Copy Number Variation Research Articles

Solving the Etiology of Developmental and Epileptic Encephalopathy with Spike-Wave Activation in Sleep (D/EE-SWAS).

To understand the etiological landscape and phenotypic differences between 2 developmental and epileptic encephalopathy (DEE) syndromes: DEE with spike-wave activation in sleep (DEE-SWAS) and epileptic encephalopathy with spike-wave activation in sleep (EE-SWAS). All patients fulfilled International League Against Epilepsy (ILAE) DEE-SWAS or EE-SWAS criteria with a Core cohort (n = 91) drawn from our Epilepsy Genetics research program, together with 10 etiologically solved patients referred by collaborators in the Expanded cohort (n = 101). Detailed phenotyping and analysis of molecular genetic results were performed. We compared the phenotypic features of individuals with DEE-SWAS and EE-SWAS. Brain-specific gene co-expression analysis was performed for D/EE-SWAS genes. We identified the etiology in 42/91 (46%) patients in our Core cohort, including 29/44 (66%) with DEE-SWAS and 13/47 (28%) with EE-SWAS. A genetic etiology was identified in 31/91 (34%). D/EE-SWAS genes were highly co-expressed in brain, highlighting the importance of channelopathies and transcriptional regulators. Structural etiologies were found in 12/91 (13%) individuals. We identified 10 novel D/EE-SWAS genes with a range of functions: ATP1A2, CACNA1A, FOXP1, GRIN1, KCNMA1, KCNQ3, PPFIA3, PUF60, SETD1B, and ZBTB18, and 2 novel copy number variants, 17p11.2 duplication and 5q22 deletion. Although developmental regression patterns were similar in both syndromes, DEE-SWAS was associated with a longer duration of epilepsy and poorer intellectual outcome than EE-SWAS. DEE-SWAS and EE-SWAS have highly heterogeneous genetic and structural etiologies. Phenotypic analysis highlights valuable clinical differences between DEE-SWAS and EE-SWAS which inform clinical care and prognostic counseling. Our etiological findings pave the way for the development of precision therapies. ANN NEUROL 2024;96:932-943.

Genomic and transcriptomic profiling of inflammatory breast cancer reveals distinct molecular characteristics to non-inflammatory breast cancers.

Inflammatory breast cancer (IBC), a rare and highly aggressive form of breast cancer, accounts for 10% of breast cancer-related deaths. Previous omics studies of IBC have focused solely on one of genomics or transcriptomics and did not discover common differences that could distinguish IBC from non-IBC. Seventeen IBC patients and five non-IBC patients as well as additional thirty-three Asian breast cancer samples from TCGA-BRCA were included for the study. We performed whole-exon sequencing (WES) to investigate different somatic genomic alterations, copy number variants, and large structural variants between IBC and non-IBC. Bulk RNA sequencing (RNA-seq) was performed to examine the differentially expressed genes, pathway enrichment, and gene fusions. WES and RNA-seq data were further investigated in combination to discover genes that were dysregulated in both genomics and transcriptomics. Copy number variation analysis identified 10 cytobands that showed higher frequency in IBC. Structural variation analysis showed more frequent deletions in IBC. Pathway enrichment and immune infiltration analysis indicated increased immune activation in IBC samples. Gene fusions including CTSC-RAB38 were found to be more common in IBC. We demonstrated more commonly dysregulated RAS pathway in IBC according to both WES and RNA-seq. Inhibitors targeting RAS signaling and its downstream pathways were predicted to possess promising effects in IBC treatment. We discovered differences unique in Asian women that could potentially explain IBC etiology and presented RAS signaling pathway as a potential therapeutic target in IBC treatment.

