Citations

9567 Background: Resected stage IIB/C and microscopic stage IIIA/B/C/D melanoma presents a significant risk of recurrence risk of 37 to 62% at 5 years (yrs). While 1 year of adjuvant PD1 therapy reduces this risk by approximately half, the individual patient’s baseline risk without treatment and their specific benefit from adjuvant PD1 remain unknown. We aimed to generate two separate predictive models for recurrence – one for untreated and one for treated pts - to calculate the individualised benefit of adjuvant PD1. Methods: Pts with resected stage IIB/C or microscopic stage IIIA/B/C/D melanoma, either treated with adjuvant PD1 or untreated at 13 major melanoma centres, and with at least 2 years of follow-up from surgery were included. We analysed pts demographics, disease characteristics, blood parameters, pathological and imaging data at baseline, and clinical outcomes. Propensity scores were estimated using logistic regression with covariates associated with treatment in univariate screening (p<0.05). Separate penalised multivariable logistic regression models were built to predict recurrence for treated and untreated pts. A tool based on these models was created to calculate the individual patient benefit from adjuvant PD1. Results: A total of 3560 pts was included, divided into untreated (discovery n=2384 and validation n=597) and treated (discovery n=404 and validation n=175) cohorts. The model for untreated pts included age, gender, primary site, histological subtype, Breslow thickness, ulceration, mitosis, number and site of regional lymph nodes (LN), mutation status and LDH (AUC 0.70 in discovery, 0.69 in validation). The model for treated pts included age, gender, Breslow thickness, site of regional LN, and mutation status (AUC 0.69 in discovery, 0.61 in validation). ADAPT-M (ADjuvant Anti-PD-1 Tool for Melanoma) calculates the individualized benefit of adjuvant PD1. For example, patient A, a woman ≤45 years old with a primary head & neck melanoma (superficial spreading, thickness >1-2 mm, no ulceration, 1 mitosis/mm 2 ), 2 clinically occult LN metastases in the neck, NRAS mutant, and normal LDH, has a 12-month recurrence risk of 21.9% untreated vs 2.3% treated (benefit 19.6%), and a 24-month risk of 41.1% untreated vs 6.4% treated (benefit 34.7%). While, patient B, a man ≤45 years old with a primary melanoma in the lower limb (nodular, thickness >1-2 mm, no ulceration, 1 mitosis/mm 2 ), 2 clinically occult LN metastases in the groin, BRAF V600 mutant, and normal LDH, has a 12-month recurrence risk of 14.2% untreated vs 11.8% treated (benefit 2.5%), and a 24-month risk of 28.0% untreated vs 30.1% treated (no benefit). Conclusions: ADAPT-M, a clinical tool that estimate individualized recurrence risks with and without adjuvant anti-PD1 therapy, quantifies the absolute benefit of treatment for pts with high-risk resected melanoma, facilitating personalized adjuvant therapy decisions.

9535 Background: MUM carries a poor prognosis with few effective treatments, especially for HLA-A*02:01-negative pts. While a subset of MUM pts responds to immune checkpoint inhibitors, the comparative efficacy of IPI+PD1 versus PD1 monotherapy is unclear. This study compares objective response rate (ORR), progression-free survival (PFS), overall survival (OS), and safety between these regimens in MUM. Methods: MUM pts treated with PD1 or IPI+PD1 at 15 major melanoma centres (from Australia, Europe, United States and Israel) were included. Demographics, patient and disease characteristics, and clinical outcomes were examined. Univariate and multivariate (MVA) analyses were performed to identify clinical predictors of response and survival. Results: Of 412 MUM pts treated, 150 (36%) had PD1 and 262 (64%) received PD1+IPI. Compared to the PD1 group, PD1+IPI-treated pts were younger (64 vs. 70 years; p<0.001), had higher rate of elevated LDH (44% vs. 31%; p=0.037), and more frequently had prior treatment with tebentafusp (6.5% vs. 1.3%; p=0.031). Median follow-up from commencement of PD1+/-IPI was 4.9 years (95% CI 4.7 – 6.1). ORR was higher in IPI+PD1 group (18%) vs. PD1 (9%) (p=0.008), particularly in males (p=0.009), patients with liver metastases (p=0.018) and with lung metastases (p=0.011), with elevated LDH (p=0.047) and with no prior treatment with tebentafusp (p=0.007). PFS and OS at 1 and 2 years were numerically higher with IPI+PD1 (1- and 2-year PFS: 23% and 15%; 1- and 2-year OS: 63% and 39%) vs. PD1 (1- and 2-year PFS: 17% and 11%; 1- and 2-year OS: 54% and 36%), but these differences were not statistically significant (p>0.05). On MVA, adjusting for predefined variables (age, gender, ECOG PS, LDH, presence/absence of liver/lung metastases, prior treatment with tebentafusp), IPI+PD1 was associated with higher ORR (OR 2.71, 1.30 – 6.05; p=0.01) but not with PFS or OS compared to PD1. Presence of liver metastases (ORR [OR 0.28; 95% CI 0.13 - 0.64], PFS [HR 1.61; 95% CI 1.11 - 2.34], OS [HR 2.02; 95% CI 1.32 - 3.10]), ECOG PS≥2 (PFS [HR 1.82; 95% CI 1.07 - 3.10], OS [HR 2.24; 95% CI 1.25-4.01]), elevated LDH (PFS [HR 1.66; 95% CI 1.30 - 2.11], OS [HR 2.39; 95% CI 1.84-3.10]) and prior tebentafusp treatment (OS [HR 2.36; 95% CI 1.21-4.59]) were also independent predictors of response and/or survival. A higher percentage of pts experienced grade ≥3 immune-related adverse events (irAEs) in the IPI+PD1 group compared to the PD1 group (34% vs 13%, p<0.0001). Most pts ceased treatment due to progression (234, 57%), and more pts stopped due to toxicity in the IPI+PD1 vs. PD1 group (25% vs. 9%, p<0.0001). Conclusions: In pts with MUM, IPI+PD1 demonstrated a higher ORR but did not improve survival compared with PD1 alone. IPI+PD1 was more toxic, leading to early treatment discontinuation in one-quarter of pts. These findings may help guide treatment selection in MUM.

