Citations

TPS7586 Background: EO2463 is a therapeutic vaccine designed to activate existing commensal bacteria-specific memory T cells that cross-react with B cell markers in order to drive anti-tumor immune activity against B-cell malignancies. The four microbial-derived, synthetically produced peptides contained in EO2463 (OMP72, OMP64, OMP65, and OMP66), correspond to cytotoxic CD8 T cell HLA-A2 restricted epitopes, and exhibit molecular mimicry with the B cell markers CD20, CD22, CD37, and CD268 (BAFF-receptor), respectively. In pre-clinical models, these peptides can generate strong immune responses and specifically stimulate cross-reactive cytotoxic CD8 T cells to recognize the chosen B cell targets. EO2463 also contains a CD4 helper peptide referred to as universal cancer peptide 2, derived from the human telomerase reverse transcriptase catalytic subunit. The present study is a first-in-human clinical trial of this microbiome-derived peptide therapeutic cancer vaccine approach in patients with follicular lymphoma (FL) and marginal zone lymphoma (MZL). Methods: This four-cohort phase 1/2 trial will investigate EO2463 monotherapy, and combinations of EO2463/lenalidomide (EL), EO2463/rituximab (ER), and EO2463/lenalidomide/rituximab (ER2), for treatment of patients with FL and MZL. Cohort 1 is a safety lead-in dose-finding in patients with relapsed/refractory (RR) disease, with a 3-by-3 design to establish the recommended phase 2 dose (RP2D) for EO2463 monotherapy and to confirm the safety of the RP2D for combination schedules of EL, and ER2. After the recommended EO2463 monotherapy dose is established, cohorts 2, 3, and 4 will open to accrual. Cohort 2 will investigate EO2463 monotherapy in patients with newly diagnosed FL/MZL who are not in need of treatment; cohort 3 will investigate EO2463 monotherapy, followed by ER in patients with limited tumor burden who need treatment, and cohort 4 will further investigate EL, followed by ER2 in the RR setting. EO2463 will be administered SC 4 times at 2-week intervals, followed by continued booster administrations every 4 weeks for 9 (Cohorts 2 and 3) or 12 (Cohorts 1 and 4) months. Inclusion/exclusion criteria, and the design and schedule of the intense immune and safety monitoring will be presented. The safety lead-in dose-finding is currently ongoing, and no safety concerns have been observed thus far. Clinical trial information: NCT04669171.

e18790 Background: Patients with SARS-CoV-2 with a diagnosis of cancer have increased risk of severe COVID-19 outcomes compared to patients without cancer. However, little is known regarding outcomes of patients with COVID-19 and cancer in the setting of human immunodeficiency virus (HIV). Given the unique risks of this population, we sought to understand COVID-19 outcomes using registry data. Methods: This is a descriptive research study utilizing the CCC19 registry, an international multi-institutional registry with healthcare provider-reported cases of patients with cancer and COVID-19. Between March 2020-December 2021, 116 persons with HIV (PWH) and 10,642 persons without HIV (PWOH) with laboratory-confirmed SARS-CoV-2 infection were identified as eligible for the analysis. Results: Median follow-up time for both groups was 90 days, with interquartile range (IQR) 30-180 days. Most PWH were actively receiving antiretroviral therapy (ART) at the time of COVID-19 diagnosis, with 71% (n = 82) having named drug information available; bictegravir/emtricitabine/tenofovir was the most common ART (n = 25). PWH were of younger age (median 57.5 yrs [IQR 46.5-63.25] vs 65 yrs [IQR 55-74]), male (81% vs 47%), and either non-Hispanic Black or Hispanic (71% vs 34%) compared to PWOH. 12% of PWH (n = 14) were current smokers compared to 6% of PWOH (n = 638), and more than half in each group were never smokers (51% of PWH and 53% of PWOH). The following comorbidities were identified in PWH vs PWOH: cardiovascular (16% vs 20%), pulmonary (16% vs 20%), renal (15% vs 14%), and diabetes mellitus (18% vs 27%). A higher proportion of PWH had hematologic malignancy compared to PWOH (33% vs 19%). More PWH had active cancer which was progressing at the time of SARS-CoV-2 infection compared to PWOH (24% vs 14%). 44% of PWH (n = 51) had received active systemic anticancer therapy within the 3 months preceding SARS-CoV-2 infection (including cytotoxic, targeted, endocrine therapies, and immunotherapy) compared to 51% of PWOH (n = 5,420). PWH had an increased rate of hospitalization (58% vs 55%) compared to PWOH. Although a lower proportion of PWH required supplemental oxygen during hospitalization compared to PWOH (34% vs 38%) and ICU admission rates were identical between the two groups (16% vs 16%), PWH had an increased rate of mechanical ventilation (14% vs 10%) and death (24% vs 18%) compared to PWOH. Conclusions: This is the first known study describing outcomes of patients with cancer and COVID-19 in the PWH population from a large multinational dataset. PWH have characteristics associated with adverse outcomes in prior analyses (male sex, non-Hispanic Black or Hispanic, hematologic malignancy, progressing cancer) but are notably younger and have fewer comorbidities. HIV infection may portend increased risk of severe COVID-19 and death; however, additional analyses, including multivariable regression, are warranted.