Lactuca super-pangenome reduces bias towards reference genes in lettuce research

BackgroundBreeding of lettuce (Lactuca sativa L.), the most important leafy vegetable worldwide, for enhanced disease resistance and resilience relies on multiple wild relatives to provide the necessary genetic diversity. In this study, we constructed a super-pangenome based on four Lactuca species (representing the primary, secondary and tertiary gene pools) and comprising 474 accessions. We include 68 newly sequenced accessions to improve cultivar coverage and add important foundational breeding lines.ResultsWith the super-pangenome we find substantial presence/absence variation (PAV) and copy-number variation (CNV). Functional enrichment analyses of core and variable genes show that transcriptional regulators are conserved whereas disease resistance genes are variable. PAV-genome-wide association studies (GWAS) and CNV-GWAS are largely congruent with single-nucleotide polymorphism (SNP)-GWAS. Importantly, they also identify several major novel quantitative trait loci (QTL) for resistance against Bremia lactucae in variable regions not present in the reference lettuce genome. The usability of the super-pangenome is demonstrated by identifying the likely origin of non-reference resistance loci from the wild relatives Lactuca serriola, Lactuca saligna and Lactuca virosa.ConclusionsThe super-pangenome offers a broader view on the gene repertoire of lettuce, revealing relevant loci that are not in the reference genome(s). The provided methodology and data provide a strong basis for research into PAVs, CNVs and other variation underlying important biological traits of lettuce and other crops.

Evaluation of cfDNA fragmentation characteristics in plasma for the diagnosis of lung cancer: A prospective cohort study.

Lung cancer is one of the most prevalent cancers worldwide, yet only approximately 16% of patients are diagnosed in early stage, highlighting the urgent need for novel, highly accurate detection models. In our study, patients with suspected lung cancer or lung disease, as identified through radiographic imaging, along with healthy individuals, were consecutively recruited from Beijing Chest Hospital. Circulating free DNA (cfDNA) was extracted from plasma samples, and low-depth whole-genome sequencing was performed to identify fragmentomic features for model construction. A total of 265 participants were prospectively enrolled, comprising 124 lung cancer patients and 141 noncancer individuals. The model we developed was based on four cfDNA fragmentation characteristics, including 20-bp breakpoint nucleotides motif, fragmentation size coverage, fragmentation size distribution, and copy number variation. In an independent test cohort, the model achieved an area under the curve (AUC) of 0.861 (95% CI: 0.781-0.942) and demonstrated a sensitivity of 70% (95% CI: 53.5%-83.4%) at a specificity of 89.4% (95% CI: 76.9%-96.5%). Notably, the model was also effective in detecting early-stage cancer, with an AUC of 0.808 (95% CI: 0.69-0.925). In summary, our lung cancer detection model shows strong screening capabilities by leveraging four cfDNA fragmentation characteristics, exhibiting robust performance in early cancer diagnosis.

Exploring tumor endothelial cells heterogeneity in hepatocellular carcinoma: insights from single-cell sequencing and pseudotime analysis

Objective This study aimed to explore the heterogeneity of tumor endothelial cells (TECs) in hepatocellular carcinoma (HCC) and their role in tumor progression, with the goal of identifying new therapeutic targets and strategies to improve patient prognosis. Methods Single-cell RNA sequencing data from nine primary liver cancer samples were analyzed, obtained from the Gene Expression Omnibus (GEO) database. Data preprocessing, normalization, dimensionality reduction, and batch effect correction were performed based on the Seurat package. HCC cell types were identified using uniform manifold approximation and projection (UMAP) and cluster analysis, and the different cell types were annotated using the CellMarker database. Pseudotime trajectory analysis was conducted with Monocle to explore the differentiation trajectory of TECs. MAPK signaling pathway activity and copy number variations (CNV) in TECs were analyzed in conjunction with data from The Cancer Genome Atlas (TCGA), the trans-well and wound healing assay was used for cell invasion and migration activity assessment. Results Two subgroups of TECs (TECs 1 and TECs 2) were identified, exhibiting distinct functional activities and signaling pathways. Specifically, TECs 1 may be involved in tumor cell proliferation and inflammatory responses, whereas TECs 2 is not only involved in cell proliferation pathways, but also enriched in pathways such as metabolic synthesis. Pseudotime analysis revealed dynamic changes in TECs subgroups during HCC progression, correlating specific gene expressions (such as PDGFRB, PGF, JUN, and NR4A1). Subsequently, the JUN gene was predicted by performing binding sites and was shown to act as a transcription factor that may regulate the expression of the PGF gene. CNV analysis highlighted key genes and pathways in TECs that might influence HCC progression, and the PGF as key regulatory factor mediated cell proliferation and migration. Conclusion The study revealed the heterogeneity of TECs in HCC and their potential roles in tumor progression, offering new perspectives and potential therapeutic targets for HCC molecular mechanisms. The findings emphasize the importance of further exploring TECs heterogeneity for understanding HCC pathogenesis and developing personalized treatment strategies.

