A5070740466- Machine Learning in Bioinformatics
- Monoclonal and Polyclonal Antibodies Research
- Immunotherapy and Immune Responses
- vaccines and immunoinformatics approaches
- Gene expression and cancer classification
- Glycosylation and Glycoproteins Research
- Molecular Biology Techniques and Applications
- Genomics and Phylogenetic Studies
- RNA and protein synthesis mechanisms
- CAR-T cell therapy research
- Protein purification and stability
- Immune Cell Function and Interaction
- Bioinformatics and Genomic Networks
Nanjing Tech University
2022
University of Science and Technology of China
2014
The development of tumor vaccines represents a significant focus within cancer therapeutics research. Nonetheless, the efficiency antigen presentation in vaccine remains suboptimal. We introduce an innovative mRNA-lipid nanoparticle platform designed to express antigenic epitopes fused with transmembrane domain and cytoplasmic tail neonatal Fc receptor (FcRn). This novel design exploits FcRn trafficking signals direct epitope-FcRn fusion toward endolysosomal degradation, thereby generating...
Precise neoepitope discovery is crucial for effective cancer therapeutic vaccines. Conventional approaches struggle to build a repertoire with sufficient immunogenic epitopes. We developed workflow leveraging full-length ribosome–nascent chain complex–bound mRNA sequencing (FL-RNC seq) and artificial intelligence–based predictive models accurately identify the landscape, especially large-scale transcript variants (LSTVs) missed by short-read sequencing. In MC38 mouse model, we identified 22...
In the past decade, substantial achievements of therapeutic cancer vaccines have shed a new light on immunotherapy. The major challenge for designing potent is to identify neoantigens capable inducing sufficient immune responses, especially involving histocompatibility complex (MHC)-II epitopes. However, most previous studies T-cell epitopes were focused either ligand binding or antigen presentation by MHC rather than immunogenicity order better facilitate vaccine design, in this study, we...
Abstract Predicting MHC-II restricted epitopes across species used to be challenging, but Alphafold (AF) may provide a structure-based pan-prediction solution. In this study, we established the new tool AF-pred with clear standard for quantitative prediction results. Compared sequence-based tools heavily trained human ligandome, does not show advantage in predicting binding patterns of HLA-II has far better performance other animals’ MHC-II. Using recently resolved bat structures, analyzed...
Background: Genetic mutations that cause the inactivation or aberrant activation of essential proteins may trigger alterations even dysfunctions in cellular signaling pathways, culminating development precancerous lesions and cancer. Mutations such can result generation "novel proteins" are not part conventional human proteome. Identification these carries a profound potential for unraveling promising drug targets designing innovative therapeutic models. Despite emergence diverse tools...
Abstract Summary Genetic modifications that cause pivotal protein inactivation or abnormal activation may lead to cell signaling pathway change even dysfunction, resulting in cancer and other diseases. In turn, dysfunction will further produce “novel proteins” do not exist the canonical human proteome. Identification of novel proteins is meaningful for identifying promising drug targets developing new therapies. recent years, several tools have been developed DNA RNA variants with extensive...
Genetic modifications that cause pivotal protein inactivation or abnormal activation may lead to cell signaling pathway change even dysfunction, resulting in cancer and other diseases. In turn, dysfunction will further produce “novel proteins” do not exist the canonical human proteome. Identification of novel proteins is meaningful for identifying promising drug targets developing new therapies. recent years, several tools have been developed DNA RNA variants with extensive application...