula recurrence was lower in the omentum flap group compared with USF primary repair (30%) or VRAM flap repair group (27.3%, p = 0.04). On multivariable analysis, USF repair with the omentum flap decreased the odds of fistula recurrence 90 days after surgery compared with primary repair (OR 0.012, p = 0.011) but not when compared with VRAM. Conclusion The omentum flap may offer a better safety profile in terms of decreasing the rate of early sepsis and rate of fistula recurrence for USF repair in comparison to primary repair. There is limited evidence regarding the superiority of the omentum flap to decrease the rate of late fistula recurrence when compared with the VRAM flap.

Abstract Objectives To address the gap between artificial intelligence (AI) model development and clinical implementation by developing a machine-learning model to predict cochlear implant (CI) eligibility based on routine hearing tests, while illustrating 3 practical lessons: reformulation for clinical utility, selection of problem-specific metrics, and handling input data variability. Materials and Methods Data were extracted from adult patients who underwent behavioral audiometric and subsequent CI candidacy testing (Arizona Biomedical and Consonant-Nucleus-Consonant tests) at Mayo Clinic between 2011 and 2023. Regression models were initially developed to predict AzBio and CNC scores using features from routine audiograms. Models were then reformulated into binary classification tasks using clinical thresholds (AzBio ≤60%; CNC <50%) and reported sensitivity and positive predictive value (PPV). Input data variability was assessed by analyzing test-retest differences in isophonemes scores. Results Binary classification models achieved sensitivity of 90.4% with PPV 80.2% at CNC 50/AzBio 60, outperforming referral heuristics (60/60 and 75/40). Applying the models to 50 700 historical audiograms identified 525 patients at PPV 90% (sensitivity 58%), 396 at PPV 94% (sensitivity 44%), and 1582 at PPV 71% (sensitivity 94%). Variability analyses indicated that attainable precision is bounded by noise in key predictors. Conclusion This study demonstrates how AI models can be translated into clinically actionable tools by reformulating regression outputs, selecting metrics aligned with clinical priorities, and addressing data variability. These strategies provide a scalable framework for implementing AI in health care and improving decision-making in diverse clinical contexts.

Failed pediatric endotracheal intubation, prompting surgical airway management via emergency front of neck access (eFONA), is an intrinsically challenging topic. While rare, all emergency airway providers must be equipped to handle these complex clinical scenarios, both through initial training and maintenance of competency. Needle cricothyrotomy is a commonly taught method in cannot intubate cannot oxygenate (CICO) scenarios for children under age eight. However, needle cricothyrotomy is technically difficult, profoundly rare, and maintaining competency is a challenge. From a multidisciplinary perspective, we examine the utility of continuing to teach needle cricothyrotomy and explore alternatives. This project group suggests that pediatric eFONA training across disciplines should focus on surgical tracheotomy rather than needle cricothyrotomy, with consideration given to specialty-specific human performance factors.

Abstract The role of DNA topoisomerase II beta (TOP2B) in cardiomyocyte differentiation is poorly understood. To address this, Human induced pluripotent stem cells (hiPSC) were differentiated into cardiomyocytes (CM) that are wildtype or contain a genomic deletion of Topoisomerase 2B (BKO). Both WT and BKO hiPSC could be induced to differentiate into sheets of beating cardiomyocytes. BKO hiPSC take slightly longer to differentiate into sheets of beating CM than WT iPSC. RNA was prepared from both undifferentiated and differentiated WT and BKO hiPSC. RNA seq was used to examine gene expression changes when the WT and BKO hiPSC were differentiated into CM. Gene expression changes following differentiation of BKO cells were largely similar to those in WT cells. In addition, the differentiated WT CM were treated with dexrazoxane (ICRF-187), a TOP2 catalytic inhibitor that targets both TOP2A and TOP2B, or topobexin, a new TOP2B selective catalytic inhibitor. Topobexin inhibition partially phenocopied a TOP2B deletion and thus providing an alternative to TOP2B gene knockout in many cell lines. In future, hiPSC derived CM with and without TOP2B and inhibition by topobexin ex vivo CM could be used to study anthracycline-induced cardiotoxicity and to screen for cardioprotectants. Highlights Used CRISPR-Cas9 to delete TOP2B from hiPSC Produced beating cardiomyocytes from both WT and TOP2B null hiPSC Transcriptome analysis of WT and TOP2B null hiPSC and derived cardiomyocytes RNA seq showed he specific TOP2B inhibitor topobexin largely phenocopies TOP2B gene inactivation in iPSC derived cardiomyocytes. Topobexin inhibition could be used as an alternative to a TOP2B gene knockout in many different cell types, speeding up the analysis of the function of TOP2B.