Biology subjects

Becht, E.

Publications and source records attributed to Becht, E..

9 recordsLinked to original sources

bioRxiv2024

T cell mediated impairment of epithelial integrity in Crohn's disease

T lymphocytes play a major role in intestinal homeostasis, with a particular impact on the balance between self-renewal and differentiation of intestinal epithelial cells (IECs). In Crohns disease (CD) patients, the intestinal mucosa is inflamed, epithelium permeability is increased, and IECs present compositional and functional defects. The role of T lymphocytes interactions with IECs in the physiopathology of CD remains in question. Here, we use a three-dimensional human autologous coculture model between purified intestinal organoids derived from primary tissues of CD and non-inflammatory control patients, and mucosal T lymphocytes extracted from the same location. We show that while in homeostatic context T cells support the proliferation and differentiation balance of organoids, mucosal T lymphocytes from CD patients present a high cytotoxicity against IECs. Importantly, this cytotoxicity is a persistent defect overtime in culture. Organoids also show defective intestinal stem cells (ISCs) proliferation and morphological changes. Single cell RNA sequencing after coculture highlights a general response of T cells to the epithelial microenvironment, and more particularly, an increase activation of a pro-inflammatory CD8+ T cells effector population in CD patients compared to controls. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=187 SRC="FIGDIR/small/621219v1_ufig1.gif" ALT="Figure 1"> View larger version (53K): org.highwire.dtl.DTLVardef@78453aorg.highwire.dtl.DTLVardef@8f484org.highwire.dtl.DTLVardef@1ed0934org.highwire.dtl.DTLVardef@f75094_HPS_FORMAT_FIGEXP M_FIG C_FIG

immunology↗

bioRxiv2020

webMCP-counter: a web interface for transcriptomics-based quantification of immune and stromal cells in heterogeneous human or murine samples

SummaryWe previously reported MCP-counter and mMCP-counter, methods that allow precise estimation of the immune and stromal composition of human and murine samples from bulk transcriptomic data, but they were only distributed as R packages. Here, we report webMCP-counter, a user-friendly web interface to allow all users to use these methods, regardless of their proficiency in the R programming language. Availability and ImplementationFreely available from http://134.157.229.105:3838/webMCP/. Website developed with the R package shiny. Source code available from GitHub: https://github.com/FPetitprez/webMCP-counter.

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↗

bioRxiv2020

The murine Microenvironment Cell Population counter method to estimate abundance of tissue-infiltrating immune and stromal cell populations in murine samples using gene expression

Quantifying tissue-infiltrating immune and stromal cells provides clinically relevant information for various diseases, notably cancer. While numerous methods allow to quantify immune or stromal cells in human tissue samples based on transcriptomic data, very few are available for mouse studies. Here, we introduce murine Microenvironment Cell Population counter (mMCP-counter), a method based on highly specific transcriptomic markers that allow to accurately quantify 12 immune and 4 stromal murine cell populations. We validated mMCP-counter with flow cytometry data. We also showed that mMCP-counter outperforms existing methods. We showed in mouse models of mesothelioma and kidney cancer that mMCP-counter quantification scores are predictive of response to immune checkpoint blockade Finally, we illustrated mMCP-counters potential to analyze immune impacts of Alzheimers disease. mMCP-counter is available as an R package from GitHub: https://github.com/cit-bioinfo/mMCP-counter.

bioinformatics↗

bioRxiv2019

Partial absence of PD-1 expression by tumor-specific CD8+ T cells in EBV-driven lymphoepithelioma-like carcinoma: a case report

