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Metastasis is the major cause of cancer-related deaths. Neuroblastoma (NB), a childhood tumor has been molecularly defined at the primary cancer site, however, the bone marrow (BM) as the metastatic niche of NB is poorly characterized. Here we perform single-cell transcriptomic and epigenomic profiling of BM aspirates from 11 subjects spanning three major NB subtypes and compare these to five age-matched and metastasis-free BM, followed by in-depth single cell analyses of tissue diversity and cell-cell interactions, as well as functional validation. We show that cellular plasticity of NB tumor cells is conserved upon metastasis and tumor cell type composition is NB subtype-dependent. NB cells signal to the BM microenvironment, rewiring via macrophage mgration inhibitory factor and midkine signaling specifically monocytes, which exhibit M1 and M2 features, are marked by activation of pro- and anti-inflammatory programs, and express tumor-promoting factors, reminiscent of tumor-associated macrophages. The interactions and pathways characterized in our study provide the basis for therapeutic approaches that target tumor-to-microenvironment interactions. The bone marrow is a common site of metastasis for neuroblastoma patients. Here, the authors perform single cell RNA-seq and ATAC-seq of bone marrow aspirates from 16 subjects and show conservation of tumor cell plasticity in metastases and identify tumor-to-bone marrow cell signals that trigger tumor promoting monocytes.

Neutrophils are evolutionarily conserved innate immune cells playing pivotal roles in host defense. Zebrafish models have contributed substantially to our understanding of neutrophil functions but similarities to human neutrophil maturation have not been systematically characterized, which limits their applicability to studying human disease. Here we show, by generating and analysing transgenic zebrafish strains representing distinct neutrophil differentiation stages, a high-resolution transcriptional profile of neutrophil maturation. We link gene expression at each stage to characteristic transcription factors, including C/ebp-β, which is important for late neutrophil maturation. Cross-species comparison of zebrafish, mouse, and human samples confirms high molecular similarity of immature stages and discriminates zebrafish-specific from pan-species gene signatures. Applying the pan-species neutrophil maturation signature to RNA-sequencing data from human neuroblastoma patients reveals association between metastatic tumor cell infiltration in the bone marrow and an overall increase in mature neutrophils. Our detailed neutrophil maturation atlas thus provides a valuable resource for studying neutrophil function at different stages across species in health and disease. Maturation of innate immune cells is a graded stereotypic process which is often conserved across species. Here authors label distinct neutrophil leukocyte developmental stages via generating combinations of transgenic zebrafish reporter strains, followed by transcriptome analysis of different neutrophil maturation stages and comparison to the gene expression profile of developing neutrophils from humans and mice.

Fully-automated nuclear image segmentation is the prerequisite to ensure statistically significant, quantitative analyses of tissue preparations,applied in digital pathology or quantitative microscopy. The design of segmentation methods that work independently of the tissue type or preparation is complex, due to variations in nuclear morphology, staining intensity, cell density and nuclei aggregations. Machine learning-based segmentation methods can overcome these challenges, however high quality expert-annotated images are required for training. Currently, the limited number of annotated fluorescence image datasets publicly available do not cover a broad range of tissues and preparations. We present a comprehensive, annotated dataset including tightly aggregated nuclei of multiple tissues for the training of machine learning-based nuclear segmentation algorithms. The proposed dataset covers sample preparation methods frequently used in quantitative immunofluorescence microscopy. We demonstrate the heterogeneity of the dataset with respect to multiple parameters such as magnification, modality, signal-to-noise ratio and diagnosis. Based on a suggested split into training and test sets and additional single-nuclei expert annotations, machine learning-based image segmentation methods can be trained and evaluated. Measurement(s) nucleus • Annotation • Frozen Section • Neuroblastoma • Touch Prep Slide • Centrifuged Smear Slide • cells grown on slide • Ganglioneuroblastoma • Wilms Tumor • HaCaT cell Technology Type(s) Fluorescence Imaging • machine learning Factor Type(s) nucleus segmentation Sample Characteristic - Organism Homo sapiens Machine-accessible metadata file describing the reported data: https://doi.org/10.6084/m9.figshare.12570854

Background Bone marrow dissemination of tumor cells, common in various cancers, including neuroblastoma, is associated with poor outcome, necessitating sensitive detection methods for bone marrow minimal residual disease (MRD) and offer detection of biomarkers for therapy stratification. Current standard-of-care diagnostics, involving cytomorphological and histological assessment of bone marrow aspirates and trephine biopsies, lack sensitivity, leading to undetected MRD in many patients, and do not allow molecular biomarker assessment. Methods This study evaluates advanced multi-modal high-sensitivity MRD detection techniques in 509 bone marrow specimens from 108 high-risk neuroblastoma patients across two centers. We employed automatic immunofluorescence plus interphase fluorescence in situ hybridization (AIPF) and reverse transcriptase quantitative polymerase chain reaction (RT-qPCR) panels to quantify disseminated tumor cells (DTCs), disialoganglioside 2 (GD2) and CD56/Neural cell adhesion molecule (NCAM) levels, and adrenergic (ADRN) and mesenchymal (MES)-phenotype mRNA markers. Results This multi-modal analysis significantly improved MRD detection compared to standard-of-care methods; 395 samples yielded results for RT-qPCR-ADRN, AIPF and CM/histology and 223 showed concordant results (64 positive, 159 negative). 114 samples did not produce results as either no cytospins were prepared ( n  = 96) or results were inconclusive (all techniques n  = 18). AIPF and RT-qPCR complemented each other in detecting MRD and characterizing ADRN- and MES-phenotypes and GD2 immunotherapy target. RT-qPCR-ADRN alone frequently detected low tumor cell burden. High DTC infiltration at diagnosis showed bilateral bone marrow disease, whereas MRD settings often involved only one side. RT-qPCR-MES, despite lower sensitivity, identified 37 additional cases and showed delayed clearance of MES markers post-chemotherapy, with increases prior to relapse. Conclusions Our findings demonstrate the feasibility of integrating high-sensitivity techniques with standard-of-care assessments in an international multicenter setting. Advanced multi-modal MRD detection, monitoring phenotype switches and assessing immunotherapy targets are crucial for improving patient outcomes in neuroblastoma and other cancers.