Background: Despite various aesthetic trends, the ideal lip proportion and lip volume remains elusive. Thus, the aim of this study was to investigate the aesthetic perception of various lip shapes to identify the most attractive lips. Methods: Fifty-nine White study participants with a mean age of 32.73 ± 9.4 years were asked to assess lips of various proportions and of various volumes. Gaze assessment and aesthetic rating of the same set of modified lip images were performed. Results: The results revealed that the lip proportion that was rated to be most attractive was the 1:1.6 ratio (upper-to-lower lip, 4.21 of a possible 5). This lip proportion, however, was not the first one to be viewed on initial image display (1.20 sec) and had the shortest duration of a stable eye fixation within the 6-second image display interval (2.18 of 6 seconds). The lip volume that received the highest aesthetic rating was the 100 percent volume (original lip size), with 4.56 of a possible 5. This lip volume, however, had the third longest interval between initial image exposure and the first stable eye fixation (0.81 second) and had the shortest duration of stable eye fixations during the 6 seconds of image display (2.22 of 6 seconds). Conclusion: The results presented could be potentially reflective of the internal cognitive processes during the involuntary and voluntary assessment of lip attractiveness.

Abstract PURPOSE: A subset of pediatric, adolescent and young adult (AYA) gliomas are located in the brainstem, eloquent locations, or present with diffuse/leptomeningeal disease, and are associated with high risk and low yield of biopsy. At the same time, accurate molecular diagnosis is necessary to direct optimal therapy. In such cases, analysis of cell free DNA (cfDNA) form cerebral spinal fluid (CSF) may represent a diagnostic alternative to biopsy. METHODS: We investigated the utility of CSF cfDNA sequencing through a stepwise approach, using clinically validated, targeted molecular assays. Testing was performed using a broad hybrid capture next generation sequencing assay (MSK-IMPACT) and subsequent targeted digital droplet PCR in a subset of cases. RESULTS: We analyzed 17 CSF samples from 17 pediatric (n=6) and AYA (n=11) glioma patients with primary or recurrent disease. Thirteen had tumors located within the brainstem, and four had leptomeningeal involvement. Somatic alterations were detected in 12/17 samples (71%). In 3/4 patients with leptomeningeal involvement, cfDNA testing revealed a BRAF fusion consistent with the diagnosis of diffuse leptomeningeal glioneuronal tumor (DLGNT). Among the 13 patients with brainstem involvement, four had somatic H3 K27M mutations, three had IDH mutations, and one had TP53 and ATRX mutations; five patients had no detectable mutations. CONCLUSION: In our analysis, we found that established glioma hotspot mutations were able to be detected within the CSF. We propose that in patients for whom tissue biopsy is high risk, not feasible, or tissue was nondiagnostic, CSF cfDNA sequencing has a substantial diagnostic yield and should be considered as a valuable novel diagnostic tool. Ongoing research is aiming to further increase the sensitivity of cfDNA testing, especially in patients with very low levels of CSF cfDNA.

Background: COVID-19 is a disease with multiple variants, and is quickly spreading throughout the world. It is crucial to identify patients who are suspected of having COVID-19 early, because the vaccine is not readily available in certain parts of the world. Methodology: Lung computed tomography (CT) imaging can be used to diagnose COVID-19 as an alternative to the RT-PCR test in some cases. The occurrence of ground-glass opacities in the lung region is a characteristic of COVID-19 in chest CT scans, and these are daunting to locate and segment manually. The proposed study consists of a combination of solo deep learning (DL) and hybrid DL (HDL) models to tackle the lesion location and segmentation more quickly. One DL and four HDL models—namely, PSPNet, VGG-SegNet, ResNet-SegNet, VGG-UNet, and ResNet-UNet—were trained by an expert radiologist. The training scheme adopted a fivefold cross-validation strategy on a cohort of 3000 images selected from a set of 40 COVID-19-positive individuals. Results: The proposed variability study uses tracings from two trained radiologists as part of the validation. Five artificial intelligence (AI) models were benchmarked against MedSeg. The best AI model, ResNet-UNet, was superior to MedSeg by 9% and 15% for Dice and Jaccard, respectively, when compared against MD 1, and by 4% and 8%, respectively, when compared against MD 2. Statistical tests—namely, the Mann–Whitney test, paired t-test, and Wilcoxon test—demonstrated its stability and reliability, with p < 0.0001. The online system for each slice was <1 s. Conclusions: The AI models reliably located and segmented COVID-19 lesions in CT scans. The COVLIAS 1.0Lesion lesion locator passed the intervariability test.

