Immunoglobulin Heavy Chain Locus Research Articles

Sequence variants influencing the regulation of serum IgG subclass levels

Immunoglobulin G (IgG) is the main isotype of antibody in human blood. IgG consists of four subclasses (IgG1 to IgG4), encoded by separate constant region genes within the Ig heavy chain locus (IGH). Here, we report a genome-wide association study on blood IgG subclass levels. Across 4334 adults and 4571 individuals under 18 years, we discover ten new and identify four known variants at five loci influencing IgG subclass levels. These variants also affect the risk of asthma, autoimmune diseases, and blood traits. Seven variants map to the IGH locus, three to the Fcγ receptor (FCGR) locus, and two to the human leukocyte antigen (HLA) region, affecting the levels of all IgG subclasses. The most significant associations are observed between the G1m (f), G2m(n) and G3m(b*) allotypes, and IgG1, IgG2 and IgG3, respectively. Additionally, we describe selective associations with IgG4 at 16p11.2 (ITGAX) and 17q21.1 (IKZF3, ZPBP2, GSDMB, ORMDL3). Interestingly, the latter coincides with a highly pleiotropic signal where the allele associated with lower IgG4 levels protects against childhood asthma but predisposes to inflammatory bowel disease. Our results provide insight into the regulation of antibody-mediated immunity that can potentially be useful in the development of antibody based therapeutics.

Genetically and Functionally Distinct Immunoglobulin Heavy Chain Locus Duplication in Bats.

The genetic locus encoding immunoglobulin heavy chains (IgH) is critical for vertebrate humoral immune responses and diverse antibody repertoires. Immunoglobulin and T cell receptor loci of most bat species have not been annotated, despite the recurrent role of bats as viral reservoirs and sources of zoonotic pathogens. We investigated the genetic structure and function of IgH loci across the largest bat family, Vespertilionidae, focusing on big brown bats (Eptesicus fuscus ). We discovered that E. fuscus and ten other species within Vespertilionidae have two complete, functional, and distinct immunoglobulin heavy chain loci on separate chromosomes. This locus organization is previously unknown in mammals, but is reminiscent of more limited duplicated loci in teleost fish. Single cell transcriptomic data validate functional rearrangement and expression of immunoglobulin heavy chains of both loci in the expressed repertoire of Eptesicus fuscus , with maintenance of allelic exclusion, bias of usage toward the smaller and more compact IgH locus, and evidence of differential selection of antigen-experienced B cells and plasma cells varying by IgH locus use. This represents a unique mechanism for mammalian humoral immunity and may contribute to bat resistance to viral pathogenesis.

Exploration of the intracellular chiral metabolome in pediatric BCP-ALL: a pilot study investigating the metabolic phenotype of IgH locus aberrations

Background and aimsAberrations in the immunoglobulin heavy chain (IgH) locus are associated with poor prognosis in pediatric precursor B-cell acute lymphoblastic leukemia (BCP-ALL) patients. The primary objective of this pilot study is to enhance our understanding of the IgH phenotype by exploring the intracellular chiral metabolome.Materials and methodsLeukemia cells were isolated from the bone marrow of BCP-ALL pediatric patients at diagnosis. The samples’ metabolome and transcriptome were characterized using untargeted chiral metabolomic and next-generation sequencing transcriptomic analyses.ResultsFor the first time D- amino acids were identified in the leukemic cells’ intracellular metabolome from the bone marrow niche. Chiral metabolic signatures at diagnosis was indicative of a resistant phenotype. Through integrated network analysis and Pearson correlation, confirmation was obtained regarding the association of the IgH phenotype with several genes linked to poor prognosis.ConclusionThe findings of this study have contributed to the understanding that the chiral metabolome plays a role in the poor prognosis observed in an exceptionally rare patient cohort. The findings include elevated D-amino acid incorporation in the IgH group, the emergence of several unknown, potentially enantiomeric, metabolites, and insights into metabolic pathways that all warrant further exploration.

IGLoo: Profiling the Immunoglobulin Heavy chain locus in Lymphoblastoid Cell Lines with PacBio High-Fidelity Sequencing reads.

New high-quality human genome assemblies derived from lymphoblastoid cell lines (LCLs) provide reference genomes and pangenomes for genomics studies. However, the characteristics of LCLs pose technical challenges to profiling immunoglobulin (IG) genes. IG loci in LCLs contain a mixture of germline and somatically recombined haplotypes, making them difficult to genotype or assemble accurately. To address these challenges, we introduce IGLoo, a software tool that implements novel methods for analyzing sequence data and genome assemblies derived from LCLs. IGLoo characterizes somatic V(D)J recombination events in the sequence data and identifies the breakpoints and missing IG genes in the LCL-based assemblies. Furthermore, IGLoo implements a novel reassembly framework to improve germline assembly quality by integrating information about somatic events and population structural variantions in the IG loci. We applied IGLoo to study the assemblies from the Human Pangenome Reference Consortium, providing new insights into the mechanisms, gene usage, and patterns of V(D)J recombination, causes of assembly fragmentation in the IG heavy chain (IGH) locus, and improved representation of the IGH assemblies.

