Endovascular release of an Adams-DeWeese clip and iliocaval reconstruction for debilitating lower extremity swelling

More than 10 million cases of venous thromboembolisms are reported on an annual basis and are major contributors to morbidity and mortality. Studies have found that ≤90% of pulmonary embolisms originate from the abdominal and lower extremity veins. The mainstay of venous thromboembolism treatment has been, and still continues to be, anticoagulation. However, for patients for whom anticoagulation is contraindicated or has failed, physicians have turned to surgical innovations such as inferior vena cava (IVC) filters to create partial interruption of the IVC. Before the invention of IVC filters, the Adams-DeWeese clip was developed to create caval interruption, which allowed for venous return while preventing pulmonary emboli from distal veins. We report a case of endovascular release of a long-term Adams-DeWeese clip, which had caused IVC occlusion and debilitating bilateral lower extremity swelling.

Readability of Spanish-Language Online Patient Educational Materials for Peripheral Artery Disease Do Not Meet Recommended Standards and Represent a Literacy Barrier to Care

BACKGROUND

Online resources are a valuable source of information for patients and have been reported to improve engagement and adherence to medical care. However, readability of online patient educational materials (OPEMs) is crucial for them to serve their intended purpose. The American Medical Association (AMA) recommends that OPEM be written at or below the sixth grade reading level. To avoid disparities in access to comprehensible health information on peripheral artery disease (PAD), it is imperative that the readability of PAD OPEM is appropriate for both English-speaking and Spanish-speaking patients. The aim of this study is to evaluate the readability of PAD OPEM in Spanish and compare to English-language OPEM.

METHODS

We conducted a Google search in English and Spanish using "peripheral arterial disease" and "enfermedad arterial periferica", respectively, and the top 25 patient-accessible articles were collected for each. Articles were categorized by source type: hospital, professional society, or other. Readability of English-language OPEM was measured using the Flesch Reading Ease Readability Formula, Automated Readability Index, Coleman-Liau Index, Flesch-Kincaid Grade Level, Gunning Fog, Linsear Write Formula, and the Simple Measure of Gobbledygook Index. Readability of Spanish OPEM was measured using the Fernández-Huerta Index and Índice Flesch-Szigriszt Scale. Readability of the articles was compared to the AMA recommendation, between English- and Spanish-language, and across sources using statistical tests appropriate to the data.

RESULTS

OPEM from professional societies represented the fewest number of English- (n = 7, 28%) and Spanish-language (n = 6, 24%) articles. Most English-speaking (n = 18, 72%) and Spanish-language (n = 20, 80%) OPEM were considered difficult as measured by the Flesch Reading Ease Readability Formula and Fernández-Huerta Index, respectively, but did not significantly differ between languages (P = 0.59). There were no significant differences in the average readability of all readability measurements across sources (hospital, professional society, or other). All the average readability grade levels for English-speaking and Spanish-language OPEM was significantly higher than the sixth grade reading level (P < 0.01). Only 3 (6%) OPEM met the AMA recommended reading level and there was no significant difference between English-language and Spanish-language OPEM (P = 1.0).

CONCLUSIONS

Nearly all Spanish-language and English-language PAD OPEM assessed were written at a reading grade level higher than recommended by the AMA. There was no significant difference in the readability of materials from hospitals or professional societies. To prevent further widening of health disparities related to literacy, health content creators, particularly hospitals and professional societies, should prioritize, develop, and ensure that English-language and Spanish-language patient education materials are written at a level appropriate for the public.

Development and Validation of a Novel Preoperative Risk Score to Identify Patients at Risk for Nonhome Discharge after Elective Endovascular Aortic Aneurysm Repair (EVAR)

BACKGROUND

Nonhome discharge (NHD) to a rehabilitation or skilled nursing facility after elective endovascular aortic repair (EVAR) is uncommon. However, NHD after surgery has an important impact on patient quality of life and postdischarge outcomes. Understanding factors that put patients undergoing EVAR at high risk for NHD is essential to providing adequate preoperative counseling and shared decision making. This study aimed to identify independent predictors of NHD following elective EVAR and to create a clinically useful preoperative risk score.

METHODS

Elective EVAR cases were queried from the Society for Vascular Surgery Vascular Quality Initiative 2014-2018. A risk score was created by splitting the data set into two-thirds for development and one-third for validation. A parsimonious stepwise hierarchical multivariable logistic regression controlling for hospital level variation was performed in the development dataset, and the beta-coefficients were used to assign points for a risk score. The score was then validated, and model performance assessed.

RESULTS

Overall, 24,426 patients were included and 932 (3.8%) required NHD. Multivariable analysis in the development group identified independent predictors of NHD, which were used to create a 20-point risk score. Patients were stratified into 3 groups based upon their risk score: low risk (0-7 points; n = 16,699) with an NHD rate of 1.8%, moderate risk (8-13 points; n = 7,315) with an NHD rate of 7.3%, and high risk (≥14 points; n = 412) with an NHD rate of 21.8%. The risk score had good predictive ability with c-statistic = 0.75 for model development and c-statistic = 0.73 in the validation dataset.

CONCLUSIONS

This novel risk score can predict NHD following EVAR using characteristics that can be identified preoperatively. Utilization of this score may allow for improved risk assessment, preoperative counseling, and shared decision making.

Identification of high-risk imaging features in hypertrophic cardiomyopathy using electrocardiography: A deep-learning approach

BACKGROUND

Patients with hypertrophic cardiomyopathy (HCM) are at risk of sudden death, and individuals with ≥1 major risk markers are considered for primary prevention implantable cardioverter-defibrillators. Guidelines recommend cardiac magnetic resonance (CMR) imaging to identify high-risk imaging features. However, CMR imaging is resource intensive and is not widely accessible worldwide.

OBJECTIVE

The purpose of this study was to develop electrocardiogram (ECG) deep-learning (DL) models for the identification of patients with HCM and high-risk imaging features.

METHODS

Patients with HCM evaluated at Tufts Medical Center (N = 1930; Boston, MA) were used to develop ECG-DL models for the prediction of high-risk imaging features: systolic dysfunction, massive hypertrophy (≥30 mm), apical aneurysm, and extensive late gadolinium enhancement. ECG-DL models were externally validated in a cohort of patients with HCM from the Amrita Hospital HCM Center (N = 233; Kochi, India).

RESULTS

ECG-DL models reliably identified high-risk features (systolic dysfunction, massive hypertrophy, apical aneurysm, and extensive late gadolinium enhancement) during holdout testing (c-statistic 0.72, 0.83, 0.93, and 0.76) and external validation (c-statistic 0.71, 0.76, 0.91, and 0.68). A hypothetical screening strategy using echocardiography combined with ECG-DL-guided selective CMR use demonstrated a sensitivity of 97% for identifying patients with high-risk features while reducing the number of recommended CMRs by 61%. The negative predictive value with this screening strategy for the absence of high-risk features in patients without ECG-DL recommendation for CMR was 99.5%.

CONCLUSION

In HCM, novel ECG-DL models reliably identified patients with high-risk imaging features while offering the potential to reduce CMR testing requirements in underresourced areas.

Association of epicardial and intramyocardial fat with ventricular arrhythmias

BACKGROUND

Among patients with ischemic cardiomyopathy (ICM) and nonischemic cardiomyopathy (NICM), myocardial fibrosis is associated with an increased risk for ventricular arrhythmia (VA). Growing evidence suggests that myocardial fat contributes to ventricular arrhythmogenesis. However, little is known about the volume and distribution of epicardial adipose tissue and intramyocardial fat and their relationship with VAs.

OBJECTIVE

The purpose of this study was to assess the association of contrast-enhanced computed tomography (CE-CT)-derived left ventricular (LV) tissue heterogeneity, epicardial adipose tissue volume, and intramyocardial fat volume with the risk of VA in ICM and NICM patients.

METHODS

Patients enrolled in the PROSE-ICD registry who underwent CE-CT were included. Intramyocardial fat volume (voxels between -180 and -5 Hounsfield units [HU]), epicardial adipose tissue volume (between -200 and -50 HU), and LV tissue heterogeneity were calculated. The primary endpoint was appropriate ICD shocks or sudden arrhythmic death.

RESULTS

Among 98 patients (47 ICM, 51 NICM), LV tissue heterogeneity was associated with VA (odds ratio [OR] 1.10; P = .01), particularly in the ICM cohort. In the NICM subgroup, epicardial adipose tissue and intramyocardial fat volume were associated with VA (OR 1.11, P = .01; and OR = 1.21, P = .01, respectively) but not in the ICM patients (OR 0.92, P =.22; and OR = 0.96, P =.19, respectively).

CONCLUSION

In ICM patients, increased fat distribution heterogeneity is associated with VA. In NICM patients, an increased volume of intramyocardial fat and epicardial adipose tissue is associated with a higher risk for VA. Our findings suggest that fat's contribution to VAs depends on the underlying substrate.

