Dynamic range compression (DRC) by hexapeptide libraries increases MS/MS-based identification of lower-abundance proteins in complex mixtures. However, two unanswered questions impede fully realizing DRC's potential in shotgun proteomics. First, does DRC enhance identification of post-translationally modified proteins? Second, can DRC be incorporated into a workflow enabling relative protein abundance profiling? We sought to answer both questions analyzing human whole saliva. Addressing question one, we coupled DRC with covalent glycopeptide enrichment and MS/MS. With DRC we identified ∼2 times more N-linked glycoproteins and their glycosylation sites than without DRC, dramatically increasing the known salivary glycoprotein catalog. Addressing question two, we compared differentially stable isotope-labeled saliva samples pooled from healthy and metastatic breast cancer women using a multidimensional peptide fractionation-based workflow, analyzing in parallel one sample portion with DRC and one portion without. Our workflow categorizes proteins with higher absolute abundance, whose relative abundance ratios are altered by DRC, from proteins of lower absolute abundance detected only after DRC. Within each of these salivary protein categories, we identified novel abundance changes putatively associated with breast cancer, demonstrating feasibility and benefits of DRC for relative abundance profiling. Collectively, our results bring us closer to realizing the full potential of DRC for proteomic studies.