While the bone marrow attracts tumor cells in many solid cancers leading to poor outcome in affected patients, comprehensive analyses of bone marrow metastases have not been performed on a single-cell level. We here set out to capture tumor heterogeneity and unravel microenvironmental changes in neuroblastoma, a solid cancer with bone marrow involvement. To this end, we employed a multi-omics data mining approach to define a multiplex imaging panel and developed DeepFLEX, a pipeline for subsequent multiplex image analysis, whereby we constructed a single-cell atlas of over 35,000 disseminated tumor cells (DTCs) and cells of their microenvironment in the metastatic bone marrow niche. Further, we independently profiled the transcriptome of a cohort of 38 patients with and without bone marrow metastasis. Our results revealed vast diversity among DTCs and suggest that FAIM2 can act as a complementary marker to capture DTC heterogeneity. Importantly, we demonstrate that malignant bone marrow infiltration is associated with an inflammatory response and at the same time the presence of immuno-suppressive cell types, most prominently an immature neutrophil/granulocytic myeloid-derived suppressor-like cell type. The presented findings indicate that metastatic tumor cells shape the bone marrow microenvironment, warranting deeper investigations of spatio-temporal dynamics at the single-cell level and their clinical relevance.

Multiplex Imaging (MI) enables the simultaneous visualization of multiple biological markers in separate imaging channels at subcellular resolution, providing valuable insights into cell-type heterogeneity and spatial organization. However, current computational pipelines rely on cell segmentation algorithms, which require laborious fine-tuning and can introduce downstream errors due to inaccurate single-cell representations. We propose a segmentation-free deep learning approach that leverages grouped convolutions to learn interpretable embedded features from each imaging channel, enabling robust cell-type identification without manual feature selection. Validated on an Imaging Mass Cytometry dataset of 1.8 million cells from neuroblastoma patients, our method enables the accurate identification of known cell types, showcasing its scalability and suitability for high-dimensional MI data.

Neutrophils are evolutionarily conserved innate defense cells implicated in diverse pathological processes. Zebrafish models have contributed substantially to our understanding of neutrophil functions, but similarities to human neutrophil maturation have not been characterized limiting applicability to study human disease. We generated transgenic zebrafish strains to distinguish neutrophil maturation grades in vivo and established a high-resolution transcriptional profile of neutrophil maturation. We linked gene expression at each stage to characteristic transcription factors, including C/ebp-beta important for late neutrophil maturation. Cross-species comparison of zebrafish, mouse, and human confirmed high molecular similarity in immature stages and discriminated zebrafish-specific from pan-species gene signatures. Applying pan-species neutrophil maturation signatures in RNA-seq data from neuroblastoma patients revealed an association of metastatic tumor cell infiltration in the bone marrow with an increase in mature neutrophils. Our detailed neutrophil maturation atlas provides a valuable resource for studying neutrophil function at different stages across species in health and disease.Competing Interest StatementThe authors have declared no competing interest.

ABSTRACT Bone marrow commonly serves as a metastatic niche for disseminated tumor cells (DTCs) of solid cancers in patients with unfavorable clinical outcome. Single-cell assessment of bone marrow metastases is essential to decipher the entire spectrum of tumor heterogeneity in these cancers, however, has previously not been performed. Here we used multi-epitope-ligand cartography (MELC) to spatially profile 20 biomarkers and assess morphology in DTCs as well as hematopoietic and mesenchymal cells of eight bone marrow metastases from neuroblastoma patients. We developed DeepFLEX, a single-cell image analysis pipeline for MELC data that combines deep learning-based cell and nucleus segmentation and overcomes frequent challenges of multiplex imaging methods including autofluorescence and unspecific antibody binding. Using DeepFLEX, we built a single-cell atlas of bone marrow metastases comprising more than 35,000 single cells. Comparisons of cell type proportions between samples indicated that microenvironmental changes in the metastatic bone marrow are associated with tumor cell infiltration and therapy response. Hierarchical clustering of DTCs revealed multiple phenotypes with highly diverse expression of markers such as FAIM2, an inhibitory protein in the Fas apoptotic pathway, which we propose as a complementary marker to capture DTC heterogeneity in neuroblastoma. The presented single-cell atlas provides first insights into the heterogeneity of human bone marrow metastases and is an important step towards a deeper understanding of DTCs and their interactions with the bone marrow niche. Competing Interest Statement The authors have declared no competing interest.