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DIS3 licenses B cells for plasma cell differentiation in humans.

DIS3 is the main catalytic subunit of the nuclear RNA exosome, a complex playing a crucial role in RNA processing and the degradation of various noncoding RNA substrates. In mice, DIS3 is essential for genomic rearrangements during B cell development, but its role in terminal plasma cell (PC) differentiation has not been explored. Although DIS3 gene alterations are frequent in multiple myeloma (MM), a PC malignancy, their molecular impact remains poorly understood. In this study, we developed an antisense oligonucleotide strategy to knock down DIS3 expression in a well-characterized model of human PC differentiation. Reducing DIS3 expression systematically led to decreased B cell proliferation and impaired PC differentiation with lower levels of switched immunoglobulin secretion. Transcriptome analyses confirmed alterations in the proliferation and differentiation programs, alongside an accumulation of noncoding RNAs. Notably, centromere-associated noncoding RNAs were highly sensitive to DIS3 activity, and their accumulation in DIS3-deficient cells, either as transcripts or DNA-associated RNAs, correlated with the mislocalization of the centromere-specific histone variant CENP-A. We finally observed reduced physiological DNA recombination and somatic hypermutation but increased genomic instability in DIS3-deficient cells, in agreement with the higher levels of IGH translocations observed in our large cohort of DIS3-mutant MM patients. Together, these results underscore the essential role of DIS3 in regulating B cell proliferation, DNA recombination, and physiological or malignant PC differentiation in humans.

Humans

Synovial short-lived plasma cells mediate adalimumab resistance in rheumatoid arthritis via MIF-CD74 axis-driven, partially TNF-α-independent inflammation.

OBJECTIVE: Synovial plasma cell infiltration predicts inadequate response to adalimumab in patients with rheumatoid arthritis (RA), yet the cellular and molecular mechanisms underlying this association remain unclear. This study aimed to dissect the functional heterogeneity of synovial plasma cells between adalimumab responders and non-responders at single-cell resolution, and to identify the molecular pathways driving treatment resistance. METHODS: This study was based on a prospective clinical cohort of 101 RA patients receiving adalimumab, from which synovial tissues of 8 patients (4 ACR20 responders and 4 non-responders) were profiled by 10x Genomics single-cell RNA sequencing (66,539 high-quality cells). A systematic ligand-receptor screening was performed to identify candidate signaling axes. Core findings were validated at four levels: an independent single-cell validation cohort (n = 4), external bulk RNA-seq cohorts (GSE15602, GSE47726), multiplex immunofluorescence on synovial tissues (n = 9 per group), and in vitro functional experiments using patient-derived peripheral blood monocyte-derived macrophages stimulated with recombinant human MIF under pharmacological intervention with adalimumab, the MIF inhibitor ISO-1, and an anti-CD74 neutralizing antibody. RESULTS: Plasma cells were significantly enriched in non-responder synovium, with a heterogeneous pattern characterized by quantitative accumulation of long-lived plasma cells (LLPCs) and functional dominance of short-lived plasma cells (SLPCs): SLPCs contributed 58.15% of total ribosomal module activity and preferentially overexpressed MIF. Systematic screening of 145 candidate ligand-receptor pairs identified MIF-CD74 as the only axis satisfying all four independent evidence layers. Tissue-level immunofluorescence confirmed that approximately 95% of synovial CD138+ plasma cells in non-responders co-expressed MIF, compared with approximately 45% in responders. In vitro, rh-MIF upregulated macrophage activation markers (CD74, CD80, CD86, HLA-DR) and induced IL-6 and TNF-α secretion. Adalimumab neutralized supernatant TNF-α but failed to suppress MIF-driven IL-6 and IL-1β activation, whereas ISO-1 and anti-CD74 effectively blocked MIF-induced effects at all levels examined. These findings were replicated in patient-derived PBMC macrophages. CONCLUSION: In adalimumab-resistant RA, a functionally active SLPC subset drives partially TNF-α-independent macrophage inflammation through the MIF-CD74 axis, representing a resistance pathway not fully addressed by anti-TNF therapy. Targeting MIF or CD74 blocked this axis in vitro, supporting MIF-CD74-directed precision intervention.

Adalimumab

Mapping the Immune cell-specific gene regulatory network in bipolar disorder: A framework from scTWMR to exploratory drug-target annotation.