Reprogramming human B cells with custom heavy-chain antibodies.

The immunoglobulin locus of B cells can be reprogrammed by genome editing to produce custom or non-natural antibodies that are not induced by immunization. However, current strategies for antibody reprogramming require complex expression cassettes and do not allow for customization of the constant region of the antibody. Here we show that human B cells can be edited at the immunoglobulin heavy-chain locus to express heavy-chain-only antibodies that support alterations to both the fragment crystallizable domain and the antigen-binding domain, which can be based on both antibody and non-antibody components. Using the envelope protein (Env) from the human immunodeficiency virus as a model antigen, we show that B cells edited to express heavy-chain antibodies to Env support the regulated expression of B cell receptors and antibodies through alternative splicing and that the cells respond to the Env antigen in a tonsil organoid model of immunization. This strategy allows for the reprogramming of human B cells to retain the potential for in vivo amplification while producing molecules with flexibility of composition beyond that of standard antibodies.

Adaptive Evolution of Two Distinct Adaptive Haplotypes of Neanderthal Origin at the Immunoglobulin Heavy-chain Locus in East Asian and European Populations.

Immunoglobulins (Igs) have a crucial role in humoral immunity. Two recent studies have reported a high-frequency Neanderthal-introgressed haplotype throughout Eurasia and a high-frequency Neanderthal-introgressed haplotype specific to southern East Asia at the immunoglobulin heavy-chain (IGH) gene locus on chromosome 14q32.33. Surprisingly, we found the previously reported high-frequency Neanderthal-introgressed haplotype does not exist throughout Eurasia. Instead, our study identified two distinct high-frequency haplotypes of putative Neanderthal origin in East Asia and Europe, although they shared introgressed alleles. Notably, the alleles of putative Neanderthal origin reduced the expression of IGHG1 and increased the expression of IGHG2 and IGHG3 in various tissues. These putatively introgressed alleles also affected the production of IgG1 upon antigen stimulation and increased the risk of systemic lupus erythematosus. Additionally, the greatest genetic differentiation across the whole genome between southern and northern East Asians was observed for the East Asian haplotype of putative Neanderthal origin. The frequency decreased from southern to northern East Asia and correlated positively with the genome-wide proportion of southern East Asian ancestry, indicating that this putative positive selection likely occurred in the common ancestor of southern East Asian populations before the admixture with northern East Asian populations.

Variation of the 3'RR1 HS1.2 Enhancer and Its Genomic Context.

In humans, the HS1.2 enhancer in the Ig heavy-chain locus is modular, with length polymorphism. Previous studies have shown the following features for this variation: (i) strong population structuring; (ii) association with autoimmune diseases; and (iii) association with developmental changes in Ig expression. The HS1.2 region could then be considered as a contributor to inter-individual diversity in humoral response in adaptive immunity. We experimentally determined the HS1.2-length class genotype in 72 of the 1000 Genomes CEU cell lines and assigned the HS1.2 alleles to haplotypes defined by 18 landmark SNPs. We also sequenced the variable portion and ~200 bp of the flanking DNA of 34 HS1.2 alleles. Furthermore, we computationally explored the ability of different allelic arrangements to bind transcription factors. Non-random association between HS1.2 and Gm allotypes in the European population clearly emerged. We show a wealth of variation in the modular composition of HS1.2, with five SNPs further contributing to diversity. Longer alleles offer more potential sites for binding but, for same-length alleles, SNP variation creates/destroys potential binding sites. Altogether, the arrangements of modules and SNP alleles both inside and outside HS1.2 denote an organization of diversity far from randomness. In the context of the strong divergence of human populations for this genomic region and the reported disease associations, our results suggest that selective forces shaped the pattern of its diversity.

Core regions in immunoglobulin heavy chain enhancers essential for survival of non-Hodgkin lymphoma cells are identified by a CRISPR interference screen.

Chromosomal translocations in non-Hodgkin lymphoma (NHL) result in activation of oncogenes by placing them under the regulation of immunoglobulin heavy chain (IGH) super-enhancers. Aberrant expression of translocated oncogenes induced by enhancer activity can contribute to lymphomagenesis. The role of the IGH enhancers in normal B-cell development is well established, but knowledge regarding the precise mechanisms of their involvement in control of the translocated oncogenes is limited. The goal of this project was to define the critical regions in the IGH regulatory elements and identify enhancer RNAs (eRNA). We designed a sgRNA library densely covering the IGH enhancers and performed tiling CRISPR interference screens in three NHL cell lines. This revealed three regions crucial for NHL cell growth. With chromatin-enriched RNA-Seq we showed transcription from the core enhancer regions and subsequently validated expression of the eRNAs in a panel of NHL cell lines and tissue samples. Inhibition of the essential IGH enhancer regions decreased expression of eRNAs and translocated oncogenes in several NHL cell lines. The observed expression and growth patterns were consistent with the breakpoints in the IGH locus. Moreover, targeting the Eμ enhancer resulted in loss of B-cell receptor expression. In a Burkitt lymphoma cell line, MYC overexpression partially rescued the phenotype induced by IGH enhancer inhibition. Our results indicated the most critical regions in the IGH enhancers and provided new insights into the current understanding of the role of IGH enhancers in B-cell NHL. As such, this study forms a basis for development of potential therapeutic approaches.