Predicting ventricular tachycardia circuits in patients with arrhythmogenic right ventricular cardiomyopathy using genotype-specific heart digital twins

Arrhythmogenic right ventricular cardiomyopathy (ARVC) is a genetic cardiac disease that leads to ventricular tachycardia (VT), a life-threatening heart rhythm disorder. Treating ARVC remains challenging due to the complex underlying arrhythmogenic mechanisms, which involve structural and electrophysiological (EP) remodeling. Here, we developed a novel genotype-specific heart digital twin (Geno-DT) approach to investigate the role of pathophysiological remodeling in sustaining VT reentrant circuits and to predict the VT circuits in ARVC patients of different genotypes. This approach integrates the patient's disease-induced structural remodeling reconstructed from contrast-enhanced magnetic-resonance imaging and genotype-specific cellular EP properties. In our retrospective study of 16 ARVC patients with two genotypes: plakophilin-2 (PKP2, n = 8) and gene-elusive (GE, n = 8), we found that Geno-DT accurately and non-invasively predicted the VT circuit locations for both genotypes (with 100%, 94%, 96% sensitivity, specificity, and accuracy for GE patient group, and 86%, 90%, 89% sensitivity, specificity, and accuracy for PKP2 patient group), when compared to VT circuit locations identified during clinical EP studies. Moreover, our results revealed that the underlying VT mechanisms differ among ARVC genotypes. We determined that in GE patients, fibrotic remodeling is the primary contributor to VT circuits, while in PKP2 patients, slowed conduction velocity and altered restitution properties of cardiac tissue, in addition to the structural substrate, are directly responsible for the formation of VT circuits. Our novel Geno-DT approach has the potential to augment therapeutic precision in the clinical setting and lead to more personalized treatment strategies in ARVC.

Predicting Ventricular Tachycardia Circuits in Patients with Arrhythmogenic Right Ventricular Cardiomyopathy using Genotype-specific Heart Digital Twins

Arrhythmogenic right ventricular cardiomyopathy (ARVC) is a genetic cardiac disease that leads to ventricular tachycardia (VT), a life-threatening heart rhythm disorder. Treating ARVC remains challenging due to the complex underlying arrhythmogenic mechanisms, which involve structural and electrophysiological (EP) remodeling. Here, we developed a novel genotype-specific heart digital twin (Geno-DT) approach to investigate the role of pathophysiological remodeling in sustaining VT reentrant circuits and to predict the VT circuits in ARVC patients of different genotypes. This approach integrates the patient's disease-induced structural remodeling reconstructed from contrast-enhanced magnetic-resonance imaging and genotype-specific cellular EP properties. In our retrospective study of 16 ARVC patients with two genotypes: plakophilin-2 (PKP2, n = 8) and gene-elusive (GE, n = 8), we found that Geno-DT accurately and non-invasively predicted the VT circuit locations for both genotypes (with 100%, 94%, 96% sensitivity, specificity, and accuracy for GE patient group, and 86%, 90%, 89% sensitivity, specificity, and accuracy for PKP2 patient group), when compared to VT circuit locations identified during clinical EP studies. Moreover, our results revealed that the underlying VT mechanisms differ among ARVC genotypes. We determined that in GE patients, fibrotic remodeling is the primary contributor to VT circuits, while in PKP2 patients, slowed conduction velocity and altered restitution properties of cardiac tissue, in addition to the structural substrate, are directly responsible for the formation of VT circuits. Our novel Geno-DT approach has the potential to augment therapeutic precision in the clinical setting and lead to more personalized treatment strategies in ARVC.

Advanced breast cancer metastasized in the brain: treatment standards and innovations

Breast cancer continues to be a difficult disease to treat due to high rates of metastasis. Metastasis to the brain presents a unique and often overlooked challenge. In this focused review, we discuss the epidemiology of breast cancer and which types frequently metastasize to the brain. Novel treatment approaches are highlighted with supporting scientific evidence. The role of the blood-brain barrier and how it may become altered with metastasis is addressed. We then highlight new innovations for Her2-positive and triple-negative breast cancer. Finally, recent directions for luminal breast cancer are discussed. This review serves to enhance understanding of pathophysiology, spark continued innovation, and provide a user-friendly resource through tables and easy-to-process figures.

Evaluation of a deep Learning-enabled automated computational heart modeling workflow for personalized assessment of ventricular arrhythmias

Personalized, image-based computational heart modeling is a powerful technology that can be used to improve patient-specific arrhythmia risk stratification and ventricular tachycardia (VT) ablation targeting. However, most state-of-the-art methods still require manual interactions by expert users. The goal of this study is to evaluate the feasibility of an automated, deep learning-based workflow for reconstructing personalized computational electrophysiological heart models to guide patient-specific treatment of VT. Contrast-enhanced computed tomography (CE-CT) images with expert ventricular myocardium segmentations were acquired from 111 patients across 5 cohorts from 3 different institutions. A deep convolutional neural network (CNN) for segmenting left ventricular myocardium from CE-CT was developed, trained, and evaluated. From both CNN-based and expert segmentations in a subset of patients, personalized electrophysiological heart models were reconstructed, and rapid pacing was used to induce VTs. CNN-based and expert segmentations were more concordant in the middle myocardium than in the heart's base or apex. Wavefront propagation during pacing was similar between CNN-based and original heart models. Between most sets of heart models, VT inducibility was the same, the number of induced VTs was strongly correlated, and VT circuits co-localized. Our results demonstrate that personalized computational heart models reconstructed from deep learning-based segmentations even with a small training set size can predict similar VT inducibility and circuit locations as those from expertly-derived heart models. Hence, a user-independent, automated framework for simulating arrhythmias in personalized heart models could feasibly be used in clinical settings to aid VT risk stratification and guide VT ablation therapy. KEY POINTS: Personalized electrophysiological heart modeling can aid in patient-specific ventricular tachycardia (VT) risk stratification and VT ablation targeting. Current state-of-the-art, image-based heart models for VT prediction require expert-dependent, manual interactions that may not be accessible across clinical settings. In this study, we develop an automated, deep learning-based workflow for reconstructing personalized heart models capable of simulating arrhythmias and compare its predictions with that of expert-generated heart models. The number and location of VTs was similar between heart models generated from the deep learning-based workflow and expert-generated heart models. These results demonstrate the feasibility of using an automated computational heart modeling workflow to aid in VT therapeutics and has implications for generalizing personalized computational heart technology to a broad range of clinical centers. Abstract figure legend In this study, we evaluate whether an automated, deep learning-based computational electrophysiological heart models can predict similar arrhythmias as those of expert, manually-derived heart models. First, we build a deep neural network to automatically segment contrast-enhanced CT scans and demonstrate that predicted imaging metrics are comparable to that of manual segmentations. Second, electrophysiological heart models reconstructed from these automated segmentations predict similar wavefront propagation and VT circuits as those of expert-reconstructed heart models. This work represents an advancement towards construction of a user-independent, computational framework to aid in VT risk stratification and guide VT ablation. CT: computed tomography, VT: ventricular tachycardia. This article is protected by copyright. All rights reserved.

Wavefront directionality and decremental stimuli synergistically improve identification of ventricular tachycardia substrate: insights from personalized computational heart models

AIMS

Multiple wavefront pacing (MWP) and decremental pacing (DP) are two electroanatomic mapping (EAM) strategies that have emerged to better characterize the ventricular tachycardia (VT) substrate. The aim of this study was to assess how well MWP, DP, and their combination improve identification of electrophysiological abnormalities on EAM that reflect infarct remodelling and critical VT sites.

METHODS AND RESULTS

Forty-eight personalized computational heart models were reconstructed using images from post-infarct patients undergoing VT ablation. Paced rhythms were simulated by delivering an initial (S1) and an extra-stimulus (S2) from one of 100 locations throughout each heart model. For each pacing, unipolar signals were computed along the myocardial surface to simulate substrate EAM. Six EAM features were extracted and compared with the infarct remodelling and critical VT sites. Concordance of S1 EAM features between different maps was lower in hearts with smaller amounts of remodelling. Incorporating S1 EAM features from multiple maps greatly improved the detection of remodelling, especially in hearts with less remodelling. Adding S2 EAM features from multiple maps decreased the number of maps required to achieve the same detection accuracy. S1 EAM features from multiple maps poorly identified critical VT sites. However, combining S1 and S2 EAM features from multiple maps paced near VT circuits greatly improved identification of critical VT sites.

CONCLUSION

Electroanatomic mapping with MWP is more advantageous for characterization of substrate in hearts with less remodelling. During substrate EAM, MWP and DP should be combined and delivered from locations proximal to a suspected VT circuit to optimize identification of the critical VT site.

Ovarian Cancer Metastasis to the Central Nervous System: A Literature Review

Ovarian cancer is one of the leading causes of cancer-related deaths among women in the United States. Metastasis to the central nervous system has become more frequent in the previous decades, however, treatment options remain limited. In this review, we discuss the pathophysiology of ovarian cancer and how metastasis to the central nervous system typically occurs. We then discuss cases of metastasis presented in the literature to evaluate current treatment regimens and protocols. Finally, we highlight emerging treatment options that are being utilized in clinics to provide personalized treatment therapy for a patient's unique diagnosis. This review aims to further the understanding of pathophysiology, stimulate further innovative treatments, and present accessible resources through tables and figures.

