Biology subjects

Goltsev, Y.

Publications and source records attributed to Goltsev, Y..

7 recordsLinked to original sources

bioRxiv2025

High-Dimensional Spatiotemporal Single-Cell and 3D Atlas of the Bone Marrow Microenvironment during Leukemic Progression

The bone marrow microenvironment (BMME) is essential for hematopoiesis and immunity, yet spatiotemporal single-cell analysis during leukemogenesis remains challenging. We characterized the BMME in femurs from wild-type and chronic myeloid leukemia (CML) mice at 7, 14 and 21 days post-induction by highly multiplexed and 3D microscopy. Using a 54-marker CODEX panel, we profiled 2,033,725 cells in 55 tissue regions of interest and identified 41 cell types through unsupervised clustering and supervised annotation. During leukemic progression, we observed an expansion of myeloid and progenitor cell populations, increased PD-L1+ leukemic cells, the upregulation of PD-1 on CD4+ and CD8+ T cells, and a profound loss of B cells, plasma cells and bone cells. Advanced CML exhibited a striking expansion of immature, pericyte-deficient vasculature that disrupted vascular niches and impaired hematopoietic stem/progenitor cell positioning. Spatial mapping revealed leukemia-specific cellular neighborhoods enriched in PD-1+CD8+ T cells, suggesting localized immune cell exhaustion. Early-stage CML showed increaseds between plasmacytoid dendritic cells and megakaryocytes, whereas advanced CML featured heightened megakaryocyte emperipolesis of non-leukemic granulocytes. Megakaryocytes were morphologically irregular in CML mice and BM trephine biopsies from CML patients. Laser-capture microdissected megakaryocytes from newly diagnosed CML patients had reduced expression of cytoskeleton genes, which was reversed in advanced cases treated with tyrosine kinase inhibitors. 3D imaging revealed vascular disorganization and depleted megakaryocytes in the diaphysis, underscoring region-specific pathology. Together, this study provides a spatiotemporal single-cell atlas of the BMME during leukemic progression, showing how leukemic cells reprogram the niche to support their expansion and immune evasion.

cancer biology↗

bioRxiv2025

Spatially organized inflammatory myeloid-CD8+ T cell aggregates linked to Merkel-cell Polyomavirus driven Reorganization of the Tumor Microenvironment

Merkel cell carcinoma (MCC) is an aggressive skin cancer with high propensity for metastasis, caused by Merkel-cell-polyomavirus (MCPyV), or chronic UV-light-exposure. How MCPyV spatially modulates immune responses within the tumor microenvironment and how such are linked to patient outcomes remains unknown. We interrogated the cellular and transcriptional landscapes of 60 MCC-patients using a combination of multiplex proteomics, in-situ RNA-hybridization, and spatially oriented transcriptomics. We identified a spatial co-enrichment of activated CD8+ T-cells and CXCL9+PD-L1+ macrophages at the invasive front of virus-positive MCC. This spatial immune response pattern was conserved in another virus-positive tumor, HPV+ head-and-neck cancer. Importantly, we show that virus-negativity correlated with high risk of metastasis through low CD8+ T-cell infiltration and the enrichment of cancer-associated-fibroblasts at the tumor boundary. By contrast, responses to immune-checkpoint blockade (ICB) were independent of viral-status but correlated with the presence of a B-cell-enriched spatial contexts. Our work is the first to reveal distinct immune-response patterns between virus-positive and virus-negative MCC and their impact on metastasis and ICB-response.

immunology↗

bioRxiv2022

A single cell spatial temporal atlas of skeletal muscle reveals cellular neighborhoods that orchestrate regeneration and become disrupted in aging

Our mobility requires muscle regeneration throughout life. Yet our knowledge of the interplay of cell types required to rebuild injured muscle is lacking, because most single cell assays require tissue dissociation. Here we use multiplexed spatial proteomics and neural network analyses to resolve a single cell spatiotemporal atlas of 34 cell types during muscle regeneration and aging. This atlas maps interactions of immune, fibrogenic, vascular, nerve, and myogenic cells at sites of injury in relation to tissue architecture and extracellular matrix. Spatial pseudotime mapping reveals sequential cellular neighborhoods that mediate repair and a nodal role for immune cells. We confirm this role by macrophage depletion, which triggers formation of aberrant neighborhoods that obstruct repair. In aging, immune dysregulation is chronic, cellular neighborhoods are disrupted, and an autoimmune response is evident at sites of denervation. Our findings highlight the spatial cellular ecosystem that orchestrates muscle regeneration, and is altered in aging. HighlightsO_LISingle cell resolution spatial atlas resolves a cellular ecosystem of 34 cell types in multicellular neighborhoods that mediate efficient skeletal muscle repair C_LIO_LIHighly multiplexed spatial proteomics, neural network and machine learning uncovers temporal dynamics in the spatial crosstalk between immune, fibrogenic, vascular, nerve, and muscle stem cells and myofibers during regeneration C_LIO_LISpatial pseudotime mapping reveals coherent formation of multicellular neighborhoods during efficacious repair and the nodal role of immune cells in coordinating muscle repair C_LIO_LIIn aged muscle, cellular neighborhoods are disrupted by a chronically inflamed state and autoimmunity C_LI

cell biology↗

bioRxiv2021

Robust Single-cell Matching and Multi-modalAnalysis Using Shared and Distinct FeaturesReveals Orchestrated Immune Responses