Purpose: The role of erectile dysfunction (ED) has recently shown an association with the risk of stroke and coronary heart disease (CHD) via the atherosclerotic pathway. Cardiovascular disease (CVD)/stroke risk has been widely understood with the help of carotid artery disease (CTAD), a surrogate biomarker for CHD. The proposed study emphasizes artificial intelligence-based frameworks such as machine learning (ML) and deep learning (DL) that can accurately predict the severity of CVD/stroke risk using carotid wall arterial imaging in ED patients. Methods: Using the PRISMA model, 231 of the best studies were selected. The proposed study mainly consists of two components: (i) the pathophysiology of ED and its link with coronary artery disease (COAD) and CHD in the ED framework and (ii) the ultrasonic-image morphological changes in the carotid arterial walls by quantifying the wall parameters and the characterization of the wall tissue by adapting the ML/DL-based methods, both for the prediction of the severity of CVD risk. The proposed study analyzes the hypothesis that ML/DL can lead to an accurate and early diagnosis of the CVD/stroke risk in ED patients. Our finding suggests that the routine ED patient practice can be amended for ML/DL-based CVD/stroke risk assessment using carotid wall arterial imaging leading to fast, reliable, and accurate CVD/stroke risk stratification. Summary: We conclude that ML and DL methods are very powerful tools for the characterization of CVD/stroke in patients with varying ED conditions. We anticipate a rapid growth of these tools for early and better CVD/stroke risk management in ED patients.

Background: Lung ultrasound detects pulmonary congestion as B-lines at rest, and more frequently, during exercise stress echocardiography (ESE). Methods: We performed ESE plus lung ultrasound (4-site simplified scan) in 4392 subjects referred for semi-supine bike ESE in 24 certified centers in 9 countries. B-line score ranged from 0 (normal) to 40 (severely abnormal). Five different populations were evaluated: control subjects (n=103); chronic coronary syndromes (n=3701); heart failure with reduced ejection fraction (n=395); heart failure with preserved ejection fraction (n=70); ischemic mitral regurgitation ≥ moderate at rest (n=123). In a subset of 2478 patients, follow-up information was available. Results: During ESE, B-lines increased in all study groups except controls. Age, hypertension, abnormal ejection fraction, peak wall motion score index, and abnormal heart rate reserve were associated with B-lines in multivariable regression analysis. Stress B lines (hazard ratio, 2.179 [95% CI, 1.015–4.680]; P =0.046) and ejection fraction <50% (hazard ratio, 2.942 [95% CI, 1.268–6.822]; P =0.012) were independent predictors of all-cause death (n=29 after a median follow-up of 29 months). Conclusions: B-lines identify the pulmonary congestion phenotype at rest, and more frequently, during ESE in ischemic and heart failure patients. Stress B-lines may help to refine risk stratification in these patients. Registration: URL: https://www.clinicaltrials.gov ; Unique identifier: NCT 03049995.

Diabetes is one of the main causes of the rising cases of blindness in adults. This microvascular complication of diabetes is termed diabetic retinopathy (DR) and is associated with an expanding risk of cardiovascular events in diabetes patients. DR, in its various forms, is seen to be a powerful indicator of atherosclerosis. Further, the macrovascular complication of diabetes leads to coronary artery disease (CAD). Thus, the timely identification of cardiovascular disease (CVD) complications in DR patients is of utmost importance. Since CAD risk assessment is expensive for low-income countries, it is important to look for surrogate biomarkers for risk stratification of CVD in DR patients. Due to the common genetic makeup between the coronary and carotid arteries, low-cost, high-resolution imaging such as carotid B-mode ultrasound (US) can be used for arterial tissue characterization and risk stratification in DR patients. The advent of artificial intelligence (AI) techniques has facilitated the handling of large cohorts in a big data framework to identify atherosclerotic plaque features in arterial ultrasound. This enables timely CVD risk assessment and risk stratification of patients with DR. Thus, this review focuses on understanding the pathophysiology of DR, retinal and CAD imaging, the role of surrogate markers for CVD, and finally, the CVD risk stratification of DR patients. The review shows a step-by-step cyclic activity of how diabetes and atherosclerotic disease cause DR, leading to the worsening of CVD. We propose a solution to how AI can help in the identification of CVD risk. Lastly, we analyze the role of DR/CVD in the COVID-19 framework.