Fat infiltration in the infarcted heart as a paradigm for ventricular arrhythmias

Infiltrating adipose tissue (inFAT) has been recently found to co-localize with scar in infarcted hearts and may contribute to ventricular arrhythmias (VAs), a life-threatening heart rhythm disorder. However, the contribution of inFAT to VA has not been well-established. We investigated the role of inFAT versus scar in VA through a combined prospective clinical and mechanistic computational study. Using personalized computational heart models and comparing the results from simulations of VA dynamics with measured electrophysiological abnormalities during the clinical procedure, we demonstrate that inFAT, rather than scar, is a primary driver of arrhythmogenic propensity and is frequently present in critical regions of the VA circuit. We determined that, within the VA circuitry, inFAT, as opposed to scar, is primarily responsible for conduction slowing in critical sites, mechanistically promoting VA. Our findings implicate inFAT as a dominant player in infarct-related VA, challenging existing paradigms and opening the door for unexplored anti-arrhythmic strategies.

Proteinopathies and Neurotrauma: Update on Degenerative Cascades

Neurotrauma, especially repetitive neurotrauma, is associated with the development of progressive neurodegeneration leading to chronic traumatic encephalopathy (CTE). Exposure to neurotrauma regularly occurs during sports and military service, often not requiring medical care. However, exposure to severe and/or repeated sub-clinical neurotrauma has been shown cause physical and psychological disability, leading to reduce life expectancy. Misfolding of proteins, or proteinopathy, is a pathological hallmark of CTE, in which chronic injury leads to local and diffuse protein aggregates. These aggregates are an overlapping feature of many neurodegenerative diseases such as CTE, Alzheimer's Disease, Parkinsons disease. Neurotrauma is also a significant risk factor for the development of these diseases, however the mechanism's underlying this association are not well understood. While phosphorylated tau aggregates are the primary feature of CTE, amyloid-beta, Transactive response DNA-binding protein 43 (TDP-43), and alpha-synuclein (αSyn) are also well documented. Aberrant misfolding of these proteins has been shown to disrupt brain homeostasis leading to neurodegeneration in a disease dependent manor. In CTE, the interaction between proteinopathies and their associated neurodegeneration is a current area of study. Here we provide an update on current literature surrounding the prevalence, characteristics, and pathogenesis of proteinopathies in CTE.

Advanced imaging for risk stratification for ventricular arrhythmias and sudden cardiac death

Sudden cardiac death (SCD) is a leading cause of mortality, comprising approximately half of all deaths from cardiovascular disease. In the US, the majority of SCD (85%) occurs in patients with ischemic cardiomyopathy (ICM) and a subset in patients with non-ischemic cardiomyopathy (NICM), who tend to be younger and whose risk of mortality is less clearly delineated than in ischemic cardiomyopathies. The conventional means of SCD risk stratification has been the determination of the ejection fraction (EF), typically via echocardiography, which is currently a means of determining candidacy for primary prevention in the form of implantable cardiac defibrillators (ICDs). Advanced cardiac imaging methods such as cardiac magnetic resonance imaging (CMR), single-photon emission computerized tomography (SPECT) and positron emission tomography (PET), and computed tomography (CT) have emerged as promising and non-invasive means of risk stratification for sudden death through their characterization of the underlying myocardial substrate that predisposes to SCD. Late gadolinium enhancement (LGE) on CMR detects myocardial scar, which can inform ICD decision-making. Overall scar burden, region-specific scar burden, and scar heterogeneity have all been studied in risk stratification. PET and SPECT are nuclear methods that determine myocardial viability and innervation, as well as inflammation. CT can be used for assessment of myocardial fat and its association with reentrant circuits. Emerging methodologies include the development of "virtual hearts" using complex electrophysiologic modeling derived from CMR to attempt to predict arrhythmic susceptibility. Recent developments have paired novel machine learning (ML) algorithms with established imaging techniques to improve predictive performance. The use of advanced imaging to augment risk stratification for sudden death is increasingly well-established and may soon have an expanded role in clinical decision-making. ML could help shift this paradigm further by advancing variable discovery and data analysis.

Real-Time Prediction of Mortality, Cardiac Arrest, and Thromboembolic Complications in Hospitalized Patients With COVID-19

Background

COVID-19 infection carries significant morbidity and mortality. Current risk prediction for complications in COVID-19 is limited, and existing approaches fail to account for the dynamic course of the disease.

Objectives

The purpose of this study was to develop and validate the COVID-HEART predictor, a novel continuously updating risk-prediction technology to forecast adverse events in hospitalized patients with COVID-19.

Methods

Retrospective registry data from patients with severe acute respiratory syndrome coronavirus 2 infection admitted to 5 hospitals were used to train COVID-HEART to predict all-cause mortality/cardiac arrest (AM/CA) and imaging-confirmed thromboembolic events (TEs) (n = 2,550 and n = 1,854, respectively). To assess COVID-HEART's performance in the face of rapidly changing clinical treatment guidelines, an additional 1,100 and 796 patients, admitted after the completion of development data collection, were used for testing. Leave-hospital-out validation was performed.

Results

Over 20 iterations of temporally divided testing, the mean area under the receiver operating characteristic curve were 0.917 (95% confidence interval [CI]: 0.916-0.919) and 0.757 (95% CI: 0.751-0.763) for prediction of AM/CA and TE, respectively. The interquartile ranges of median early warning times were 14 to 21 hours for AM/CA and 12 to 60 hours for TE. The mean area under the receiver operating characteristic curve for the left-out hospitals were 0.956 (95% CI: 0.936-0.976) and 0.781 (95% CI: 0.642-0.919) for prediction of AM/CA and TE, respectively.

Conclusions

The continuously updating, fully interpretable COVID-HEART predictor accurately predicts AM/CA and TE within multiple time windows in hospitalized COVID-19 patients. In its current implementation, the predictor can facilitate practical, meaningful changes in patient triage and resource allocation by providing real-time risk scores for these outcomes. The potential utility of the predictor extends to COVID-19 patients after hospitalization and beyond COVID-19.

Association of Left Ventricular Tissue Heterogeneity and Intramyocardial Fat on Computed Tomography with Ventricular Arrhythmias in Ischemic Cardiomyopathy

Background

Gray zone, a measure of tissue heterogeneity on late gadolinium enhanced–cardiac magnetic resonance (LGE-CMR) imaging, has been shown to predict ventricular arrhythmias (VAs) in ischemic cardiomyopathy (ICM) patients. However, no studies have described whether left ventricular (LV) tissue heterogeneity and intramyocardial fat mass on contrast-enhanced computed tomography (CE-CT), which provides greater spatial resolution, is useful for assessing the risk of VAs in ICM patients with LV systolic dysfunction and no previous VAs.

Objective

The purpose of this proof-of-concept study was to determine the feasibility of measuring global LV tissue heterogeneity and intramyocardial fat mass by CE-CT for predicting the risk of VAs in ICM patients with LV systolic dysfunction and no previous history of VAs.

Methods

Patients with left ventricular ejection fraction ≤35% and no previous VAs were enrolled in a prospective, observational registry and underwent LGE-CMR. From this cohort, patients with ICM who additionally received CE-CT were included in the present analysis. Gray zone on LGE-CMR was defined as myocardium with signal intensity (SI) > peak SI of healthy myocardium but <50% maximal SI. Tissue heterogeneity on CE-CT was defined as the standard deviation of the Hounsfield unit image gradients (HU/mm) within the myocardium. Intramyocardial fat on CE-CT was identified as regions of image pixels between –180 and –5 HU. The primary outcome was VAs, defined as appropriate implantable cardioverter-defibrillator shock or sudden arrhythmic death.

Results

The study consisted of 47 ICM patients, 13 (27.7%) of whom experienced VA events during mean follow-up of 5.6 ± 3.4 years. Increasing tissue heterogeneity (per HU/mm) was significantly associated with VAs after multivariable adjustment, including for gray zone (odds ratio [OR] 1.22; P = .019). Consistently, patients with tissue heterogeneity values greater than or equal to the median (≥22.2 HU/mm) had >13-fold significantly increased risk of VA events, relative to patients with values lower than the median, after multivariable adjustment that included gray zone (OR 13.13; P = .028). The addition of tissue heterogeneity to gray zone improved prediction of VAs (area under receiver operating characteristic curve increased from 0.815 to 0.876). No association was found between intramyocardial fat mass on CE-CT and VAs (OR 1.00; P = .989).

Conclusion

In ICM patients, CE-CT–derived LV tissue heterogeneity was independently associated with VAs and may represent a novel marker useful for risk stratification.

Computational Signatures for Post-Cardiac Arrest Trajectory Prediction: Importance of Early Physiological Time Series

BACKGROUND

There is an unmet need for timely and reliable prediction of post-cardiac arrest (CA) clinical trajectories. We hypothesized that physiological time series (PTS) data recorded on the first day of intensive care would contribute significantly to discrimination of outcomes at discharge.