A new selective force driving metabolic gene clustering.

The formation of clusters of functionally related genes in microbial genomes has puzzled microbiologists since their discovery. Here, we suggest that replication, and the copy number variations due to the replisome passage, might play a role in the process through a perturbation in metabolite homeostasis. We provide theoretical support to this hypothesis, and we found that both simulations and genomic analysis support our hypothesis.

A burden of rare copy number variants in obsessive-compulsive disorder.

Current genetic research on obsessive-compulsive disorder (OCD) supports contributions to risk specifically from common single nucleotide variants (SNVs), along with rare coding SNVs and small insertion-deletions (indels). The contribution to OCD risk from rare copy number variants (CNVs), however, has not been formally assessed at a similar scale. Here we describe an analysis of rare CNVs called from genotype array data in 2248 deeply phenotyped OCD cases and 3608 unaffected controls from Sweden and Norway. Cases carry an elevated burden of CNVs ≥30 kb in size (OR = 1.12, P = 1.77 × 10-3). The excess rate of these CNVs in cases versus controls was around 0.07 (95% CI 0.02-0.11, P = 2.58 × 10-3). This signal was largely driven by CNVs overlapping protein-coding regions (OR = 1.19, P = 3.08 × 10-4), particularly deletions impacting loss-of-function intolerant genes (pLI >0.995, OR = 4.12, P = 2.54 × 10-5). We did not identify any specific locus where CNV burden was associated with OCD case status at genome-wide significance, but we noted non-random recurrence of CNV deletions in cases (permutation P = 2.60 × 10-3). In cases where sufficient clinical data were available (n = 1612) we found that carriers of neurodevelopmental duplications were more likely to have comorbid autism (P < 0.001), and that carriers of deletions overlapping neurodevelopmental genes had lower treatment response (P = 0.02). The results demonstrate a contribution of rare CNVs to OCD risk, and suggest that studies of rare coding variation in OCD would have increased power to identify risk genes if this class of variation were incorporated into formal tests.

Highly demarcated structural alterations in the brain and impaired social incentive learning in Tbx1 heterozygous mice.

Copy number variants (CNVs) are robustly associated with psychiatric disorders and changes in brain structures. However, because CNVs contain many genes, the precise gene-phenotype relationship remains unclear. Although various volumetric alterations in the brains of 22q11.2 CNV carriers have been identified in humans and mouse models, it is unknown how each gene encoded in the 22q11.2 region contributes to structural alterations, associated mental illnesses, and their dimensions. Our previous studies identified Tbx1, a T-box family transcription factor encoded in the 22q11.2 CNV, as a driver gene for social interaction and communication, spatial and working memory, and cognitive flexibility. However, it remains unclear how TBX1 impacts the volumes of various brain regions and their functionally linked behavioral dimensions. In this study, we used volumetric magnetic resonance imaging analysis to comprehensively evaluate brain region volumes and behavioral alterations relevant to affected structures in congenic Tbx1 heterozygous mice. Our data showed that the volumes of the anterior and posterior portions of the amygdaloid complex and its surrounding cortical regions were most robustly reduced in Tbx1 heterozygous mice. In an amygdala-dependent task, Tbx1 heterozygous mice were impaired in their ability to learn the incentive value of a social partner. The volumes of the primary and secondary auditory cortexes were increased, and acoustic, but not non-acoustic, sensorimotor gating was impaired in Tbx1 heterozygous mice. Our findings identify the brain's regional volume alterations and their relevant behavioral dimensions associated with Tbx1 heterozygosity.