BACKGROUND: Although the involvement of the immune system in the genetic susceptibility of bipolar disorder (BD) is widely acknowledged, the causal relationship between gene expression in specific immune cell subtypes and BD requires systematic elucidation. METHODS: We implemented an analytical framework integrating single-cell transcriptome-wide Mendelian randomization (scTWMR) with colocalization analysis. This approach utilized cis-expression quantitative trait loci (cis-eQTLs) derived from 14 distinct immune cell types as instrumental variables to interrogate BD genome-wide association study (GWAS) summary statistics (comprising 41,917 cases and 371,549 controls). Subsequent investigations encompassed functional enrichment analysis, protein-protein interaction (PPI) network construction, phenome-wide association study (PheWAS), and performed an exploratory drug-target annotation. RESULTS: Our analysis identified 33 gene-immune cell associations. Colocalization analysis provided robust evidence (PPH4 > 90%) for shared causal variants implicating the MAD1L1, APOM, and NFKBIL1 loci. Significantly enriched biological pathways included cell cycle regulation, circadian rhythm entrainment, and neuroinflammation. The PPI network revealed a core regulatory module centered on histone-encoding and immune-related genes. Exploratory drug-target annotation nominated compounds for further investigation for compounds targeting APOM, TMEM258, and NFKBIL1. CONCLUSION: This study systematically delineates a genetically supported regulatory network of immune cell-specific gene expression in BD, predominantly implicating CD8⁺ effector T cells, plasma cells, and B cells. The findings corroborate established pathological pathways while uncovering novel cell type-specific therapeutic targets, thereby providing a genetic framework for prioritizing candidate targets for future investigation.

Bipolar disorder

Genomic and the tumor microenvironment heterogeneity in multifocal hepatocellular carcinoma.

BACKGROUND AND AIMS: Ambiguous understanding of tumors and tumor microenvironments (TMEs) hinders accurate diagnosis and available treatment for multifocal hepatocellular carcinoma (HCC) covering intrahepatic metastasis (IM) and multicentric occurrence (MO). Here, we characterized the diverse TMEs of IM and MO identified by whole-exome sequencing at single-cell resolution. APPROACH AND RESULTS: We performed parallel whole-exome sequencing and scRNA-seq on 23 samples from 7 patients to profile their TMEs when major results were validated by immunohistochemistry in the additional cohort. Integrative analysis of whole-exome sequencing and single-cell RNA sequencing found that malignant cells in IM showed higher intratumor heterogeneity, stemness, and more activated metabolism than those in MO. Tumors from IM shared similar TMEs while distinct TMEs were noticed in those from MO. Furthermore, CD20+ B cells, plasma cells, and conventional type II dendritic cells (cDC2s) were decreased in IM relative to MO while T cells in IM exhibited a more terminally exhausted capacity with a higher proportion of proliferative/exhausted T cells than that in MO. Both CD20 and CD1C correlated with better prognosis in multifocal HCC. Additionally, MMP9+ tumor-associated macrophages were enriched across IM and MO, which formed cellular niches with regulatory T cells and proliferative/exhausted T cells. CONCLUSIONS: Our findings deeply decipher the heterogeneous TMEs between IM and MO, which provide a comprehensive landscape of multifocal HCC.

Humans

Digital and computational morphology in hematology: current platforms, clinical evidence, and future requirements.

INTRODUCTION: Morphologic examination of peripheral blood and bone marrow remains central to the diagnosis and classification of hematologic disorders. Conventional optical microscopy, however, is labor-intensive, dependent on operator expertise, and affected by interobserver variability. Digital morphology has developed from automated image acquisition and cell pre-classification into a broader field that includes whole-slide imaging, remote review, quantitative morphometry, and artificial intelligence-based analysis. CONTENT: This review examines current applications of digital morphology in peripheral blood, bone marrow aspirates, malaria detection, and body-fluid analysis. Commercial platforms are evaluated with particular attention to the distinction between raw automated pre-classification, expert digital post-classification, and comparison with independent optical microscopy. Digital systems generally perform well for common mature leukocyte populations but remain less reliable for rare or diagnostically critical cells, including blasts, abnormal lymphoid cells, plasma cells, and intermediate maturation stages. Research systems increasingly extend analysis from individual-cell classification to whole-slide, specimen-level, and patient-level assessment. SUMMARY: Digital morphology can improve standardization, image traceability, remote consultation, education, proficiency testing, quality assurance, and selected aspects of laboratory workflow. Its clinical value depends on appropriate validation, transparent reporting of reference methods, recognition of algorithm-specific failure modes, and clearly defined criteria for expert review and conventional microscopy. Human expertise remains essential not only for validating results but also for adapting cell taxonomies and interpretive rules to evolving classifications of hematologic diseases. OUTLOOK: Future progress will require representative multicenter datasets, harmonized morphologic terminology, external validation, interoperability with laboratory information systems, and continuous monitoring after software or hardware updates. Integration of morphology with quantitative hematology, flow cytometry, cytogenetics, genomics, and clinical data may support more comprehensive computational diagnosis. Digital platforms may also broaden access to specialist expertise, training, and quality programs in resource-limited institutions and regions, provided that infrastructure, governance, and professional competency are adequately supported.

artificial intelligence

Identification of NR4A2 as a Potential Predictive Biomarker for Atherosclerosis.

