Epstein-Barr Virus Orchestrates Spatial Reorganization and Immunomodulation within the Classic Hodgkin Lymphoma Tumor Microenvironment.

Classic Hodgkin Lymphoma (cHL) is a tumor composed of rare malignant Hodgkin and Reed-Sternberg (HRS) cells nested within a T-cell rich inflammatory immune infiltrate. cHL is associated with Epstein-Barr Virus (EBV) in 25% of cases. The specific contributions of EBV to the pathogenesis of cHL remain largely unknown, in part due to technical barriers in dissecting the tumor microenvironment (TME) in high detail. Herein, we applied multiplexed ion beam imaging (MIBI) spatial pro-teomics on 6 EBV-positive and 14 EBV-negative cHL samples. We identify key TME features that distinguish between EBV-positive and EBV-negative cHL, including the relative predominance of memory CD8 T cells and increased T-cell dysfunction as a function of spatial proximity to HRS cells. Building upon a larger multi-institutional cohort of 22 EBV-positive and 24 EBV-negative cHL samples, we orthogonally validated our findings through a spatial multi-omics approach, coupling whole transcriptome capture with antibody-defined cell types for tu-mor and T-cell populations within the cHL TME. We delineate contrasting transcriptomic immunological signatures between EBV-positive and EBV-negative cases that differently impact HRS cell proliferation, tumor-immune interactions, and mecha-nisms of T-cell dysregulation and dysfunction. Our multi-modal framework enabled a comprehensive dissection of EBV-linked reorganization and immune evasion within the cHL TME, and highlighted the need to elucidate the cellular and molecular fac-tors of virus-associated tumors, with potential for targeted therapeutic strategies.

Liquid biopsy-based circulating tumour (ct)DNA analysis of a spectrum of myeloid and lymphoid malignancies yields clinically actionable results.

AIMS: Liquid biopsy (LBx)-based next-generation sequencing (NGS) of circulating tumour DNA (ctDNA) can facilitate molecular profiling of haematopoietic neoplasms (HNs), particularly when tissue-based NGS is infeasible. METHODS AND RESULTS: We studied HN LBx samples tested with FoundationOne Liquid CDx, FoundationOne Liquid, or FoundationACT between July 2016 and March 2022. We identified 271 samples: 89 non-Hodgkin lymphoma (NHL), 43 plasma-cell neoplasm (PCN), 41 histiocytoses, 27 myelodysplastic syndrome (MDS), 25 diffuse large B-cell lymphoma (DLBCL), 22 myeloproliferative neoplasm (MPN), 14 Hodgkin lymphoma (HL), and 10 acute myeloid leukaemia (AML). Among 73.4% with detectable pathogenic alterations, median maximum somatic allele frequency (MSAF) was 16.6%, with AML (36.2%), MDS (19.7%), and MPN (44.5%) having higher MSAFs than DLBCL (3.9%), NHL (8.4%), HL (1.5%), PCN (2.8%), and histiocytoses (1.8%) (P = 0.001). LBx detected characteristic alterations across HNs, including in TP53, KRAS, MYD88, and BTK in NHLs; TP53, KRAS, NRAS, and BRAF in PCNs; IGH in DLBCL; TP53, ATM, and PDCD1LG2 in HL; BRAF and MAP2K1 in histiocytoses; TP53, SF3B1, DNMT3A, TET2, and ASXL1 in MDS; JAK2 in MPNs; and FLT3, IDH2, and NPM1 in AML. Among 24 samples, the positive percent agreement by LBx was 75.7% for variants present in paired buffy coat, marrow, or tissues. Also, 75.0% of pairs exhibited alterations only present on LBx. These were predominantly subclonal (clonal fraction of 3.8%), reflecting the analytical sensitivity of LBx. CONCLUSION: These data demonstrate that LBx can detect relevant genomic alterations across HNs, including at low clonal fractions, suggesting a potential clinical utility for identifying residual or emerging therapy-resistant clones that may be undetectable in site-specific tissue biopsies.

MAPS: pathologist-level cell type annotation from tissue images through machine learning.

