Biology subjects

Massenet-Regad, L.

Publications and source records attributed to Massenet-Regad, L..

3 recordsLinked to original sources

bioRxiv2024

Spatial transcriptomics unveils immune cellular ecosystems associated with patient survival in diffuse large B-cell lymphoma

Diffuse Large B-cell Lymphoma (DLBCL) is the most prevalent subtype of non-Hodgkins lymphoma for which current therapeutic strategies remain insufficient. The diffuse nature of DLBCL, lacking distinct tissue structures, represents a challenge to elucidate the cellular organization and interactions within the tumor microenvironment (TME). In this study, we applied spatial transcriptomics to identify spatially-resolved gene expression profiles in 10 DLBCL tissue samples, identifying distinct immune cell infiltration and colocalization patterns. These profiles were classified into six cellular ecosystems (Cell-Eco) that differ in cellular composition, functional patterns, and neighborhood characteristics. The spatially-resolved Cell-Eco signatures provided prognostic scores that stratified patients with different overall survival rates. We also found that C1q+ tumor-associated macrophages are the primary cells interacting with malignant B cells and influencing the spatial architecture of the TME. This study provides novel biological insights into the complexity of the TME in DLBCL and highlights the potential prognostic value of its spatial organization. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=163 SRC="FIGDIR/small/613252v1_ufig1.gif" ALT="Figure 1"> View larger version (43K): org.highwire.dtl.DTLVardef@147a46eorg.highwire.dtl.DTLVardef@7c5236org.highwire.dtl.DTLVardef@1f99506org.highwire.dtl.DTLVardef@a6d271_HPS_FORMAT_FIGEXP M_FIG C_FIG Key findingsO_LISpatial transcriptomics classifies DLBCL tissues based on immune cell infiltration and colocalization patterns. C_LIO_LIDLBCL tumor microenvironment consists of cellular ecosystems (Cell-Eco) that differ in cellular composition, transcriptomic profiles and neighborhood characteristics. C_LIO_LISpatially-resolved Cell-Eco signatures stratify patients with different overall survival. C_LIO_LIC1q+ tumor-associated macrophages primarily interact with malignant B cells and contribute to the spatial organization of the tumor microenvironment. C_LI

immunology↗

bioRxiv2021

Differentiation of exhausted CD8 T cells after termination of chronic antigen stimulation stops short of achieving functional T cell memory

T cell exhaustion is associated with failure to clear chronic infections and malignant cells. Defining the molecular mechanisms of T cell exhaustion and reinvigoration is essential to improving immunotherapeutic modalities. Analysis of antigen-specific CD8+ T cells before and after antigen removal in human hepatitis C virus (HCV) infection confirmed pervasive phenotypic, functional, and transcriptional differences between exhausted and memory CD8+ T cells. After viral cure, we observed broad phenotypic and transcriptional changes in clonally stable exhausted T-cell populations suggesting differentiation towards a memory-like profile. However, functionally, the cells showed little improvement and critical transcriptional regulators remained in the exhaustion state. Notably, T cells from chronic HCV infection that were exposed to antigen for shorter periods of time because of viral escape mutations were functionally and transcriptionally more similar to memory T cells from spontaneously resolved acute HCV infection. Thus, duration of T cell stimulation impacts the ability to recover from exhaustion, as antigen removal after long-term T cell exhaustion is insufficient for the development of key T cell memory characteristics.

immunology↗

bioRxiv2020

ICELLNET: a transcriptome-based framework to dissect intercellular communication

Cell-to-cell communication can be inferred from ligand-receptor expression in cell transcriptomic datasets. However, important challenges remain: 1) global integration of cell-to-cell communication, 2) biological interpretation, and 3) application to individual cell population transcriptomic profiles. We developed ICELLNET, a transcriptomic-based framework integrating: 1) an original expert-curated database of ligand-receptor interactions accounting for multiple subunits expression, 2) quantification of communication scores, 3) the possibility to connect a cell population of interest with 31 reference human cell types (BioGPS), and 4) three visualization modes to facilitate biological interpretation. We applied ICELLNET to uncover different communication in breast cancer associated fibroblast (CAF) subsets. ICELLNET also revealed autocrine IL-10 as a switch to control human dendritic cell communication with up to 12 other cell types, four of which were experimentally validated. In summary, ICELLNET is a global, versatile, biologically validated, and easy-to-use framework to dissect cell communication from single or multiple cell-based transcriptomic profile(s).

systems biology↗