INTRODUCTION/OBJECTIVE: Atherosclerosis, a leading cause of death globally, is characterized by the buildup of immune cells and lipids in medium to large-sized arteries. However, its precise mechanism remains unclear. The purpose of this study is to explore innovative and reliable biomarkers as a viable approach for the identification and management of atherosclerosis. METHODS: The atherosclerosis-related datasets GSE100927 and GSE66360 were retrieved from the Gene Expression Omnibus (GEO) database. The Limma package in the R programming language was utilized, applying the criteria of |logFC| > 1 and P < 0.05. Subsequently, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed on the 127 identified DEGs using R. Machine learning techniques were then applied to these data to explore and pinpoint potential biomarkers. The diagnostic potential of these markers was assessed via Receiver Operating Characteristic (ROC) curve analysis. Finally, western blot, real-time quantitative PCR (qRT-PCR), and immunohistochemistry (IHC) were employed to confirm the key biomarkers. RESULTS: Our research indicated that a total of 127 DEGs linked to atherosclerosis were successfully identified. Through the application of machine learning methods, eight critical genes were highlighted. Among these, Nuclear Receptor Subfamily 4 Group A Member-2 (NR4A2) emerged as the most promising marker for further investigation. CIBERSORT analysis revealed that NR4A2 expression levels were significantly correlated with multiple immune cell types, including B cells, plasma cells, and macrophages. Additional validation experiments confirmed that NR4A2 expression was indeed elevated in atherosclerotic plaques, supporting its potential as a biomarker for atherosclerosis. CONCLUSION: Our study identified NR4A2 as a potential immune-related biomarker for the diagnosis and treatment of atherosclerosis.

Atherosclerosis

Plasma cell-CD8+ T cell co-enrichment distinguishes immunotherapy-responsive hepatocellular carcinoma subtypes.

BACKGROUND: Hepatocellular carcinoma (HCC) is characterised by significant racial disparities in incidence and outcomes, yet whether these reflect distinct tumour biology or differential distribution of molecular subtypes among immunotherapy patients remains unclear. METHODS: We characterised molecular heterogeneity among 46 patients with HCC of differing background population from the NCI-CLARITY cohort receiving immune checkpoint inhibitor therapy, using transcriptomic and genomic profiling, with validation across multiple independent cohorts. RESULTS: Differential expression analysis comparing African American versus non-African American patients identified 126 genes, of which 55 demonstrated tumour-specific expression across independent validation cohorts with paired tumour-normal samples. Consensus clustering revealed two molecular subtypes with no significant race association, indicating these clusters capture tumour-intrinsic biology rather than ancestry. The genomic landscape showed minimal differences between subtypes. A prognostic signature derived from these expression profiles demonstrated significant risk stratification in the NCI-CLARITY cohort and TCGA-LIHC, but not in Asian cohorts, suggesting population-specific applicability. Immune deconvolution revealed that the two subtypes represent distinct immune microenvironments: one subtype exhibited markedly elevated plasma cell infiltration with strong plasma cell-CD8+T&#x2009;cell correlation suggesting coordinated adaptive immunity, along with elevated tertiary lymphoid structure signatures. The other subtype showed regulatory T cell-macrophage correlation and enrichment for immune-excluded phenotypes. The immune-enriched subtype trended towards higher immunotherapy response rates. CONCLUSIONS: Molecular heterogeneity in HCC reveals distinct tumour-immune ecosystems that transcend racial classification. Tumour immune heterogeneity in HCC reflects distinct molecular patterns, with immune hot tumours characterised by elevated tertiary lymphoid structure signatures and enriched plasma cell and CD8+T cells. These patterns may serve as prognostic biomarkers for immunotherapy patient stratification and demonstrate the value of diverse cohort representation in identifying clinically relevant therapeutic targets.

Gastrointestinal Cancer

Localized PD-1 CAR T therapy reprograms neuroinflammation.

