CEDAR中的癌症表位预测工具与分析流程

The identification of immunogenic cancer epitopes, including patient-specific neoepitopes and shared tumor-associated antigens (TAAs), is a central challenge for the development of effective cancer immunotherapies. To accelerate their discovery, the Cancer Epitope Database and Analysis Resource (CEDAR), a comprehensive resource for immuno-oncology, curates epitope data from the literature and develops tailored computational tools. Building on this foundation, we introduce the modular Next-Generation IEDB Tools (NGT) platform (nextgen-tools.iedb.org/) that integrates a wide array of cancer-focused computational tools. The NGT platform allows users to construct, save, and share customized, reproducible, end-to-end computational pipelines for tumor antigen discovery. This architecture enables systematic prioritization of epitope candidates by applying multiple, sequential filtering criteria based on predicted and calculated relevant immune features, such as antigen expression, antigen presentation, self-similarity, and immunogenicity. Key tools include the Mutated Peptide Generator (MPG), which translates genomic variants (e.g., SNVs, indels) into candidate neoepitope sequences; Peptide Expression Annotation (PepX), which integrates public RNA-Seq data from resources like TCGA and GTEx to quantify antigen-encoding transcript abundance in tumor tissue; the Patient-Specific Presentation Metric (PHBR), a metric that estimates the likelihood of a mutation being presented by a patient's specific MHC Class I alleles; ICERFIRE (via Peptide Variant Comparison, PVC), a robust immunogenicity model that predicts the T-cell recognition potential of neoepitopes; PEPMatch, a tool to filter out candidate neoepitopes that are highly similar to self-peptides, which can indicate potential tolerance or autoimmunity risks; and Cluster, which groups highly similar peptide sequences to reduce redundancy and focus on the most representative candidates for experimental validation. The CEDAR computational tools and integrated pipeline architecture on the NGT platform provide cancer immunologists with a flexible, user-friendly, and state-of-the-art resource. This comprehensive framework accelerates the translation of genomic and transcriptomic sequencing data into clinically actionable epitope candidates. Here, we present how these integrated tools can be applied to patient-level analyses, enabling personalized identification and prioritization of tumor epitopes to guide cancer vaccine design and immunotherapy development.