Citations

The bone marrow immune microenvironment (BMME) is a critical factor in multiple myeloma (MM) pathogenesis. Despite higher incidence of MM among self-identified African Americans, the relationship between African genetic similarity and the BMME remains unclear. We present the largest analysis to date assessing the impact of Ancestry on the BMME in myeloma (N=320, including 64 with ≥50% African genetic similarity, AFR-High) leveraging our recently generated Immune Atlas. AFR-High was associated with enrichment of late T-effector cells, driven by rare cytotoxic CD4⁺ T cells, suggesting a distinct adaptive BMME. AFR-High exhibited expansion of late-differentiated adaptive NK cells with high cytotoxic GNLY and GZMH expression. AFR-High depicted reduced CD14⁺ monocytes, increased CD16⁺ non-classical monocytes, and expansion of macrophage-like monocyte populations with enrichment of metabolic adaptation, efferocytosis and phagocytic clearance programs, and immunoregulatory pathways. These findings reveal a shift from an innate inflammatory immune landscape toward adaptive cytotoxic and immunoregulatory remodeling associated with African genetic similarity in MM.

Abstract Studies have reported conflicting findings regarding the contribution of germline variants or somatic genomic drivers to racial disparities in multiple myeloma. To comprehensively investigate somatic drivers in relation to inherited genetics in multiple myeloma, we combined newly sequenced whole-genome sequencing data with publicly available datasets (total n = 1,286). Overall, we did not identify germline or somatic genomic differences that explain the different risk of developing multiple myeloma between patients with genetic similarity to African (AFR) or European (EUR) reference populations. A difference in the detectability and timing of APOBEC-associated and germinal center mutational activity was observed. Integrating epidemiologic data and mutational signature-based temporal estimates, we challenge the assumption that individuals in the AFR group develop multiple myeloma at a younger age. Finally, we demonstrate that, with equal access to efficacious therapies, patients in the AFR and EUR groups have equivalent clinical outcomes. Significance: Multiple myeloma is reported to occur at higher rates in individuals who self-identify as non-Hispanic Black. In this large dataset, genomic drivers occur at the same rate among ancestry groups, except for APOBEC mutagenesis. With equivalent therapy, clinical outcomes did not differ for patients grouped by genetic ancestry similarity.

8021 Background: Lung cancer is the leading cause of cancer-related mortality worldwide, primarily due to delayed diagnosis and diagnostic variability in histopathological assessment. Advances in deep learning applied to medical imaging offer the potential to enhance early detection accuracy, reduce interobserver variability, and improve diagnostic efficiency in lung cancer. Methods: In this retrospective study, we evaluated DAVINCI using a dataset of 8,962 patients with confirmed lung malignancies. The model utilizes a specialized architecture combining convolutional neural networks (CNNs) and residual blocks to optimize feature extraction from high-resolution pathological slides. Performance was measured via detection accuracy, recall, specificity, and Area Under the Curve (AUC). Results: A total of 8,962 patients were included in the analysis. The DAVINCI model correctly identified lung cancer in 93% of cases, corresponding to 8,334 of 8,962 patients, with a 95% confidence interval (CI) of 86%–100% (7,707–8,962 patients). Model specificity was also 93% (95% CI, 86%–100%), indicating a high true-negative rate. Sensitivity (recall) was 87%, with correct detection in 7,797 patients and a 95% CI of 80%–94% (7,170–8,425 patients). The model demonstrated strong discriminatory performance, achieving an area under the curve (AUC) of 0.91 (95% CI, 0.84–0.98). In comparison, active pathologists achieved a mean diagnostic accuracy of 83%, corresponding to 7,438 of 8,962 cases, with a 95% CI of 76%–90% (6,811–8,066 cases). In terms of efficiency, DAVINCI processed whole-slide images in 16–19 seconds, substantially faster than conventional manual review, which typically requires several minutes per slide. Conclusions: DAVINCI demonstrated superior accuracy, robust discriminatory performance, and markedly faster processing compared with human review, supporting its potential role in early lung cancer detection at scale.

Abstract Intercellular communication between multiple myeloma (MM) cells and osteoclast precursor cells (pre-OCs) contributes extensively to the occurrence and development of myeloma-related bone destruction. However, key interacting modes and the exchanged substances involved in this communication remain unclear. In this study, we discover that tunneling nanotubes (TNTs) directly connect MM and pre-OCs. Using the stable isotope labeling with amino acids in cell culture assay and a positive-negative double selection strategy, we identify filamin A (FLNA) as a major protein transported from MM to pre-OCs. FLNA acts as a molecular clutch linking extracellular matrix–bound MAC1 to the cytoskeleton, activating Rho and MAPK signaling pathways and promoting F-actin polymerization, which subsequently enhances osteoclast differentiation by modulating cellular stiffness, traction force, and deformability. In addition, FLNA directly binds vinculin and promotes its recruitment to podosomes, thereby enhancing the functions of podosomes and the bone resorption capacity of osteoclasts. The conditional depletion of Flna in mice suppresses podosome activity and reduces stiffness, traction force, and deformability in pre-OCs, leading to significantly impaired osteoclast differentiation and increased bone mass. In the Vk∗MYC mouse model of myeloma, the administration of the TNT inhibitor latrunculin B disrupts FLNA transport to osteoclasts and alleviates osteolytic bone disease. These findings highlight the critical role of MM-transferred FLNA in osteoclastogenesis and suggest that targeting TNTs may represent a therapeutic strategy to limit pathological bone resorption associated with MM.

