Biology subjects

Eugster, A.

Publications and source records attributed to Eugster, A..

8 recordsLinked to original sources

bioRxiv2026

Targeting poorly differentiated thyroid cancer with bispecific antibodies and CAR T cells from the human anti-TSHR autoantibody repertoire

Background: Poorly differentiated thyroid carcinoma (PDTC) has no effective systemic treatment option once radioactive iodine and tyrosine kinase inhibitors fail. The thyroid-stimulating hormone receptor (TSHR) is highly tissue-restricted and the anti-TSHR autoantibody repertoire of thyroid autoimmunity offers sequence-defined, fully human binders. We asked whether this repertoire can be converted into an off-the-shelf T cell-redirecting therapy for PDTC. Methods: TSHR expression was profiled on a 151-case thyroid cancer tissue microarray (TMA), 50 healthy controls and on fresh tumor material. Eight anti-TSHR clones, four of human autoimmune origin (M22, K1-18, K1-70, 5C9) and four murine (IRI-SAb2, IRI-SAb3, 9D33, 1H7), were reformatted as CD3-engaging bispecific antibodies (bsAbs; anti-TSHR Fab x anti-CD3 scFv) and, for leading clones, as chimeric antigen receptor (CAR) T cells. Activity was compared in vitro, across graded and mixed antigen densities and in a CAL-62-Luc-TSHR xenograft model, using healthy-donor (HD) or thyroid cancer-patient T cells. Results: TSHR was retained on a substantial fraction of PDTC, including metastatic lesions. Both formats mediated potent, antigen-selective killing and the leading bsAbs suppressed xenograft growth in vivo. For CAR T cells, scFv heavy/light-chain orientation was decisive. Anti-TSHR bsAbs cleared mixed cultures far beyond the antigen-positive fraction matching mosunetuzumab and indicating a modality-intrinsic bystander effect. Patient-derived T cells obtained on or after oncological treatment retained full effector function. Conclusions: The anti-TSHR autoantibody repertoire provides a promising source of binders for off-the-shelf bispecific antibodies targeting TSHR-positive thyroid cancer, while CAR T cells offer an autologous alternative.

cancer biology↗

bioRxiv2025

Functional Dichotomy of Developmental Foxp3+ Treg Cell Subsets in the Visceral Adipose Tissue of Lean and Obese Mice

Chronic inflammation and loss of Foxp3+ regulatory T (Treg) cells in the visceral adipose tissue (VAT) are hallmarks of the pathogenesis of insulin resistance and obesity. This study explores the roles of VAT Treg cells from thymic (tTreg) and peripheral (pTreg) developmental origin, revealing their opposing roles in metabolic inflammation. Obesity destabilized VAT tTreg cells, causing them to clonally expand into obesogenic Foxp3-IFN-{gamma}+ T effector cells, enhancing pro-inflammatory type 1 responses. Genetic tTreg ablation prevented this shift, promoting anti-inflammatory type 2 response, reduced body weight, and improved insulin resistance. Compared to their tTreg counterpart, pTreg cells were functionally well adapted to maintain VAT homeostasis and protect against obesity. Genetic pTreg ablation promoted spontaneous obesity symptoms even with physiological calorie intake, and worsened VAT inflammation and liver steatosis on a high-calorie diet. These findings highlight tTreg instability as a pathogenic threat and pTreg cells as crucial regulators of metabolic homeostasis. HighlightsO_LIVAT Tregs of lean mice originate from both thymic and peripheral Treg development C_LIO_LIHigh-calorie diet destabilizes tTregs that clonally expand into obesogenic IFN-{gamma}+ Th1 cells C_LIO_LIGenetic tTreg deficiency improves steady-state metabolism and prevents diet-induced obesity C_LIO_LIGenetic pTreg deficiency promotes obesity in both sexes even with normal calorie intake C_LIO_LIVAT pTregs are particularly adapted to regulate VAT homeostasis, including adipogenesis C_LI In BriefObesity and type 2 diabetes are characterized by insulin resistance, regulatory T (Treg) cell loss, and chronic inflammation in visceral adipose tissue (VAT). In this context, Yilmazer et al. dissect the functional roles of tTreg and pTreg cells. They show that VAT pTreg cells are particularly adapted to exert non-redundant homeostatic functions, and that pTreg deficiency predisposes to obesity even with normal calorie intake. In contrast, VAT tTreg cells can contribute to local inflammation by dedifferentiating into Foxp3- Th1-polarized effector cells. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/642664v1_ufig1.gif" ALT="Figure 1"> View larger version (60K): org.highwire.dtl.DTLVardef@19c740corg.highwire.dtl.DTLVardef@86d52borg.highwire.dtl.DTLVardef@152a88org.highwire.dtl.DTLVardef@19b7b13_HPS_FORMAT_FIGEXP M_FIG C_FIG

