GeNeo: A Bioinformatics Toolbox for Genomics-Guided Neoepitope Prediction

Area of Science:

• Genomics
• Bioinformatics
• Oncology

Background:

• High-throughput DNA and RNA sequencing are advancing precision oncology.
• Personalized therapies, like cancer vaccines, target tumor-specific neoepitopes from somatic mutations.
• Identifying neoepitopes from next-generation sequencing data is complex and requires sophisticated bioinformatics pipelines.

Purpose of the Study:

• To present GeNeo, a bioinformatics toolbox designed for genomics-guided neoepitope prediction.
• To provide a comprehensive suite of tools for somatic variant calling, filtering, validation, and neoepitope prediction.
• To enhance the accessibility of neoepitope prediction tools through web-based interfaces and local deployment options.

Main Methods:

• GeNeo offers integrated tools for somatic variant calling and filtering.
• Includes variant validation capabilities.
• Provides neoepitope prediction and filtering functionalities.

Main Results:

• GeNeo streamlines the process of neoepitope identification from clinical sequencing data.
• The toolbox facilitates the use of complex bioinformatics pipelines for neoepitope prediction.
• Web-based interfaces on a Galaxy portal and a downloadable virtual machine image enhance usability.

Conclusions:

• GeNeo provides a valuable resource for researchers in precision oncology.
• The toolbox simplifies the identification of neoepitopes, crucial for developing personalized cancer vaccines.
• GeNeo aims to accelerate the application of genomics in cancer therapy development.