Citations

Introduction: Co-stimulatory proteins are master regulators of the immune system. We identified the co-stimulatory CD40-CD40L dyad as a key driver of inflammation during atherosclerosis and have shown that CD40 and CD40L exert cell-type divergent functions. Hypothesis: CD40 is abundantly expressed on endothelial cells (EC) undergoing endothelial mesenchymal transition (EndMT). We hypothesize that EC CD40 drives atherosclerosis via EndMT. Methods: We analyzed scRNAseq data from human carotid plaques, performed multiplex IHC, and used human aortic endothelial cells (HAECs) for in vitro studies. A tamoxifen-inducible EC specific CD40 deficient atherosclerotic mouse model (cadherin5 (cdh5)ERT2-CD40 flfl -ApoE -/- ) was generated. Results: Besides its presence on immune cells, CD40 is expressed on endothelial cells in both human and mouse atherosclerotic plaques. Analysis of scRNAseq data of human carotid atherosclerotic plaques showed that CD40 is highly expressed in COL1A2/FN1 expressing endothelial cells (ECs), a subset undergoing EndMT. Multiplex staining revealed that CD40 colocalized with the EndMT markers αSMA, NOTCH3, TWIST and VCAM1 in human plaques. In vitro , stimulation of human arterial endothelial cells (HAECs) with CD40L resulted in an increase in the EndMT markers markers fibronectin, vimentin, sm22α, FSP1 and snail. Using phosphoproteomics, CD40L was found to decrease phosphorylation of the junctional integrity proteins CTNNA1 [S652; S655] and ARHGAP21 [S1383]. To investigate the endothelial-specific effects of CD40 in atherosclerosis, 8-week-old cdh5ERT2-CD40 flfl -ApoE -/- mice and their CD40 flfl -ApoE -/- littermate controls were treated with tamoxifen and fed a high cholesterol diet for 10 wks. Deletion of EC-CD40 resulted in a significant reduction in plaque size. This reduction was accompanied by a shift from fibrous cap atheromas (FCA) towards intimal xanthoma (IX) and pathological intimal thickening (PIT). Flow cytometry analysis of the spleen showed that CD40 deletion in ECs results in a significant decrease in CD8 and CD4 effector T cells. This decrease in CD8 and CD4 effector T cells was accompanied by a diminished activation status, shown by a decrease in CD69 + CD8 + CD62 - CD44 + T cells, CD40L + CD8 + CD62 - CD44 + T cells and CD40L + CD4 + CD62 - CD44 + T cells. These findings demonstrate that endothelial CD40 drives atherosclerosis by inducing EndMT-driven plaque inflammation.

Background Coronary flow reserve reflects microvascular function, whereas filling pressure indicates myocardial hemodynamic burden. In angina with nonobstructive coronary arteries, abnormalities in either could contribute to a supply–demand mismatch; however, their combined prognostic significance remains unclear. Methods Patients with angina with nonobstructive coronary arteries who underwent invasive coronary reactivity tests were studied retrospectively. Coronary microvascular dysfunction (CMD) was coronary flow reserve <2.5. An artificial intelligence–enabled ECG marker of elevated filling pressure (AIEFP) was applied as a scalable prognostic marker of myocardial hemodynamic stress. Associations with major adverse cardiovascular events were evaluated using Cox regression and propensity score overlap weighting. Results Among 1957 patients with angina with nonobstructive coronary arteries (median age, 51.8 years; 67.2% women), CMD+ was identified in 26.4% and AIEFP+ in 6.6%. Over 8 years, 204 patients (10.4%) experienced major adverse cardiovascular events. In nested models, both CMD (hazard ratio [HR]=1.42 [95% CI=1.13–1.78]; P =0.002) and AIEFP (HR=2.28 [95% CI=1.67–3.11]; P <0.001) remained associated with major adverse cardiovascular events after adjustment. Adding AIEFP to the base model improved model fitness (Δχ 2 =23.65, P <0.001; ΔAkaike Information Criterion=−21.7) and modestly improved discrimination (ΔHarrell concordance index=0.02, P =0.02). In a 4‐group model, adjusted risks increased in a graded manner. Overlap‐weighted analysis after covariate balance demonstrated distinct temporal risk trajectories: CMD+/AIEFP+ had the highest 1‐year risk (12.7%), and AIEFP+ had the highest cumulative 8‐year risk (57% in CMD− and 51.8% in CMD+). Conclusions CMD and AIEFP provide complementary prognostic information, with AIEFP remaining significantly associated with outcomes after multivariable adjustment. A dual‐axis framework integrating myocardial hemodynamic stress (AIEFP) and microvascular function (coronary flow reserve) may enhance risk stratification and enable identification of clinically distinct angina with nonobstructive coronary arteries phenotypes with divergent trajectories.

