Biology subjects

Ramon, A.

Publications and source records attributed to Ramon, A..

5 recordsLinked to original sources

bioRxiv2026

Engineering armoured in vivo CAR T cells through targeted delivery and transient mRNA gating

In vivo generation of chimeric antigen receptor (CAR) T cells offers an off-the-shelf, scalable alternative to ex-vivo therapies, but is constrained by inefficiency, toxicity and durability. We report the first armoured in-vivo CAR T platform with tunable, transient activity, that enhances safety and efficacy. Our platform utilises CD8 targeted lipid nanoparticles (LNP) to transiently deliver CAR and armouring membrane-bound IL12 mRNAs. Payloads utilize a T-cell-restricted (T-trex) strategy to constrain CAR and IL-12 expression to T cells, enabling potent antigen-dependent activity with spatio-temporal control. Selective targeting of T-cells with a T-trex CAR showed enhanced expression. The addition of T-trex IL12 mRNA provides a tunable, localised amplification of CAR function, enhancing antigen-dependent cytotoxicity and cytokine production with robust tumour control. These findings establish a novel dose-efficient armoured in-vivo CAR T approach and general framework for programmable immune cell engineering.

immunology↗

bioRxiv2025

Deep learning assessment of nativeness and pairing likelihood for antibody and nanobody design with AbNatiV2

1Immune systems create antibodies that balance good binding and stability with low toxicity and self- reactivity. Quantifying the nativeness of a candidate sequence - its likelihood of belonging to natural immune repertoires - has thus emerged as a valuable strategy for hit selection from synthetic libraries, optimisation and humanisation, and for guiding de novo design towards developable candidates. We previously introduced AbNatiV, a transformer-based VQ-VAE for nativeness assessment, which proved effective across multiple nanobody engineering tasks. However, AbNatiV1 operated on unpaired sequences, limiting applicability to conventional VH-VL antibodies. Moreover, its performance on nanobody nativeness was constrained by the limited number and diversity of nanobody repertoires available at the time. Here, we sequenced new camelid repertoires, curated additional recent datasets, and present AbNatiV2: an enhanced architecture comprising various models each trained on [≥] 20 million sequences. AbNatiV2 improves nanobody nativeness classification across held-out and diverse test sets, and more robustly detects nativeness changes upon CDR grafting. We also introduce p-AbNatiV2, a cross-attention model fine-tuned on 3.7 million paired human sequences. p-AbNatiV2 provides residue- and sequence-level humanness for VH/VL pairs and learns pairing-likelihood via noise-contrastive training. On held-out tests, it assigns the native pair a higher score in 74% of cases, substantially outperforming recent pairing models. Together, AbNatiV2 and p-AbNatiV2 extend nativeness assessment and engineering to both nanobodies and conventional antibodies, supporting design decisions at single-residue, Fv-sequence, and paired-domain levels. We make AbNatiV2 available as downloadable software and webserver.

bioengineering↗

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↗