Abstract Multiple myeloma (MM) with t(11;14)(CCND1;IGH) remains the only subset sensitive to the BCL2 inhibitor venetoclax. However, not all patients with t(11;14)(CCND1;IGH) respond to treatment, and some progress early after initial response. To investigate this, we examined 44 whole-genome and whole-exome sequencing data samples from 34 patients with t(11;14) MM treated with venetoclax. The presence of mutations in the RAS pathway was strongly associated with shortened progression-free survival (PFS) and was validated in an independent cohort of 21 patients with MM. The presence of 1q gain was also associated with shorter PFS in patients without RAS mutations. In 10 patients with paired prevenetoclax and postvenetoclax treatment samples, postvenetoclax progression was recurrently driven by the selection of genomic events in the BCL2/MCL1 and RAS pathways and of high-risk features (eg, loss of TP53 and CDKN2C). Overall, our study shows that comprehensive genomic profiling can identify most mechanisms underlying resistance to BCL2 inhibition in t(11;14)(CCND1;IGH) MM.

Abstract Background: Sickle cell disease (SCD) is marked by wide variability in clinical phenotypes and severity due to environmental, clinical, and genetic factors. Variants in iron-regulatory genes are well described modifiers of clinical presentation in different diseases, but their role in modulating SCD phenotype has been sparsely studied in African populations. In this cross-sectional study, we investigated the role of single nucleotide polymorphisms (SNPs) in iron-regulatory genes in SCD severity and lifetime transfusion(Tx) requirement. Methods: The study was approved by the institutional review board of Lagos University Teaching Hospital, Lagos, Nigeria. Clinical data were abstracted from medical records and patient interviews using a structured questionnaire. Participants were recruited in steady state and were stratified according to the severity score previously described by Shah et al. (Clinicoecon Outcomes Res. 2020;12:625). Biochemical analyses included serum transferrin and serum iron; transferrin saturation (TS) was calculated. Genotyping was performed using the Axiom Precision Medicine Research Array (PMRA; Thermo Fisher Scientific). Seventy-one single nucleotide polymorphisms (SNPs) in genes implicated in iron metabolism were analyzed, including SLC40A1 (ferroportin), HFE (homeostatic iron regulator), HJV (hemojuvelin), HAMP (hepcidin), and TFR2 (transferrin receptor 2). SNPs whose variants were not represented in this cohort, including HFE C282Y and H63D, were excluded. Ensembl and NCBI databases were used to describe the wild-type (WT)/variant alleles and gene consequences. Univariate and multivariate logistic regression were used to analyze binary outcomes, and age-adjusted linear regression for Tx burden. Odds ratios (OR) and regression coefficients (β) were estimated using the WT as the reference. Multiple-testing correction was performed as necessary. Statistical analyses were conducted in R version 4.4.1, with p<0.05 considered significant. Results: We included 60 genotyped, confirmed HbSS patients; median age was 22 years (range: 18–43), 22 (37.3%) were female, 42 (70.0%) were classified as mild severity (Class I), 5 (8.0%) as Class II, and 13 (22.0%) as severe (Class III). Twenty-seven (45.0%) had never received a blood Tx, while 33 (55.0%) had received Tx, median of 2units (range: 1-10). On univariate analysis (UVA), five SNPs (rs10218795, rs10188230, rs114250626, rs4287798, and rs634349) were significantly associated with severe phenotype; three of these remained significant on multivariable analysis (MVA). Two were associated with higher odds of severe phenotype: rs10177654 (OR = 28.9, 95% CI: 3.0–100.0, p = 0.03) and rs10218795 (OR = 15.0, 95% CI: 2.4–327.0, p<0.01), while rs10188230 was associated with lower odds (OR = 0.03, 95% CI: 0.008–0.28, p<0.01). Results remained consistent after adjusting for age. For lifetime transfusion burden, both UVA and MVA identified two significant SNPs: rs4667289, associated with higher transfusion burden (β = 2.6, 95% CI: 0.04–5.2, p = 0.047) and rs11568344, associated with lower transfusion burden (β = –1.8, 95% CI: –3.5 to –0.36, p = 0.02). Genotype distributions for the five significant SNPs were as follows: rs10177654 (SLC40A1, transcription factor binding site), TT(WT) 12 (20.3%), TC 30 (50.8%), CC 17 (28.8%); rs10188230 (SLC40A1, intron variant), TT (WT) 32 (54.2%), TC 22 (37.3%), CC 5 (8.5%); rs10218795 (HJV, intron variant), CC (WT) 22 (37.3%), TC 29 (49.2%), TT 8 (13.6%); rs4667289 (SLC40A1 proximal intergenic), GG (WT) 46 (78.0%), AG 10 (16.9%), AA 3 (5.1%); rs11568344 (SLC40A1 splice region variant), GG (WT) 47 (79.7%), AG 9 (15.3%), AA 3 (5.1%). Compared with the homozygous WT, patients with rs10188230 had a lower median TS (21.65% vs. 43.3%, p = 0.04), while those with rs4667289 had a higher median TS (83% vs. 31%, p<0.01). When adjusted for age and lifetime Tx, rs4667289 remained significant (β = 47.8, 95% CI 3.6-82.8, p = 0.03). No other SNPs showed association with TS. Conclusion: We present novel genetic data on iron-regulatory variants in African patients with sickle cell disease, identifying SNPs in SLC40A1 and HJV associated with disease severity. Most of these are yet to be fully described in the literature, and their intronic locations suggest possible regulatory roles. We hope to further validate these findings in larger cohorts and through functional studies to clarify their impact on iron metabolism and clinical significance.