Highly multiplexed protein imaging is emerging as a potent technique for analyzing protein distribution within cells and tissues in their native context. However, existing cell annotation methods utilizing high-plex spatial proteomics data are resource intensive and necessitate iterative expert input, thereby constraining their scalability and practicality for extensive datasets. We introduce MAPS (Machine learning for Analysis of Proteomics in Spatial biology), a machine learning approach facilitating rapid and precise cell type identification with human-level accuracy from spatial proteomics data. Validated on multiple in-house and publicly available MIBI and CODEX datasets, MAPS outperforms current annotation techniques in terms of speed and accuracy, achieving pathologist-level precision even for typically challenging cell types, including tumor cells of immune origin. By democratizing rapidly deployable and scalable machine learning annotation, MAPS holds significant potential to expedite advances in tissue biology and disease comprehension.

Cutaneous Manifestations of Myeloid Neoplasms Exhibit Broad and Divergent Morphologic and Immunophenotypic Features but Share Ancestral Clonal Mutations With Bone Marrow.

In this study, we performed a comprehensive molecular analysis of paired skin and peripheral blood/bone marrow (BM) samples from 17 patients with cutaneous myeloid or cutaneous histiocytic-dendritic neoplasms. The cutaneous manifestations included 10 patients with cutaneous acute myeloid leukemia (c-AML), 2 patients with full or partial Langerhans cell differentiation, 2 patients with blastic plasmacytoid dendritic cell neoplasms (BPDCN), 1 patient with both Langerhans cell differentiation and BPDCN, and 2 patients with full or partial indeterminate dendritic cell differentiation. Seven of the 10 c-AML patients (70%) exhibited concurrent or subsequent marrow involvement by acute myeloid leukemia, with all 7 cases (100%) demonstrating shared clonal mutations in both the skin and BM. However, clonal relatedness was documented in one additional case that never had any BM involvement. Nevertheless, NPM1 mutations were identified in 7 of the 10 (70%) of these c-AML cases while one had KMT2A rearrangement and one showed inv(16). All 3 patients (100%) with Langerhans cell neoplasms, 2 patients with BPDCN (100%), and one of the 2 patients (50%) with other cutaneous dendritic cell neoplasms also demonstrated shared mutations between the skin and concurrent or subsequent myeloid neoplasms. Both BM and c-AML shared identical founding drivers, with a predominance of NPM1, DNMT3A, and translocations associated with monocytic differentiation, with common cutaneous-only mutations involving genes in the signal transduction and epigenetic pathways. Cutaneous histiocytic-dendritic neoplasms shared founding drivers in ASXL1, TET2, and/or SRSF2. However, in the Langerhans cell histiocytosis or histiocytic sarcoma cases, there exist recurrent secondary RAS pathway hits, whereas cutaneous BPDCN cases exhibit copy number or structural variants. These results enrich and broaden our understanding of clonally related cutaneous manifestations of myeloid neoplasms and further illuminate the highly diverse spectrum of morphologic and immunophenotypic features they exhibit.

Slide-tags enables single-nucleus barcoding for multimodal spatial genomics.

Recent technological innovations have enabled the high-throughput quantification of gene expression and epigenetic regulation within individual cells, transforming our understanding of how complex tissues are constructed1-6. However, missing from these measurements is the ability to routinely and easily spatially localize these profiled cells. We developed a strategy, Slide-tags, in which single nuclei within an intact tissue section are tagged with spatial barcode oligonucleotides derived from DNA-barcoded beads with known positions. These tagged nuclei can then be used as an input into a wide variety of single-nucleus profiling assays. Application of Slide-tags to the mouse hippocampus positioned nuclei at less than 10 µm spatial resolution and delivered whole-transcriptome data that are indistinguishable in quality from ordinary single-nucleus RNA-sequencing data. To demonstrate that Slide-tags can be applied to a wide variety of human tissues, we performed the assay on brain, tonsil and melanoma. We revealed cell-type-specific spatially varying gene expression across cortical layers and spatially contextualized receptor-ligand interactions driving B cell maturation in lymphoid tissue. A major benefit of Slide-tags is that it is easily adaptable to almost any single-cell measurement technology. As a proof of principle, we performed multiomic measurements of open chromatin, RNA and T cell receptor (TCR) sequences in the same cells from metastatic melanoma, identifying transcription factor motifs driving cancer cell state transitions in spatially distinct microenvironments. Slide-tags offers a universal platform for importing the compendium of established single-cell measurements into the spatial genomics repertoire.