Inference of genomic lesions from single-cell RNA-seq in myeloma improves functional intraclonal and interclonal analysis

AbstractSmoldering multiple myeloma (SMM) is an asymptomatic plasma cell (PC) neoplasm that may evolve with variable frequency into multiple myeloma (MM). SMM is initiated by chromosomal translocations involving the immunoglobulin heavy-chain locus or by hyperdiploidy and evolves through acquisition of additional genetic lesions. In this scenario, we aimed at establishing a reliable analysis pipeline to infer genomic lesions from transcriptomic analysis, by combining single-cell RNA sequencing (scRNA-seq) with B-cell receptor sequencing and copy number abnormality (CNA) analysis to identify clonal PCs at the genetic level along their specific transcriptional landscape. We profiled 20 465 bone marrow PCs derived from 5 patients with SMM/MM and unbiasedly identified clonal and polyclonal PCs. Hyperdiploidy, t(11;14), and t(6;14) were identified at the scRNA level by analysis of chimeric reads. Subclone functional analysis was improved by combining transcriptome with CNA analysis. As examples, we illustrate the different functional properties of a light-chain escape subclone in SMM and of different B-cell and PC subclones in a patient affected by Wäldenstrom macroglobulinemia and SMM. Overall, our data provide a proof of principle for inference of clinically relevant genotypic data from scRNA-seq, which in turn will refine functional annotation of the clonal architecture of PC dyscrasias.

Generation of nanobodies from transgenic ‘LamaMice’ lacking an endogenous immunoglobulin repertoire

Due to their exceptional solubility and stability, nanobodies have emerged as powerful building blocks for research tools and therapeutics. However, their generation in llamas is cumbersome and costly. Here, by inserting an engineered llama immunoglobulin heavy chain (IgH) locus into IgH-deficient mice, we generate a transgenic mouse line, which we refer to as ‘LamaMouse’. We demonstrate that LamaMice solely express llama IgH molecules without association to Igκ or λ light chains. Immunization of LamaMice with AAV8, the receptor-binding domain of the SARS-CoV-2 spike protein, IgE, IgG2c, and CLEC9A enabled us to readily select respective target-specific nanobodies using classical hybridoma and phage display technologies, single B cell screening, and direct cloning of the nanobody-repertoire into a mammalian expression vector. Our work shows that the LamaMouse represents a flexible and broadly applicable platform for a facilitated selection of target-specific nanobodies.

Three-dimensional chromatin reorganization regulates B cell development during ageing

The contribution of three-dimensional genome organization to physiological ageing is not well known. Here we show that large-scale chromatin reorganization distinguishes young and old bone marrow progenitor (pro-) B cells. These changes result in increased interactions at the compartment level and reduced interactions within topologically associated domains (TADs). The gene encoding Ebf1, a key B cell regulator, switches from compartment A to B with age. Genetically reducing Ebf1 recapitulates some features of old pro-B cells. TADs that are most reduced with age contain genes important for B cell development, including the immunoglobulin heavy chain (Igh) locus. Weaker intra-TAD interactions at Igh correlate with altered variable (V), diversity (D) and joining (J) gene recombination. Our observations implicate three-dimensional chromatin reorganization as a major driver of pro-B cell phenotypes that impair B lymphopoiesis with age.

Genome-wide 5-hydroxymethylation mapping and epigenetic pathways in multiple myeloma.

7566 Background: Multiple myeloma (MM), a B-cell neoplasm characterized by bone marrow infiltration of malignant plasma cells, is the second most common blood malignancy, with an estimated number of ~35,000 new patients annually in the United States. The molecular pathogenesis of MM is complex and involves various genetic and epigenetic alterations. Key molecular mechanisms, including chromosomal abnormalities such as translocations involving the immunoglobulin heavy chain locus and various oncogenes (e.g., MMSET, FGFR3, CCND1, MAF), alterations in epigenetic regulators (e.g., EZH2, DNMT3A), dysregulation of cell cycle control, and aberrant activation of signaling pathways (e.g., NF-kB, PI3K/AKT, and JAK/STAT), play critical roles in MM pathogenesis. However, epigenetic pathways implicated in MM has not been comprehensively investigated, partly due to technical limitations that cannot distinguish major cytosine modification types. Methods: Using the 5hmC-Seal, a highly sensitive chemical labeling technique, we profiled genome-wide 5-hydroxymethylcytosines (5hmC) in circulating cell-free DNA (cfDNA) from a population-based case-control study of MM (cases, n = 313; controls, n = 317) conducted in Canada. Results: The 5hmC modification levels were summarized for various genomic features, showing an enrichment in gene bodies and enhancer markers, consistent with the putative role of gene regulation for 5hmC modification. A genome-wide scan of gene bodies identified 771 differential features between cases and controls, adjusting for age, sex, smoking status, education, and first two principal components, at a permutation-based empirical p-value cutoff of 10-4. For instance, IL1RAP, a component of the interleukin-1 signaling cascade, may impact tumor progression and immune system evasion. Furthermore, functional analysis indicated canonical pathways associated with MM pathology and treatment, such as calcium signaling, and synthesis and secretion of cortisol/aldosterone, were enriched in the differential 5hmC features between cases and controls. Notably, the calcium signaling pathway, integral to Ca2+ transport and involved in various physiological and pathological processes, plays a critical role in MM pathogenesis. Within this pathway, the CAMK1D gene, which has been identified as a crucial regulator of tumor-intrinsic immune resistance, showed differential 5hmC level between cases and controls, highlighting a vital connection between epigenetic modifications and immune evasion mechanisms in MM. Conclusions: Leveraging a state-of-the-art technique, we identified novel epigenetic modifications and pathways in the risk of MM. This approach establishes a solid foundation for further investigating etiology of MM, deepening our understanding of the disease, and advancing the discovery of biomarkers, which could potentially guide preventive strategies.