Abstract Cyclin D1, encoded by CCND1, is a cell cycle regulator, overexpressed in ~15% of multiple myeloma (MM) cases via CCND1::IGH super-enhancer juxtaposition through t(11;14). Cyclin D1 also plays a non-canonical role in transcriptional regulation, but in t(11;14) MM its function in gene regulation remains undefined. We investigated the global transcriptional and epigenomic consequences of CCND1overexpression in t(11;14) MM. To define a CCND1 signature, RNA-seq from two independent primary MM patient cohorts, CoMMpass and Mayo, was utilized to compare high CCND1 t(11;14) cases (≥300 transcripts-per-million [TPM], n=271) vs. low CCND1 hyperdiploid cases (<30 TPM, n=233). Two CCND1 knockout (KO) clones in t(11;14) MM U266B1 were also generated by CRISPR/Cas9, introducing a frameshift insertion (A) after chr11:69641478 (hg38) in exon 1. ATAC-seq and ChIP-seq (H3K4me3, H3K4me1, and H3K27ac) were performed in duplicates, and RNA-seq in triplicates in U266B1 wild-type (WT) and KO. Libraries were sequenced on Illumina NextSeq 2000 (2x51 bp for ChIP/ATAC, 2x150 bp for RNA-seq). Reads were mapped to hg38 by BWA (ChIP/ATAC) or STAR (RNA-seq), peaks called by MACS2 (FDR< 0.01), peak and gene raw counts estimated by featureCounts. Differential peaks (fold-change ≥1.5) and differentially expressed genes (fold-change ≥2) were identified by edgeR (FDR<0.05), including peaks detected in ≥2 samples and genes with TPM ≥0.1 in ≥1 sample. Interactions between promoters and distal regulatory regions were identified using publicly available chromatin interaction data in blood cell types. Pathway analysis was performed using Enrichr. Co-immunoprecipitation was performed in t(11;14) KMS12BM cells. Differential analysis comparing CCND1-high t(11;14) and CCND1-low MM cases in the two patient cohorts identified 21 upregulated and 21 downregulated genes associated with CCND1 expression which were also captured in the wild-typevs. CCND1 KO U266 cells. Enriched pathways (p<0.05) included Notch signaling, early/late estrogen response, epithelial-mesenchymal transition and reduced mitotic spindle and myogenesis. Dysregulated genes included those related to apoptosis, ubiquitin-proteosome, extracellular matrix, adhesion, and immune response, demonstrating a broader role for cyclin D1 in MM beyond cell cycle control. To explore the epigenomic basis of this transcriptional regulation, for each of the 42 differentially expressed genes we examined the changes of histone marks and chromatin accessibility in promoter and the interacting distal regulatory regions in the U266 KO model. Ten of the 21 genes upregulated in CCND1-high (downloaded in KO; e.g., argininosuccinate synthase 1 [ASS1], PMAIP1, MYEOV, CCR7, and DTX1) and 12 of the 21 genes downregulated in CCND1-high (upregulated in KO; e.g., UACA, RASAL2, PTPRZ1, PPT2, and IL23R) showed concordant changes in histone marks and/or chromatin accessibility, predominantly in distal regulatory regions, suggesting a chromatin-mediated mechanism of gene regulation by cyclin D1. The most prominent changes involved H3K27ac, a mark defining active enhancers. As H3K27ac is deposited by histone acetyltransferases CBP, we tested for the possible cyclin D1-CBP interaction. Co-IP confirmed this interaction, suggesting a role for this complex in chromatin remodeling and transcriptional control in t(11;14) MM. One gene notably upregulated in association with CCND1 is ASS1, which encodes a urea cycle enzyme responsible for endogenous arginine synthesis. Metabolomic studies demonstrated KO cells had elevated aspartate and citrulline and lowered arginine and ornithine compared to WT cells (p<0.01) demonstrating impaired urea cycle function. Further, KO cells displayed significantly reduced ASS1 protein expression, cell growth and S-phase entry compared to WT cells in arginine-replete conditions, with both WT and KO cell types further inhibited by arginine depletion (p<0.05). Together, a cyclin D1-associated gene signature was identified supporting its role in t(11;14) MM beyond the CDK4/6 mediated cell cycle control, including a role in metabolic plasticity and survival under arginine depleted conditions. These findings highlight cyclin D1 as a therapeutic vulnerability and open new avenues for personalized treatment strategies.

