TSNAdb

TSNAdb catalogs tumor-specific neoantigens and provides curated predicted and experimentally validated neoantigen data to support neoantigen-based cancer immunotherapy research.

Key Features:

• Stringent neoantigen identification criteria: Applies rigorous filtering criteria to increase the reliability and specificity of neoantigen entries.
• Diverse mutation types (SNVs, indels, SVs): Includes predicted neoantigens derived from single nucleotide variants (SNVs), insertions/deletions (indels), and structural variations (SVs).
• Experimental validation levels: Categorizes experimentally validated neoantigens according to the level of experimental evidence.
• Predicted and experimentally validated entries: Integrates both computationally predicted neoantigens and experimentally validated neoantigens within the database.

Scientific Applications:

• Personalized vaccine development: Identifies patient-specific neoantigens for designing personalized cancer vaccines.
• Immunotherapy target identification: Supports discovery and prioritization of novel neoantigen targets for immunotherapies.
• Clinical study support: Provides curated neoantigen data to inform design and selection of neoantigen-based clinical trials.

Methodology:

Curates predicted and experimentally validated neoantigens using bioinformatics-based stringent identification criteria and categorizes entries by mutation type (SNVs, indels, SVs) and level of experimental evidence.