B cell-depleting therapies are effective in multiple sclerosis (MS), yet some patients relapse, underscoring the need for more precise interventions. To identify new therapeutic targets, we generated a single-cell RNA sequencing (scRNA-seq) atlas of cerebrospinal fluid (CSF), brain, and blood from non-inflammatory controls and patients with MS or other neuroinflammatory diseases. We found disease-associated enrichment of class-switched immunoglobulin G+ (IgG+) B cells and plasma cells in MS CSF. Unbiased analysis identified a rare disease-enriched subset of activated, T cell receptor (TCR)-restricted, PD-1+ T follicular helper-like cells with B cell-recruiting features. To target this population, we developed PD-1-directed chimeric antigen receptor (CAR) T cells that selectively depleted pathogenic PD-1+ CD4 T cells and locally released IL-10. This strategy attenuated central nervous system (CNS) inflammation, reprogrammed the local immune milieu, and improved clinical outcomes across murine neuroinflammation models. These findings define a CNS-localized adaptive immune circuit in MS and nominate programmable PD-1 CAR T cells as a strategy to disrupt it.

Animals

Pathogenesis of psoriasis and psoriatic arthritis: Insights from animal models and single-cell and spatial transcriptomic analyses of skin, synovium and entheses.

Psoriasis (PsO) and psoriatic arthritis (PsA) are immune-mediated diseases characterized by chronic systemic inflammation, including inflammation of the skin and joints. Recent advances in animal models, single-cell transcriptomics, spatial transcriptomics, and proteomics have greatly enhanced our understanding of disease pathogenesis. Mouse models exhibit key features of skin and joint inflammation, facilitating analysis of molecular pathways, and identification of therapeutic targets. Single-cell and spatial transcriptomic analyses have revealed cell-type-specific contributions to inflammation, highlighting interactions between keratinocytes, T cells, fibroblasts, and dendritic cells that drive psoriatic pathology. In psoriatic synovium, type 17 tissue-resident memory T cells, monocytes, and fibroblasts contribute to local inflammation and joint damage, whereas the roles of B cells and plasma cells are less clear. Proteomic and metabolomic profiling in patients with PsA has identified circulating protein signatures and metabolites associated with disease progression, sex-specific differences, and response to therapy. The integration of these multiomic approaches provides a detailed map of immune-stromal-epithelial crosstalk across skin, synovium, and entheses, uncovering mechanisms that were previously inaccessible. These insights have implications for predicting disease progression, identifying novel therapeutic targets, and optimizing treatment strategies. Collectively, advances in animal models and multiomic profiling are reshaping our understanding of PsO and PsA, providing a framework for future research, disease monitoring, and therapeutic development.

Animals

Spatial habitat radiomics predicts tertiary lymphoid structure status and identifies an IDO1+ migratory dendritic cell axis in breast cancer.

BACKGROUND: Tertiary lymphoid structures (TLS) are spatially organized immune niches associated with therapeutic response and favorable outcomes in breast cancer (BC). However, TLS assessment currently relies on invasive tissue-based analyses, and the biological mechanisms underlying imaging-based TLS prediction remain poorly understood. METHODS: We developed and validated a spatial heterogeneity-based radiomic TLS signature (shTLS) using dynamic contrast-enhanced MRI to non-invasively predict TLS status across multicenter BC cohorts. Spatial habitat radiomics were used to capture intratumoral and peritumoral immune-related heterogeneity. Integrated multi-omics analyses, including transcriptomics, pathomics, genomics, single-cell RNA sequencing, immunohistochemistry, and multiplex immunofluorescence, were performed to biologically interpret shTLS-defined subgroups. Functional drug-sensitivity assays were conducted to assess therapeutic implications. RESULTS: The shTLS model achieved robust predictive performance across independent cohorts and molecular subtypes. High shTLS scores were associated with immune-inflamed tumors characterized by spatially clustered activated T cells and dendritic cells (DCs). In contrast, shTLS-low tumors exhibited an immunosuppressive spatial niche with peripheral accumulation of CD4+ PD-1+ T cells and plasma cells, increased immune-tumor separation, and enhanced inflammatory and immunoregulatory signaling. An indoleamine 2,3-dioxygenase 1 (IDO1)-associated immunoregulatory program was observed in the shTLS-low tumors, which appeared to be preferentially expressed by LAMP3+CCR7+ migratory DCs. Pharmacologic inhibition of IDO1 enhanced chemotherapy and CDK4/6 inhibitor sensitivity in vitro. CONCLUSION: This study establishes spatial radiomics as a non-invasive approach to decode TLS-associated immune ecosystems and supports the presence of an IDO1-associated immunosuppressive phenotype, providing biological insight and translational rationale for patient stratification and future combination strategies.