PATIENTS AND METHODS

Adult patients in the multicenter eICU database who were mechanically ventilated after resuscitation from out-of-hospital CA were included. Outcomes of interest were survival, neurological status based on Glasgow motor subscore (mGCS) and surrogate functional status based on discharge location (DL), at hospital discharge. Three machine learning predictive models were trained, one with features from the electronic health records (EHR), the second using features derived from PTS collected in the first 24 hours after ICU admission (PTS₂₄), and the third combining PTS₂₄ and EHR. Model performances were compared, and the best performing model was externally validated in the MIMIC-III dataset.

RESULTS

Data from 2,216 admissions were included in the analysis. Discrimination of prediction models combining EHR and PTS₂₄ features was higher than models using either EHR or PTS₂₄ for prediction of survival (AUROC 0.83, 0.82 and 0.79 respectively), neurological outcome (0.87, 0.86 and 0.79 respectively), and DL (0.80, 0.78 and 0.76 respectively). External validation in MIMIC-III (n = 86) produced similar model performance. Feature analysis suggested prognostic significance of previously unknown EHR and PTS₂₄ variables.

CONCLUSION

These results indicate that physiological data recorded in the early phase after CA resuscitation contain signatures that are linked to post-CA outcome. Additionally, they attest to the effectiveness of ML for post-CA predictive modeling.

Zotatifin, an eIF4A-Selective Inhibitor, Blocks Tumor Growth in Receptor Tyrosine Kinase Driven Tumors

Oncoprotein expression is controlled at the level of mRNA translation and is regulated by the eukaryotic translation initiation factor 4F (eIF4F) complex. eIF4A, a component of eIF4F, catalyzes the unwinding of secondary structure in the 5'-untranslated region (5'-UTR) of mRNA to facilitate ribosome scanning and translation initiation. Zotatifin (eFT226) is a selective eIF4A inhibitor that increases the affinity between eIF4A and specific polypurine sequence motifs and has been reported to inhibit translation of driver oncogenes in models of lymphoma. Here we report the identification of zotatifin binding motifs in the 5'-UTRs of HER2 and FGFR1/2 Receptor Tyrosine Kinases (RTKs). Dysregulation of HER2 or FGFR1/2 in human cancers leads to activation of the PI3K/AKT and RAS/ERK signaling pathways, thus enhancing eIF4A activity and promoting the translation of select oncogenes that are required for tumor cell growth and survival. In solid tumor models driven by alterations in HER2 or FGFR1/2, downregulation of oncoprotein expression by zotatifin induces sustained pathway-dependent anti-tumor activity resulting in potent inhibition of cell proliferation, induction of apoptosis, and significant in vivo tumor growth inhibition or regression. Sensitivity of RTK-driven tumor models to zotatifin correlated with high basal levels of mTOR activity and elevated translational capacity highlighting the unique circuitry generated by the RTK-driven signaling pathway. This dependency identifies the potential for rational combination strategies aimed at vertical inhibition of the PI3K/AKT/eIF4F pathway. Combination of zotatifin with PI3K or AKT inhibitors was beneficial across RTK-driven cancer models by blocking RTK-driven resistance mechanisms demonstrating the clinical potential of these combination strategies.

Analyzing the Role of Repolarization Gradients in Post-infarct Ventricular Tachycardia Dynamics Using Patient-Specific Computational Heart Models

Aims: Disease-induced repolarization heterogeneity in infarcted myocardium contributes to VT arrhythmogenesis but how apicobasal and transmural (AB-TM) repolarization gradients additionally affect post-infarct VT dynamics is unknown. The goal of this study is to assess how AB-TM repolarization gradients impact post-infarct VT dynamics using patient-specific heart models.

Method: 3D late gadolinium-enhanced cardiac magnetic resonance images were acquired from seven post-infarct patients. Models representing the patient-specific scar and infarct border zone distributions were reconstructed without (baseline) and with repolarization gradients along both the AB-TM axes. AB only and TM only models were created to assess the effects of each ventricular gradient on VT dynamics. VTs were induced in all models via rapid pacing.

Results: Ten baseline VTs were induced. VT inducibility in AB-TM models was not significantly different from baseline (p>0.05). Reentry pathways in AB-TM models were different than baseline pathways due to alterations in the location of conduction block (p<0.05). VT exit sites in AB-TM models were different than baseline VT exit sites (p<0.05). VT inducibility of AB only and TM only models were not significantly different than that of baseline (p>0.05) or AB-TM models (p>0.05). Reentry pathways and VT exit sites in AB only and TM only models were different than in baseline (p<0.05). Lastly, repolarization gradients uncovered multiple VT morphologies with different reentrant pathways and exit sites within the same structural, conducting channels.

Conclusion: VT inducibility was not impacted by the addition of AB-TM repolarization gradients, but the VT reentrant pathway and exit sites were greatly affected due to modulation of conduction block. Thus, during ablation procedures, physiological and pharmacological factors that impact the ventricular repolarization gradient might need to be considered when targeting the VTs.

Assessment of an ECG-Based System for Localizing Ventricular Arrhythmias in Patients With Structural Heart Disease

Background

We have previously developed an intraprocedural automatic arrhythmia‐origin localization (AAOL) system to identify idiopathic ventricular arrhythmia origins in real time using a 3‐lead ECG. The objective was to assess the localization accuracy of ventricular tachycardia (VT) exit and premature ventricular contraction (PVC) origin sites in patients with structural heart disease using the AAOL system.

Methods and Results

In retrospective and prospective case series studies, a total of 42 patients who underwent VT/PVC ablation in the setting of structural heart disease were recruited at 2 different centers. The AAOL system combines 120‐ms QRS integrals of 3 leads (III, V2, V6) with pace mapping to predict VT exit/PVC origin site and projects that site onto the patient‐specific electroanatomic mapping surface. VT exit/PVC origin sites were clinically identified by activation mapping and/or pace mapping. The localization error of the VT exit/PVC origin site was assessed by the distance between the clinically identified site and the estimated site. In the retrospective study of 19 patients with structural heart disease, the AAOL system achieved a mean localization accuracy of 6.5±2.6 mm for 25 induced VTs. In the prospective study with 23 patients, mean localization accuracy was 5.9±2.6 mm for 26 VT exit and PVC origin sites. There was no difference in mean localization error in epicardial sites compared with endocardial sites using the AAOL system (6.0 versus 5.8 mm, P=0.895).

Conclusions

The AAOL system achieved accurate localization of VT exit/PVC origin sites in patients with structural heart disease; its performance is superior to current systems, and thus, it promises to have potential clinical utility.

Relationship between blood type and outcomes following COVID-19 infection

Since the onset of the COVID-19 pandemic, a concentrated research effort has been undertaken to elucidate risk factors underlying viral infection, severe illness, and death. Recent studies have investigated the association between blood type and COVID-19 infection. This article aims to comprehensively review current literature and better understand the impact of blood type on viral susceptibility and outcomes.

Whole-heart ventricular arrhythmia modeling moving forward: Mechanistic insights and translational applications

Ventricular arrhythmias are the primary cause of sudden cardiac death and one of the leading causes of mortality worldwide. Whole-heart computational modeling offers a unique approach for studying ventricular arrhythmias, offering vast potential for developing both a mechanistic understanding of ventricular arrhythmias and clinical applications for treatment. In this review, the fundamentals of whole-heart ventricular modeling and current methods of personalizing models using clinical data are presented. From this foundation, the authors summarize recent advances in whole-heart ventricular arrhythmia modeling. Efforts in gaining mechanistic insights into ventricular arrhythmias are discussed, in addition to other applications of models such as the assessment of novel therapeutics. The review emphasizes the unique benefits of computational modeling that allow for insights that are not obtainable by contemporary experimental or clinical means. Additionally, the clinical impact of modeling is explored, demonstrating how patient care is influenced by the information gained from ventricular arrhythmia models. The authors conclude with future perspectives about the direction of whole-heart ventricular arrhythmia modeling, outlining how advances in neural network methodologies hold the potential to reduce computational expense and permit for efficient whole-heart modeling.

Electromechanical modeling of human ventricles with ischemic cardiomyopathy: numerical simulations in sinus rhythm and under arrhythmia

We developed a novel patient-specific computational model for the numerical simulation of ventricular electromechanics in patients with ischemic cardiomyopathy (ICM). This model reproduces the activity both in sinus rhythm (SR) and in ventricular tachycardia (VT). The presence of scars, grey zones and non-remodeled regions of the myocardium is accounted for by the introduction of a spatially heterogeneous coefficient in the 3D electromechanics model. This 3D electromechanics model is firstly coupled with a 2-element Windkessel afterload model to fit the pressure-volume (PV) loop of a patient-specific left ventricle (LV) with ICM in SR. Then, we employ the coupling with a 0D closed-loop circulation model to analyze a VT circuit over multiple heartbeats on the same LV. We highlight similarities and differences on the solutions obtained by the electrophysiology model and those of the electromechanics model, while considering different scenarios for the circulatory system. We observe that very different parametrizations of the circulation model induce the same hemodynamical considerations for the patient at hand. Specifically, we classify this VT as unstable. We conclude by stressing the importance of combining electrophysiological, mechanical and hemodynamical models to provide relevant clinical indicators in how arrhythmias evolve and can potentially lead to sudden cardiac death.