Abstract P13: Genetic and epigenetic characterization of B-cell chronic lymphocytic leukemia with IG::BCL3-translocation provides evidence for a distinct biological entity

Abstract IG translocations occur in various B-cell neoplasms and result in the deregulation of (onco)genes due to their juxtaposition with regulatory elements in the immunoglobulin loci, predominantly the immunoglobulin heavy chain (IGH) locus (14q32). Some of these IGH translocations are pathognomonic for distinct disease entities, like those involving MYC, BCL2 or CCND1 in Burkitt, Follicular or Mantle Cell Lymphomas, respectively. In Chronic Lymphocytic Leukemia (CLL), the BCL3 gene (19q13), a transcriptional coactivator of the nuclear factor-kappaB (NF-κB) family, is a known partner gene in these translocations. Two subsets of IG::BCL3 translocation-positive B-cell neoplasms have been described that exhibit differences in chromosomal aberrations, IGHV mutation status, and histopathology [Martín-Subero et al. 2007]. In CLL, IG::BCL3 translocation is linked to a younger age at diagnosis, a more aggressive clinical course, and an atypical tumor cell phenotype [Michaux et al. 1997; Au et al. 2002]. A total of 89 B-cell neoplasms, primarily diagnosed as CLL, displaying IG::BCL3 translocation detected by fluorescence in situ hybridization (FISH), were examined. Analysis of DNA methylation and copy number aberrations (CNA) was conducted for 86 IGH::BCL3-translocated B-cell neoplasms using 850K EPIC BeadChip array data. Evaluation of chromosomal aberrations typical for CLL was moreover performed by FISH and the IGHV mutation status was determined. IGH::BCL3 breakpoint junctions were sequenced in 23 samples using targeted capture and whole-genome sequencing approaches. RNA expression of BCL3 was assessed using the HTG mRNA pan B-cell panel. In UMAP analysis of DNA methylation, CLLs with IG::BCL3 translocation exhibited segregation from other CLLs, irrespective of IGH translocations. Supervised analysis revealed global hypomethylation of B-cell neoplasms with IG::BCL3 translocation compared to other CLL. A total of 66/69 CLLs with IG::BCL3 translocation showed an unmutated IGHV status (96%). Copy number determination using BeadChip data (n=86) and FISH analysis (n=85) showed a significantly higher incidence of trisomy 12 in IG::BCL3-translocated cases compared to the general CLL population (p=0.011). Breakpoint sequencing indicated IG::BCL3 junctions to be recurrently associated with aberrant class-switch recombination at the IGH locus, involving IGHA (n=11/23), IGHG (n=5/23) and IGHM segments (n=5/23). Breakpoints at the BCL3 locus displayed two groups. 80 cases (all CLL) were located upstream of BCL3 and two other B-cell neoplasms (NHL, DLBCL) were located downstream of BCL3. BCL3 expression analysis in 15 IG::BCL3-translocated CLLs confirmed its transcriptional upregulation compared to the general CLL population. Our genetic and epigenetic analyses support the view that CLL with IG::BCL3 translocation may constitute a genetically and epigenetically distinct subtype of B-cell neoplasms, diverging from the typical CLL. Citation Format: Cosima Drewes, Cristina López, Nnamdi Okeke, Sina Hillebrecht, Petra Schütz, Anja Fischer, Anja Mottok, Susanne Bens, Christof Schneider, Stephan Stilgenbauer, Eugen Tausch, Reiner Siebert. Genetic and epigenetic characterization of B-cell chronic lymphocytic leukemia with IG::BCL3-translocation provides evidence for a distinct biological entity [abstract]. In: Proceedings of the Blood Cancer Discovery Symposium; 2024 Mar 4-6; Boston, MA. Philadelphia (PA): AACR; Blood Cancer Discov 2024;5(2_Suppl):Abstract nr P13.

Novel identification of t(14;18)(q32;q21)/IGH::MALT1 in chronic lymphocytic leukaemia.