Humans

The prognostic significance of ubiquitination-related genes in multiple myeloma by bioinformatics analysis.

BACKGROUND: Immunoregulatory drugs regulate the ubiquitin-proteasome system, which is the main treatment for multiple myeloma (MM) at present. In this study, bioinformatics analysis was used to construct the risk model and evaluate the prognostic value of ubiquitination-related genes in MM. METHODS AND RESULTS: The data on ubiquitination-related genes and MM samples were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. The consistent cluster analysis and ESTIMATE algorithm were used to create distinct clusters. The MM prognostic risk model was constructed through single-factor and multiple-factor analysis. The ROC curve was plotted to compare the survival difference between high- and low-risk groups. The nomogram was used to validate the predictive capability of the risk model. A total of 87 ubiquitination-related genes were obtained, with 47 genes showing high expression in the MM group. According to the consistent cluster analysis, 4 clusters were determined. The immune infiltration, survival, and prognosis differed significantly among the 4 clusters. The tumor purity was higher in clusters 1 and 3 than in clusters 2 and 4, while the immune score and stromal score were lower in clusters 1 and 3. The proportion of B cells memory, plasma cells, and T cells CD4 na&#xef;ve was the lowest in cluster 4. The model genes KLHL24, HERC6, USP3, TNIP1, and CISH were highly expressed in the high-risk group. AICAr and BMS.754,807 exhibited higher drug sensitivity in the low-risk group, whereas Bleomycin showed higher drug sensitivity in the high-risk group. The nomogram of the risk model demonstrated good efficacy in predicting the survival of MM patients using TCGA and GEO datasets. CONCLUSIONS: The risk model constructed by ubiquitination-related genes can be effectively used to predict the prognosis of MM patients. KLHL24, HERC6, USP3, TNIP1, and CISH genes in MM warrant further investigation as therapeutic targets and to combat drug resistance.

Humans

Diagnostic value of plasma cell-free DNA metagenomic next-generation sequencing in patients with suspected infections and exploration of clinical scenarios-a retrospective study from a single center.

BACKGROUND: Plasma cell-free DNA metagenomic next-generation sequencing (mNGS) is a non-invasive comprehensive method for the etiological diagnosis of various infectious diseases. However, research on the early diagnosis and real-world clinical impact of plasma mNGS in patients with suspected infection are still limited. MATERIALS AND METHODS: This study retrospectively included 140 patients with suspected infections who underwent early plasma mNGS and conventional culture testing. Referring to the clinical diagnosis of infectious diseases, the diagnostic performance of plasma mNGS and culture tests was compared, and the application scenarios and clinical effects of plasma mNGS were evaluated. RESULTS: The positive rate of plasma mNGS was significantly higher than that of culture methods (55.71% vs 25.10%, p&#x2009;<&#x2009;0.001) and blood cultures (55.71% vs 12.86%, p&#x2009;<&#x2009;0.001). Regarding clinical diagnosis, the sensitivity of plasma mNGS was significantly higher than that of culture (58.27% vs 37.80%, p&#x2009;=&#x2009;0.002). The combination of mNGS and culture achieved a higher detection sensitivity (69.29%), especially in patients with multi-site co-infections (73.68%) and blood infections (73.17%). Plasma mNGS demonstrated higher sensitivity in patients with procalcitonin (PCT) index > 5&#x2009;ng/ml or human neutrophil lipocalin (HNL) index > 200&#x2009;ng/ml. In terms of treatment, a total of 69 patients (54.33%) benefited from plasma mNGS. CONCLUSION: This study highlights the significant improvement in pathogen detection performance by combining conventional culture with plasma mNGS detection, especially in patients with multi-site co-infections and blood infections. Early use of plasma mNGS as an adjunct to culture can better guide clinicians to initiate appropriate anti-infective therapy.

Humans

Development and preliminary validation of plasma cell-free DNA methylation-based diagnostic prediction model for colorectal cancer detection.