Assessment of arrhythmia mechanism and burden of the infarcted ventricles following remuscularization with pluripotent stem cell-derived cardiomyocyte patches using patient-derived models

AIMS

Direct remuscularization with pluripotent stem cell-derived cardiomyocytes (PSC-CMs) seeks to address the onset of heart failure post-myocardial infarction (MI) by treating the persistent muscle deficiency that underlies it. However, direct remuscularization with PSC-CMs could potentially be arrhythmogenic. We investigated two possible mechanisms of arrhythmogenesis-focal vs reentrant-arising from direct remuscularization with PSC-CM patches in two personalized, human ventricular computer models of post-MI. Moreover, we developed a principled approach for evaluating arrhythmogenicity of direct remuscularization that factors in the VT propensity of the patient-specific post-MI fibrotic substrate and use it to investigate different conditions of patch remuscularization.

METHODS & RESULTS

Two personalized, human ventricular models of post-MI (P1 & P2) were constructed from late gadolinium enhanced (LGE)-magnetic resonance images (MRI). In each model, remuscularization with PSC-CM patches were simulated under different treatment conditions that included patch engraftment, patch myofibril orientation, remuscularization site, patch size (thickness and diameter), and patch maturation. To determine arrhythmogenicity of treatment conditions, VT burden of heart models was quantified prior to and after simulated remuscularization and compared. VT burden was quantified based on inducibility (i.e., weighted sum of pacing sites that induced) and severity (i.e., the number of distinct VT morphologies induced). Prior to remuscularization, VT burden was significant in P1 (0.275) and not in P2 (0.0, not VT inducible). We highlight that reentrant VT mechanisms would dominate over focal mechanisms; spontaneous beats emerging from PSC-CM grafts were always a fraction of resting sinus rate. Moreover, incomplete patch engraftment can be particularly arrhythmogenic, giving rise to particularly aberrant electrical activation and conduction slowing across the PSC-CM patches along with elevated VT burden when compared to complete engraftment. Under conditions of complete patch engraftment, remuscularization was almost always arrhythmogenic in P2 but certain treatment conditions could be anti-arrhythmogenic in P1. Moreover, the remuscularization site was the most important factor affecting VT burden in both P1 and P2. Complete maturation of PSC-CM patches, both ionically and electrotonically, at the appropriate site could completely alleviate VT burden.

CONCLUSION

We identified that reentrant VT would be the primary VT mechanism in patch remuscularization. To evaluate the arrhythmogenicity of remuscularization, we developed a principled approach that factors in the propensity of the patient-specific fibrotic substrate for VT. We showed that arrhythmogenicity is sensitive to the patient-specific fibrotic substrate and remuscularization site. We demonstrate that targeted remuscularization can be safe in the appropriate individual and holds the potential to nondestructively eliminate VT post-MI in addition to addressing muscle deficiency underlying heart failure progression.

TRANSLATIONAL PERSPECTIVE

If safety from ventricular arrhythmias can be addressed, direct remuscularization with PSC-CMs-achieved either through engineered myocardial patches or intramyocardial injections-holds the potential to halt heart failure progression post-MI. Using personalized 3 D models of the post-MI ventricles derived from LGE-MRI, we provide evidence that arrhythmogenesis following remuscularization with PSC-CM patches is driven by a reentrant as opposed to focal VT mechanism. Moreover, the existing patient-specific fibrotic substrate together with the remuscularization site were primary determinants of arrhythmogenesis. These results suggest that the clinical safety of remuscularization can be achieved through patient-specific optimization guided in-part by computational modeling.

Feasibility study shows concordance between image-based virtual-heart ablation targets and predicted ECG-based arrhythmia exit-sites

INTRODUCTION

We recently developed two noninvasive methodologies to help guide VT ablation: population-derived automated VT exit localization (PAVEL) and virtual-heart arrhythmia ablation targeting (VAAT). We hypothesized that while very different in their nature, limitations, and type of ablation targets (substrate-based vs. clinical VT), the image-based VAAT and the ECG-based PAVEL technologies would be spatially concordant in their predictions.

OBJECTIVE

The objective is to test this hypothesis in ischemic cardiomyopathy patients in a retrospective feasibility study.

METHODS

Four post-infarct patients who underwent LV VT ablation and had pre-procedural LGE-CMRs were enrolled. Virtual hearts with patient-specific scar and border zone identified potential VTs and ablation targets. Patient-specific PAVEL based on a population-derived statistical method localized VT exit sites onto a patient-specific 238-triangle LV endocardial surface.

RESULTS

Ten induced VTs were analyzed and 9-exit sites were localized by PAVEL onto the patient-specific LV endocardial surface. All nine predicted VT exit sites were in the scar border zone defined by voltage mapping and spatially correlated with successful clinical lesions. There were 2.3 ± 1.9 VTs per patient in the models. All five VAAT lesions fell within regions ablated clinically. VAAT targets correlated well with 6 PAVEL-predicted VT exit sites. The distance between the center of the predicted VT-exit-site triangle and nearest corresponding VAAT ablation lesion was 10.7 ± 7.3 mm.

CONCLUSIONS

VAAT targets are concordant with the patient-specific PAVEL-predicted VT exit sites. These findings support investigation into combining these two complementary technologies as a noninvasive, clinical tool for targeting clinically induced VTs and regions likely to harbor potential VTs.

Targeting Oncogene mRNA Translation in B-Cell Malignancies with eFT226, a Potent and Selective Inhibitor of eIF4A

The PI3K/AKT/mTOR pathway is often activated in lymphoma through alterations in PI3K, PTEN, and B-cell receptor signaling, leading to dysregulation of eIF4A (through its regulators, eIF4B, eIF4G, and PDCD4) and the eIF4F complex. Activation of eIF4F has a direct role in tumorigenesis due to increased synthesis of oncogenes that are dependent on enhanced eIF4A RNA helicase activity for translation. eFT226, which inhibits translation of specific mRNAs by promoting eIF4A1 binding to 5'-untranslated regions (UTR) containing polypurine and/or G-quadruplex recognition motifs, shows potent antiproliferative activity and significant in vivo efficacy against a panel of diffuse large B-cell lymphoma (DLBCL), and Burkitt lymphoma models with ≤1 mg/kg/week intravenous administration. Evaluation of predictive markers of sensitivity or resistance has shown that activation of eIF4A, mediated by mTOR signaling, correlated with eFT226 sensitivity in in vivo xenograft models. Mutation of PTEN is associated with reduced apoptosis in vitro and diminished efficacy in vivo in response to eFT226. In models evaluated with PTEN loss, AKT was stimulated without a corresponding increase in mTOR activation. AKT activation leads to the degradation of PDCD4, which can alter eIF4F complex formation. The association of eFT226 activity with PTEN/PI3K/mTOR pathway regulation of mRNA translation provides a means to identify patient subsets during clinical development.

Personalized Digital-Heart Technology for Ventricular Tachycardia Ablation Targeting in Hearts With Infiltrating Adiposity

BACKGROUND

Infiltrating adipose tissue (inFAT) is a newly recognized proarrhythmic substrate for postinfarct ventricular tachycardias (VT) identifiable on contrast-enhanced computed tomography. This study presents novel digital-heart technology that incorporates inFAT from contrast-enhanced computed tomography to noninvasively predict VT ablation targets and assesses the capability of the technology by comparing its predictions with VT ablation procedure data from patients with ischemic cardiomyopathy.

METHODS

Digital-heart models reflecting patient-specific inFAT distributions were reconstructed from contrast-enhanced computed tomography. The digital-heart identification of fat-based ablation targeting (DIFAT) technology evaluated the rapid-pacing-induced VTs in each personalized inFAT-based substrate. DIFAT targets that render the inFAT substrate noninducible to VT, including VTs that arise postablation, were determined. DIFAT predictions were compared with corresponding clinical ablations to assess the capabilities of the technology.

RESULTS

DIFAT was developed and applied retrospectively to 29 ischemic cardiomyopathy patients with contrast-enhanced computed tomography. DIFAT ablation volumes were significantly less than the estimated clinical ablation volumes (1.87±0.35 versus 7.05±0.88 cm³, P<0.0005). DIFAT targets overlapped with clinical ablations in 79% of patients, mostly in the apex (72%) and inferior/inferolateral (74%). In 3 patients, DIFAT targets colocalized with redo ablations delivered years after the index procedure.

CONCLUSIONS

DIFAT is a novel digital-heart technology for individualized VT ablation guidance designed to eliminate VT inducibility following initial ablation. DIFAT predictions colocalized well with clinical ablation locations but provided significantly smaller lesions. DIFAT also predicted VTs targeted in redo procedures years later. As DIFAT uses widely accessible computed tomography, its integration into clinical workflows may augment therapeutic precision and reduce redo procedures.