Cellular and molecular heterogeneity in the liver has been increasingly recognized to drive liver fibrosis progression, but the particular events that occur initially in response to liver injury and trigger immune cell recruitment remain unclear. Here, we identify epigenetically aberrant liver sinusoidal endothelial cells (LSECs) as key players in this process. Mechanistically, the epigenetic readers like bromodomain-containing protein 4–dependent (BRD4-dependent) super enhancers (SEs) activate proinflammatory genes, including promyelocytic leukemia (PML). The PML protein, in turn, binds BRD4 and amplifies proinflammatory angiocrine signaling through phase separation–dependent SE activation via PML/BRD4 condensate formation. In mouse models, LSEC-specific depletion of the PML/BRD4 complex mitigates liver inflammation and fibrosis. Single-cell RNA-seq reveals that epigenetically aberrant LSECs exhibit a reprogrammed proinflammatory angiocrine landscape in mouse fibrotic livers. TIMP1 + LSECs promote the recruitment of CD63 + monocyte–derived macrophages (MoMFs) during liver fibrosis progression. Thereby, PML/BRD4 in LSECs governs inflammatory immune cell recruitment in liver fibrosis. Pharmacological BRD4 inhibition or epigenetic PML-SE repression alleviates liver inflammation and fibrosis. In conclusion, PML/BRD4-mediated SE activation via phase separation drives proinflammatory angiocrine signaling in LSECs, initiating the inflammatory cascade and subsequent immune cell recruitment during liver fibrosis.

BACKGROUND: Bicuspid aortic valve (BAV) is a frequent congenital heart defect with a high heritability. Despite this, only a limited number of genes have been associated with the disease, and the molecular mechanisms remain unexplained in most cases. This study aimed to further understand the genetic architecture of BAV. METHODS: A genome-wide association study meta-analysis including 9631 cases among 65 677 participants was performed. Genes were prioritized using transcriptomic analyses based on RNA sequencing in relevant tissues, including human fetal and adult aortic valves. The impact of the knockdown or knockout of 4 candidate genes on cardiac development was verified in zebrafish. A polygenic risk score was developed, its association with BAV was evaluated in an independent cohort, and its association with a wide range of phenotypes (n=976) was evaluated in UK Biobank (n=355 618 individuals). RESULTS: Thirty-six genomic loci were identified, including 32 that were not described previously. Among the prioritized genes, KANK2 and ERBB4 were identified as potentially causal through transcriptomic analyses, colocalization, and Mendelian randomization based on gene expression in human aortic valves (n=484), whereas PRDM6 and STRN were prioritized using similar analyses from aortic (n=326) and left ventricular tissues (n=326), respectively. Targeting 4 candidate genes ( WNT4 , LEF1 , STRN , and KANK2 ) in zebrafish led to disruption in cardiac development. A polygenic risk score was associated with an odds ratio of 2.07 (95% CI, 1.90–2.25; P =5.43×10 -62 ) per SD for BAV and significantly associated with thoracic aortic aneurysm and atrial fibrillation in UK Biobank. CONCLUSIONS: This study supports a significant polygenic contribution to BAV, where the combination of multiple common variants in genes involved in heart morphogenesis disrupts aortic valve development.