BACKGROUND: Colorectal cancer (CRC) is a common malignancy associated with genetic and epigenetic alterations. Several methylation biomarkers have been investigated for non-invasive CRC detection; however, their reported performance varies across clinical settings, and the detection of early-stage or precancerous disease and discrimination from non-malignant colorectal conditions remain challenging. This exploratory study aimed to identify reproducible CRC-associated plasma cell-free DNA (cfDNA) methylation regions and to develop and preliminarily evaluate diagnostic prediction model for distinguishing CRC from healthy controls and benign samples. METHODS: Public CRC tissue methylation datasets from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) were analyzed to identify reproducible CRC-associated methylation alterations. Plasma cfDNA methylation was profiled using methyl-CpG-binding-domain enrichment followed by paired-end sequencing in patients with CRC, patients with colorectal polyps, and healthy controls. After quality-control filtering, 30 CRC and healthy-control samples were randomly allocated at the participant level in a 7:3 ratio to a development set comprising 10 patients with CRC and 11 healthy controls and a held-out test set comprising 4 patients with CRC and 5 healthy controls. Hypermethylated regions were selected using least absolute shrinkage and selection operator (LASSO) logistic regression. The 12-region model was evaluated in the held-out test set and subsequently applied to 10 colorectal polyp samples without refitting or recalibration. RESULTS: Tissue methylation analysis identified reproducible CRC-associated alterations across independent datasets. In the plasma development set, 707 differentially methylated regions (DMRs) were identified between CRC and healthy-control samples, including 324 hypermethylated and 383 hypomethylated regions. LASSO regression selected a 12-region hypermethylation signature. In the held-out test set, the model achieved an area under the curve (AUC) of 0.85 [95% confidence interval (CI): 0.579-1.000]. At the development-set-derived threshold, sensitivity was 75.0% (3/4), specificity was 60.0% (3/5), and accuracy was 66.7% (6/9). When the original model was applied to colorectal polyp samples, model scores were significantly higher in both CRC and polyp samples than in healthy controls, while CRC samples showed a tendency toward higher scores than polyp samples. CONCLUSIONS: This exploratory study identified a 12-region plasma cfDNA hypermethylation signature associated with CRC and developed a LASSO-based diagnostic prediction model that showed preliminary discrimination between CRC and healthy controls in a small held-out test set. By integrating tissue methylation evidence with plasma cfDNA profiling, this study expands the repertoire of candidate region-level methylation markers for blood-based CRC detection.

Colorectal cancer (CRC)

Real-world clinical impact of plasma cell-free DNA metagenomic next-generation sequencing assay.

OBJECTIVE: To describe the real-world clinical impact of a commercially available plasma cell-free DNA metagenomic next-generation sequencing assay, the Karius test (KT). METHODS: We retrospectively evaluated the clinical impact of KT by clinical panel adjudication. Descriptive statistics were used to study associations of diagnostic indications, host characteristics, and KT-generated microbiologic patterns with the clinical impact of KT. Multivariable logistic regression modeling was used to further characterize predictors of higher positive clinical impact. RESULTS: We evaluated 1000 unique clinical cases of KT from 941 patients between January 1, 2017-August 31, 2023. The cohort included adult (70%) and pediatric (30%) patients. The overall clinical impact of KT was positive in 16%, negative in 2%, and no clinical impact in 82% of the cases. Among adult patients, multivariable logistic regression modeling showed that culture-negative endocarditis (OR 2.3; 95% CI, 1.11-4.53; P .022) and concern for fastidious/zoonotic/vector-borne pathogens (OR 2.1; 95% CI, 1.11-3.76; P .019) were associated with positive clinical impact of KT. Host immunocompromised status was not reliably associated with a positive clinical impact of KT (OR 1.03; 95% CI, 0.83-1.29; P .7806). No significant predictors of KT clinical impact were found in pediatric patients. Microbiologic result pattern was also a significant predictor of impact. CONCLUSIONS: Our study highlights that despite the positive clinical impact of KT in select situations, most testing results had no clinical impact. We also confirm diagnostic indications where KT may have the highest yield, thereby generating tools for diagnostic stewardship.

Humans

Nonbacterial Thrombotic Endocarditis Unmasking Concomitant Monoclonal Gammopathy of Undetermined Significance (MGUS) by Manifesting as Stroke.