A comprehensive map of copy number variations in dromedary camels based on whole genome sequence data

Copy number variants (CNVs) are structural variants within the eukaryotic genome that vary among individuals of a species. These variants have been associated with different phenotypic traits, making them a valuable consideration as markers for designing breeding programmes. In this study, whole genome sequence data of 60 dromedary camel samples originating from the Arabian Peninsula were analyzed to construct a comprehensive dromedary CNV map. Utilizing four CNV callers employing read-depth, split-read and paired-end mapping approaches, a total of 37,519 CNV events (17,847 deletions and 19,672 duplications) were called on the dromedary autosomes. These CNV events were merged into 2,557 regions, categorized as 1,322 losses, 122 gains, and 1,113 “mixed regions” comprising both types. The cumulative size of the CNV regions amounted to 22.5 Mb, covering roughly 1.16% of the dromedary autosomes. Approximately 32% of the defined CNV regions (comprising 60% losses, 18% gains, and 0.27% mixed regions) were found in ≥ 90% of the dromedary samples, classifying them as prevalent regions. Genes with biological functions related to the different adaptive physiologies of dromedary camels, such as fertility, heat stress, musculoskeletal development, and fat metabolism, were overlapping with or in close proximity to ~ 68% of the defined CNV regions, demonstrating their potential role in dromedaries’ physiology. This study presents the first comprehensive CNV map of dromedary camels and builds on the present knowledge in understanding the genetic structure of this species.

Comprehensive reanalysis for CNVs in ES data from unsolved rare disease cases results in new diagnoses

We report the results of a comprehensive copy number variant (CNV) reanalysis of 9171 exome sequencing datasets from 5757 families affected by a rare disease (RD). The data reanalysed was extremely heterogeneous, having been generated using 28 different enrichment kits by 42 different research groups across Europe partnering in the Solve-RD project. Each research group had previously undertaken their own analysis of the data but failed to identify disease-causing variants. We applied three CNV calling algorithms to maximise sensitivity, and rare CNVs overlapping genes of interest, provided by four partner European Reference Networks, were taken forward for interpretation by clinical experts. This reanalysis has resulted in a molecular diagnosis being provided to 51 families in this sample, with ClinCNV performing the best of the three algorithms. We also identified partially explanatory pathogenic CNVs in a further 34 individuals. This work illustrates the value of reanalysing ES cold cases for CNVs.

CancerSCEM 2.0: an updated data resource of single-cell expression map across various human cancers.

The field of single-cell RNA sequencing (scRNA-seq) has advanced rapidly in the past decade, generating significant amounts of valuable data for researchers to study complex tumor profiles. This data is crucial for gaining innovative insights into cancer biology. CancerSCEM (https://ngdc.cncb.ac.cn/cancerscem) is a public resource that integrates, analyzesand visualizes scRNA-seq data related to cancer, and it provides invaluable support to numerous cancer-related studies. With CancerSCEM 2.0, scRNA-seq data have increased from 208 to 1466 datasets, covering tumor, matching-normaland peripheral blood samples across 127 research projects and 74 cancer types. The new version of this resource enhances transcriptome analysis by adding copy number variation evaluation, transcription factor enrichment, pseudotime trajectory construction, and diverse biological feature scoring. It also introduces a new cancer metabolic map at the single-cell level, providing an intuitive understanding of metabolic regulation across different cancer types. CancerSCEM 2.0 has a more interactive analysis platform, including four modules and 14 analytical functions, allowing researchers to perform cancer scRNA-seq data analyses in various dimensions. These enhancements are expected to expand the usability of CancerSCEM 2.0 to a broader range of cancer research and clinical applications, potentially revolutionizing our understanding of cancer mechanisms and treatments.

