Biology subjects

Besson, S.

Publications and source records attributed to Besson, S..

7 recordsLinked to original sources

bioRxiv2026

Immunomodulatory impact of PTPN11/SHP2-based vertical RAS-MAPK pathway inhibition in pancreatic cancer

Protein tyrosine phosphatase non-receptor 11 (PTPN11/SHP2) is a critical upstream mediator of RAS-MAPK signaling and a central node in adaptive resistance mechanisms evolving with RAS and MEK/ERK inhibition. Accordingly, clinical trials are currently evaluating allosteric SHP2 inhibitors in vertical RAS pathway combination therapies for various KRAS-mutant malignancies, including pancreatic ductal adenocarcinoma (PDAC). Here, we aimed to delineate the immunomodulatory effects of SHP2-based vertical RAS pathway inhibition in notoriously immunotherapy-refractory PDAC, spanning from early treatment response to invariably evolving adaptive resistance. Employing human and murine PTPN11 knockout and wild-type PDAC cell lines, an autochthonous murine PDAC model (KPC), and patient-derived PDAC organoids, we find that short term dual MEK/SHP2 inhibition induces increased T cell infiltration and a reduction in immunosuppressive M2-like macrophages. However, these effects are accompanied by a decrease in mature dendritic cells and a concomitant expansion of monocytic myeloid-derived suppressor cells, indicative of a mixed immunological response with both immune-activating and immune-suppressing features. These changes are associated with tumor cell-intrinsic upregulation of CXCR3 ligands and TGF-{beta}, as well as increased expression of checkpoint ligands for TIGIT and TIM-3 across molecular subtypes and species. With prolonged treatment and transition to an adaptive resistant tumor cell state, the initial immune-sensitizing effects are lost and the immune-suppressive features prevail. M2-like macrophages re-accumulate, dendritic cell maturation remains impaired, TGF-{beta} expression persists, and TIGIT and TIM-3 ligand expression is further enhanced. Notably, dual SHP2/RAS inhibition recapitulates the observed induction of TGF-{beta} and checkpoint ligands. Collectively, these findings identify a dynamic but ultimately immunosuppressive remodeling of the tumor microenvironment in response to SHP2-based vertical RAS pathway inhibition in PDAC and provide a rationale for combinatorial immunotherapy strategies. In particular, concurrent targeting of TGF-{beta}, combined TIGIT/TIM-3 checkpoint blockade, and likely CD40 agonism may help sustain early immune activation while counteracting emerging suppressive features, thereby improving the durability of tumor control.

immunology↗

bioRxiv2025

Vertical RAS-pathway inhibition in pancreatic cancer drives therapeutically exploitable mitochondrial alterations

Background & AimsOncogenic KRAS mutations drive metabolic rewiring in pancreatic ductal adenocarcinoma (PDAC). Src-homology 2 domain-containing phosphatase 2 (SHP2) is essential for full KRAS activity and promising dual SHP2/mitogen-activated protein kinase (MAPK) inhibition is currently being tested in clinical trials. Exploitable metabolic adaptations may contribute to an invariably evolving resistance. MethodsTo understand the metabolic changes induced by dual inhibition, we comprehensively tested cell lines, endogenous tumor models, and patient-derived organoids representing the full spectrum of PDAC molecular subtypes. ResultsWe find that dual SHP2/mitogen-activated protein kinase kinase (MEK1/2) inhibition induces major mitochondrial alterations, elevates reactive oxygen species (ROS) levels and triggers a lipid peroxidase dependency. While anabolic pathways, glycolysis and autophagy were also affected, mitochondrial alterations persisted longterm into a therapy resistant state. ConclusionsThe resulting vulnerability to induction of ferroptotic cell death via combined SHP2/MEK1/2 and glutathione peroxidase (GPX4) inhibition provides a metabolic lever to reinforce RAS-pathway inhibition for targeted PDAC treatment.

cancer biology↗

bioRxiv2023

OME-Zarr: a cloud-optimized bioimaging file format with international community support

A growing community is constructing a next-generation file format (NGFF) for bioimaging to overcome problems of scalability and heterogeneity. Organized by the Open Microscopy Environment (OME), individuals and institutes across diverse modalities facing these problems have designed a format specification process (OME-NGFF) to address these needs. This paper brings together a wide range of those community members to describe the cloud-optimized format itself - OME-Zarr - along with tools and data resources available today to increase FAIR access and remove barriers in the scientific process. The current momentum offers an opportunity to unify a key component of the bioimaging domain -- the file format that underlies so many personal, institutional, and global data management and analysis tasks.