Abstract B33: Targeting PI3K/mTOR signaling with potent, selective and orally-available small-molecule inhibitors of eIF4E

Aberrant protein translation plays a role in the pathogenesis of multiple solid tumors and hematologic malignancies. The translation initiation factor eIF4E is essential for the translation of m7G-capped mRNA and is a key point of convergence for several signaling pathways, such as PI3K/mTOR and MAPK, which are intimately involved in tumor cell growth and survival. As such, eIF4E has generated intense interest as a target for anticancer drug discovery. We have designed a series of potent, selective, and orally available m7G cap-competitive inhibitors of eIF4E (eFT-4Ei) with favorable drug-like properties. These inhibitors bind free eIF4E, eIF4E-4EBP and eIF4E-eIF4F complexes within tumor cells. Ribosomal profiling of eIF4E inhibitor-treated tumor cells has identified a subset of translationally regulated target genes that overlap with mTORC1/2 regulated genes, but also include a larger set of unique translationally regulated target mRNAs that are enriched for 5'-TOP, PRTE and CERT sequence elements in their 5'-untranslated regions. eIF4E inhibition results in potent antiproliferative activity and induction of apoptosis in a subset of tumor cell lines. Consistent with this observation, our eIF4E inhibitors show some similarities, yet several important differences from existing mTORC1 or mTORC1/2 dual inhibitors in both cellular and physiologic assays. Finally, significant antitumor efficacy was observed with eIF4E inhibition in both solid tumor and hematologic xenografts in vivo. Taken together, these results highlight the potential of targeting eIF4E as a novel and differentiated therapeutic strategy to treat cancer.

Citation Format: Gregory S. Parker, Ivy N.J. Hung, Jocelyn Staunton, Maria Barrera, Eric Sung, Ana Parra, Craig R. Stumpf, Joan Chen, Peggy A. Thompson, Andreas Nevarez, Christopher J. Wegerski, Jeff Clarine, Samuel Sperry, Alan Xiang, Christian Nilewski, Garrick K. Packard, Kaveri Urklalan, Takasuke Mukaiyama, Theo Michels, Justin T. Ernst, Paul A. Sprengeler, Siegfried H. Reich, Gary G. Chiang, Kevin R. Webster. Targeting PI3K/mTOR signaling with potent, selective and orally-available small-molecule inhibitors of eIF4E [abstract]. In: Proceedings of the AACR Special Conference on Targeting PI3K/mTOR Signaling; 2018 Nov 30-Dec 8; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Res 2020;18(10_Suppl):Abstract nr B33.

Abstract 3399: Preclinical evaluation of eFT226, a potent and selective eIF4A inhibitor with anti-tumor activity in FGFR1,2 and HER2 driven cancers

Mutations or amplifications affecting receptor tyrosine kinases (RTKs) activate the RAS/MAPK and PI3K/AKT signaling pathways thereby promoting cancer cell proliferation and survival. Oncoprotein expression is tightly controlled at the level of mRNA translation and is regulated by the eukaryotic translation initiation factor 4F (eIF4F) complex consisting of eIF4A, eIF4E, and eIF4G. eIF4A functions to catalyze the unwinding of secondary structure in the 5'-untranslated region (5'-UTR) of mRNA facilitating ribosome scanning and translation initiation. The activation of oncogenic signaling pathways, including RAS and PI3K, facilitate formation of eIF4F and enhance eIF4A activity promoting the translation of oncogenes with highly structured 5'-UTRs that are required for tumor cell proliferation, survival and metastasis. eFT226 is a selective eIF4A inhibitor that converts eIF4A into a sequence specific translational repressor by increasing the affinity between eIF4A and 5'-UTR polypurine motifs leading to selective downregulation of mRNA translation. The polypurine element is highly enriched in the 5'-UTR of eFT226 target genes, many of which are known oncogenic drivers, including FGFR1,2 and HER2, enabling eFT226 to selectively inhibit dysregulated oncogene expression. Formation of a ternary complex [eIF4A-eFT226-mRNA] blocks ribosome scanning along the 5'-UTR leading to dose dependent inhibition of RTK protein expression. The 5'-UTR sequence dependency of eFT226 translational inhibition was evaluated in cell-based reporter assays demonstrating 10-45-fold greater sensitivity for reporter constructs containing an RTK 5'-UTR compared to a control. In solid tumor cell lines driven by alterations in FGFR1, FGFR2 or HER2, downregulation of RTK expression by eFT226 resulted in decreased MAPK and AKT signaling, potent inhibition of cell proliferation and an induction of apoptosis suggesting that eFT226 could be effective in treating tumor types dependent on these oncogenic drivers. Solid tumor xenograft models harboring FGFR1,2 or HER2 amplifications treated with eFT226 resulted in significant in vivo tumor growth inhibition and regression at well tolerated doses in breast, non-small cell lung and colorectal cancer models. Treatment with eFT226 also decreased RTK protein levels supporting the potential to use these eFT226 target genes as pharmacodynamic markers of target engagement. Further evaluation of predictive markers of sensitivity or resistance showed that RTK tumor models with mTOR mediated activation of eIF4A are most sensitive to eFT226. The association of eFT226 activity in RTK tumor models with mTOR pathway activation provides a means to further enrich for sensitive patient subsets during clinical development. Clinical trials with eFT226 in patients with solid tumor malignancies have initiated.

Citation Format: Peggy A. Thompson, Nathan P. Young, Adina Gerson-Gurwitz, Boreth Eam, Vikas Goel, Craig R. Stumpf, Joan Chen, Gregory S. Parker, Sarah Fish, Maria Barrera, Eric Sung, Jocelyn Staunton, Gary G. Chiang, Kevin R. Webster. Preclinical evaluation of eFT226, a potent and selective eIF4A inhibitor with anti-tumor activity in FGFR1,2 and HER2 driven cancers [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 3399.

Subclinical thyroid dysfunction, bone mineral density, and osteoporosis in a middle-aged Korean population

Thyroid dysfunction is associated with the loss of bone density (osteoporosis). However, the connection between subclinical thyroid dysfunction and osteoporosis remains controversial. This study found no apparent association between subclinical hypothyroidism or subclinical hyperthyroidism and bone mineral density (BMD) in the lumbar spine and femur.

INTRODUCTION

The present study examined the relationship between subclinical thyroid dysfunction and BMD in healthy middle-aged adults.

METHODS

A total of 25,510 healthy Koreans with normal free thyroxine levels were enrolled from January 2011 to December 2016, and 91% of subjects visited only once. The average age of the 15,761 women was 45, and the average age of the 9749 men was 48. Levels of thyroid-stimulating hormone (TSH) and BMD were recorded in all subjects. BMD was measured using dual-energy X-ray absorptiometry.

RESULTS

No apparent association was found between subclinical thyroid dysfunction and BMD in the lumbar spine, femur-neck, and proximal femur sites compared with a euthyroid group. Age, body mass index (BMI), and postmenopausal status affected BMD in women, and only BMI affected BMD in men. Subclinical hypothyroidism was independently associated with a lower risk of osteoporosis (odds ratio 0.657, 95% confidence interval 0.464-0.930) in 4710 postmenopausal women.

CONCLUSIONS

No apparent association was found between subclinical hypothyroidism or subclinical hyperthyroidism defined on single TSH measurement and BMD at the lumbar spine and femur in a large cohort of middle-aged men and women. Subclinical hypothyroidism was independently associated with a lower risk of osteoporosis in postmenopausal women.

Widely tunable mid-infrared light emission in thin-film black phosphorus

Thin-film black phosphorus (BP) is an attractive material for mid-infrared optoelectronic applications because of its layered nature and a moderate bandgap of around 300 meV. Previous photoconduction demonstrations show that a vertical electric field can effectively reduce the bandgap of thin-film BP, expanding the device operational wavelength range in mid-infrared. Here, we report the widely tunable mid-infrared light emission from a hexagonal boron nitride (hBN)/BP/hBN heterostructure device. With a moderate displacement field up to 0.48 V/nm, the photoluminescence (PL) peak from a ~20-layer BP flake is continuously tuned from 3.7 to 7.7 μm, spanning 4 μm in mid-infrared. The PL emission remains perfectly linear-polarized along the armchair direction regardless of the bias field. Moreover, together with theoretical analysis, we show that the radiative decay probably dominates over other nonradiative decay channels in the PL experiments. Our results reveal the great potential of thin-film BP in future widely tunable, mid-infrared light-emitting and lasing applications.