Background Carotid artery calcification represents a common feature of atherosclerotic plaques. However, the geometric relationships of calcific clusters have not been systematically investigated. This study aimed to develop a geometry-based atlas, independent of symptom status, characterizing the three-dimensional properties of calcium clusters within carotid plaques and quantifying population-level distributions and data-driven couplings between size, shape, and density. Methods Standardized three-dimensional calcium masks of clinical CT scans were analyzed using connected-component labeling. Extracted features included cluster volume, aspect ratio, eccentricity, compactness, and CT attenuation values (mean μ, standard deviation σ). Associations between cluster features were assessed using Spearman correlations with Benjamini–Hochberg false discovery rate correction. Independent associations were determined using partial Spearman correlation and restricted cubic spline regression. Results Among 107 plaques, 149 distinct clusters were identified, most frequently presenting as a single elongated cluster (aspect ratio = 2.23). Independent associations (all p < 0.001) were identified for: eccentricity with μ (ρ = −0.39), volume with μ (ρ = 0.47), compactness with μ (ρ = 0.39), and volume with eccentricity (ρ = 0.82). Multi-cluster plaques exhibited smaller mean cluster volume (76.1 vs 359.5 mm 3 ; p < 0.001) and lower eccentricity (0.5 vs 1.6; p < 0.001) compared with single-cluster plaques. Conclusion Carotid calcification most frequently manifests as a single elongated cluster, with robust couplings between cluster size, shape, and density. These geometric archetypes provide a quantifiable framework for future biomechanical and biological studies of plaque vulnerability.

Abstract The detection of genetic abnormalities is required during diagnostic workup and for potential individualization of therapy selection in multiple myeloma (MM) and its precursor conditions. At present, this relies on invasive bone marrow (BM) biopsies, severely limiting early detection, frequent longitudinal monitoring, and the precise selection of therapy. The current standard for detecting genetic alterations in MM is fluorescence in situ hybridization (FISH), which cannot detect point mutations and other clinically relevant alterations. Consequently, the IMS-IMWG guidelines were recently updated to require next-generation sequencing for the classification of high-risk MM. To address these needs, we recently launched GenoPredicta, a CLIA-approved LDT that enables routine monitoring, informing diagnosis, and treatment selection by comprehensively characterizing MM genomes with whole genome sequencing (WGS) from as few as 50 circulating tumor cells (CTCs) isolated from peripheral blood (PB) or tumor cells from BM. Briefly, tumor cells are isolated from samples using fluorescence-activated cell sorting and subjected to WGS, from which copy number alterations, structural variants, and short variants (SNVs/indels) are identified using a fully automated pipeline generating physician-ready clinical reports from raw sequencing data in ∼6h. Analytical validation of GenoPredicta showed complete concordance with FISH results. Identifying alterations in therapeutic targets (e.g., BCMA, GPRC5D) for guiding MM immunotherapies is becoming increasingly important. Here, we describe GenoPredicta results from relapsed/refractory MM patients, highlighting resistance-conferring alterations that can only be detected by WGS, such as deletions in the kilo- to megabase scales that are observed in conjunction with SNVs and indels, leading to biallelic loss/inactivation of the gene, including at subclonal levels. In addition to biallelic loss of BCMA and GPRC5D in response to CAR T or T cell engager therapies, we observed similar resistance mechanisms for targets of immunomodulatory drugs, e.g., CRBN. The observation of these resistance mechanisms was consistent with patients’ clinical histories. In summary, we demonstrate that low input WGS-based characterization of MM from BM or CTCs is a viable replacement for FISH for clinical diagnosis and monitoring, with CTC-based measurements enabling comprehensive profiling of the MM genome. Crucially, this includes genetic alterations that confer resistance to therapy, allowing for both early detection of such alterations and more precise selection and guidance of therapy. The dramatically improved variant calling ability from WGS, especially in low-input CTC applications, extends to other malignancies and will gain wider adoption as sequencing costs continue to decrease. Citation Format: Bruno Paiva, Peter Voorhees, Patricia T. Greipp, Danielle Sookiasian, Julian Hess, Marisa DeMeo, Vicki Pounder, Sarah Calkins, Reid Meyer, Linda B. Baughn, Christine-Ivy Liacos, Meletios-Athanasios Dimopoulos, Alexandra Papadimou, Taouxi Konstantina, Efstathios Kastritis, Jesus Berdeja, Daniel Auclair, Valentina Nardi, Thomas Mullen, Francois Aguet, Shaji Kunnathu Kumar. Whole genome sequencing of multiple myeloma genomes with a novel clinical assay enables identification of genetic alterations underlying immunotherapy resistance [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 1067.

