Biology subjects

Engblom, C.

Publications and source records attributed to Engblom, C..

7 recordsLinked to original sources

bioRxiv2026

Immune repertoire profiling reveals extensive clonal expansion of T and B cells in CXCL9-rich niches in sinonasal cancer

Sinonasal cancer (SNC) is a rare and aggressive head and neck cancer with limited therapeutic options and an incompletely defined immune microenvironment. Although histopathology remains central to clinical tumor evaluation, immune profiling typically requires tissue dissociation and therefore loses the spatial relationships that shape antitumor immunity. Here, we combined single-cell RNA-sequencing approaches, spatial transcriptomics and Spatial V(D)J, a technique we recently pioneered, to analyse the cellular, spatial, and clonal architecture of SNC. We found that SNC tumors were marked by a robust T cell infiltration, including substantial proportions of classical tissue resident memory (TRM) and exhausted (TExh) CD8+ T cells. This inflamed phenotype was accompanied by an immense infiltration of suppressive regulatory T (Treg) cells, which differentiated towards a Tbet+CXCR3+ phenotype. Spatially, expanded Treg, CD8 T and B cell clones concentrated within specialized peritumoral immune niches enriched for cancer-associated fibroblasts, CXCL9 tumor-associated macrophages and LAMP3IDO1 dendritic cells. T cell clones occupying these niches were clonally related to those infiltrating epithelial tumor regions, linking lymphoid hubs to the broader tumor immune response. Together, these data identify SNC as an inflamed but highly immunoregulatory tumor type and reveal a spatially organized clonal architecture in which suppressive and cytotoxic lymphocyte states coexist within CXCL9 myeloid niches.

immunology↗

bioRxiv2022

Spatial transcriptomics of T and B cell receptors uncovers lymphocyte clonal dynamics in human tissue.

The spatial distribution of lymphocyte clones within tissues is critical to their development, selection, and expansion. We have developed Spatial Transcriptomics of VDJ sequences (Spatial VDJ), which maps immunoglobulin and TR antigen receptors in human tissue sections. Spatial VDJ captures lymphocyte clones matching canonical T, B, and plasma cell distributions in tissues and amplifies clonal sequences confirmed by orthogonal methods. We confirm spatial congruency between paired receptor chains, develop a computational framework to predict receptor pairs, and link the expansion of distinct B cell clones to different tumor-associated gene expression programs. Spatial VDJ delineates B cell clonal diversity, class switch recombination, and lineage trajectories within their spatial context. Taken together, Spatial VDJ captures lymphocyte spatial clonal architecture across tissues, which could have important therapeutic implications. One-Sentence SummarySpatial transcriptomics-based technology co-captures T and B cell receptors within their anatomical niche in human tissue.

immunology↗

bioRxiv2022

Tumoroscope: a probabilistic model for mapping cancer clones in tumor tissues

Spatial and genomic heterogeneity of tumors is the key for cancer progression, treatment, and survival. However, a technology for direct mapping the clones in the tumor tissue based on point mutations is lacking. Here, we propose Tumoroscope, the first probabilistic model that accurately infers cancer clones and their high-resolution localization by integrating pathological images, whole exome sequencing, and spatial transcriptomics data. In contrast to previous methods, Tumoroscope explicitly addresses the problem of deconvoluting the proportions of clones in spatial transcriptomics spots. Applied to a reference prostate cancer dataset and a newly generated breast cancer dataset, Tumoroscope reveals spatial patterns of clone colocalization and mutual exclusion in sub-areas of the tumor tissue. We further infer clone-specific gene expression levels and the most highly expressed genes for each clone. In summary, Tumoroscope enables an integrated study of the spatial, genomic, and phenotypic organization of tumors.