Increasing evidence strongly links neuroinflammation to Alzheimer’s disease (AD) pathogenesis. Peripheral monocytes are crucial components of the human immune system, but their contribution to AD pathogenesis is still largely understudied partially due to limited human models. Here, we introduce human cortical organoid microphysiological systems (hCO-MPSs) to study AD monocyte-mediated neuroinflammation. By culturing doughnut-shape organoids on 3D-printed devices within standard 96-well plates, we generate hCO-MPSs with reduced necrosis, minimized hypoxia, and improved viability. Using these models, we found that monocytes from AD patients exhibit increased infiltration ability, decreased amyloid-β clearance capacity, and stronger inflammatory response than monocytes from age-matched control donors. Moreover, we observed that AD monocytes induce pro-inflammatory effects such as elevated astrocyte activation and neuronal apoptosis. Furthermore, the marked increase in IL1B and CCL3 expression underscores their pivotal role in AD monocyte-mediated neuroinflammation. Our findings provide insight into understanding monocytes’ role in AD pathogenesis, and our lab-compatible MPS models may offer a promising way for studying various neuroinflammatory diseases.

Abstract Motivation Efforts to address health disparities are often limited by the lack of robust computational tools for inferring genetic ancestry by calculating an individual’s genetic similarity to continental groups. We have already shown that a preferred alternative to self-described race is using ancestry-informative markers (AIMs) that can be classified into ancestral components and used to estimate their similarity to those of known populations to identify continental groups. However, real-world genomic data can present challenges, including limited availability of germline DNA, a small number of AIMs for each sample, and the use of different variant calling software, limiting the application of existing solutions. Results Here, we describe a novel supervised machine-learning tool AncestryGeni, which infers genetic ancestry for samples with even a hundred markers and is applicable to any genomic data, including whole exome sequencing (WES) and RNA sequencing (RNA-Seq) data. Applying AncestryGeni to a real-world genomic dataset obtained from the Multiple Myeloma Research Foundation (MMRF) CoMMpass study, we show that it is more accurate than the commonly used FastNGSadmix when using nonstandard genomic material. We also demonstrate that when using AncestryGeni, the tumor-derived sequence obtained from WES and RNA-Seq can be a robust data source to accurately estimate an individual’s genetic similarity to a continental group. Availability and implementation AncestryGeni pipeline is available at https://github.com/eelhaik/AncestryGeni/tree/main.

Pediatric central nervous system tumors are the leading cause of cancer-related deaths in children. The five-year survival rate for high-grade glioma in children is less than 20%. The development of new treatments is dependent upon multi-institutional collaborative clinical trials requiring reproducible and accurate centralized response assessment. We present the results of the BraTS-PEDs 2023 challenge, the first Brain Tumor Segmentation (BraTS) challenge focused on pediatric brain tumors. This challenge utilized data acquired from multiple international consortia dedicated to pediatric neuro-oncology and clinical trials. BraTS-PEDs 2023 aimed to evaluate volumetric segmentation algorithms for pediatric brain gliomas from magnetic resonance imaging using standardized quantitative performance evaluation metrics employed across the BraTS 2023 challenges. The top-performing AI approaches for pediatric tumor analysis included ensembles of nnU-Net and Swin UNETR, Auto3DSeg, or nnU-Net with a self-supervised framework. The BraTS-PEDs 2023 challenge fostered collaboration between clinicians (neuro-oncologists, neuroradiologists) and AI/imaging scientists, promoting faster data sharing and the development of automated volumetric analysis techniques. These advancements could significantly benefit clinical trials and improve the care of children with brain tumors.