Biology subjects

Dutertre, C.-A.

Publications and source records attributed to Dutertre, C.-A..

8 recordsLinked to original sources

bioRxiv2026

Monocytes promote intraepithelial infiltration of effector memory CD8+ T cells in regressing tumors

Despite the clinical success of cancer immunotherapies, the cellular interactions driving tumor regression remain incompletely understood. Here, we investigated the dynamic remodeling of the tumor immune microenvironment during regression of transplanted PyMT mammary tumors following STING agonist treatment. Using scRNA-seq of sorted CD8+ T cells and myeloid cells, combined with imaging approaches, we identified major changes in both lymphoid and myeloid compartments during tumor regression. Regressing tumors showed a transient accumulation of Ly6Chi monocyte populations associated with a decline in macrophage subsets, while effector and memory CD8+ T-cell populations increased at the expense of exhausted T cells. Interaction analyses predicted enhanced chemotactic and adhesion interactions between CXCL9+ Ly6Chi monocytes and effector CD8+ T cells. Consistently, dynamic imaging revealed increased CD8+ T-cell motility and infiltration into tumor cores following treatment. In particular, CXCR6+ effector CD8+ T cells transiently accumulated within tumor islets during regression before relocalizing to stromal regions. Together, these findings reveal a coordinated spatiotemporal remodeling of myeloid and CD8+ T-cell populations during immunotherapy-induced tumor regression and highlight cooperative interactions that may promote durable anti-tumor immunity.

immunology↗

bioRxiv2023

Sopa: a technology-invariant pipeline for analyses of image-based spatial-omics

Spatial-omics data allow in-depth analysis of tissue architectures, opening new opportunities for biological discovery. In particular, imaging techniques offer single-cell resolutions, providing essential insights into cellular organizations and dynamics. Yet, the complexity of such data presents analytical challenges and demands substantial computing resources. Moreover, the proliferation of diverse spatial-omics technologies, such as Xenium, MERSCOPE, CosMX in spatial-transcriptomics, and MACSima and PhenoCycler in multiplex imaging, hinders the generality of existing tools. We introduce Sopa (https://github.com/gustaveroussy/sopa), a technology-invariant, memory-efficient pipeline with a unified visualizer for all image-based spatial omics. Built upon the universal SpatialData framework, Sopa optimizes tasks like segmentation, transcript/channel aggregation, annotation, and geometric/spatial analysis. Its output includes user-friendly web reports and visualizer files, as well as comprehensive data files for in-depth analysis. Overall, Sopa represents a significant step toward unifying spatial data analysis, enabling a more comprehensive understanding of cellular interactions and tissue organization in biological systems.

bioinformatics↗

bioRxiv2021

Tissue-resident FOLR2+ macrophages associate with tumor-infiltrating CD8+ T cells and with increased survival of breast cancer patients.

Macrophage infiltration is a hallmark of solid cancers and overall macrophage infiltration is correlated with lower patient survival and resistance to therapy. However, tumor-associated macrophages are phenotypically and functionally heterogeneous. Specific tumor-associated macrophage subsets might be endowed with antagonistic role on cancer progression and on the development of anti-tumor immunity. For instance, monocyte-derived TREM2+ tumor-associated macrophages have pro-tumorigenic and immunosuppressive functions. Here, we identify a discrete population of FOLR2+ tumor-associated macrophages positively correlating with patient survival in breast cancer. FOLR2+ macrophages are evolutionarily conserved across species and populate human and murine healthy mammary gland. Moreover, FOLR2+ macrophages co-localize with lymphoid aggregates containing CD8+ T cells in breast cancer and across ten other types of cancers. This study highlights antagonistic roles for tumor-associated macrophage subsets and paves the way for subset-specific therapeutic interventions in macrophages-based cancer therapies.

immunology↗

bioRxiv2020

Highly functional virus-specific cellular immune response in asymptomatic SARS-CoV-2 infection

