Abstract 5503: Ultrahigh-plex spatial phenotyping of head and neck cancer tissue uncovers multiomic signatures of immunotherapy response

Abstract Background Targeted immune checkpoint inhibitors (ICI) with anti-PD-1/PD-L1 therapy offer durable treatment of mucosal head and neck squamous cell cancer (HNSCC), in both human papillomavirus-positive (HPV+) and negative (HPV-) patients. However, currently available biomarker signatures for targeted ICI therapies have limited predictive value. Our recent ultrahigh-plex profiling of HNSCC tissue with 100+ cancer hallmarks of tumor and immunobiology uncovered distinct spatial domains that serve as defining factors for clinical response and resistance. Methods Our unbiased analysis of whole-slide metastatic HNSCC tumors is from a clinical cohort of patients treated with Pembrolizumab/Nivolumab. The cohort consisted of patients with a range of outcomes from complete vs partial vs progressive disease responses to ICI therapy. We first characterized the tumor microenvironment using our ultrahigh-plex protein panel with 100+ antibodies on the PhenoCycler®-Fusion platform. To expand upon our biomarker discovery, we included multiomic cancer hallmarks with a multimodal protein/RNA detection panel. Targeted spatial RNA detection was performed to complement and augment the microenvironment characterization achieved by our protein panel. To further consolidate the multiomic data, we leveraged MaxFuse, a state-of-the art computational framework that integrates multimodal spatial and single-cell expression data. Results Our multiomic spatial phenotyping uncovered diverse tumor regions, each with distinct biomarker expression that is reflected across modalities including protein, RNA, and metabolic activity, indicating regions likely associated with resistance to immunotherapy. Our multiomic data integration also revealed spatial signatures associated with different tissue compartments, such as the tumor and non-tumor associated tertiary lymphoid structures. Conclusions We demonstrate a multi-pronged approach that incorporated both novel experimental and computational techniques for elucidating tumor microenvironment in HNSCC tissue prior to ICI-based immunotherapy. Our multiomic approach provides deeper characterization of the HNSCC at the transcriptomic and proteomic level incorporating depth across the entire transcriptome and single-cell spatial resolution of key protein determinants for predicting and furthering our understanding of immunotherapy response to ICI therapy. Citation Format: Aditya Pratapa, Lydia Hernandez, Bassem Ben Cheikh, Niyati Jhaveri, Arutha Kulasinghe. Ultrahigh-plex spatial phenotyping of head and neck cancer tissue uncovers multiomic signatures of immunotherapy response abstract. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts) ; 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84 (6Suppl): Abstract nr 5503.