MAPS: Pathologist-level cell type annotation from tissue images through machine learning.

Highly multiplexed protein imaging is emerging as a potent technique for analyzing protein distribution within cells and tissues in their native context. However, existing cell annotation methods utilizing high-plex spatial proteomics data are resource intensive and necessitate iterative expert input, thereby constraining their scalability and practicality for extensive datasets. We introduce MAPS (Machine learning for Analysis of Proteomics in Spatial biology), a machine learning approach facilitating rapid and precise cell type identification with human-level accuracy from spatial proteomics data. Validated on multiple in-house and publicly available MIBI and CODEX datasets, MAPS outperforms current annotation techniques in terms of speed and accuracy, achieving pathologist-level precision even for challenging cell types, including tumor cells of immune origin. By democratizing rapidly deployable and scalable machine learning annotation, MAPS holds significant potential to expedite advances in tissue biology and disease comprehension.

Ultraviolet radiation shapes dendritic cell leukaemia transformation in the skin.

Tumours most often arise from progression of precursor clones within a single anatomical niche. In the bone marrow, clonal progenitors can undergo malignant transformation to acute leukaemia, or differentiate into immune cells that contribute to disease pathology in peripheral tissues1-4. Outside the marrow, these clones are potentially exposed to a variety of tissue-specific mutational processes, although the consequences of this are unclear. Here we investigate the development of blastic plasmacytoid dendritic cell neoplasm (BPDCN)-an unusual form of acute leukaemia that often presents with malignant cells isolated to the skin5. Using tumour phylogenomics and single-cell transcriptomics with genotyping, we find that BPDCN arises from clonal (premalignant) haematopoietic precursors in the bone marrow. We observe that BPDCN skin tumours first develop at sun-exposed anatomical sites and are distinguished by clonally expanded mutations induced by ultraviolet (UV) radiation. A reconstruction of tumour phylogenies reveals that UV damage can precede the acquisition of alterations associated with malignant transformation, implicating sun exposure of plasmacytoid dendritic cells or committed precursors during BPDCN pathogenesis. Functionally, we find that loss-of-function mutations in Tet2, the most common premalignant alteration in BPDCN, confer resistance to UV-induced cell death in plasmacytoid, but not conventional, dendritic cells, suggesting a context-dependent tumour-suppressive role for TET2. These findings demonstrate how tissue-specific environmental exposures at distant anatomical sites can shape the evolution of premalignant clones to disseminated cancer.

Slide-tags: scalable, single-nucleus barcoding for multi-modal spatial genomics.

Recent technological innovations have enabled the high-throughput quantification of gene expression and epigenetic regulation within individual cells, transforming our understanding of how complex tissues are constructed. Missing from these measurements, however, is the ability to routinely and easily spatially localise these profiled cells. We developed a strategy, Slide-tags, in which single nuclei within an intact tissue section are 'tagged' with spatial barcode oligonucleotides derived from DNA-barcoded beads with known positions. These tagged nuclei can then be used as input into a wide variety of single-nucleus profiling assays. Application of Slide-tags to the mouse hippocampus positioned nuclei at less than 10 micron spatial resolution, and delivered whole-transcriptome data that was indistinguishable in quality from ordinary snRNA-seq. To demonstrate that Slide-tags can be applied to a wide variety of human tissues, we performed the assay on brain, tonsil, and melanoma. We revealed cell-type-specific spatially varying gene expression across cortical layers and spatially contextualised receptor-ligand interactions driving B-cell maturation in lymphoid tissue. A major benefit of Slide-tags is that it is easily adaptable to virtually any single-cell measurement technology. As proof of principle, we performed multiomic measurements of open chromatin, RNA, and T-cell receptor sequences in the same cells from metastatic melanoma. We identified spatially distinct tumour subpopulations to be differentially infiltrated by an expanded T-cell clone and undergoing cell state transition driven by spatially clustered accessible transcription factor motifs. Slide-tags offers a universal platform for importing the compendium of established single-cell measurements into the spatial genomics repertoire.