Chronic lymphocytic leukaemia (CLL) is a clonal B-cell malignancy and remains a chronic disease despite improvements in clinical outcomes since the use of targeted therapies. Both clinical and biological parameters are important for determining prognosis. Unlike other mature B-cell lymphomas, translocations involving the immunoglobulin heavy chain (IGH) locus are uncommon in CLL. There have been few case reports of CLL harbouring t(14;18)/IGH::BCL2 and t(14;19)/IGH::BCL3. Here we describe the first two cases of patients with CLL with documented t(14;18)(q32;q21)/IGH::MALT1. Both cases in this report were associated with lower-risk biological parameters. Thus, FISH testing for MALT1 in cases with unknown IGH translocation partners in the setting of CLL should be implemented in clinical practice to better define such cases.

Genome-Wide Mapping of R-Loops in Single Cells Reveals Cell-Type Specific Roles for R-Loops in Hematopoietic Cell Identity

R-loops are three-stranded structures composed of an RNA-DNA hybrid and a single strand of DNA. R-loops play critical roles in gene regulation and pathologic roles in DNA damage response. Current methods to map R-loops require at least 500,000 cells. Consequently, R-loop characterization in primary cells is limited. Furthermore, there are no genomic tools to identify R-loops in single cells. We therefore developed here methods to map genome-wide R-loops at single cell resolution. R-loop mapping in primary stem and mature hematopoietic cell populations, and individual single cells revealed striking cell-type specific R-loops. Current methods to map R-loops utilize immunoprecipitation with a monoclonal antibody (clone “S9.6”) or catalytically inactive, but R-loop binding competent, RNAseH1. Motivated by success mapping chromatin modifications in single cells through fusion of Tn5 transposase to a nanobody as well as insertion of T7 promoters to amplify DNA at sites of transposition, we combined both techniques to identify R-loops in limited cell numbers, down to the single cell level. We used a nanobody-Tn5 fusion to identify S9.6 and developed an orthogonal recombinant fusion protein of enzymatic dead RNAseH1 fused to Tn5 (Figure A). We first applied our nanobody-Tn5 method to identify R-loops bound by S9.6 in mouse lineage-negative c-Kit + bone marrow cells in biological duplicates of increasingly reduced cell numbers (64,000, 32,000, 16,000, and 8,000 cells). This revealed remarkable reproducibility of R-loop detection and characteristics. R-loops identified were sensitive to RNAseH1 and enriched at sites with G/C skew and mitochondrial DNA (a site with abundant physiologic R-loops), suggesting authentic, bona fide R-loops mapped in as few 8,000 cells. We next evaluated R-loops across FACS-isolated hematopoietic stem and mature cells from mouse and human bone marrow. Mapping of R-loops in 10,000 cells in duplicate revealed reproducible R-loops which were characteristic of each cell population. Hierarchical clustering of R-loop profiles delineated mature from stem and progenitor cells and discovered increased abundance of genic R-loops in hematopoietic stem and progenitors relative to mature cells (Figure B). Application of our enzymatic dead RNaseH1/Tn5 fusion protein to CD34 + cells revealed a similar genome-wide distribution of R-loops as with the S9.6/nanobody-Tn5 method. There was high correlation of long- and short-term HSC-specific R-loops with sites characteristic of active transcription (based on H3K4me1/2/3 as well as H3K27Ac). Transcription factor motifs activated in unique hematopoietic cell types were enriched at R-loops within the same cell types. For example, GATA motif usage was enriched at R-loops in CMP, MEP, and erythroid precursors. We also detected massive increases in R-loop abundance at the immunoglobulin heavy chain locus in primary B-cells stimulated to undergo class switch recombination. This provides further proof of our low input method to identify R-loops, as physiologic R-loops are known to occur at this locus to promote class switch recombination. Despite recent advances in single cell genomics there are no single cell maps of R-loops. We therefore profiled R-loops using our nanobody-Tn5, low-input S9.6 CUT&Tag approach in individual human CD34 + and mouse c-Kit + cells. We obtained 1,579 single-cell profiles from human and 1,716 from mouse. Uniform manifold approximation and projection (UMAP) identified 12 clusters in human and 9 mouse hematopoietic clusters. Aggregated single-cell R-loop profiles closely resembled bulk profiles indicating that single-cell data captured features of multi-cell maps. Pseudotime analyses of R-loops inferred LT-HSCs as the shared root of hematopoiesis in both mouse and human and identified seven terminal states without prior knowledge of the number of branches in the hematopoietic development. These data provide the first maps of R-loops in primary normal hematopoietic cells and identify scheduled, physiologic cell-type specific R-loops which have not previously been uncovered. The atlas of R-loops across hematopoiesis generated here will motivate future studies to understand the roles of R-loops in hematopoietic differentiation. Moreover, the methods presented map R-loop abundance at nucleotide resolution in primary and limited cell types which can be used for wide-reaching applications.

