Oral squamous cell carcinoma (OSCC) is the most common head and neck malignancy, with an estimated 5-year survival rate of only 40-50%, largely due to late detection and diagnosis. Emerging evidence suggests that the human microbiome may be implicated in OSCC, with oral microbiome studies putatively identifying relevant bacterial species. As the impact of other microbial organisms, such as fungi and viruses, has largely been neglected, a bioinformatic approach utilizing the Trans-Proteomic Pipeline (TPP) and the R statistical programming language was implemented here to investigate not only bacteria, but also viruses and fungi in the context of a publicly available, OSCC, mass spectrometry (MS) dataset. Overall viral, bacterial, and fungal composition was inferred in control and OSCC patient tissue from protein data, with a range of proteins observed to be differentially enriched between healthy and OSCC conditions, of which the fungal protein profile presented as the best potential discriminator of OSCC within the analysed dataset. While the current project sheds new light on the fungal and viral spheres of the oral microbiome in cancer in silico, further research will be required to validate these findings in an experimental setting.
Keywords: metaproteomics; microbiome; mycobiome; oral cancer.