Abstract Introduction Detecting genetic abnormalities is mandatory during diagnostic workup and for potential individualization of therapy selection in multiple myeloma (MM) and its precursor conditions. At present, this requires invasive bone marrow (BM) biopsies, severely limiting early detection, patient monitoring, and the precise selection of therapy. The current standard for detecting genetic alterations in MM is fluorescence in situ hybridization (FISH), which cannot detect point mutations and other clinically relevant alterations. Consequently, the IMS-IMWG guidelines were recently updated to require next-generation sequencing for the classification of high-risk MM. Moreover, the importance of identifying alterations in therapeutic targets (e.g., BCMA, GPRC5D) for guiding immunotherapies is becoming increasingly recognized. To address this need, we recently launched GenoPredicta, a CLIA-approved Laboratory Developed Test that enables routine monitoring, informing diagnosis, and treatment selection by comprehensively and robustly characterizing MM genomes with whole genome sequencing (WGS) from a minimum of ~50 circulating tumor cells (CTCs) isolated from peripheral blood (PB) or tumor cells from BM. Here, we describe the characterization of clinical and research samples with GenoPredicta, highlighting resistance-conferring genetic alterations that can only be detected by sequencing and that are consistent with patients' clinical histories, while further demonstrating the complete concordance of GenoPredicta with prior FISH results. Methods Tumor cells were isolated from BM and/or PB samples using fluorescence-activated cell sorting (FACS) (after CD138+ enrichment for PB) and subjected to whole genome sequencing (WGS), from which we identified copy number alterations, structural variants, and single nucleotide variants and indels. For a subset of samples, the BM was also characterized by FISH, using a standard clinical panel for characterizing MM; for other samples prior FISH results were available from patients' clinical records. Results The analytical validation of GenoPredicta, conducted on a retrospective cohort of &gt;60 viably frozen samples from &gt;30 patients, showed complete concordance between BM and PB for detected genomic abnormalities, with all clinically relevant events (11 translocations and 125 CNVs) observed in BM recapitulated in PB (100% recall). All events identified by FISH in 14 samples (8 translocations and 30 CNVs) were also identified in the BM (100% recall), with 50 translocations and 30 CNVs not detected by FISH also absent in the WGS data (100% precision). The abnormalities detected in these samples also included multiple high-risk events not assayed by FISH, including biallelic TP53 loss (Del 17p coupled with a deleterious TP53 mutation, observed in 4 patients) and MYC::IGL translocations (2 patients). Moreover, for all fresh peripheral blood clinical samples with FISH results available from patients' histories, GenoPredicta recalled 100% of reported events. Among these clinical samples, we notably observed a case with both a biallelic GPRC5D deletion and a TNFRSF17 (BCMA) deletion combined with a truncating mutation on the remaining allele. This was consistent with the patient's clinical history showing progression after therapy with talquetamab (anti-GPRC5D bispecific), and previous nonresponse to teclistamab (anti-BCMA bispecific) after prior therapy with Cilta-cel (BCMA-directed CAR T). GenoPredicta also detected other mutations likely to confer resistance to immunotherapies, including loss-of-function mutations in IKZF3 and deletions of FCRL5 in frozen peripheral blood research samples. Conclusion We demonstrate that WGS-based characterization of MM from BM or CTCs is a viable replacement for FISH for clinical diagnosis and monitoring, with blood-based measurements enabling comprehensive profiling of the myeloma cancer genome. Importantly, this includes genetic alterations that confer resistance to therapy, allowing for both early detection of such alterations and more precise selection of therapy.

