The development of a high-plex spatial proteomic methodology for the characterisation of the head and neck tumour microenvironment

Mucosal head and neck squamous cell carcinoma (HNSCC) is a debilitating disease that accounts for an estimated 890,000 new cases per year, making it the seventh most common cancer globally. HNSCC is a heterogenous group of cancers that affect various regions of the head and neck which stem from the epithelial cells in the mucosal lining. Despite advancements in chemotherapy, radiotherapy, surgery and immunotherapy, the prognosis of HNSCC has remained relatively unchanged for more than a decade. There is a need to better understand the tumour microenvironment (TME) using spatially resolved approaches, to gain insights into the TME associated with clinical endpoints such as Disease-Free Survival (DFS) and Overall Survival (OS). Here, we profiled 84 mucosal HNSCC tissue samples using next-generation ultra-high plex spatial protein profiling (580-proteins, Immuno-Oncology Proteome Atlas) and spatial transcriptome mapping (18,000 mRNA, Whole Transcriptome Atlas) from Nanostring Technologies (Bruker). Patient specimens were collected during tumour resection, where patients then went on to receive either chemotherapy and/or radiotherapy. Each patient tissue sample was subdivided into tumour and stromal regions prior to digital spatial profiling. We found that patient survival outcomes (both DFS and OS) were associated with anatomical locations and tumour stage. Notably, there were specific proteomic and transcriptomic features in both the tumour and stromal regions that associated with DFS and OS. Independent validation of key proteomic findings (including CD34 and CD44) was performed using single-cell protein profiling (PhenoCycler-Fusion, Akoya Biosciences). Finally, cell type deconvolution based on transcriptomic signatures revealed cell types associated with patient survival. Taken together, this study provides a systematic workflow for discovery and validation of high-plex protein and transcriptomic profiling in mucosal HNSCC.