Nonbacterial thrombotic endocarditis (NBTE) is a rare condition characterized by sterile platelet-fibrin vegetations on cardiac valves in the absence of systemic infection. The pathogenesis of marantic endocarditis is driven by endothelial dysfunction and a systemic hypercoagulable state. In contrast to infective endocarditis, vegetations in NBTE lack significant inflammatory infiltrates and do not yield positive blood cultures. NBTE typically comes to clinical attention via systemic embolic events, with cerebrovascular accidents serving as a clinical hallmark and constituting over 50% of cases. While NBTE is commonly associated with mucin-producing adenocarcinomas of the lung, pancreas, and gastrointestinal tract, its occurrence secondary to hematological malignancies or precursor plasma cell dyscrasias like monoclonal gammopathy of undetermined significance (MGUS) is exceedingly rare, particularly in young individuals. We report the case of a previously healthy 35-year-old woman who presented with acute-onset blurred vision. Neuroimaging via magnetic resonance imaging (MRI) revealed an acute left occipital infarct along with multiple chronic infarcts, raising a strong suspicion of a recurrent embolic process. A transesophageal echocardiogram (TEE) demonstrated two vegetations on the aortic valve with moderate transvalvular regurgitation; in the context of persistent negative blood cultures, these findings supported the diagnosis of NBTE. The patient was managed with systemic anticoagulation. A comprehensive hypercoagulable and autoimmune workup revealed an elevated lambda free light chain level with a decreased kappa/lambda ratio. Subsequent bone marrow biopsy and cytogenetic analysis established a diagnosis of MGUS featuring high-risk genomic aberrations, specifically an immunoglobulin heavy chain/musculoaponeurotic fibrosarcoma (IGH/MAF) rearrangement and the loss of chromosome 13 in a polyploid (3n, 4n) background, findings consistent with plasma cell neoplasia. The prevalence of MGUS in individuals under the age of 40 is exceptionally low, estimated at less than 0.3%. This case underscores NBTE as a critical finding that can unmask underlying, atypical plasma cell neoplasms. It highlights the necessity of an exhaustive diagnostic evaluation for occult hematological disorders and high-risk cytogenetic features in young patients presenting with multi-territory embolic strokes.

igh/maf rearrangement

Comprehensive Viral Detection and Profiling of Plasma Cell-Free RNA in Patients With Suspected Hemophagocytic Lymphohistiocytosis.

Hemophagocytic lymphohistiocytosis (HLH) is a severe, rapidly progressive disease. While viral infection is considered a common etiology of pediatric HLH, specific causative viruses other than the Epstein-Barr virus (EBV) have been rarely identified. This study utilized metagenomic next-generation sequencing (NGS) to identify potential causative pathogens in plasma samples from 17 pediatric patients with suspected HLH. Additionally, one case each of confirmed EBV- and cytomegalovirus (CMV)-associated HLH was analyzed for methodological validation. Plasma cell-free RNA (cfRNA) profiling was performed using NGS data to assess the host transcriptome response. Significant viral reads of human herpesvirus-6B, human herpesvirus-7, and Hubei reo-like virus (HRLV) 14 were detected using metagenomic NGS in one patient each. Plasma cfRNA profiles from five patients with viral infection (including EBV and CMV) were compared to those of 14 patients without viral infection. By comparing the two patient groups, 1053 differentially expressed genes were identified. The gene ontology (GO) term of "adaptive immune response" (GO: 0002250) was significantly enriched among upregulated genes in the virus-positive group. Furthermore, an isolated cluster consisting specifically of mitochondrial RNAs, was identified in the upregulated genes of the virus-positive group. Using metagenomic NGS, several candidate viral pathogens were identified in patients with suspected infection-related HLH. The viral genome of HRLV 14, previously undetected in human clinical samples, was identified in one patient. The results from plasma cfRNA profiling suggest that mitochondrial RNAs may reflect the underlying pathogenesis of virus-associated HLH and have potential utility as disease biomarkers.

Humans

A single-cell atlas of multiple myeloma defines malignant archetypes and proliferative states.

Multiple myeloma (MM) is a plasma-cell malignancy with extensive genomic and transcriptional heterogeneity, limiting disease classification and precision therapy. Here we generated a clinically annotated, population-scale, single-cell atlas of MM from 341 individuals spanning the disease and treatment continuum. We identified five recurrent malignant transcriptional archetypes and an orthogonal proliferative program associated with genomic features, therapeutic resistance and clinical outcomes. Validation in the independent CoMMpass cohort demonstrated robustness, prognostic relevance and portability across platforms. We developed a single-cell, target-discovery pipeline prioritizing malignant enrichment, cell-type specificity and tissue restriction, identifying FCRL2 as a plasma-restricted or B cell-lineage-restricted surface target expressed by malignant plasma cells. FCRL2-targeted chimeric antigen receptor T cells demonstrated antigen-specific activity in vitro and survival benefit in vivo. Together, these data provide a clinically actionable blueprint for patient stratification and precision target nomination in plasma-cell malignancies.

Multiple Myeloma

Predicting bloodstream infection by plasma cell-free metagenomic sequencing: a prospective cohort study.