Comprehensive genome analysis and variant detection at scale using DRAGEN.

Research and medical genomics require comprehensive, scalable methods for the discovery of novel disease targets, evolutionary drivers and genetic markers with clinical significance. This necessitates a framework to identify all types of variants independent of their size or location. Here we present DRAGEN, which uses multigenome mapping with pangenome references, hardware acceleration and machine learning-based variant detection to provide insights into individual genomes, with ~30 min of computation time from raw reads to variant detection. DRAGEN outperforms current state-of-the-art methods in speed and accuracy across all variant types (single-nucleotide variations, insertions or deletions, short tandem repeats, structural variations and copy number variations) and incorporates specialized methods for analysis of medically relevant genes. We demonstrate the performance of DRAGEN across 3,202 whole-genome sequencing datasets by generating fully genotyped multisample variant call format files and demonstrate its scalability, accuracy and innovation to further advance the integration of comprehensive genomics. Overall, DRAGEN marks a major milestone in sequencing data analysis and will provide insights across various diseases, including Mendelian and rare diseases, with a highly comprehensive and scalable platform.

Pangenome graph analysis reveals extensive effector copy-number variation in spinach downy mildew.

Plant pathogens adapt at speeds that challenge contemporary disease management strategies like the deployment of disease resistance genes. The strong evolutionary pressure to adapt, shapes pathogens' genomes, and comparative genomics has been instrumental in characterizing this process. With the aim to capture genomic variation at high resolution and study the processes contributing to adaptation, we here leverage an innovative, multi-genome method to construct and annotate the first pangenome graph of an oomycete plant pathogen. We expand on this approach by analysing the graph and creating synteny based single-copy orthogroups for all genes. We generated telomere-to-telomere genome assemblies of six genetically diverse isolates of the oomycete pathogen Peronospora effusa, the economically most important disease in cultivated spinach worldwide. The pangenome graph demonstrates that P. effusa genomes are highly conserved, both in chromosomal structure and gene content, and revealed the continued activity of transposable elements which are directly responsible for 80% of the observed variation between the isolates. While most genes are generally conserved, virulence related genes are highly variable between the isolates. Most of the variation is found in large gene clusters resulting from extensive copy-number expansion. Pangenome graph-based discovery can thus be effectively used to capture genomic variation at exceptional resolution, thereby providing a framework to study the biology and evolution of plant pathogens.

Genetic analysis of preaxial polydactyly: identification of novel variants and the role of ZRS duplications in a Chinese cohort of 102 cases.

Preaxial polydactyly (PPD) is a congenital limb malformation, previously reported to be caused primarily by variants in the ZRS and upstream preZRS regions. This study investigated genetic variations associated with PPD, focusing on point variants and copy number variations (CNVs) in the ZRS and preZRS regions. Comprehensive genetic analyses were conducted on 102 patients with PPD, including detailed clinical examinations and Sanger sequencing of the ZRS and preZRS regions. Additionally, real-time quantitative PCR (qPCR) was used to detect CNVs in the ZRS region. The evolutionary conservation and population frequencies of identified variants were also evaluated. Six point variants were identified, among which four are likely pathogenic novel variants: 93G > T (g.156584477G > T), 106G > A (g.156584464G > A), 278G > A (g.156584292G > A), and 409A > C (g.156585378A > C). Additionally, qPCR analysis revealed that 66.67% of patients exhibited ZRS duplications. Notably, these duplications were also present in cases with newly identified potential pathogenic point variants. These findings suggest the possible interaction of point variants in ZRS and preZRS through a common pathogenic mechanism, leading jointly to PPD. The findings expand the variant spectrum associated with non-syndromic polydactyly and highlight that, despite different classifications, anterior polydactyly caused by variants in ZRS and nearby regions may share common pathogenic mechanisms. The incorporation of various variant types in genetic screening can effectively enhance the rate of pathogenic variant detection and contribute to the cost-effectiveness of genetic testing for limb developmental defects, thereby promoting healthy births.