immunology↗

bioRxiv2024

Epigenome profiling identifies H3K27me3 regulation of extra-cellular matrix composition in human corticogenesis

Epigenetic mechanisms regulate gene expression programs during neurogenesis, but the extent of epigenetic remodelling during human cortical development remains unknown. Here, we characterize the epigenetic landscape of the human developing neocortex by leveraging Epi-CyTOF, a mass cytometry-based approach for the simultaneous single cell analysis of more than 30 epigenetic marks. We identify H3K27me3, deposited by Polycomb Repressive Complex 2 (PRC2), as the modification with the strongest cell type-specific enrichment. Inhibition of PRC2 in human cortical organoids resulted in a shift of neural progenitor cell (NPC) proliferation towards differentiation. Cell type- specific profiling of H3K27me3 not only identified neuronal differentiation genes in the human neocortex, but also extra-cellular matrix (ECM) genes. PRC2 inhibition resulted in increased production of the proteoglycan Syndecan 1. Overall, this study comprehensively characterizes the epigenetic state of specific neural cell types and highlights a novel role for H3K27me3 in regulating the ECM composition in the human developing neocortex.

developmental biology↗

bioRxiv2022

Benchmarking solutions to the T-cell receptor epitope prediction problem: IMMREP22 workshop report

Many different solutions to predicting the cognate epitope target of a T-cell receptor (TCR) have been proposed. However several questions on the advantages and disadvantages of these different approaches remain unresolved, as most methods have only been evaluated within the context of their initial publications and data sets. Here, we report the findings of the first public TCR-epitope prediction benchmark performed on 23 prediction models in the context of the ImmRep 2022 TCR-epitope specificity workshop. This benchmark revealed that the use of paired-chain alpha-beta, as well as CDR1/2 or V/J information, when available, improves classification obtained with CDR3 data, independent of the underlying approach. In addition, we found that straight-forward distance-based approaches can achieve a respectable performance when compared to more complex machine-learning models. Finally, we highlight the need for a truly independent follow-up benchmark and provide recommendations for the design of such a next benchmark.

bioinformatics↗

bioRxiv2019

Heme induces innate immunity memory

Trained immunity defines long-lasting adaptive responses of innate immunity, mediated by transcriptional and epigenetic modifications of myeloid cells. Here, we report that labile heme, an alarmin released extracellularily upon tissue damage and hemolysis, induces trained immunity in human and murine primary cells and in mice. Heme-trainning in monocytes is associated with epigenetic and transcriptional profiles that overlap to some extent with those seen in {beta}-glucan-training, the prototype agonist of trained immunity. In sharp contrast to {beta}-glucan training however, heme-training relied on activation of the Syk/JNK-pathway. Heme training in mice was associated with long-lasting expansion of myeloid-biased progenitor cells as well as with altered chromatin accessibility in hematopoietic stem and progenitor cells. Finally, heme-induced training was protective against bacterial sepsis in mice. In conclusion, we reveal that heme, a bona fide alarmin, induces innate immune memory regulating host response to infection.

