Data-independent acquisition (DIA) based quantitative proteomic analysis of oral cancer tissue samples

Oral cancer ranks as the 7th most common cancer worldwide with an increasing incidence and mortality rate. Currently, immunotherapy has emerged as a promising approach for cancer treatment including in head and neck cancer, characterised by prolonged survival rate. We conducted a data-independent acquisition (DIA) based quantitative proteomics analysis to identify the differentially expressed proteins in oral cancer patients. The LC-MS/MS analysis resulted in the identification of 29459 precursors corresponding to 3429 proteins. Among these 1197 proteins showed significant differential expression between control and oral cancer tissue samples. Additionally, our downstream bioinformatics analysis identified 185 proteins with a potential role in immune regulation.