Prostate cancer remains a major health concern, with prostate-specific antigen (PSA) being a key biomarker for its detection and monitoring. However, PSA levels often fall into a "gray zone", where PSA levels are not clearly indicative of cancer, thus complicating early diagnosis and treatment decisions. Glycosylation profiles, which often differ between healthy and diseased cells, have emerged as potential biomarkers to enhance the specificity and sensitivity of cancer diagnosis in these ambiguous cases. We propose the integration of two complementary techniques, namely quartz-crystal microbalance with dissipation (QCM-D) and surface-enhanced Raman scattering (SERS) to study PSA glycan profiles. QCM-D offers real-time operation, PSA mass quantification, and label-free detection with high sensitivity, as well as enhanced specificity and reduced cross-reactivity when using nucleic acid aptamers as capture ligands. Complementary SERS sensing enables the determination of the glycosylation pattern on PSA, at low concentrations and without the drawbacks of photobleaching, thereby facilitating multiplexed glycosylation pattern analysis. This integrated setup could retrieve a data set comprising analyte concentrations and associated glycan profiles in relevant biological samples, which may eventually improve early disease detection and monitoring. