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Capietto, A.-H.

Publications and source records attributed to Capietto, A.-H..

3 recordsLinked to original sources

Recurrent RNA-lipoplex vaccination is required to sustain functional tumor-infiltrating neoantigen-specific CD8 T cells and therapeutic efficacy

Cancer vaccines induce durable, polyepitopic T cell responses, and show promising clinical benefit in adjuvant settings, yet they are largely ineffective in advanced disease. Using a clinically relevant RNA-lipoplex vaccine, we investigated the efficacy constraints in a preclinical model. Vaccination remodeled the tumor microenvironment (TME), increasing T cell infiltration and promoting a proinflammatory myeloid compartment. This was associated with complete regression of smaller, immature tumors, but only delayed growth of larger, established tumors. While vaccine-induced T cells were long-lived and functional in peripheral tissues, intratumoral T cells declined rapidly in abundance, diversity, and function, reverting to a prevaccine-like state. scRNA-seq suggested that this was driven by a pro-apoptotic program, with surviving T cells showing signatures of cellular stress and impaired activation. Importantly, recurrent vaccination replenished functional T cells in the TME and enhanced efficacy. These findings highlight the importance of optimizing vaccine schedules and tailoring therapeutic strategies to tumor stage.

immunology↗

A single MHCII neoepitope mRNA vaccine elicits CD4 T- and B- cell responses promoting endogenous CD8 anti-tumor immunity

Recent progress in therapeutic cancer vaccines has shown promising clinical activity, especially when targeting MHC class I (MHCI) neoantigen-specific CD8+ T cell responses in post-surgical patients. To explore the role of CD4+ T cells in vaccine-dependent tumor rejection, we constructed an mRNA lipoplex vaccine encoding a single MHCII-restricted neoantigen. The vaccine elicited Tfh and Th1 cell responses while decreasing Tregs, leading to rejection of established tumors in mice. IL-21 and IFN-{gamma}, crucial for Tfh and Th1 function respectively, contributed to anti-tumor activity. B cells and neoantigen-specific antibodies were also shown to participate in vaccine efficacy. Additionally, conventional type 1 dendritic cells (cDC1s) were essential for eliciting vaccine-induced CD4+ T cells, and both cDC1s and CD4+ T cells were required to enhance endogenous CD8+ responses, which were crucial for tumor control. Our results suggest that immunizing against MHCII neoantigens alone is sufficient to orchestrate a potent and cooperative immune response against cancer.

immunology↗

HLApollo: A superior transformer model for pan-allelic peptide-MHC-I presentation prediction, with diverse negative coverage, deconvolution and protein language features.

Antigen presentation on MHC class I (MHC-I) is key to the adaptive immune response to cancerous cells. Computational prediction of peptide presentation by MHC-I has enabled individualized cancer immunotherapies. Here, we introduce HLApollo, a transformer-based approach with end-to-end modeling of MHC-I sequence, deconvolution, and flanking sequences. To achieve this, we develop a novel training strategy, negative set switching, which greatly reduces overfitting to falsely presumed negatives that are necessarily found in presentation datasets. HLApollo shows a meaningful improvement compared to recent MHC-I models on peptide presentation (20.19% average precision (AP)) and immunogenicity (4.1% AP). As expected, adding gene expression boosts the performance of HLApollo. More interestingly, we show that introduction of features from a protein language model, ESM 1b, remarkably recoups much of the benefits of gene expression in absence of true expression measurements. Finally, we demonstrate excellent pan-allelic generalization, and introduce a framework for estimating the expected accuracy of HLApollo for untrained alleles. This guides the use of HLApollo in a clinical setting, where rare alleles may be observed in some subjects, particularly for underrepresented minorities.

immunology↗