Abstract Isolated/idiopathic rapid-eye-movement (REM)-Sleep Behavior Disorder (iRBD) is characterized by dream enactment behaviors associated with loss of REM atonia. iRBD is in most cases a prodromal synucleinopathy, and emerging evidence suggests associations between RBD and other neurological and psychiatric conditions. In this study, we performed pathway-based polygenic risk score (PRS) and rare variant burden analyses to examine these potential associations. Pathway-specific PRS were constructed from genome-wide association study summary statistics of five neurodegenerative and seven psychiatric traits across 10 biologically relevant pathway categories, including a total of 279 pathways, in 1,573 iRBD cases and 16,022 controls from the International RBD Study Group and UK Biobank. Rare variant burden tests were performed in 1,264 iRBD cases and 2,581 controls. We identified multiple potential pathways indicating shared polygenic risk between RBD and both neurodegenerative and psychiatric disorders. Lewy body diseases and post-traumatic stress disorder had the most shared polygenic risk pathways in neurological and psychiatric disorders, respectively. Two pathways, the serotonin transport pathway and the chaperone-mediated autophagy pathway, showed the strongest association with iRBD, and gene-based rare variants analyses revealed five genes associated with iRBD: GBA1 , PLEKHM1 , LRP2 , P2RX1 , and HAP1. Subsequent analysis of these genes in Parkinson’s disease and dementia with Lewy bodies replicated several associations. Together, these findings provide novel insights into the shared genetic architecture underlying iRBD, neurodegenerative disorders, and psychiatric traits, with implications for early identification and mechanistic understanding.

Abstract Background Mitral regurgitation (MR) and tricuspid regurgitation (TR) are prevalent valvular heart diseases associated with significant morbidity and mortality. Traditional echocardiography faces limitations in availability, cost, consistency, and reliability, leading to misdiagnosis and undertreatment. The application of artificial intelligence (AI) to echocardiographic scans has the potential to address these challenges. Methods This study evaluates the performance of an AI algorithm on an external population. The algorithm utilizes deep learning networks to analyze echocardiographic exams for diagnosing atrioventricular valve disorders. We tested the algorithm on transthoracic echocardiography data collected from a single center between 2013 and 2023. The model's performance was compared to ground truth values using two classification schemes: distinguishing between normal-mild and moderate-severe regurgitation, and categorizing results into four groups: normal, mild, moderate, and severe. Results The MR cohort included 280 patients, while the TR cohort comprised 298 patients. The model demonstrated a robust ability to identify clinically significant (moderate and above) atrioventricular valve regurgitation. The MR model achieved an area under the curve (AUC) of 0.98 (95% CI: 0.97–0.99), with 91% accuracy, 95% sensitivity, and 89% specificity. In comparison, the TR model exhibited an AUC of 0.96 (95% CI: 0.94–0.98), with 84% accuracy, 91% sensitivity, and 80% specificity. Conclusion The model demonstrated high diagnostic accuracy and reliability in assessing atrioventricular valve regurgitation severity, highlighting its potential as a valuable clinical tool. The findings underscore the role of AI in complementing expert evaluations and improving access to effective diagnostics, with future applications potentially including point-of-care diagnosis and monitoring of disease progression.

Abstract When using real-world data to construct an external comparator arm for a single-arm trial, there may be differences in how and when patients are assessed for disease between trial and real-world settings. Such differences can generate outcome measurement error when comparing time-to-event endpoints and lead to biased findings. Recent methods have been developed to mitigate measurement error bias in real-world endpoints; however, they rely on the existence of a validation sample, ie, data on a set of patients where both the “true” trial-like and “mis-measured” real-world measures are collected. We demonstrate how novel statistical methods can be leveraged as quantitative bias analyses (QBA) to contextualize real-world evidence findings when outcome measurement error is of concern, but validation samples are infeasible to collect. Quantitative bias analyses allow researchers to set plausible ranges for the amount of error when not directly measurable. We highlight how to conduct QBA with two recent methods, cumulative incidence curve correction and survival regression calibration, and illustrate how to generate plausible parameter values through simulation. We provide an illustrative QBA example in a cohort of real-world patients with newly diagnosed multiple myeloma and provide practical guidance to apply QBA for outcome measurement error and interpret results.