Abstract B133: eFT226, a first in class inhibitor of eIF4A1, targets FGFR1/2 and HER2 driven cancers

Background: Mutations or amplifications affecting receptor tyrosine kinases (RTKs) activate the RAS/MAPK and PI3K/AKT signaling pathways thereby promoting cancer cell proliferation and survival. Oncoprotein expression is tightly controlled at the level of mRNA translation and is regulated by the eukaryotic translation initiation factor 4F (eIF4F) complex consisting of eIF4A, eIF4E, and eIF4G. eIF4A functions to catalyze the unwinding of secondary structure in the 5’-untranslated region (5’-UTR) of mRNA facilitating ribosome scanning and translation initiation. eFT226 is a first in class inhibitor that converts eIF4A1 into a sequence specific translational repressor. eFT226 increases the affinity between eIF4A1 and polypurine recognition elements in the 5’-UTR leading to selective downregulation of mRNA translation. The polypurine element is highly enriched in the 5’-UTR of eFT226 target genes, many of which are known oncogenic drivers, including FGFR1/2 and HER2, enabling eFT226 to selectively inhibit dysregulated oncogene expression. Methods: 5’-UTR dependency was evaluated using cell-based luciferase reporter assays. Regulation of protein expression was analyzed by western blot analysis. Antitumor activity was assessed in vitro by proliferation and apoptosis assays. For in vivo experiments, athymic nude or NOD/SCID mice were implanted with subcutaneous xenograft models of FGFR1, FGFR2 or HER2 driven tumors and treated with eFT226 administered Q4D IV. Results: eFT226 inhibits the translation of FGFR1, FGFR2 and HER2 through formation of a sequence dependent ternary complex with eIF4A1 and polypurine elements within the 5’-UTR of mRNA [eFT226-eIF4A1-mRNA]. Formation of this ternary complex blocks ribosome scanning along the 5’-UTR leading to dose dependent inhibition of RTK protein expression. Cells transiently transfected with luciferase reporter constructs containing the 5’-UTR of each RTK resulted in 10-45-fold greater sensitivity to inhibition by eFT226 compared to a control 5’-UTR confirming the 5’-UTR dependency. In solid tumor cell lines driven by alterations in FGFR1, FGFR2 or HER2, downregulation of RTK expression by eFT226 resulted in decreased MAPK and AKT signaling, potent inhibition of cell proliferation and an induction of apoptosis suggesting that eFT226 could be effective in treating tumor types dependent on these oncogenic drivers. Solid tumor xenograft models harboring FGFR1/2 or HER2 amplifications treated with eFT226 resulted in significant in vivo tumor growth inhibition and regression at well tolerated doses in breast, non-small cell lung and colorectal cancer models. Treatment with eFT226 also decreased RTK protein levels supporting the potential to use these eFT226 target genes as pharmacodynamic markers of target engagement. Conclusions: eFT226 is efficacious against tumor models with alterations in FGFR1, FGFR2 and HER2 RTKs. The antitumor response observed in preclinical in vivo models driven by RTK amplifications demonstrates the potential for eFT226 in the treatment of solid tumors with FGFR1/2 or HER2 alterations. Furthermore, this data provides a means to select sensitive patient subsets during clinical development. Clinical trials in patients with solid tumor malignancies are planned.

Citation Format: Peggy A Thompson, Nathan P Young, Craig R Stumpf, Boreth Eam, Vikas K Goel, Joan Chen, Sarah Fish, Gregory S Parker, Adina Gerson-Gurwitz, Maria Barrera, Eric Sung, Jocelyn Staunton, Gary G Chiang, Christopher J Wegerski, Samuel Sperry, Kevin R Webster, Siegfried H Reich. eFT226, a first in class inhibitor of eIF4A1, targets FGFR1/2 and HER2 driven cancers [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference on Molecular Targets and Cancer Therapeutics; 2019 Oct 26-30; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2019;18(12 Suppl):Abstract nr B133. doi:10.1158/1535-7163.TARG-19-B133

Abstract 1302: Targeting hormone receptor-dependent cancers with potent, selective and orally-available small molecule inhibitors of eIF4E

The PI3K/mTOR pathway is commonly dysregulated in many hormone receptor-dependent tumors and plays a key role in promoting tumor growth and mediating drug resistance. In particular, PI3K and mTORC1/2 inhibitors have been intensively studied in the treatment of hormone receptor-dependent cancers and have shown benefit in some clinical settings. However, issues such as dose-limiting toxicities and emergent resistance limit the broader utility of these inhibitors. The translation initiation factor eIF4E is essential for the translation of m7G-capped mRNA and is a key point of convergence for both the PI3K/mTOR and MAPK signaling pathways. We have designed a series of potent, selective and orally-available m7G cap-competitive inhibitors of eIF4E (eFT-4Ei) with favorable drug-like properties. These inhibitors bind to eIF4E either as its free form or with eIF4E-4EBP and eIF4F complexes within tumor cells and downregulate hormone receptor-dependent signaling. Ribosomal profiling of eIF4E inhibitor-treated tumor cells identified a subset of translationally regulated target genes that overlap with mTORC1/2 regulated genes, but also a unique set of translationally regulated target mRNAs. Consistent with this observation, our eIF4E inhibitors show some similarities yet several important differences from existing mTORC1 or mTORC1/2 dual inhibitors in both cellular and physiological assays. Finally, significant anti-tumor efficacy was observed with eIF4E inhibition in vitro and in vivo. Taken together, these results highlight the potential for targeting eIF4E as a novel therapeutic strategy to treat hormone-receptor dependent cancers.

Citation Format: Gary G. Chiang, Gregory S. Parker, Ivy N. Hung, Vikas K. Goel, Jocelyn Staunton, Maria Barrera, Eric Sung, Ana Parra, Craig R. Stumpf, Joan Chen, Peggy A. Thompson, Andreas Nevarez, Christopher J. Wegerski, Cody Parker, Jeff Clarine, Samuel Sperry, Alan Xiang, Christian Nilewski, Garrick K. Packard, Kaveri Urkalan, Takasuke Mukaiyama, Theo Michels, Justin T. Ernst, Paul A. Sprengeler, Siegfried H. Reich, Kevin R. Webster. Targeting hormone receptor-dependent cancers with potent, selective and orally-available small molecule inhibitors of eIF4E [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1302.

Abstract 2698: eFT226, a potent and selective inhibitor of eIF4A, is efficacious in preclinical models of lymphoma

Dysregulated messenger RNA (mRNA) translation drives the pathogenesis of multiple hematological malignancies. In lymphoma this includes the upregulation of key driver oncogenes and anti-apoptotic proteins (e.g., MYC, CCND1/3, BCL2 and MCL1) that contain a highly structured 5’-untranslated region (UTR) in their mRNA requiring enhanced eIF4A helicase activity for translation. eIF4A is a component of the eIF4F translation initiation complex and catalyzes the ATP-dependent unwinding of RNA duplexes and facilitates 43S ribosome scanning within the 5’-UTR. The activation of oncogenic signaling pathways, including RAS and PI3K, enhance eIF4A activity through phosphorylation of eIF4B, eIF4G and PDCD4 which facilitates formation of eIF4F and full activation of eIF4A. The PI3K/AKT/mTOR pathway is frequently activated in lymphoma, promoting the translation of oncogenes with complex 5’-UTRs that are required for tumor cell proliferation, survival and metastasis.

eFT226 is a potent and sequence selective eIF4A1 inhibitor that promotes eIF4A1 binding to specific 5’-UTR polypurine and/or G-quadraplex recognition motifs leading to a selective block in ribosome mRNA scanning. The sequence dependency of eFT226 translational inhibition was evaluated in cell-based reporter assays demonstrating &gt;100-fold greater sensitivity for reporter constructs containing a polypurine motif in the 5’-UTR (IC50 ~2 nM). Direct binding studies also confirmed the formation of a stable ternary complex with increased drug residence time between eFT226, eIF4A1 and RNA oligonucleotides containing polypurine motifs. The ability of eFT226 to inhibit MYC or MCL1 expression was found to be dependent on the presence of their respective 5’-UTR supporting a translational regulation mechanism dependent on recognition elements within the 5’-UTR.

eFT226 shows potent anti-proliferative activity (GI50 &lt; 15 nM) against a panel of B-cell lymphoma cell lines. Treatment with eFT226 leads to coordinated inhibition of MYC, CCND1/3, BCL2 or MCL1 protein expression resulting in significant anti-tumor activity. eFT226 has good pharmacokinetic properties and exhibits significant in vivo activity across a panel of diffuse large B cell lymphoma (DLBCL), and Burkitt lymphoma tumor models with ≤1 mg/kg/week IV administration. Further evaluation of predictive markers of sensitivity or resistance has shown that tumors with mTOR mediated activation of eIF4A are most sensitive to eFT226. In addition, tumors with PTEN mutations do not exhibit activated eIF4A and are generally resistant to induction of apoptosis by eFT226, resulting in reduced in vivo efficacy. The association of eFT226 activity with PI3K/mTOR pathway activation and mutational status provides a means to identify patient subsets during clinical development. Clinical trials in patients with lymphoma and other malignancies are planned.

Citation Format: Peggy A. Thompson, Boreth Eam, Nathan P. Young, Sarah Fish, Joan Chen, Maria Barrera, Haleigh Howard, Eric Sung, Ana Parra, Jocelyn Staunton, Gary G. Chiang, Christopher J. Wegerski, Andres Nevarez, Jeff Clarine, Samuel Sperry, Alan Xiang, Chinh Tran, Christian Nilewski, Garrick K. Packard, Theodore Michels, Paul A. Sprengeler, Justin T. Ernst, Siegfried H. Reich, Kevin R. Webster. eFT226, a potent and selective inhibitor of eIF4A, is efficacious in preclinical models of lymphoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 2698.

