Biology subjects

Baertsch, M. A.

Publications and source records attributed to Baertsch, M. A..

5 recordsLinked to original sources

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↗

bioRxiv2025

MONTAGE: A Computation Framework to Identify Spatially Resolved Functional Enrichment Gradients in the Tissue Microenvironment via Spatial Communities

Single-cell spatial-omics has advanced our understanding of how tumor microenvironment contributes to cancer progression. However, most single-cell spatial-omics studies focus on cell types and neighborhoods, offering limited information about functional and clinical relevance of cellular organization. We introduce MONTAGE, a computational framework to reconstruct, functionally analyze, and identify clinically relevant cellular spatial communities (SCs). MONTAGE generates a gene signature matrix of SCs from integrated atlases that offer single-cell resolution with transcriptomics, and reconstructs tissue maps ("montages"), reflecting sequential SC compositional changes along spatial gradients of biological function enrichments. The MONTAGE signature matrix can also be used to deconvolve bulk and spot-based spatial transcriptomic data, and combining with clinical metadata, allows assessing SC clinical relevance. In a head and neck cancer study, MONTAGE reveals SCs enriched with malignant cells and granulocytes shifting to SCs enriched with macrophages and fibroblasts along gradient of epithelial-mesenchymal transition, and clinical prognostic significance of the SCs.

systems biology↗

bioRxiv2024

CD38 biallelic loss is a recurrent mechanism of resistance to anti-CD38 antibodies in multiple myeloma.

Monoclonal antibodies targeting CD38 are a therapeutic mainstay in multiple myeloma (MM). While they have contributed to improved outcomes, most patients still experience disease relapse, and little is known about tumor-intrinsic mechanisms of resistance to these drugs. Antigen escape has been implicated as a mechanism of tumor cell evasion in immunotherapy. Yet, it is unknown whether MM cells can develop permanent resistance to anti-CD38 antibodies by acquiring genomic events leading to biallelic disruption of the CD38 gene locus. Here, by using whole genome and whole exome sequencing data from 701 newly diagnosed patients, 67 patients at relapse with naivety to anti-CD38 antibodies, and 50 patients collected at relapse following anti-CD38 antibodies. We report a loss of CD38 in 20% (10/50) of patients post-CD38 therapy, three of which exhibited a loss of both copies. Two of these cases showed convergent evolution where distinct subclones independently acquired similar advantageous variants. Functional studies on missense mutations involved in biallelic CD38 events revealed that two variants, L153H and C275Y, decreased binding affinity and antibody-dependent cellular cytotoxicity of the commercial antibodies Daratumumab and Isatuximab. However, a third mutation, R140G, conferred selective resistance to Daratumumab, while retaining sensitivity to Isatuximab. Clinically, patients with MM are often rechallenged with CD38 antibodies following disease progression and these data support a role for next generation sequencing to guide treatment selection.

cancer biology↗

bioRxiv2023

A single-cell multi-omic and spatial atlas of nodal B-cell lymphomas reveals B-cell maturation drives intratumor heterogeneity

Intratumor heterogeneity underpins cancer pathogenesis and evolution, although it is typically considered independent from the differentiation processes that drive physiological cell-type diversity. As cancer types and subtypes arise from different cell types, we investigated whether cellular differentiation influences intratumor heterogeneity. Nodal B-cell non-Hodgkin lymphomas are a diverse set of cancers originating from different stages of B-cell maturation. Through single-cell transcriptome and surface epitope profiling (CITE-Seq) of diffuse large B-cell, mantle cell, follicular, and marginal zone lymphomas in addition to reactive lymph nodes from 51 patients, we found multiple B-cell maturation states within tumors. Intratumor maturation states emerged from the same clone, revealing divergent differentiation from a shared cell of origin. Maturation state composition varied across subtypes and tumors, which encompassed mixed cell-of-origin diagnostic subtypes. Through highly multiplexed immunohistochemistry (CODEX) of samples from 19 of these patients, we found that intratumor maturation states inhabited distinct spatial niches, displaying cellular interactions and regulatory networks typical of their maturation states while harboring different genetic variants. By deconvoluting intratumor maturation states from a microarray dataset of 507 patients, we identified risk groups within diagnoses with striking differences in survival, including IgM memory-enriched germinal center B-cell (M = 1.9 vs >10 years, p = 0.00039) and activated B-cell (M = 2.4 vs 9.6 years, p = 0.016) diffuse large B-cell lymphoma, and dark zone-enriched follicular lymphoma (M = 8.6 vs 13 years; p = 0.0019). Our findings reveal cellular differentiation remains plastic in B-cell lymphomas, driving tumor variation, evolution, and response. Key PointsO_LICellular differentiation remains plastic in B-cell lymphomas, driving tumor variation, evolution, and response. C_LIO_LIIntratumor maturation states occupy unique immune niches, harbor distinct genetic variants, and are tied to different survival outcomes. C_LI

cancer biology↗

bioRxiv2022

Multimodal and spatially resolved profiling identifies distinct patterns of T-cell infiltration in nodal B-cell lymphoma entities

T-cell-engaging immunotherapies have improved the treatment of nodal B-cell lymphoma, but responses vary highly. Future improvements of such therapies require better understanding of the variety of lymphoma-infiltrating T-cells. We employed single-cell RNA and T-cell receptor sequencing alongside quantification of surface proteins, flow cytometry and multiplexed immunofluorescence on 101 lymph nodes from healthy controls, and patients with diffuse large B-cell, mantle cell, follicular, or marginal zone lymphoma. This multimodal resource revealed entity-specific quantitative and spatial aberrations of the T-cell microenvironment. Clonal PD1+ TCF7- but not PD1+ TCF7+ cytotoxic T-cells converged into terminally exhausted T-cells, the proportions of which were variable across entities and linked to inferior prognosis. In follicular and marginal zone lymphoma, we observed expansion of follicular helper and IKZF3+ regulatory T-cells, which were clonally related and inversely associated with tumor grading. Overall, we portray lymphoma-infiltrating T-cells with unprecedented comprehensiveness and decipher both beneficial and adverse dimensions of T-cell response.

cancer biology↗