Revealing Novel Mechanisms Underlying Inactivation of Tumor Suppressor Genes on Duplicated Chromosomes in Multiple Myeloma

INTRODUCTION: Multiple myeloma (MM) evolution is complex and heterogeneous. Hyperdiploidy (HRD) and translocations affecting the immunoglobulin heavy chain (IGH) locus are historically considered initiating genomic events of MM. The potential impact of genomic events acquired before known MM initiating events has never been addressed. METHODS: To investigate whether genomic deletions are acquired before and after known MM initiating events we interrogated whole-genome sequencing (WGS) data from patients with newly diagnosed MM (NDMM, n=319) and relapsed MM (RRMM, n=59). Our newly developed analytical and chronological workflow integrating single nucleotide variants (SNV), structural variants (SV), and copy number variants (CNV) comprises two main steps. First, we estimated the molecular time (i.e. corrected ratio between duplicated and non-duplicated clonal SNV) of large clonal chromosomal duplications and identified the earliest set of chromosomal gains in each patient. Second, within each early large chromosomal gain we identified clonal SV mediating CNV loss. A deletion on a gain can generate three possible scenarios: 1) one of the duplicated alleles is lost after the gain (i.e. post-gain) causing a CNV jump from 3:1 to 2:1 (total alleles : minor alleles); 2) there is a deletion before the duplication (i.e., pre-gain) causing a CNV jump from 3:1 to 1:0. 3) the deletion occurs on the minor, non-duplicated allele, causing a CNV jump from 3:1 to 2:0. Timing the deletion in relation with the chromosomal duplication is impossible in this scenario. RESULTS: Molecular time data were successfully generated for 249/319 (78%) NDMM and 51/59 (86%) RRMM patients. Restricting our analysis to NDMM with HRD without canonical IGH translocations, 16/170 (9%) of patients acquired deletions before the earliest multi-chromosomal gains, suggesting MM precursors can acquire deletions before HRD. Investigating the entire series, post-gain deletions were observed in 126/417 (30%) samples considering both early and late time windows. Leveraging a background model, we demonstrated that pre-gain events involved more tumor-suppressor genes (TSG) than expected by chance, including TCF3, ATM and TRAF3. In contrast, oncogenes were involved less than expected. In post-gain deletions, both oncogenes and TSG were involved more than expected by chance . To validate and assess the impact of deletions on driver gene expression we investigated WGS and RNAsequencing data from the MMRF CoMMpass study (n=752 NDMM). Because of the low coverage not allowing for molecular time estimation, we limited our analysis to HRD without IGH translocations. Pre-gain and post-gain deletions were observed in 47/431 (11%) and 225/431 (52%) of patients, respectively. We defined loss and gain of function events based on whether the expression level of a gene affected by the deletion was in the first or fourth quartile, respectively. Pre-gain deletions were mostly associated with downregulation of TSG expression [n=31 events in 13/431 (3%) patients]. In contrast,post-gain deletions had a more heterogenous impact with loss- and gain-of-function events. Gain-of-function events were driven by two main mechanisms: 1) the deletion joined an oncogene with a distal regulatory region inducing its overexpression [n=44 events in 6/431 (1.3%) patients]; 2) the deletion caused a new and expressed fusion [n=231 events in 109/431 (25%) patients], resulting in either loss- or gain-of-function. Surprisingly, post-gain deletions had also a major impact on TSG expression. In 60 patients (14%), we observed 146 post-gain deletions where the affected tumor suppressor gene (TSG) expression was downregulated to the level of cases with monoallelic and biallelic deletions, even though two alleles were retained. Finally, to validate these findings, we investigated 16 RRMM patients with available WGS, scATAC-seq and scRNA-seq and observed additional evidence of TSG downregulation after both pre- and post-gain deletions. CONCLUSION: Leveraging a large cohort of NDMM we show that somatic deletions can be acquired before HRD trisomies that are assumed to be initiating events. Furthermore, post-gain deletions emerged as a new mechanism inducing TSG down-regulation, despite an apparently diploid gene status.

Unraveling Diverse Mechanisms of Complex Structural Variant Interactions through Multiomic Data in Multiple Myeloma