Localization of Parotid Gland Tumors in Relation to the Intraparotid Facial Nerve on 3D Double-Echo Steady-State with Water Excitation Sequence

BACKGROUND AND PURPOSE

Reliable preoperative facial nerve mapping may help avoid or minimize facial nerve injury during parotid tumor resection. The purpose of this study was to investigate the diagnostic performance of the 3D double-echo steady-state with water excitation sequence in localizing parotid gland tumors through direct visualization of the intraparotid facial nerve in comparison with indirect methods of estimating the facial nerve location.

MATERIALS AND METHODS

We retrospectively reviewed 91 parotid gland tumors in 90 patients who underwent surgical resection and preoperative MR imaging, including the 3D double-echo steady-state with water excitation sequence. The tumor locations were categorized as deep or superficial on the basis of direct and 3 indirect methods: the facial nerve line, retromandibular vein, and Utrecht line. Surgical localization was considered the criterion standard. The diagnostic performance for localizing deep lobe lesions using direct and indirect methods was calculated and compared using the McNemar test.

RESULTS

Surgical localization confirmed 75 superficial lesions and 16 deep lesions. The interobserver variability of the 3D double-echo steady-state with water excitation sequence was excellent (κ = 0.870). The diagnostic accuracy, sensitivity, specificity, positive predictive value, and negative predictive value for localizing deep lobe lesions using the 3D double-echo steady-state with water excitation method were 97.8%, 87.5%, 100%, 100%, and 97.4%, respectively. These findings were significantly higher than the facial nerve line in sensitivity, the retromandibular vein in sensitivity, and the Utrecht line in accuracy and specificity (P < .05). Overall, the direct method was the most accurate, sensitive, and specific in localizing parotid gland tumors.

CONCLUSIONS

We can achieve higher diagnostic performance in localizing parotid gland tumors by directly visualizing the intraparotid facial nerve using the 3D double-echo steady-state with water excitation sequence compared with indirect methods.

Anti-Stokes Emission from Hot Carriers in Gold Nanorods

The origin of light emission from plasmonic nanoparticles has been strongly debated lately. It is present as the background of surface-enhanced Raman scattering and, despite the low yield, has been used for novel sensing and imaging applications because of its photostability. Although the role of surface plasmons as an enhancing antenna is widely accepted, the main controversy regarding the mechanism of the emission is its assignment to either radiative recombination of hot carriers (photoluminescence) or electronic Raman scattering (inelastic light scattering). We have previously interpreted the Stokes-shifted emission from gold nanorods as the Purcell effect enhanced radiative recombination of hot carriers. Here we specifically focused on the anti-Stokes emission from single gold nanorods of varying aspect ratios with excitation wavelengths below and above the interband transition threshold while still employing continuous wave lasers. Analysis of the intensity ratios between Stokes and anti-Stokes emission yields temperatures that can only be interpreted as originating from the excited electron distribution and not a thermally equilibrated phonon population despite not using pulsed laser excitation. Consistent with this result as well as previous emission studies using ultrafast lasers, the power-dependence of the upconverted emission is nonlinear and gives the average number of participating photons as a function of emission wavelength. Our findings thus show that hot carriers and photoluminescence play a major role in the upconverted emission.

Abstract 5546: eFT508, a potent and highly selective inhibitor of MNK1 and MNK2, regulates T-cell differentiation promoting an antitumor immune response

An effective and durable T-cell response is a cornerstone of current immunotherapies. We show that eFT508, a potent, selective inhibitor of MNK1 and MNK2, establishes a regulatory program that promotes multiple steps in the cancer immunity cycle including expansion of memory T cells and prevention of T-cell exhaustion. Using OT-I and OT-II transgenic systems, we show that eFT508 shifts the distribution of T cells towards a CD62LhighCD44high central memory (CM) phenotype in both CD4 and CD8 T cells upon activation with SIINFEKL peptide in vitro without adverse effects on T-cell proliferation, interferon-γ production or cytotoxic function. Similar effects are seen in vivo, where eFT508 treatment also enriches the CM T-cell pool in a SIINFEKL vaccine-induced OT-I adoptive T-cell transfer model, which results in increased persistence as demonstrated by a higher memory-recall T-cell response upon rechallenge. In addition, the CM bias elicited by eFT508 remains dominant when combined with agonists of co-stimulatory molecules, such as 4-1BB, OX-40 and GITR, or checkpoint inhibitors, such as PD-1, PD-L1 and CTLA-4, suggesting that eFT508 can affect the rate of T-cell differentiation in these combinations. eFT508 treatment also reduces the expression of exhaustion markers such as PD-1, LAG3 and TIM3, leading to increased cytotoxic T-cell function. eFT508 is currently under evaluation as a single agent in two phase 1/2 clinical trials for patients with advanced solid tumors and patients with advanced lymphoma. In addition, a phase 2 study evaluating eFT508, alone or in combination with avelumab, a PD-L1 immune checkpoint inhibitor, in microsatellite stable relapsed or refractory CRC patients is ongoing. The preclinical studies presented here provide further evidence that eFT508 may combine well with additional immunotherapies beyond checkpoint blockade.

Citation Format: Rajesh K. Sharma, Vikas K. Goel, Jocelyn Staunton, Maria Barrera, Ana Parra, Eric Sung, Gary G. Chiang, Kevin R. Webster. eFT508, a potent and highly selective inhibitor of MNK1 and MNK2, regulates T-cell differentiation promoting an antitumor immune response [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 5546.

Photoluminescence of Gold Nanorods: Purcell Effect Enhanced Emission from Hot Carriers

We demonstrate, experimentally and theoretically, that the photon emission from gold nanorods can be viewed as a Purcell effect enhanced radiative recombination of hot carriers. By correlating the single-particle photoluminescence spectra and quantum yields of gold nanorods measured for five different excitation wavelengths and varied excitation powers, we illustrate the effects of hot carrier distributions evolving through interband and intraband transitions and the photonic density of states on the nanorod photoluminescence. Our model, using only one fixed input parameter, describes quantitatively both emission from interband recombination and the main photoluminescence peak coinciding with the longitudinal surface plasmon resonance.

Correlated Absorption and Scattering Spectroscopy of Individual Platinum-Decorated Gold Nanorods Reveals Strong Excitation Enhancement in the Nonplasmonic Metal

Bimetallic nanocatalysts have the potential to surmount current limitations in industrial catalysis if their electronic and optical properties can be effectively controlled. However, improving the performance of bimetallic photocatalysts requires a functional understanding of how the intricacies of their morphology and composition dictate every element of their optical response. In this work, we examine Au and Pt-decorated Au nanorods on a single-particle level to ascertain how Pt influences the plasmon resonance of the bimetallic nanostructure. We correlated scattering, photoluminescence, and pure absorption of individual nanostructures separately to expose the impact of Pt on each component. We found that the scattering and absorption spectra of uncoated Au nanorods followed expected trends in peak intensity and shape and were accurately reproduced by finite difference time domain simulations. In contrast, the scattering and absorption spectra of single Pt-decorated Au nanorods exhibited red-shifted, broad features and large deviations in line shape from particle to particle. Simulations using an idealized geometry confirmed that Pt damps the plasmon resonance of individual Au nanorods and that spectral changes after Pt deposition were a consequence of coupling between Au and Pt in the hybrid nanostructure. Simulations also revealed that the Au nanorod acts as an antenna and enhances absorption in the Pt islands. Furthermore, comparing photoluminescence spectra from Au and Pt-decorated Au nanorods illustrated that emission was significantly reduced in the presence of Pt. The reduction in photoluminescence intensity indicates that Pt lowers the number of hot carriers in the Au nanorod available for radiative recombination through either direct production of hot carriers in Pt following enhanced absorption or charge transfer from Au to Pt. Overall, these results confirm that the Pt island morphology and distribution on the nanorod surface contribute to the optical response of individual hybrid nanostructures and that the damping observed in ensemble measurements originates not only from structural heterogeneity but also because of significant damping in single nanostructures.

Sleep duration and progression to diabetes in people with prediabetes defined by HbA1c concentration

AIMS

To evaluate the association between sleep duration and the risk of progression to diabetes among people with prediabetes, defined by HbA_1c values.

METHODS

We conducted a cohort study in 17 983 adults who underwent health check-up examinations, including assessments of sleep duration and quality. Diabetes was defined as either HbA_1c ≥48 mmol/mol (6.5%), or the use of antidiabetic medication. Time-dependent proportional hazards models were used to evaluate the association between sleep duration and the risk of progression to diabetes.

RESULTS

During 31,582 person-years of follow-up, 664 incident cases of diabetes were identified; the incidence rate was 21.0 per 1000 person-years. The multivariate adjusted hazard ratios for progression to diabetes in people with sleep durations of ≤5, 6 and ≥8 h compared with 7 h were 1.68 (95% CI 1.30-2.16), 1.44 (95% CI 1.17-1.76) and 1.23 (95% CI 0.85-1.78), respectively (P for quadratic trend <0.001). This association was partially mediated by biomarkers of adiposity, fatty liver and insulin resistance.

CONCLUSION

In this large study in young and middle-aged adults with prediabetes, we found an association between short sleep duration and the risk of progression to diabetes. Our findings suggest that sufficient sleep duration is important for delaying or preventing the progression of prediabetes to diabetes.