Advances in bacterial artificial chromosome (BAC) transgenic mice for gene analysis and disease research.

Transgenic mice, including those created using Bacterial Artificial Chromosomes (BACs), are artificial manipulations that have become critical tools for studying gene function. While conventional transgenic techniques face challenges in achieving precise expression of foreign genes in specific cells and tissues, BAC transgenic mice offer a solution by incorporating large DNA segments that can include entire expression units with tissue-specific enhancers. This review provides a thorough examination of BAC transgenic mouse technology, encompassing both traditional and humanized models. We explore the benefits and drawbacks of BAC transgenesis compared to other techniques such as knock-in and CRISPR/Cas9 technologies. The review emphasizes the applications of BAC transgenic mice in various disciplines, including neuroscience, immunology, drug metabolism, and disease modeling. Additionally, we address crucial aspects of generating and analyzing BAC transgenic mice, such as position effects, copy number variations, and strategies to mitigate these challenges. Despite certain limitations, humanized BAC transgenic mice have proven to be invaluable tools for studying the pathogenesis of human diseases, drug development, and understanding intricate gene regulatory mechanisms. This review discusses current topics on BAC transgenic mice and their evolving significance in biomedical research.

Genetic analysis using next-generation sequencing and multiplex ligation probe amplification in Chinese aniridia patients

BackgroundCongenital aniridia is a rare pan-ocular disease characterized by complete irideremia, partial iridocoloboma. The progressive nature of aniridia is frequently accompanied by secondary ocular complications such as glaucoma and aniridia-associated keratopathy, which can lead to severely impaired vision or blindness. The genetic basis of aniridia has been the subject of numerous studies, leading to the development of innovative therapeutic options based on PAX6 nonsense mutations. Specific knowledge of the genetics of aniridia has become increasingly important. To report the clinical features, elucidate the genetic etiology, and reveal the mutational spectrum of congenital aniridia in the Chinese population, sixty patients with congenital aniridia from 51 families were recruited. Candidate genes associated with developmental eye diseases were identified and analyzed using panel-based next-generation sequencing (NGS), and mutations were confirmed through polymerase chain reaction and Sanger sequencing. Multiplex ligation probe amplification (MLPA) of PAX6 and FOXC1 was performed to detect copy number variations in the patients without intragenic mutations.ResultsClinical examination revealed complete iris hypoplasia in 58 patients and partial iris hypoplasia in two patients. Additionally, two patients were diagnosed with Wilms’ tumor-aniridia-genital anomalies-retardation syndrome and nephroblastoma. By combining panel-based NGS and MLPA, 43 intragenic mutations or deletions of PAX6, FOXC1, and BCOR were identified in 59 patients, including 33 point mutations (76.7%) in 43 patients and 10 deletions (23.3%) in 16 patients. The total detection rate was 98.3%. Phenotypic variation was observed between and within families.ConclusionsVariations in PAX6 and its adjacent regions were the predominant causes of aniridia in China. In addition to intragenic point mutations in PAX6, deletion of PAX6 or its adjacent genes is a common cause of congenital aniridia. Furthermore, FOXC1 is an important gene associated with congenital aniridia. The combination of panel-based NGS and MLPA significantly enhanced the detection rate of gene mutations in patients with congenital aniridia.

NRXN1 as a Prognostic Biomarker: Linking Copy Number Variation to EMT and Survival in Colon Cancer

NRXN1 as a Prognostic Biomarker: Linking Copy Number Variation to EMT and Survival in Colon Cancer

Unravelling the architecture of major histocompatibility complex class II haplotypes in rhesus macaques.