The efficacy of virus-specific T cells in clearing pathogens involves a fine balance between their antiviral and inflammatory features. SARS-CoV-2-specific T cells in individuals who clear SARS-CoV-2 infection without symptoms or disease could reveal non-pathological yet protective characteristics. We therefore compared the quantity and function of SARS-CoV-2-specific T cells in a cohort of asymptomatic individuals (n=85) with that of symptomatic COVID-19 patients (n=76), at different time points after antibody seroconversion. We quantified T cells reactive to structural proteins (M, NP and Spike) using ELISpot assays, and measured the magnitude of cytokine secretion (IL-2, IFN-{gamma}, IL-4, IL-6, IL-1{beta}, TNF- and IL-10) in whole blood following T cell activation with SARS-CoV-2 peptide pools as a functional readout. Frequencies of T cells specific for the different SARS-CoV-2 proteins in the early phases of recovery were similar between asymptomatic and symptomatic individuals. However, we detected an increased IFN-{gamma} and IL-2 production in asymptomatic compared to symptomatic individuals after activation of SARS-CoV-2-specific T cells in blood. This was associated with a proportional secretion of IL-10 and pro-inflammatory cytokines (IL-6, TNF- and IL-1{beta}) only in asymptomatic infection, while a disproportionate secretion of inflammatory cytokines was triggered by SARS-CoV-2-specific T cell activation in symptomatic individuals. Thus, asymptomatic SARS-CoV-2 infected individuals are not characterized by a weak antiviral immunity; on the contrary, they mount a robust and highly functional virus-specific cellular immune response. Their ability to induce a proportionate production of IL-10 might help to reduce inflammatory events during viral clearance.

immunology↗

bioRxiv2020

Infinity Flow: High-throughput single-cell quantification of 100s of proteins using conventional flow cytometry and machine learning

Modern immunologic research increasingly requires high-dimensional analyses in order to understand the complex milieu of cell-types that comprise the tissue microenvironments of disease. To achieve this, we developed Infinity Flow combining hundreds of overlapping flow cytometry panels using machine learning to enable the simultaneous analysis of the co-expression patterns of 100s of surface-expressed proteins across millions of individual cells. In this study, we demonstrate that this approach allows the comprehensive analysis of the cellular constituency of the steady-state murine lung and to identify novel cellular heterogeneity in the lungs of melanoma metastasis bearing mice. We show that by using supervised machine learning, Infinity Flow enhances the accuracy and depth of clustering or dimensionality reduction algorithms. Infinity Flow is a highly scalable, low-cost and accessible solution to single cell proteomics in complex tissues.

immunology↗

bioRxiv2019

Engineered niches support the development of human dendritic cells in humanized mice

Classical dendritic cells (cDCs) are rare sentinel cells specialized in the regulation of adaptive immunity. Modeling cDC development is both crucial to study cDCs and harness their potential in immunotherapy. Here we addressed whether cDCs could differentiate in response to trophic cues delivered by mesenchymal components of the hematopoietic niche where they physiologically develop and maintain. We found that expression of the membrane bound form of human FLT3L and SCF together with CXCL12 in a bone marrow mesenchymal stromal cell line is sufficient to induce the contact-dependent specification of both type 1 and type 2 cDCs from CD34+ hematopoietic stem and progenitor cells (HSPCs). Engraftment of these engineered mesenchymal stromal cells (eMSCs) together with CD34+ HSPCs creates an in vivo synthetic niche in the dermis of immunodeficient mice. Cell-to-cell contact between HSPCs and stromal cells within these organoids drive the local specification of cDCs and CD123+AXL+CD327+ pre/AS-DCs. cDCs generated in vivo display higher levels of resemblance with human blood cDCs unattained by in vitro generated subsets. Altogether, eMSCs provide a novel and unique platform recapitulating the full spectrum of cDC subsets enabling their functional characterization in vivo.

immunology↗

bioRxiv2019

Constitutive Siglec-1 expression by human dendritic cell precursors enables HIV-1 replication and transmission

Human dendritic cell (DC) lineage has been recently unraveled by high dimensional mapping revealing the existence of a discrete new population of blood circulating DC precursor (pre-DC also referred to as AS DC). Among all blood DC subsets, only pre-DC highly express Siglec-1, a lectin-like receptor able to bind HIV-1. We show that pre-DC are uniquely equipped among blood DC populations to promote HIV-1 replication and dissemination. Pre-DC stands out as the most susceptible DC population to infection by both HIV-1 CXCR4- and CCR5-tropic viral particles in a Siglec-1-dependent manner. HIV-1-infected pre-DC produce new viral progeny and transmit the virus to CD4+ T cells. Upon TLR activation, pre-DC become resistant to HIV-1 fusion and thus to infection and switch to a replication-independent mechanism of virus transfer to activated primary T lymphocytes mediated by Siglec-1. Thus, beside their role in DC ontogeny, blood pre-DC possess stage-specific properties that HIV-1 may exploit for viral spreading and modulation of the immune response.

immunology↗

bioRxiv2018

Evaluation of UMAP as an alternative to t-SNE for single-cell data

Uniform Manifold Approximation and Projection (UMAP) is a recently-published non-linear dimensionality reduction technique. Another such algorithm, t-SNE, has been the default method for such task in the past years. Herein we comment on the usefulness of UMAP high-dimensional cytometry and single-cell RNA sequencing, notably highlighting faster runtime and consistency, meaningful organization of cell clusters and preservation of continuums in UMAP compared to t-SNE.

bioinformatics↗