Abstract 2124: Concurrent in vitro and in silico approach for the identification of surface proteome targets on HPV-associated cancer cells

Human papillomavirus (HPV)-associated Head and neck cancer (HNSCC) are among the fastest growing cancer types. In contrast to non-viral HNSCC caused by traditional risk factors, tobacco and alcohol, HPV-HNSCC displayed distinct molecular alterations and prognosis from HPV-negative HNSCC. Currently, there is no clinically-approved therapeutic vaccine, and no targeted therapy approach for HPV-driven cancer which exploits the unique biology of HPV infection. In order to identify novel targets suitable for therapeutic and diagnostic development, we developed two parallel approaches to identification of proteins/antigens expressed on the surface of the host cells, whose expression is altered by HPV infection. One is an “antigen-agnostic” approach by using immortalized HNSCC cell membrane fractions to generate monoclonal antibodies, which does not require advance knowledge of the identities of target antigens. The second approach is bioinformatics analyses of the TCGA database using the epigenomic deconvolution tool (EDec) to identify surface proteins that are differentially overexpressed in HPV- HNSCC. Five thousand hybridoma colonies were generated by the “antigen-agnostic” approach, and were then screened by flow cytometry to test the specificity of binding to HPV-positive cancer cell lines (2 HNSCC and 2 Cervical Cancer) and HPV-negative cancer cell lines (4 HNSCC and 1 CC). After primary screening, we narrowed down to forty-four clones with preliminarily favorable binding characteristics; among these hybridoma clones, we have identified seven which preferentially bind to HPV-positive cancer cells. We then identified the binding targets of three clones via immunoprecipitation and mass spectrometry. These targets are integrin alpha6 beta4 (ITGA6, ITGB4), tissue factor (F3) and keratin 8 (KRT8) respectively. The bioinformatics-based approach identified several surface proteins that are differentially overexpressed in HPV-positive HNSCC and at levels significantly higher than found in normal control tissue. Evaluation of gene and protein expression in cancer cell lines and/or patient tissue validated several genes identified by the deconvolution approach, including: ROR2, a non-canonical WNT member not previously associated with head and neck cancer; and LY6K, a cancer-testis antigen that overexpressed in both HPV-positive and negative HNSCC. We propose targeting membrane-expressed antigens on HPV-related cancer cells as a platform for further development of novel tumor imaging and therapeutic approaches for HNSCC and other HPV-associated cancers. Citation Format: Hsuan-Chen Liu, Ivenise Carrero, Falguni Parikh, Thomas Kraus, Thomas M. Moran, Mathew J. Ellis, Elizabeth Y. Chiao, Aleksandar Milosavljevic, Andrew G. Sikora. Concurrent in vitro and in silico approach for the identification of surface proteome targets on HPV-associated cancer cells [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 2124.