Target Selection for T-Cell Therapy in Epithelial Ovarian Cancer: Systematic Prioritization of Self-Antigens

Paul Schossig1, Ebru Coskun1,2, Ruza Arsenic3

  • 1Department of Hematology, Oncology and Cancer Immunology, Campus Benjamin Franklin, Charité-Universitätsmedizin Berlin, 10117 Berlin, Germany.

Insights

Identifying novel tumor-associated antigens (TAAs) is crucial for epithelial ovarian cancer (EOC) immunotherapy. This study highlights KIF20A, CT45, and LY6K as promising TAAs for adoptive T cell-receptor therapy (ACT) in EOC.

Area of Science:

  • Oncology
  • Immunology
  • Cancer Research

Background:

  • Adoptive T cell-receptor therapy (ACT) shows promise for epithelial ovarian cancer (EOC).
  • Identifying suitable tumor-associated antigens (TAAs) for ACT in EOC is a significant challenge.
  • Effective TAAs are needed to enhance targeted immunotherapeutic strategies for EOC.

Purpose of the Study:

  • To identify and prioritize TAAs for ACT and other immunotherapies in epithelial ovarian cancer (EOC).
  • To evaluate the expression and prognostic relevance of potential TAAs in EOC patient samples.
  • To validate promising TAAs using immunohistochemistry and HLA-ligandome analysis.

Main Methods:

  • Systematic review and prioritization of pre-described TAAs using weighted criteria.
  • Immunohistochemical staining of TAAs in a tissue microarray of 58 EOC samples.
  • Analysis of TAA expression association with clinical parameters and prognostic relevance, supported by HLA-ligandome data.

Main Results:

  • 38 TAAs were preselected based on expression data and further prioritized.
  • KIF20A, CT45, and LY6K emerged as highly promising TAAs, alongside Cyclin A1.
  • These TAAs demonstrated significant expression in EOC and prognostic relevance, independent of molecular subtypes.

Conclusions:

  • KIF20A, CT45, and LY6K are identified as promising candidates for EOC immunotherapy, particularly for ACT.
  • The study validates these TAAs using immunohistochemistry and HLA-ligandome data.
  • The systematic vetting algorithm can aid TAA prioritization in other cancer types.

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