cancer biology↗

bioRxiv2021

The spatial transcriptomic landscape of the healing intestine following damage

The intestinal barrier is composed of a complex cell network defining highly compartmentalized and specialized structures. Here, we use spatial transcriptomics (ST) to define how the transcriptomic landscape is spatially organized in the steady state and healing murine colon. At steady state conditions, we demonstrate a previously unappreciated molecular regionalization of the colon, which dramatically changes during mucosal healing. Here, we identified spatially-organized transcriptional programs defining compartmentalized mucosal healing, and regions with dominant wired pathways. Furthermore, we showed that decreased p53 activation defined areas with increased presence of proliferating epithelial stem cells. Finally, we used our resource to map transcriptomics modules associated with human diseases demonstrating that ST can be used to inform clinical practice. Overall, we provide a publicly available resource defining principles of transcriptomic regionalization of the colon during mucosal healing and a framework to develop and progress further hypotheses.

systems biology↗

bioRxiv2021

PhylEx: Accurate reconstruction of clonal structure via integrated analysis of bulk DNA-seq and single cell RNA-seq data

We propose PhylEx: a clonal-tree reconstruction method that integrates bulk genomics and single-cell transcriptomics data. In addition to the clonal-tree, PhylEx also assigns single-cells to clones, which effectively produce clonal expression profiles, and generates clonal genotypes. By analyzing scRNA-seq integrated with bulk DNA-seq, PhylEx can take advantage of co-occurrences of the mutations found in the cells. In the probabilistic model underlying PhylEx, the raw read counts from scRNA-seq follow a mixture of Beta-Binomial distributions, which accounts for the sparse nature of single-cell gene expression data; the mixture lessens the penalty caused by mutations not observed due to mono-allelic expression. We rigorously evaluated PhylEx on simulated datasets as well as a biological dataset consisting of a previously well-characterized high-grade serous ovarian cancer (HGSOC) cell line. PhylEx outperformed the state-of-the-art methods by a wide margin both when comparing capacity for clonal-tree reconstruction and capacity for correctly clustering mutations. By analyzing HGSOC and HER2+ breast cancer data, we also show that PhylEx clears the way for phylo-phenotypic analysis of cancer, i.e., that the clonal expression profiles, induced by the cell-to-clone assignments, can be exploited in a manner beyond what is possible with only expression-based clustering.

bioinformatics↗

bioRxiv2020

Spatial Deconvolution of HER2-positive Breast Tumors Reveals Novel Intercellular Relationships

In the past decades, transcriptomic studies have revolutionized cancer treatment and diagnosis. However, tumor sequencing strategies typically result in loss of spatial information, critical to understand cell interactions and their functional relevance. To address this, we investigate spatial gene expression in HER2-positive breast tumors using Spatial Transcriptomics technology. We show that expression-based clustering enables data-driven tumor annotation and assessment of intra-and interpatient heterogeneity; from which we discover shared gene signatures for immune and tumor processes. We integrate and spatially map tumor-associated types from single cell data to find: segregated epithelial cells, interactions between B and T-cells and myeloid cells, co-localization of macrophage and T-cell subsets. A model is constructed to infer presence of tertiary lymphoid structures, applicable across tissue types and technical platforms. Taken together, we combine different data modalities to define novel interactions between tumor-infiltrating cells in breast cancer and provide tools generalizing across tissues and diseases.

cancer biology↗

bioRxiv2018

Efficient and specific Ly6G+ cell depletion: A change in the current practices toward more relevant functional analyses of neutrophils

Neutrophils orchestrate the innate immune response against microorganisms and are increasingly recognized to modulate cancer development in primary tumors and metastases. To address their function in vivo, different approaches are used, the most common ones relying on antibody-mediated neutrophil depletion. By comparing the effects of two widely used antibodies, we demonstrate a strong efficacy but a lack of specificity for anti-Gr1. In contrast, anti-Ly6G lacks neutrophil-depletion capacity in C57BL/6 mice, which can be explained by an insufficient celerity of neutrophil clearance that is counterbalanced by exacerbated mobilization of immature cells. When combined with a secondary antibody, anti-Ly6G treatment results in specific and efficient neutrophil depletion. Using a mouse model of lung adenocarcinoma, we demonstrate the efficacy of this new approach to diminish primary tumor growth and propose the existence of a local intercellular communication between neutrophils and alveolar macrophages that fosters regulatory T cell proliferation in lung cancer.

immunology↗