Spatial maps of T cell receptors and transcriptomes reveal distinct immune niches and interactions in the adaptive immune response.

T cells mediate antigen-specific immune responses to disease through the specificity and diversity of their clonotypic T cell receptors (TCRs). Determining the spatial distributions of T cell clonotypes in tissues is essential to understanding T cell behavior, but spatial sequencing methods remain unable to profile the TCR repertoire. Here, we developed Slide-TCR-seq, a 10-µm-resolution method, to sequence whole transcriptomes and TCRs within intact tissues. We confirmed the ability of Slide-TCR-seq to map the characteristic locations of T cells and their receptors in mouse spleen. In human lymphoid germinal centers, we identified spatially distinct TCR repertoires. Profiling T cells in renal cell carcinoma and melanoma specimens revealed heterogeneous immune responses: T cell states and infiltration differed intra- and inter-clonally, and adjacent tumor and immune cells exhibited distinct gene expression. Altogether, our method yields insights into the spatial relationships between clonality, neighboring cell types, and gene expression that drive T cell responses.

Cell type-specific inference of differential expression in spatial transcriptomics.

A central problem in spatial transcriptomics is detecting differentially expressed (DE) genes within cell types across tissue context. Challenges to learning DE include changing cell type composition across space and measurement pixels detecting transcripts from multiple cell types. Here, we introduce a statistical method, cell type-specific inference of differential expression (C-SIDE), that identifies cell type-specific DE in spatial transcriptomics, accounting for localization of other cell types. We model gene expression as an additive mixture across cell types of log-linear cell type-specific expression functions. C-SIDE's framework applies to many contexts: DE due to pathology, anatomical regions, cell-to-cell interactions and cellular microenvironment. Furthermore, C-SIDE enables statistical inference across multiple/replicates. Simulations and validation experiments on Slide-seq, MERFISH and Visium datasets demonstrate that C-SIDE accurately identifies DE with valid uncertainty quantification. Last, we apply C-SIDE to identify plaque-dependent immune activity in Alzheimer's disease and cellular interactions between tumor and immune cells. We distribute C-SIDE within the R package https://github.com/dmcable/spacexr .

miR-15a/16-1 deletion in activated B cells promotes plasma cell and mature B-cell neoplasms.

Chromosome 13q deletion [del(13q)], harboring the miR-15a/16-1 cluster, is one of the most common genetic alterations in mature B-cell malignancies, which originate from germinal center (GC) and post-GC B cells. Moreover, miR-15a/16 expression is frequently reduced in lymphoma and multiple myeloma (MM) cells without del(13q), suggesting important tumor-suppressor activity. However, the role of miR-15a/16-1 in B-cell activation and initiation of mature B-cell neoplasms remains to be determined. We show that conditional deletion of the miR-15a/16-1 cluster in murine GC B cells induces moderate but widespread molecular and functional changes including an increased number of GC B cells, percentage of dark zone B cells, and maturation into plasma cells. With time, this leads to development of mature B-cell neoplasms resembling human extramedullary plasmacytoma (EP) as well as follicular and diffuse large B-cell lymphomas. The indolent nature and lack of bone marrow involvement of EP in our murine model resembles human primary EP rather than MM that has progressed to extramedullary disease. We corroborate human primary EP having low levels of miR-15a/16 expression, with del(13q) being the most common genetic loss. Additionally, we show that, although the mutational profile of human EP is similar to MM, there are some exceptions such as the low frequency of hyperdiploidy in EP, which could account for different disease presentation. Taken together, our studies highlight the significant role of the miR-15a/16-1 cluster in the regulation of the GC reaction and its fundamental context-dependent tumor-suppression function in plasma cell and B-cell malignancies.

Notch activation is pervasive in SMZL and uncommon in DLBCL: implications for Notch signaling in B-cell tumors.

