The challenge of discovering a completely new human tumor virus of unknown phylogeny or sequence depends on detecting viral molecules and differentiating them from host molecules in the virus-associated neoplasm. We developed differential peptide subtraction (DPS) using differential mass spectrometry (dMS) followed by targeted analysis to facilitate this discovery. We validated this approach by analyzing Merkel cell carcinoma (MCC), an aggressive human neoplasm, in which ~80% of cases are caused by the human Merkel cell polyomavirus (MCV). Approximately 20% of MCC have a high mutational burden and are negative for MCV, but are microscopically indistinguishable from virus positive cases. Using 23 (12 MCV+, 11 MCV–) formalin-fixed MCC, DPS identified both viral and human biomarkers (MCV large T antigen, CDKN2AIP, SERPINB5, and TRIM29) that discriminate MCV+ and MCV– MCC. Statistical analysis of 498,131 dMS features not matching the human proteome by DPS revealed 562 (0.11%) to be upregulated in virus-infected samples. Remarkably, 4 (20%) of the top 20 candidate MS spectra originated from MCV T oncoprotein peptides and confirmed by reverse translation degenerate oligonucleotide sequencing. DPS is a robust proteomic approach to identify potentially novel viral sequences in infectious tumors when nucleic acid–based methods are not feasible.
Tuna Toptan, Pamela S. Cantrell, Xuemei Zeng, Yang Liu, Mai Sun, Nathan A. Yates, Yuan Chang, Patrick S. Moore
List of the top 20 significant proteomic features