Scholarlink

Tumor-specific and tumor-associated antigens presented on the tumor cell surface by MHC molecules are enticing targets for personalized vaccination and T cell receptor-engineered T cell (TCR-T) therapy. Accurately predicting suitable tumor antigens is a considerable challenge and requires flexibility in both computational tools and experimental methods. Here we describe our framework for reproducible bioinformatics, RAFT, as well as our highly modular neoantigen prediction workflow, LENS. We provide step-by-step instructions for installation, running, and modifying LENS to suit different purposes.

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Predicting Tumor Antigens Using the LENS Workflow Through RAFT

  • 实验方案

  • 发表日期：

    2025年

查看全文
  • Steven P. Vensko II,
  • Dante Bortone,
  • Benjamin G. Vincent

摘要

Tumor-specific and tumor-associated antigens presented on the tumor cell surface by MHC molecules are enticing targets for personalized vaccination and T cell receptor-engineered T cell (TCR-T) therapy. Accurately predicting suitable tumor antigens is a considerable challenge and requires flexibility in both computational tools and experimental methods. Here we describe our framework for reproducible bioinformatics, RAFT, as well as our highly modular neoantigen prediction workflow, LENS. We provide step-by-step instructions for installation, running, and modifying LENS to suit different purposes.