BACKGROUND: Patients receiving myelosuppressive chemotherapy or haematopoietic cell transplantation are at high risk for life-threatening bloodstream infections. A novel pre-emptive treatment paradigm guided by pathogen detection before symptoms appear might reduce this risk, but no validated screening test is available. This study evaluated the sensitivity and specificity of plasma microbial cell-free DNA metagenomic sequencing (mcfDNA-Seq) for predicting bloodstream infections in children and adolescents receiving therapy for high-risk leukaemia. METHODS: In this prospective cohort study, between Aug 9, 2017, and Feb 28, 2022, leftover clinical plasma samples were prospectively collected up to once per day from patients who were younger than 25 years, receiving care for leukaemia at St Jude Children's Research Hospital (Memphis, TN, USA), and at high risk for life-threatening bloodstream infections. mcfDNA-Seq was used to identify pathogen DNA in blood samples obtained during the 7 days before to 1 day after bloodstream infection onset, and in control samples from the same population in the absence of fever or infection. The testing laboratory was masked to sample status. Primary outcomes were predictive sensitivity of mcfDNA-Seq for detecting the expected bloodstream infection pathogen during the 3 days preceding the day of bloodstream infection onset, with a prespecified favourable sensitivity of 50%, and predictive specificity of mcfDNA-Seq in control samples. Exploratory analyses comprised assessing sensitivity and specificity restricted to bacteria or common bloodstream infection pathogens, and after applying a data-derived DNA fragment concentration cutoff; estimating the predictive sensitivity on each of the 7 days before bloodstream infection onset; identifying clinical characteristics that affected predictive sensitivity or specificity; and examining the clinical relevance of additional organisms identified by mcfDNA-Seq during bloodstream infection episodes. Diagnostic sensitivity was also assessed on samples collected on the day of, or day after, diagnosis of bloodstream infection. This study is registered with ClinicalTrials.gov, NCT03226158. FINDINGS: 94 evaluable bloodstream infections occurred in 60 (38%) of 158 enrolled participants; 19 episodes were previously described in the pilot phase of this study. The predictive sensitivity of mcfDNA-Seq was 51&#xb7;9% (95% CI 40&#xb7;5-63&#xb7;1) for all bloodstream infection episodes, 53&#xb7;8% (42&#xb7;2-65&#xb7;2) for bacterial infection only, and 51&#xb7;9% (40&#xb7;5-63&#xb7;1) when applying a DNA fragment concentration cutoff of 140 molecules per &#x3bc;L. Sensitivity was lowest at day -7 and increased daily until the day of diagnosis. Diagnostic sensitivity was 81&#xb7;3% (95% CI 71&#xb7;0-89&#xb7;1) for all bloodstream infection episodes and 83&#xb7;1% (72&#xb7;9-90&#xb7;7) for bacterial infections only. Predictive specificity was 82&#xb7;7% (95% CI 76&#xb7;0-88&#xb7;2), but improved to 88&#xb7;9% (83&#xb7;0-93&#xb7;3) for common bloodstream infection pathogens, and to 93&#xb7;8% (88&#xb7;9-97&#xb7;0) when also applying the DNA fragment concentration cutoff. Predictive sensitivity was higher in participants with acute lymphoblastic leukaemia (adjusted odds ratio [aOR] 11&#xb7;1 [1&#xb7;7-74&#xb7;2] vs those with acute myeloid leukaemia), and it was lower in polymicrobial infections (aOR 0&#xb7;0 [0&#xb7;0-0&#xb7;2] vs monomicrobial Gram-positive infections). Clinical false-positive results were positively associated with gastrointestinal disturbance alone (p=0&#xb7;037) or combined with recent administration of high-dose cytarabine (p=0&#xb7;012). Additional organisms identified by mcfDNA-Seq that were not identified by blood culture were less likely than expected organisms to have an increasing DNA concentration during the days preceding bloodstream infection diagnosis. INTERPRETATION: mcfDNA-Seq can detect causative pathogens before the onset of some bloodstream infection episodes in profoundly immunocompromised patients. Predictive specificity might be improved by restricting results to a subgroup of relevant organisms, excluding patients with high risk of false-positive results, or applying a higher concentration cutoff. Clinical trials are needed to evaluate mcfDNA-Seq-guided pre-emptive therapy for preventing life-threatening bloodstream infections in patients with high risk. FUNDING: The National Cancer Institute, American Lebanese Syrian Associated Charities, St Jude Children's Research Hospital, and Karius.

Adolescent