Abstract Isolated/idiopathic rapid eye movement sleep behavior disorder (iRBD) is a usually prodromal manifestation of neurodegenerative disorders with α-synuclein pathology: Parkinson’s disease (PD), dementia with Lewy bodies (DLB), and multiple system atrophy (MSA). Clinical trials in the iRBD population face substantial barriers: limited access to well-characterized cohorts, inconsistent assessment protocols across centers, and the absence of validated biomarkers of disease burden. The North American Prodromal Synucleinopathy (NAPS) Consortium was established to address these challenges and facilitate clinical trials for neuroprotective therapies targeting synucleinopathy at the earliest known stages. In this multi-site, longitudinal, observational study, nine academic centers across North America will enroll and follow over 500 individuals with iRBD from existing sleep centers. Sixty control participants, matched for age, sex, and race will also be recruited. A harmonized protocol—including a standardized clinical battery assessing motor, cognitive, autonomic, psychiatric, sensory, and sleep function; structured diagnostic adjudication; biospecimen collection; and centralized analysis of both polysomnography and neuroimaging data—is outlined herein and reflects NAPS Stage 2. Each participants completes these assessments annually, and are replaced in the event of phenoconversion. By unifying assessments and expanding geographic reach, NAPS lays the groundwork for efficient, well-powered clinical trials designed to delay or prevent progression of iRBD to overt PD, DLB, or MSA—ultimately enabling earlier, more effective therapeutic intervention for neurodegenerative disease. Registered at clinicaltrials.gov (NCT05826457).

Abstract Background Isolated REM sleep behavior disorder (iRBD) is a parasomnia that reflects an evolving α‐synucleinopathy disorder, providing an opportunity to study early pathological changes. While diffusion tensor imaging (DTI) studies have shown white matter changes in iRBD, Neurite Orientation Dispersion and Density Imaging (NODDI) may offer better biological specificity in characterizing microstructural alterations through measures of Neurite Density Index (NDI), Orientation Dispersion Index (ODI), and Free Water Fraction (FWF). Method We included 77 participants with polysomnography‐confirmed iRBD from the North American Prodromal Synucleinopathy (NAPS) Consortium and 154 age‐ and sex‐matched cognitively unimpaired controls from the Mayo Clinic Study of Aging. White matter microstructure was evaluated using standardized multi‐shell diffusion on 3T MRI, quantifying DTI metrics (fractional anisotropy, FA; and mean diffusivity, MD) and NODDI parameters across bilateral white matter tracts defined by the JHU “Eve” WM atlas. Group differences were assessed using conditional logistic regression, with correlations to motor performance evaluated using the Purdue Pegboard and Alternating Finger Tapping tests. Result Compared to controls, iRBD participants demonstrated widespread and bidirectional white matter changes across major white matter pathways (see Figure 1 for glass brain visualizations). While predominantly showing decreases, FA exhibited some increases, particularly in the corticospinal tract. MD showed a largely opposite pattern with predominantly increased values across tracts. NODDI metrics revealed complex bidirectional patterns: ODI was broadly increased across multiple tracts with focal decreases, while NDI showed a pattern of predominantly decreased values alongside localized increases. FWF demonstrated a mixed pattern with predominant decreases across most tracts. In addition, both DTI and NODDI metrics showed extensive, moderate correlations with the Purdue Pegboard Test and Alternating Finger Tapping performance ( T = 2.0, p < 0.05, Figure 2). Conclusion Our study highlighted widespread and complex bidirectional white matter microstructural alterations in individuals with iRBD, demonstrating significant correlations with dexterity and motor performance even during the prodromal stage. These results suggest that extensive white matter abnormalities occur early in prodromal α‐synucleinopathies and highlight the value of advanced diffusion imaging techniques in characterizing iRBD and its potential prediction of phenoconversion to overt neurodegenerative disorders.

Abstract Two recent studies suggested that the APOE ε4 haplotype was associated with increased α-synuclein pathology in cell and mouse models. Genetic variants in the SNCA region have strong association with Parkinson’s disease (PD), dementia with Lewy bodies (DLB) and idiopathic REM sleep behaviour disorder (iRBD), while APOE is a genetic risk determinant for only DLB. To determine if genetic-level interactions between SNCA and APOE exists that can explain the protein-level association, we investigated the genotypic interaction of APOE and SNCA in cohorts of PD, DLB and iRBD. We analysed genome-wide association study (GWAS) data from 5229 PD patients and 5480 controls, 2610 DLB patients and 1920 controls, and 1055 iRBD patients and 3667 controls. We used logistic regression interaction models across all three cohorts independently between the (i) top GWAS signals of SNCA single nucleotide polymorphisms (SNPs) and APOE haplotypes and (ii) SNP×SNP and three-way SNP interaction across the entire coding region plus 200 kb flanking each gene. No significant interactions were found to be associated with any of the synucleinopathies after correction for multiple testing. Our results do not support a role for genetic interactions between APOE and SNCA across PD, DLB and iRBD. Since the tested genetic variants affect the expression and function of these proteins, it is likely that any interactions between them do not affect the risk of PD, DLB and iRBD.