Identification of OSCC signatures via multiplexed quantitative proteomics and post-translational modification profiling in high-purity plasma and saliva extracellular vesicles

Abstract

Extracellular vesicles (EVs) are key players in cancer progression and metastasis by inducing changes in the tumour-microenvironment, extracellular matrix and pre-metastatic niches towards favourable sites for tumour growth and spread. Lymph node metastasis is the main prognostic factor in patients with oral squamous cell carcinoma (OSCC) and can decrease the 5-year survival rates to less than 50%, but no molecular markers are currently available. In this context, the current FAPESP post-doctorate project (2018/11958-4) proposed the application of proteomics and peptidomics to characterized EV cargo and identify potential markers of OSCC progression and lymph node metastasis. During the first year of the main project we developed a complete pipeline for peptidomic and proteomic analyses of patients' saliva (manuscript in preparation). We successfully pinpointed potential prognostic signatures via peptidomics, and this data combined with bottom-up (peptide-based) proteomics provided a multi-layered understanding of OSCC progression. However, compared to whole saliva, proteomics and peptidomics analyses of EVs is more challenging due to its intrinsic low protein yield, even with optimized conditions for maximal EV recovery. Therefore, a successful molecular characterization demands refined experimental design and sensitive instrumentation to achieve adequate EV proteome/peptidome coverage and reliable quantification. We propose this internship (BEPE) project to deploy TMT-based quantification for multiplexed sensitive LC-MS analysis of patient's saliva and plasma EVs (healthy, n=20, OSCC with, n=20, and without lymph node metastasis, n=20). This will enable the acquisition of high-quality quantitative data for assessment of group differences and profiling of protein post-translational modifications (PTMs) from EV cargo. By increasing the sensitivity of analyses, supplementing quantitative peptidomics data with information about PTMs, we will be in a unique position to uncover potential signatures for verification in phase 2 of the main project to be carried out in Brazil on a separate cohort of patients. (AU)