Targeting Neoepitopes to Treat Solid Malignancies: Immunosurgery.

Area of Science:

• Oncology
• Immunology
• Genomics

Background:

• Successful cancer immunotherapy relies on T-cell recognition of tumor neoantigens, influenced by tumor mutational burden (TMB) and T-cell receptor (TCR) repertoire.
• Interferon gamma (IFN-γ) is crucial for anti-tumor immunity, enhancing cancer cell immunogenicity and T-cell responses.
• Tumor heterogeneity and the tumor microenvironment (TME) present challenges for effective T-cell targeting.

Purpose of the Study:

• To develop and validate a bioinformatics pipeline for predicting patient-specific neoantigens from tumor genomic data.
• To assess the immunological response to predicted neoantigens using functional immunoassays and T-cell adaptome analysis.
• To advance personalized precision medicine strategies for cancer treatment, including vaccination and cell-based therapies.

Main Methods:

• Whole-exome sequencing (WES) and RNA sequencing (RNA-Seq) of cancer tissues to identify mutations.
• Bioinformatic analysis pipeline to predict neoantigens and guide synthetic peptide construction.
• Immunoassays measuring IFN-γ production and T-cell responses to neoantigens, alongside histopathology and T-cell adaptome analysis.

Main Results:

• Identification of private tumor mutations and prediction of potential neoepitopes.
• Detection of differential IFN-γ production patterns correlating with T-cell responses to neoantigens.
• Integration of multi-omics data and functional assays for comprehensive neoantigen assessment.

Conclusions:

• The developed pipeline enables accurate prediction of neoantigens and assessment of T-cell reactivity.
• This approach supports the development of next-generation personalized cancer immunotherapies.
• Optimizing neoantigen-directed therapies can improve clinical outcomes in solid cancers.