immunology↗

bioRxiv2019

Gene expression-based identification of antigen-responsive CD8+ T cells on a single-cell level

CD8+ T cells are important effectors of adaptive immunity against pathogens, tumors and self antigens. Here, we asked how human cognate antigen-responsive CD8+ T cells and their receptors could be identified in unselected single-cell gene expression data. Single-cell RNA sequencing and qPCR of dye-labelled antigen-specific cells identified large gene sets that were congruently up- or downregulated in virus-responsive CD8+ T cells under different antigen presentation conditions. Combined expression of TNFRSF9, XCL1, XCL2, and CRTAM was the most distinct marker of virus-responsive cells on a single-cell level. Using transcriptomic data, we developed a machine learning-based classifier that provides sensitive and specific detection of virus-responsive CD8+ T cells from unselected populations. Gene response profiles of CD8+ T cells specific for the autoantigen islet-specific glucose-6-phosphatase catalytic subunit-related protein differed markedly from virus-specific cells. These findings provide single-cell gene expression parameters for comprehensive identification of rare antigen-responsive cells and T cell receptors.\n\nOne-sentence summaryIdentification of genes, gene sets, and development of a machine learning-based classifier that distinguishes antigen-responsive CD8+ T cells on a single-cell level.

immunology↗

bioRxiv2018

Machine learning based classification of cells into chronological stages using single-cell transcriptomics.

Age-associated deterioration of cellular physiology leads to pathological conditions. The ability to detect premature aging could provide a window for preventive therapies against age-related diseases. However, the techniques for determining cellular age are limited, as they rely on a limited set of histological markers and lack predictive power. Here, we implement GERAS (GEnetic Reference for Age of Single-cell), a machine learning based framework capable of assigning individual cells to chronological stages based on their trans criptomes. GERAS displays greater than 90% accuracy in classifying the chronological stage of zebrafish and human pancreatic cells. The framework demonstrates robustness against biological and technical noise, as evaluated by its performance on independent samplings of single-cells. Additionally, GERAS determines the impact of differences in calorie intake and BMI on the aging of zebrafish and human pancreatic cells, respectively. We further harness the predictive power of GERAS to identify genome-wide molecular factors that correlate with aging. We show that one of these factors, junb, is necessary to maintain the proliferative state of juvenile beta-cells. Our results showcase the applicability of a machine learning framework to classify the chronological stage of heterogeneous cell populations, while enabling to detect pro-aging factors and candidate genes associated with aging.

bioinformatics↗

bioRxiv2018

Hematopoietic stem cells differentiate into restricted myeloid progenitors before cell division

Hematopoietic stem cells (HSCs) continuously replenish all blood cell types through a series of differentiation steps that involve the generation of lineage-committed progenitors as well as necessary expansion due to repeated cell divisions. However, whether cell division in HSCs precedes differentiation is unclear. To this end, we used an HSC cell tracing approach and Ki67RFP knock-in mice to assess simultaneously divisional history, cell cycle progression, and differentiation of adult HSCs in vivo. Our results reveal that HSCs are able to differentiate into restricted progenitors, especially common myeloid progenitors, restricted megakaryocyte-erythroid progenitors (PreMEs) and pre-megakaryocyte progenitors (PreMegs), without undergoing cell division and even before entering the S phase of the cell cycle. Additionally, the phenotype of the undivided but differentiated progenitors correlated with expression of lineage-specific genes that manifested as functional differences between HSCs and restricted progenitors. Thus, HSC fate decisions appear to be uncoupled from physical cell division. Our results facilitate a better understanding of the mechanisms that control fate decisions in hematopoietic cells. Our data, together with separate findings from embryonic stem cells, suggest that cell division and fate choice are independent processes in pluripotent and multipotent stem cells.

cell biology↗