Notch receptors participate in a signaling pathway in which ligand-induced proteolysis frees the Notch intracellular domain (NICD), allowing it to translocate to the nucleus, form a transcription complex, and induce target gene expression. Chronic lymphocytic leukemia/small lymphocytic lymphoma (CLL/SLL), splenic marginal zone B-cell lymphoma (SMZL), and distinct subsets of diffuse large B-cell lymphoma (DLBCL) are strongly associated with mutations in the 3' end of NOTCH1 or NOTCH2 that disrupt a proline, glutamic acid, serine, and threonine (PEST) degron domain and stabilize NICD1 and NICD2. By contrast, mutations leading to constitutive Notch activation are rare in primary B-cell neoplasms, suggesting that Notch activation is confined to ligand-rich tumor microenvironments, or that cryptic strong gain-of-function mutations have been missed in prior analyses. To test these ideas, we used immunohistochemical stains to screen a broad range of B-cell tumors for Notch activation. Our analyses reveal that among small B-cell neoplasms, NICD2 is primarily detected in SMZL and is a common feature of both NOTCH2 wild-type and NOTCH2-mutated SMZLs, similar to prior findings with NOTCH1 in CLL/SLL. The greatest NOTCH2 activation was observed in NOTCH2-mutated SMZLs, particularly within splenic marginal zones. By contrast, little evidence of NOTCH2 activation was observed in DLBCL, even in NOTCH2-mutated tumors, suggesting that selective pressure for NOTCH2 activation is mainly confined to low-grade B-cell neoplasms, whereas DLBCLs with NOTCH1 mutations frequently showed evidence of ongoing NOTCH1 activation. These observations have important implications for the pathogenic role of Notch and its therapeutic targeting in B-cell lymphomas.

Triaging abnormal cervical cancer screening tests using p16INK4a detection by ELISA on fresh cervical samples.

PROBLEM: Cervical cancer screening strategies in the United States include cotesting (human papillomavirus (HPV) with cytology), primary HPV with genotyping and reflex cytology, and cytology alone. An ongoing challenge is the appropriate triage of patients to colposcopy to those at highest risk. We investigated whether incorporation of p16INK4a immunodetection by enzyme-linked immunosorbent assay (ELISA) on fresh cervical samples obtained at the time of screening could improve appropriate referral to colposcopy. METHOD OF STUDY: A derivation group comprised of cervical swabs collected from subjects with high-grade dysplasia or cancer (positive control) and from subjects with negative screening history (negative control). Samples collected from colposcopy were used to evaluate the existing screening strategies individually and with incorporation of p16INK4a ELISA. Histology was used as the gold standard. RESULTS: Among 163 subjects recruited, 138 were included. In the derivation group, mean p16INK4a level was 2.86 ng/mL (n = 31) and 0.58 ng/mL (n = 20) among positive and negative controls respectively (p = 0.002) with an area under the receiver operator characteristic curve of 0.79 (p < 0.001). Among colposcopy subjects, sensitivity/specificity for cotesting, primary HPV, and cytology were 94%/42%, 88%/45%, and 88%/49%, respectively. Incorporation of p16INK4a resulted in similar sensitivity and improved specificity (cotesting+p16 88%/58%, primary HPV+p16 88%/57%, cytology+p16 81%/62%; p = 0.23/p = 0.008) with decrease in colposcopy referrals by 15% to 22% (p = 0.01). CONCLUSIONS: These results demonstrate the feasibility of quantifying p16INK4a by ELISA in fresh cervical samples, and its potential as an adjunct to existing screening strategies in the identification of high grade-dysplasia while reducing the number of colposcopic referrals.

Imaging of IgG4-Related Disease in the Head and Neck: A Systematic Review, Case Series, and Pathophysiology Update.

This systematic review aims to clarify and comprehensively detail the sometimes variable published imaging features as well as the pathogenesis, clinical diagnostic criteria, and treatment options of IgG4-Related Diseases (IgG4-RD) in the head and neck to aid the radiologist in diagnosing relapse and new sites of disease. A literature search in PubMed and EMBASE for reported cases of IgG4-RD was performed in December 2019. Case reports or series of IgG4-RD in the head and neck in adults that included sufficient imaging and pathology findings were included. This yielded 50 reports. IgG4-RD locations included the orbits, thyroid, pituitary gland, paranasal sinuses, salivary and parotid glands, larynx, pharynx, cervical lymph nodes, meninges, and skull base. Most lesions demonstrated non-specific homogenous CT attenuation, diffuse enhancement, isointense/low T2 signal intensity, and low T1 signal intensity. 6 cases from our institution followed previously reported imaging patterns.