Introduction: Structural variants (SVs) play a role in proliferation of plasma cells that characterizes multiple myeloma (MM). Several hallmark SVs have been identified in MM, including translocations involving the immunoglobulin heavy chain locus and several partner genes, as well as deletions and duplications affecting key genes such as TP53, RB1, and MYC. Complex SVs such as templated insertions, chromothripsis, and chromoplexy are associated with disease progression but have not yet systematically been studied. Methods: Paired short-read (Illumina, average depth 75x), long-read HiFi (PacBio, 16x), optical genome mapping (OGM; Bionano Genomics, 341x) and Micro-C (Cantata Bio, 45x) data were sequenced from 8 relapsed MM patient-derived xenograft samples and 2 cell lines, covering t(11;14), t(4;14), and hyperdiploid subgroups. Reads were aligned to the hg38 reference genome while complex SVs (chromothripsis, chromoplexy and templated insertion) were systematically identified and accurately reconstructed by combining short-read (Manta), HiFi (pbsv), OGM, and Micro-C data (EagleC). Chromosome organization including loops, topologically associated domains (TADs) and A/B compartments were called from Micro-C data (Mustache and Juicer). Haplotype phasing was conducted using small variants detected from HiFi data. De novo assembly of the genome was conducted using HiFi and Micro-C data and compared to the reference genome. Reconstructed derivative chromosome interactions due to complex SVs were further identified by aligning Micro-C reads to the newly assembled genomes. Previously identified super-enhancers from H3K27Ac ChIP-seq from MM cell lines were mapped onto these SVs and expression of target genes assessed by RNA-seq. Results: 1,340 SVs were found in 10 samples using OGM of which 828 were identified in short-read WGS data. 16 complex SVs including chromothripsis, chromoplexy and templated insertions were detected in 10 samples, and we describe two (Fig.1) in detail here. A complex templated insertion consisting of a t(2;6;8) was found in a t(11;14) PDX sample with copy number gains at breakpoints which could not be resolved from short-read data alone. OGM data revealed a single contig consisting of DNA from chromosomes 2, 6, and 8. Micro-C data revealed interactions between these chromosomes, specifically the gained regions on chromosomes 2 and 8 showed more interactions with chromosome 6 than with other chromosomes, indicating insertions into chromosome 6. As a result, both MYC at chromosome 8 and GALM at chromosome 2 were inserted into the TXNDC5 locus, containing a known MM super-enhancer, leading to the over-expression of both MYC and GALM (log 2FC=1.7 and 1.0) in this sample. A de novo genome assembly indicated neo-TAD formation encompassing the super-enhancer and both genes. In coMMpass dataset, high expression of GALM and MYC are significantly associated with inferior overall (p=0.002 and 0.05, logrank test) and progression-free survival (p=0.01 and 0.09). Another complex templated insertion consisting of a t(3;4;16) was identified in a hyperdiploid PDX sample, again with copy number gains at breakpoints. Although the short-read data indicated an assembly similar to the previous templated insertion SV, the OGM and Micro-C data indicated a 3-way chromosome swap where the short arm of chromosome 3 was translocated to the short arm of chromosome 4, the short arm of chromosome 4 was translocated to the long arm of chromosome 16, and the long arm of chromosome 16 was translocated to the short arm of chromosome 3. Separate contigs for the t(4;16), t(3;16) and t(3;4) were confirmed by OGM data and only 2-way chromosomal interactions were seen in the Micro-C data. This complex event led to numerous oncogenes juxtaposed to super-enhancers, which caused over-expression of target genes such as ACD and RANBP10 (log 2FC=1.0 and 0.4), both of which were on chromosome 16 and are significantly associated with inferior overall (p=0.02 and p=0.004) and progression-free survival (p=0.003 and p=0.005). Conclusion: By utilizing multiomic techniques we were able to reconstruct complex SV events, showing different mechanisms of generating templated insertion events and identifying their biological consequences. We demonstrated how these complex events could potentially facilitate tumor proliferation via engaging the super-enhancers and regulating the expression of key oncogenes.

Minimal residual disease detection by next-generation sequencing of different immunoglobulin gene rearrangements in pediatric B-ALL

While the prognostic role of immunoglobulin heavy chain locus (IGH) rearrangement in minimal residual disease (MRD) in pediatric B-acute lymphoblastic leukemia (B-ALL) has been reported, the contribution of light chain loci (IGK/IGL) remains elusive. This study is to evaluate the prognosis of IGH and IGK/IGL rearrangement-based MRD detected by next-generation sequencing in B-ALL at the end of induction (EOI) and end of consolidation (EOC). IGK/IGL rearrangements identify 5.5% of patients without trackable IGH clones. Concordance rates for IGH and IGK/IGL are 79.9% (cutoff 0.01%) at EOI and 81.0% (cutoff 0.0001%) at EOC, respectively. Patients with NGS-MRD < 0.01% at EOI or <0.0001% at EOC present excellent outcome, with 3-year event-free survival rates higher than 95%. IGH-MRD is prognostic at EOI/EOC, while IGK-MRD at EOI/EOC and IGL-MRD at EOI are not. At EOI, NGS identifies 26.2% of higher risk patients whose MRD < 0.01% by flow cytometry. However, analyzing IGK/IGL along with IGH fails to identify additional higher risk patients both at EOI and at EOC. In conclusion, IGH is crucial for MRD monitoring while IGK and IGL have relatively limited value.

Identification of MYC-Driven High-Grade B-Cell Lymphoma Using Deep Learning-Based Whole Slide Image Analysis