Lymphoepithelioma-like carcinoma (LELC) is an uncommon lung cancer, typically observed in young, non-smoking Asian populations. LELC is associated with Epstein-Barr virus (EBV) infection of lung tumor cells of epithelial origin, suggesting a carcinogenic role of EBV as observed in nasopharyngeal carcinoma (NPC). Here, we studied the antigen specificity and phenotype of CD8+ tumor infiltrating lymphocytes (TILs) in one LELC patient positive for EBV infection in lung tumor cells. Using MHC class I tetramers, we detected two populations of EBV-specific CD8+ TILs, which can be considered as tumor-specific CD8+ T cells, in the tumor of this patient. Transcriptomic analyses of these two populations reveal their distinct exhausted profiles and polyclonal TCR repertoire. High dimensional analyses at single cell level using mass cytometry showed showed that populations of tumor specific CD8+ TILs are phenotypically heterogeneous, although they consistently express CD39. Unexpectedly, although the LELC tumor cells expressed abundant PD-L1, these tumor-specific CD8+ TILs mostly did not express PD-1, suggesting that anti-PD1/PD-L1 immunotherapy may not be an appropriate strategy for disinhibiting EBV-specific cells for the treatment of LELC patients. These results might also help to explain low rates of checkpoint blockade immunotherapy response for NPC, despite the antigenicity of EBV for both tumor types.

cancer biology↗

bioRxiv2019

Reply to \"A discriminative learning approach to differential expression analysis for single-cell RNA-seq\"

Multivariate logistic regression (mLR) has been recently proposed by Ntranos et al. to perform gene differential expression analyses of single-cell RNA-sequencing (scRNAseq) data. Herein we reproduce and extend some of their findings. We notably show that while mLR performs better in simulated datasets, these simulations do not recapitulate important features of experimental datasets. Indeed, our results suggest that MAST followed by Sidak aggregation of the p-values perform better than mLR on experimental datasets. Overall, we highlight that most of the new results obtained by Ntranos et al is likely due to the quantification of scRNAseq data at the transcript or transcript compatibility classes level, rather than the use of mLR.

bioinformatics↗

bioRxiv2018

Cancer stemness, intratumoral heterogeneity, and immune response across cancers

Regulatory programs that control the function of stem cells are active in cancer and confer properties that promote progression and therapy resistance. However, the impact of a stem cell-like tumor phenotype (\"sternness\") on the immunological properties of cancer has not been systematically explored. Using gene expression-based metrics, we evaluate the association of stemness with immune cell infiltration and genomic, transcriptomic, and clinical parameters across 21 solid cancers. We find pervasive negative associations between cancer stemness and anticancer immunity. This occurs despite high stemness cancers exhibiting increased mutation load, cancer-testis antigen expression, and intratumoral heterogeneity. Stemness was also strongly associated with cell-intrinsic suppression of endogenous retroviral expression and type I interferon signaling and increased expression of several therapeutically accessible signaling pathways. Thus, stemness is not only a fundamental process in cancer progression but may represent a unifying mechanism linking antigenicity, intratumoral heterogeneity, and immune suppression across cancers.

cancer biology↗

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↗

bioRxiv2018

Reverse-engineering flow-cytometry gating strategies for phenotypic labelling and high-performance cell sorting

MotivationRecent flow and mass cytometers generate 1,000,000 single cell datasets of dimensions 20 to 40. Many tools facilitate the discovery of new cell populations associated with diseases or physiology. These discoveries require the identification of new gating strategies, but gating strategies become exponentially harder to optimize when dimensionality increases. To facilitate this step we developed Hypergate, an algorithm which given a cell population of interest identifies a gating strategy optimized for high yield and purity.\n\nResultsHypergate achieves higher yield and purity than human experts, Support Vector Machines and Random-Forests on public datasets. We use it to revisit some established gating strategies for the identification of Innate lymphoid cells, which identifies concise and efficient strategies that allow gating these cells with fewer parameters but higher yield and purity than the current standards. For phenotypic description, Hypergates outputs are consistent with fields knowledge and sparser than those from a competing method.\n\nAvailability and ImplementationHypergate is implemented in R and available at http://github.com/ebecht/hypergate under an Open Source Initiative-compliant licence.

bioinformatics↗