Gaurav Behera

Post-translational modifications (PTMs) diversify the function of proteins in cellular physiology by altering a protein’s conformation, interactions with other proteins, or stability. Abnormalities in PTM dynamics have been associated in carcinogenesis, and abnormal PTM patterns have served as hallmarks for cancer. Phosphorylation is a well-studied PTM that has been implicated in a variety of cellular signaling pathways in cancer, especially where tyrosine kinase is involved. Other novel PTMs including acetylation, proline hydroxylation, and ubiquitination have become of interest as growing evidence reveals their roles in signaling pathways that have been associated with cancer. However, the characterization of novel PTM proteomes in cancer remains limited. Here we conducted an in silico analysis of the cancer proteome aggregated from cancer-specific quantitative proteomic studies that utilized data-independent acquisition mass spectrometry (DIA-MS), a next-generation proteomics strategy, to identify and characterize PTM sites and cellular pathways that could play a role in cancer progression. We quantified over 1000 acetylation sites, 1700 proline hydroxylation sites, and 8600 ubiquitination sites in the lung cancer, breast cancer, and kidney cancer proteomes, respectively. We also conducted comparative analysis of novel PTM sites between cancerous and healthy tissue. Our results demonstrate how DIA-MS data can be reprocessed to detect and quantify PTMs with high reproducibility. The identification of PTM sites and their differential profiling in the cancer proteome can serve as biomarkers to help determine cancer prognosis or be used to indicate upstream enzymatic activities that could be potential drivers for cancer progression. We anticipate such in silico analysis to spur on initiatives for deeper DIA-MS cancer proteome PTM analysis with more advanced PTM-specific spectral libraries.