bioinformatics↗

bioRxiv2021

Elicitation of potent SARS-CoV-2 neutralizing antibody responses through immunization using a versatile adenovirus-inspired multimerization platform

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has shown that vaccine preparedness is critical to anticipate a fast response to emergent pathogens with high infectivity. To rapidly reach herd immunity, an affordable, easy to store and versatile vaccine platform is thus desirable. We previously designed a non-infectious adenovirus-inspired nanoparticle (ADDomer), and in the present work, we efficiently decorated this original vaccine platform with glycosylated receptor binding domain (RBD) of SARS-CoV-2. Cryo-Electron Microscopy structure revealed that up to 60 copies of this antigenic domain were bound on a single ADDomer particle with the symmetrical arrangements of a dodecahedron. Mouse immunization with the RBD decorated particles showed as early as the first immunization a significant anti-coronavirus humoral response, which was boosted after a second immunization. Neutralization assays with spike pseudo-typed-virus demonstrated the elicitation of strong neutralization titers. Remarkably, the existence of pre-existing immunity against adenoviral-derived particles enhanced the humoral response against SARS-CoV-2. This plug and play vaccine platform revisits the way of using adenovirus to combat emergent pathogens while potentially taking advantage of the adenovirus pre-immunity.

microbiology↗

bioRxiv2021

OME-NGFF: scalable format strategies for interoperable bioimaging data

Biological imaging is one of the most innovative fields in the modern biological sciences. New imaging modalities, probes, and analysis tools appear every few months and often prove decisive for enabling new directions in scientific discovery. One feature of this dynamic field is the need to capture new types of data and data structures. While there is a strong drive to make scientific data Findable, Accessible, Interoperable and Reproducible (FAIR 1), the rapid rate of innovation in imaging impedes the unification and adoption of standardized data formats. Despite this, the opportunities for sharing and integrating bioimaging data and, in particular, linking these data to other "omics" datasets have never been greater. Therefore, to every extent possible, increasing "FAIRness" of bioimaging data is critical for maximizing scientific value, as well as for promoting openness and integrity. In the absence of a common, FAIR format, two approaches have emerged to provide access to bioimaging data: translation and conversion. On-the-fly translation produces a transient representation of bioimage metadata and binary data but must be repeated on each use. In contrast, conversion produces a permanent copy of the data, ideally in an open format that makes the data more accessible and improves performance and parallelization in reads and writes. Both approaches have been implemented successfully in the bioimaging community but both have limitations. At cloud-scale, those shortcomings limit scientific analysis and the sharing of results. We introduce here next-generation file formats (NGFF) as a solution to these challenges.

bioinformatics↗

bioRxiv2019

Community Standards for Open Cell Migration Data

Cell migration research has become a high-content field. However, the quantitative information encapsulated in these complex and high-dimensional datasets is not fully exploited due to the diversity of experimental protocols and non-standardised output formats. In addition, typically the datasets are not open for reuse. Making the data open and Findable, Accessible, Interoperable, and Reusable (FAIR) will enable meta-analysis, data integration, and data mining. Standardised data formats and controlled vocabularies are essential for building a suitable infrastructure for that purpose but are not available in the cell migration domain. We here present standardisation efforts by the Cell Migration Standardisation Organization, CMSO, an open community-driven organisation to facilitate the development of standards for cell migration data. This work will foster the development of improved algorithms and tools, and enable secondary analysis of public datasets, ultimately unlocking new knowledge of the complex biological process of cell migration.

bioinformatics↗

bioRxiv2016

OME Files - An open source reference library for the OME-XML metadata model and the OME-TIFF file format

Digital imaging is now used throughout biological and biomedical research to measure the architecture, composition and dynamics of cells, tissues and organisms. The many different imaging technologies create data in many different formats. This diversity of data formats arises because the creation of common, cross-domain data standards is difficult and the pace of innovation challenges the durability of any defined standard and the implementation of data stewardship principles such as FAIR1. The Open Microscopy Environment (OME; http://openmicroscopy.org) has therefore developed the OME Data Model, an open, extensible specification for imaging metadata, that supports metadata related to an imaging experiment, data acquisition and any derived analytic results2-4. The OME Data Model has been implemented in OME-XML so that metadata can be stored and accessed by any sof ...

bioinformatics↗