Background α‐Klotho is a multifunctional protein implicated in vascular aging. Declining Klotho levels are associated with arterial stiffness, endothelial dysfunction, and vascular calcification. We investigated the associations between circulating klotho, aortoiliac calcification, endothelial progenitor cells, and 10‐year survival. Methods In this retrospective cohort, blinded clinicians scored calcification on computed tomography (0–10 scale: aorta 6 points, iliac 4 points). Plasma klotho was measured by ELISA; endothelial progenitor cell subsets were quantified via flow cytometry. Mortality data were obtained from the Minnesota Death Registry. Results This study included 148 participants (mean age 72.4±9.6 years; 41% female). Median calcification score was 3 (interquartile range, 1–5). Patients with low calcification had higher Klotho levels (669 [567–841] versus 556 [457–678] pg/mL; P <0.01), with Klotho inversely correlated with calcification (r=−0.315, P <0.01). Stratified by calcification location and severity, the highest Klotho levels were seen in patients without aortic or iliac calcification ( P =0.015). Over 10 years, low Klotho was independently associated with higher mortality (hazard ratio [HR], 3.056 [95% CI 1.288–7.878]; P =0.014). Klotho inversely correlated with mature osteocalcin‐positive EPCs; B=−0.16 (95% CI, −0.29 to −0.02; P =0.027). Immunohistochemistry and immunofluorescence confirmed endothelial Klotho expression in internal mammary artery. Conclusions Lower circulating Klotho levels are associated with increased aortoiliac calcification and higher 10‐year mortality, supporting a role for Klotho in vascular aging.

Introduction: Carotid artery intraplaque hemorrhage (IPH) is increasingly recognized as a predictive marker of cerebrovascular events. Despite widespread utilization of contrast-enhanced CT angiography (CTA) for the evaluation of carotid atherosclerosis, diagnosis of IPH on CTA is challenging, limiting risk stratification capabilities. We evaluated convolutional neural networks (CNN) for detection of histology-proven IPH in carotid CTA. Methods: The study included carotid endarterectomy patients from our center who had preoperative CTA and available plaque specimens from the Mayo Clinic Carotid Artery Atherosclerosis Trial (MCAT) Biobank. A validated segmentation model localized common and internal carotid arteries (CCA/ICA). CCA bifurcation served as landmark after a large language model, Llama3.0-70B, verified culprit plaque proximity to the bifurcation from CTA reports. A 3×3×4cm box around ipsilateral CCA bifurcation was sampled from CTA volumes and images were labeled IPH by histology study of carotid specimen (Fig 1). Given limited cases with concurrent imaging and histology, we employed a robust cross-validation strategy: 22 cases (20%) held-out for testing, with remaining data 86 cases used for 5-fold cross-validation (stratified by IPH presence). The five resulting models independently generated IPH probability scores, and ensembled predictions calculated by three methods to enhance generalizability: Majority and weighted voting based on binary IPH class and soft voting based on IPH probability scores. Results: Of 418 patients with histological analysis, 130 had CTA studies available. After excluding 22 cases lacking histological consensus, 108 cases were analyzed. In the 22 test cases the mean age was 68.1±8.5 years and 59% were male; In the cross-validation folds age ranged from 67.1±6.9 to 75.3±7.6 years 56-82% were male. Individual models' performance on the test set showed mean ROC-AUC of 0.79 (95% CI: ±0.05) and average precision of 0.85 (±0.05) (Fig 2). The ensemble approach achieved superior performance with soft voting demonstrated 82% ROC-AUC, 77% accuracy, 79% precision, 85% sensitivity, and 82% F1-score for IPH detection, outperforming majority voting and weighted voting (Fig 3). Conclusion: Automated IPH detection in widely available CTA imaging can turn it to a powerful stroke risk assessment tool, supporting personalized prevention strategies and surgical decision-making, ultimately reducing cerebrovascular morbidity and mortality.

