Biology subjects

Alemany, R.

Publications and source records attributed to Alemany, R..

4 recordsLinked to original sources

bioRxiv2023

Unraveling the Power of NAP-CNB's Machine Learning-enhanced Tumor Neoantigen Prediction

In this study, we present a proof-of-concept classical vaccination experiment that validates the in silico identification of tumor neoantigens (TNAs) using a machine learning-based platform called NAP-CNB. Unlike other TNA predictors, NAP-CNB leverages RNAseq data to consider the relative expression of neoantigens in tumors. Our experiments show the efficacy of NAP-CNB. Predicted TNAs elicited potent antitumor responses in vivo following classical vaccination protocols. Notably, optimal antitumor activity was observed when targeting the antigen with higher expression in the tumor, which was not the most immunogenic. Additionally, the vaccination combining different neoantigens resulted in vastly improved responses compared to each one individually, showing the worth of multiantigen-based approaches. These findings validate NAP-CNB as an innovative TNA-identification platform and make a substantial contribution to advancing the next generation of personalized immunotherapies

immunology↗

bioRxiv2022

Driver mutations in GNAQ and GNA11 genes as potential targets for precision immunotherapy in uveal melanoma patients

Uveal melanoma (UM) is the most common ocular malignancy in adults. Nearly 95% of UM patients carry the mutually exclusive mutations in the homologous genes GNAQ (aminoacid change Q209L/Q209P) and GNA11 (aminoacid change Q209L). UM is located in an immunosuppressed organ and do not suffer immunoediting. Therefore, we hypothesize that driver mutations in GNAQ/11 genes could be recognized by the immune system. Genomic and transcriptomic data for primary uveal tumors was collected from TCGA-UM dataset (n=80). The immunogenic potential for GNAQ/GNA11 Q209L/Q209P mutations was assessed using a variety of tools and HLA types information. The immune microenvironment was characterized using gene expression data. All prediction tools showed stronger GNAQ/11 Q209L binding to HLA. The immunogenicity analysis revealed that Q209L is likely to be presented by more than 73% of individuals in 1000G database whereas Q209P is only predicted to be presented in 24% of individuals. GNAQ/11 Q209L showed higher likelihood to be presented by HLA-I molecules than almost all driver mutations analyzed. Samples carrying Q209L had a higher immune-reactive phenotype: (i) expression of antigen presenting genes HLA-A (p=0.009) and B2M (p=0.043); (ii) immunophenoscore (p=0.008); (iii) infiltration of immune system cells NK (p=0.002) and CD8+ T lymphocytes (p=0.02). Results suggest a high potential immunogenicity of the GNAQ/11 Q209L variant that could allow the generation of novel therapeutic tools to treat UM like neoantigen vaccinations.

genomics↗

bioRxiv2020

NAP-CNB: Bioinformatic pipeline to predict MHC-I-restricted T cell epitopes in mice

Lack of a dedicated integrated pipeline for neoantigen discovery in mice hinders cancer immunotherapy research. Novel sequential approaches through recurrent neural networks can improve the accuracy of T-cell epitope immunogenicity predictions in mice, and a simplified variant selection process can reduce operational requirements. We have developed a web server tool (NAP-CNB) for a full and automatic pipeline based on recurrent neural networks, to predict putative neoantigens from tumoral RNA sequencing reads. The developed software can estimate H-2 peptide ligands, with an AUC of 0.95, directly from tumor samples. As a proof-of-concept, we used the B16 melanoma model to test the systems predictive capabilities, and we report its putative neoantigens. NAP-CNB web server is freely available at http://biocomp.cnb.csic.es/NeoantigensApp/ with scripts and datasets accessible through the download section.

bioinformatics↗

bioRxiv2020

Transgene codon usage drives viral fitness and therapeutic efficacy in oncolytic adenoviruses

Arming oncolytic adenoviruses with therapeutic transgenes is a well-established strategy for multimodal tumour attack. However, this strategy sometimes leads to unexpected attenuated viral replication and a loss of oncolytic effects, preventing these viruses from reaching the clinic. Previous work has shown that altering codon usage in viral genes can hamper viral fitness. Here, we have analysed how transgene codon usage impacts viral replication and oncolytic activity. We observe that, although transgenes with optimised codons show high expression levels at a first round of infection, they impair viral fitness and are therefore not expressed in a sustained manner. Conversely, transgenes encoded by suboptimal codons do not compromise viral replication and are thus stably expressed over time allowing a greater oncolytic activity both in vitro and in vivo. Altogether, our work shows that fine-tuning codon usage leads to a concerted optimisation of transgene expression and viral replication paving the way for the rational design of more efficacious oncolytic therapies.Competing Interest StatementM.FS is a VCN Biosciences S.L. employee. All the other authors declare no conflict of interest.View Full Text

bioengineering↗