Introduction High-grade B-cell lymphoma (HGBL) is an aggressive lymphoma that often harbors MYC rearrangements ( MYC-R) and molecular signatures attributed to aberrant MYC activation (Olszewski et al. Blood 2022). Identifying and classifying HGBL is challenging; current classification systems recognize diffuse large B cell lymphoma/HGBL with MYC and BCL2 rearrangements ( MYC-R/ BCL2-R; double-hit; defined molecularly) and HGBL-not otherwise specified (defined morphologically) in which MYC-R occur in up to 45% of cases and the double-hit signature (DHITsig) occurs in 54% of cases (Alaggio et al. Leukemia 2022, Campo et al. Blood 2022, Olszewski et al. Blood 2022). Existing methods for molecular classification, such as fluorescence in situ hybridization (FISH), are expensive, time-consuming and not widely available, and morphological classification is subjective and associated with high inter-reader variability (Natkunam et al. Histopathology 2023). Therefore, we applied a deep-learning approach to identify MYC-driven HGBL from whole-slide images (WSIs) of ubiquitously available hematoxylin and eosin-stained slides. Methods The model was trained on a real-world data set containing 600 WSIs from multiple sites using MYC-R status determined by FISH as a label. The model was evaluated on an independent test set comprised of 287 WSIs from the GOYA study (ClinicalTrials.gov identifier: NCT01287741). WSIs were scanned with a Roche Ventana DP200 scanner at 0.25 μm/px. Model architecture extracted cytological features from single cells and architectural features from larger tissue regions, enabling the quantification of high-grade morphology characterized by monomorphic sheets of dense cells with round, intermediately sized nuclei and finely dispersed chromatin. Model predictions were compared with MYC-R and BCL2-R with the immunoglobulin heavy chain locus (IGH), gene expression signatures (including DHITsig and cell of origin [COO]), gene mutation signatures obtained by next generation sequencing, computationally derived morphological measurements, and morphological evaluation by hematopathologists. MCD ( MYD88/CD79B mutations) and A53 ( TP53 mutations) genetic subtypes were determined by LymphGen. Statistical comparisons were made using Kendall's tau-b (τb) correlation for continuous variables and Fisher's exact test with conditional maximum likelihood estimated odds ratios (ORs) for categorical variables. Results In the test set, the model distinguished between cases with and without MYC-R (IGH) with an area under the receiver operating characteristic curve of 0.85, sensitivity of 0.95, specificity of 0.59, positive predictive value of 0.16, and negative predictive value of 0.99. The model correctly classified 21/22 MYC-R (IGH) cases and all four MYC-R/ BCL2-R (IGH) double-hit cases. Of DHITsig cases, the model classified 25/33 as MYC-driven HGBL. Model scores correlated with MYC expression (τb = 0.25; p &amp;lt; 0.0001) and Ki67 expression (τb = 0.15, p &amp;lt; 0.0001) ( Figure 1A). Tumors classified as MYC-driven HGBL were enriched for the non-germinal center B-cell-like COO (OR 2.0; p &amp;lt; 0.01) and the MCD genetic subtype (OR 1.9; p &amp;lt; 0.05), and depleted for the A53 genetic subtype (OR 0.3; p &amp;lt; 0.001). Additionally, enrichment was observed for MCD hallmark mutations in MYD88 (OR 1.9; p &amp;lt; 0.05), CD79b (OR 4.6; p &amp;lt; 0.001) and CDKN2A (OR 3.6; p &amp;lt; 0.0001) ( Figure 1A). Cell density (τb = 0.30; p &amp;lt; 0.0001), mean nuclei roundness (τb = 0.15; p &amp;lt; 0.001), coefficient of variation of nucleus roundness (τb = −0.19; p &amp;lt; 0.0001) and size (τb = −0.29; p &amp;lt; 0.0001), and mean nuclear pixel intensity (τb = −0.36; p &amp;lt; 0.0001) were associated with positive model predictions ( Figure 1A) corresponding to high-grade morphology. WSIs labeled as having high-grade cytomorphology by hematopathologists also had high model scores (p = 0.07; OR 3.5). Conclusions Our deep learning model, trained using MYC-R status, identified MYC-driven HGBL by enriching for cases with MYC-R, MYC overexpression, molecular gene expression profiles associated with aberrant MYC activation and cell proliferation, and high-grade morphology. The model also identified molecular characteristics other than MYC-R, such as MCD genetic subtype, associated with increased MYC expression (Schmitz et al. N Engl J Med 2018, Lacy et al. Blood 2020, Varano et al. Nature 2017), which converge on a common phenotype and high-grade morphology ( Figure 1B).

Reproducible Bioinformatics Analysis Workflows for Detecting IGH Gene Fusions in B-Cell Acute Lymphoblastic Leukaemia Patients.

B-cell acute lymphoblastic leukaemia (B-ALL) is characterised by diverse genomic alterations, the most frequent being gene fusions detected via transcriptomic analysis (mRNA-seq). Due to its hypervariable nature, gene fusions involving the Immunoglobulin Heavy Chain (IGH) locus can be difficult to detect with standard gene fusion calling algorithms and significant computational resources and analysis times are required. We aimed to optimize a gene fusion calling workflow to achieve best-case sensitivity for IGH gene fusion detection. Using Nextflow, we developed a simplified workflow containing the algorithms FusionCatcher, Arriba, and STAR-Fusion. We analysed samples from 35 patients harbouring IGH fusions (IGH::CRLF2 n = 17, IGH::DUX4 n = 15, IGH::EPOR n = 3) and assessed the detection rates for each caller, before optimizing the parameters to enhance sensitivity for IGH fusions. Initial results showed that FusionCatcher and Arriba outperformed STAR-Fusion (85-89% vs. 29% of IGH fusions reported). We found that extensive filtering in STAR-Fusion hindered IGH reporting. By adjusting specific filtering steps (e.g., read support, fusion fragments per million total reads), we achieved a 94% reporting rate for IGH fusions with STAR-Fusion. This analysis highlights the importance of filtering optimization for IGH gene fusion events, offering alternative workflows for difficult-to-detect high-risk B-ALL subtypes.