Introduction: Atherosclerosis, the underlying cause of cardiovascular disease (CVD), is a lipid-driven chronic inflammatory disease. We have identified the co-stimulatory CD40-CD40L immune checkpoint dyad as a key driver of inflammation during atherosclerosis. CD40 and CD40L exert cell-type divergent functions via different signaling pathways. Hypothesis: We hypothesize that CD40 on endothelial cell (ECs) induces endothelial-to-mesenchymal transition (EndMT)-mediated vascular inflammation in atherosclerosis. Methods & Results: Using single cell RNAseq, we found that CD40 (TNFRSF5) is expressed on PDE3A + GJA5 + and KDR + COL15A1 + ECs of advanced human carotid atherosclerotic plaques. CD40 is highly expressed in the endothelial lining of human and mouse atherosclerotic plaques, and colocalizes with the EndMT markers fibronectin and collagen and adhesion molecule ICAM-1. CD40L activation of human aortic endothelial cells (HAECs) results in expression of the EndMT markers fibronectin, vimentin, sm22α, FSP1 and snail. Activation of CD40 in EC induces filamin A dependent translocation of CD40 into lipid rafts, increases TNF-receptor associated factor (TRAFs) -2, -3 and 6 levels, induces Akt signaling and increases expression of VCAM1 and CCL2. Conclusions: The endothelial cell has been more and more regarded as a cell type that plays a major role in driving inflammation. Our data suggest that the CD40-CD40L axis plays a significant role in EC-mediated inflammation in atherosclerosis by driving EndMT.

The NCCN Clinical Practice Guidelines in Oncology (NCCN Guidelines) for Pediatric Acute Lymphoblastic Leukemia (ALL) were developed as a result of meetings convened by a multidisciplinary panel of pediatric ALL experts, with the goal of providing recommendations on standard treatment approaches based on current evidence. The NCCN Guidelines for pediatric ALL focus on risk assessment and stratification of risk-adapted therapy; treatment strategies for BCR::ABL1 (Philadelphia chromosome [Ph])-negative and BCR::ABL1-positive B-cell lineage, T-cell lineage, and infant ALL; and supportive care considerations. This selection from the NCCN Guidelines for pediatric ALL focuses on the diagnosis of and management of pediatric T-ALL.

Background: Previous studies have linked pericoronary artery adipose tissue attenuation to major adverse cardiac event (MACE). However, the association between pericarotid artery fat and prognosis remains underexplored. This study aimed to investigate the association between preoperative pericarotid fat characteristics and the subsequent prognosis in patients undergoing carotid endarterectomy (CEA). Methods: This study included patients with preoperative computed tomography angiography (CTA) followed by CEA. Preoperative neck CTA images were obtained and analyzed with novel methods using 3D Slicer software. We segmented the common and internal carotid arteries. The segment was horizontally trimmed, isolating the region around the bifurcation, extending 15 mm above and 10 mm below. Pericarotid fat was defined as adipose tissue within a 5 mm radial distance from the outer vessel wall, with Hounsfield units (HU) between -190 and -30 (Figure 1, carotid segmentation [green] and pericarotid fat [yellow]) . For each patient, we calculated the HU average and the volume (mm3) of the pericarotid fat. MACE was defined as a composite of all-cause mortality, myocardial infarction, and cerebrovascular events. The relationship between both pericarotid fat characteristics and MACE was investigated. Results: Of the 43 patients initially included, one was excluded due to an inability to perform segmentation caused by chronic total occlusion, leaving 42 patients (age 73 [67-78] years, 33 [76.7%] male). The comparison of mean pericarotid fat HU between the ipsilateral and contralateral sides showed no significant difference (-60.3±11.0 HU vs. -60.9 ±11.3 HU, p=0.437). However, the median ipsilateral fat volume was significantly higher than the contralateral volume (528 [248, 1100] mm3 vs. 328 [184, 697] mm3, p=0.020). When comparing patients with and without MACE, those with MACE had a significantly lower ipsilateral fat density (-59.4±10.2 HU vs. -66.8 ±11.1 HU, p=0.022) and a higher fat volume (468 [233, 746] mm3 vs. 845 [458, 1451] mm3, p=0.044). Kaplan-Meier analysis revealed that higher volume and lower fat density than the median were significant predictors of MACE (log-rank p=0.015 and p=0.042, respectively) (Figure 2). Conclusions: Assessment of pericarotid fat using a novel CTA analytic method in patients undergoing CEA identified ipsilateral lower fat density and higher fat volume as predictors of adverse outcomes.