Analysis of Bacterial Microbiome and Human Proteome for Lung Cancer Characterization via Affinity Nanoparticles and De Novo Assisted Database Search Mass Spectrometry

Abstract

Lung cancer (LC) is the deadliest cancer in the world, affecting 230,000 people in the US every year. While much about LC remains unanswered, several studies suggest that that the microbiome within an organ can influence disease onset and progression. Here, we attempt to compare the microbiome as well as the human proteome of healthy and cancerous lung tissue to identify bacterial and human proteins associated with LC. Both healthy and tumor tissue were extracted from LC patient lungs (n=14 patients, n=42 samples), processed with affinity nanoparticles and analyzed with LC-MS/MS. Proteins from human and microbial species were identified via PEAKS (Bsi) De Novo Assisted Database Search. Statistical analysis was conducted in Perseus (MaxQuant) to investigate differences in protein expression between tumor and healthy tissues. Of the bacterial proteins identified by PEAKS, 15 were found to be differentially expressed (Alpha p < 0.05) between tumor and healthy tissue. Staphylococcus aureus chaperone proteins were overexpressed in tumor tissue, suggesting an increase in proinflammatory cellular processes which could have influenced LC. Of the human proteins identified by PEAKS, 118 were found to be statistically significant (Alpha p < 0.05), many mitochondria-derived. While further analyses need to be performed to validate the bacterial and human protein candidates identified, the approach illustrated in this study proves to be a powerful tool for the identification of LC diagnostic and/or prognostic biomarkers.