The ability to align individual cellular information from multiple experimental sources, techniques and systems is fundamental for a true systems-level understanding of biological processes. While single-cell transcriptomic studies have transformed our appreciation for the complexities and contributions of diverse cell types to disease, they can be limited in their ability to assess protein-level phenotypic information and beyond. Therefore, matching and integrating single-cell datasets which utilize robust protein measurements across multiple modalities is critical for a deeper understanding of cell states, and signaling pathways particularly within their native tissue context. Current available tools are mainly designed for single-cell transcriptomics matching and integration, and generally rely upon a large number of shared features across datasets for mutual Nearest Neighbor (mNN) matching. This approach is unsuitable when applied to single-cell proteomic datasets, due to the limited number of parameters simultaneously accessed, and lack of shared markers across these experiments. Here, we introduce a novel cell matching algorithm, Matching with pARtIal Overlap (MARIO), that takes into account both shared and distinct features, while consisting of vital filtering steps to avoid sub-optimal matching. MARIO accurately matches and integrates data from different single-cell proteomic and multi-modal methods, including spatial techniques, and has cross-species capabilities. MARIO robustly matched tissue macrophages identified from COVID-19 lung autopsies via CODEX imaging to macrophages recovered from COVID-19 bronchoalveolar lavage fluid via CITE-seq. This cross-platform integrative analysis enabled the identification of unique orchestrated immune responses within the lung of complement-expressing macrophages and their impact on the local tissue microenvironment. MARIO thus provides an analytical framework for unified analysis of single-cell data for a comprehensive understanding of the underlying biological system.

bioinformatics↗

bioRxiv2021

A community-based approach to image analysis of cells, tissues and tumors

Emerging multiplexed imaging platforms provide an unprecedented view of an increasing number of molecular markers at subcellular resolution and the dynamic evolution of tumor cellular composition. As such, they are capable of elucidating cell-to-cell interactions within the tumor microenvironment that impact clinical outcome and therapeutic response. However, the rapid development of these platforms has far outpaced the computational methods for processing and analyzing the data they generate. While being technologically disparate, all imaging assays share many computational requirements for post-collection data processing. We convened a workshop to characterize these shared computational challenges and a follow-up hackathon to implement solutions for a selected subset of them. Here, we delineate these areas that reflect major axes of research within the field, including image registration, segmentation of cells and subcellular structures, and identification of cell types from their morphology. We further describe the logistical organization of these events, believing our lessons learned can aid others in uniting the imaging community around self-identified topics of mutual interest, in designing and implementing operational procedures to address those topics and in mitigating issues inherent in image analysis (e.g., sharing exemplar images of large datasets and disseminating baseline solutions to hackathon challenges through open-source code repositories).

bioinformatics↗

bioRxiv2019

Coordinated cellular neighborhoods orchestrate antitumoral immunity at the colorectal cancer invasive front

Antitumoral immunity requires organized, spatially nuanced interactions between components of the immune tumor microenvironment (iTME). Understanding this coordinated behavior in effective versus ineffective tumor control will advance immunotherapies. We optimized CO-Detection by indEXing (CODEX) for para ffin-em bedded tissue microarrays, enabling profiling of 140 tissue regions from 35 advanced-stage colorectal cancer (CRC) patients with 56 protein markers simultaneously. We identified nine conserved, distinct cellular neighborhoods (CNs)-a collection of components characteristic of the CRC iTME. Enrichment of PD-1+CD4+ T cells only within a granulocyte CN positively correlated with survival in a high-risk patient subset. Coupling of tumor and immune CNs, fragmentation of T cell and macrophage CNs, and disruption of inter-CN communication was associated with inferior outcomes. This study provides a framework for interrogating complex biological processes, such as antitumoral immunity, demonstrating an example of how tumors can disrupt imm une functionality through interference in the concerted action of cells and spatial domains.

immunology↗

bioRxiv2017

Deep profiling of mouse splenic architecture with CODEX multiplexed imaging.

A highly multiplexed cytometric imaging approach, termed CO-Detection by indEXing (CODEX), is used here to create multiplexed datasets of normal and lupus (MRL/lpr) murine spleens. CODEX iteratively visualizes antibody binding events using DNA barcodes, fluorescent dNTP analogs, and an insitu polymerization-based indexing procedure. An algorithmic pipeline for single-cell antigen quantification in tightly packed tissues was developed and used to overlay well-known morphological features with de novo characterization of lymphoid tissue architecture at a single-cell and cellular neighborhood levels. We observed an unexpected, profound impact of the cellular neighborhood on the expression of protein receptors on immune cells. By comparing normal murine spleen to spleens from animals with systemic autoimmune disease (MRL/lpr), extensive and previously uncharacterized splenic cell interaction dynamics in the healthy versus diseased state was observed. The fidelity of multiplexed spatial cytometry demonstrated here allows for quantitative systemic characterization of tissue architecture in normal and clinically aberrant samples.

systems biology↗