The regions in the genome that encode components of the immune system are often featured by polymorphism, copy number variation, and segmental duplications. There is a need to thoroughly characterize these complex regions to gain insight into the impact of genomic diversity on health and disease. Here we resolve the organization of complete major histocompatibility complex (MHC) class II regions in rhesus macaques by using a long-read sequencing strategy (Oxford Nanopore Technologies) in concert with adaptive sampling. In particular, the expansion and contraction of the primate DRB-region appear to be a dynamic process that involves the rearrangement of different cassettes of paralogous genes. These chromosomal recombination events are propagated by a conserved pseudogene, DRB6, which features the integration of two retroviral elements. In contrast, the DRA locus appears to be protected from rearrangements, which may be owing to the presence of an adjacently located truncated gene segment, DRB9 With our sequencing strategy, the annotation, evolutionary conservation, and potential function of pseudogenes can be reassessed, an aspect that was neglected by most genome studies in primates. Furthermore, our approach facilitates the characterization and refinement of an animal model essential to study human biology and disease.

Locoregional event or dyssynchronous distant metastasis: clinicopathological and molecular analysis of contralateral axillary lymph node metastasis in breast cancer patients.

Contralateral axillary lymph node metastasis (CAM) is a rare clinical condition in patients with breast cancer (BC). CAM can be either a locoregional event or a distant metastasis. Molecular application for clonal evolution in BC has not been reported in CAM cases. We studied six patients with CAM with clinical, pathological and/or molecular evidence of distant metastasis; those patients had poor outcomes. Two cases with molecular analysis of paired primary and CAM established clonal evolution of the CAM with its corresponding primary with additional molecular alteration, increased tumour mutation burden, and copy number variations (CNVs) in the CAMs. Four cases containing alterations from genes potentially modulate chromatin organization, supporting chromatin and subsequent transcriptional signature changes are essential in CAM. Molecular analysis is critical to establish the connection between CAM and its primary counterpart. Distant CAM shows clonal evolution compared with its corresponding primary with additional molecular alterations, increased mutation burden and/or copy number variations. CAM should be evaluated individually and handled in a personalized fashion. Evidence of a true metastatic CAM can be supported by distant metastasis to other organs, specific morphological features and/or clonal evolution.

Single-cell RNA-seq analysis revealed the stemness of a specific cluster of B cells in acute lymphoblastic leukemia progression.

Childhood acute lymphoblastic leukemia (ALL) is a common pediatric cancer. The heterogeneous characterization of B cells in ALL progression poses new challenges to researchers. We used single-cell sequencing to explore the critical role of B cells in regulating the ALL immune microenvironment. We collected the single cell (sc) RNA-seq data of ALL and health sample from the gene expression omnibus (GEO) database, the "Seurat" and "harmony" R package was used for quality control and scRNA-seq analysis, in which the CellMarker2.0 database was used for cell type annotation. Subsequently, the FindAllMarkers function was used to identify the differentially expressed genes (DEGs) among various cell types and the DAVID database was applied for the biological process of DEGs. Then, the "inferCNV" package was used for copy number variation, regulons and cell communication were performed by SCENIC tool and CellChat package. The role of the target gene in regulating ALL progression was assessed using RT-qPCR, Transwell and scratch healing assays. We identified nine mainly cell clusters after scRNA-seq analysis, in which the B cells had higher infiltration proportion in the ALL samples and were sub-clustered into five cell sub-groups. The B cells 1 is closely associated with cell proliferation and stemness (TNFAIP3 and KDM5B), and the significant CNV of amplification occurred on chr6 and chr21 that supported stemness of B cells1. RXRB is a key transcription factor mediated the proliferation of B cells 1, which in turn suppressed hematopoietic stem cells (HSCs) proliferation and promoted cytotoxic NK/T cells activation through diverse cell communication ways. One of the key regulators of B cells is MYC, which promotes the migration and invasive ability of cell line leukemia cell lines. This study reveals the stemness characteristics of B cells and their critical role in ALL progression, a finding that provides new potential directions for the development of targeted therapies against ALL.