Biology subjects

Ramon, A.

Publications and source records attributed to Ramon, A..

3 recordsLinked to original sources

bioRxiv2025

Highly potent novel multi-armoured IL13Rα2 CAR-T subverts the immunosuppressive microenvironment of Glioblastoma

Glioblastoma remains one of the most challenging and lethal brain cancers, with limited treatment options. While CAR-T cells have shown promise in some patients, sustaining T-cell activity and overcoming the immunosuppressive tumour microenvironment remain significant hurdles. Here, we present an armoured CAR-T cell design to address these challenges and enhance persistence in GBM tumours. We developed a highly specific humanised single-domain antibody targeting IL13R2 and included it alongside four additional modular elements in a single retroviral vector for CAR-T generation. Our results demonstrate that this single-cassette CAR-T cell design possesses high resilience against TGF-{beta}-mediated immunosuppression, enhanced tumour-killing capacity through IL-12 secretion while maintaining a favourable safety profile, extended persistence in the host, and an additional layer of safety control through the incorporation of a suicide switch. Importantly, despite its complexity, the construct can still be manufactured efficiently. These advancements represent a significant step forward in addressing key challenges associated with CAR-T cell therapy in solid tumours.

cancer biology↗

bioRxiv2024

A direct computational assessment of vinculin-actin unbinding kinetics reveals catch bonding behavior

Vinculin forms a catch bond with the cytoskeletal polymer actin, displaying an increased bond lifetime upon force application. Notably, this behavior depends on the direction of the applied force, which has significant implications for cellular mechanotransduction. In this study, we present a comprehensive molecular dynamics simulation study, employing enhanced sampling techniques to investigate the thermodynamic, kinetic, and mechanistic aspects of this phenomenon at physiologically relevant forces. We dissect a catch bond mechanism in which force shifts vinculin between either a weakly- or strongly-bound state. Our results demonstrate that models for these states have unbinding times consistent with those from single-molecule studies, and suggest that both have some intrinsic catch bonding behavior. We provide atomistic insight into this behavior, and show how a directional pulling force can promote the strong or weak state. Crucially, our strategy can be extended to capture the difficult-to-capture effects of small mechanical forces on biomolecular systems in general, and those involved in mechanotransduction more specifically.

biophysics↗

bioRxiv2023

AbNatiV: VQ-VAE-based assessment of antibody and nanobody nativeness for engineering, selection, and computational design

Monoclonal antibodies have emerged as key therapeutics, and nanobodies are rapidly gaining momentum following the approval of the first nanobody drug in 2019. Nonetheless, the development of these biologics as therapeutics remains a challenge. Despite the availability of established in vitro directed evolution technologies that are relatively fast and cheap to deploy, the gold standard for generating therapeutic antibodies remains discovery from animal immunization or patients. Immune-system derived antibodies tend to have favourable properties in vivo, including long half-life, low reactivity with self-antigens, and low toxicity. Here, we present AbNatiV, a deep-learning tool for assessing the nativeness of antibodies and nanobodies, i.e., their likelihood of belonging to the distribution of immune-system derived human antibodies or camelid nanobodies. AbNatiV is a multi-purpose tool that accurately predicts the nativeness of Fv sequences from any source, including synthetic libraries and computational design. It provides an interpretable score that predicts the likelihood of immunogenicity, and a residue-level profile that can guide the engineering of antibodies and nanobodies indistinguishable from immune-system-derived ones. We further introduce an automated humanisation pipeline, which we applied to two nanobodies. Wet-lab experiments show that AbNatiV-humanized nanobodies retain binding and stability at par or better than their wild type, unlike nanobodies humanised relying on conventional structural and residue-frequency analysis. We make AbNatiV available as downloadable software and as a webserver.

bioengineering↗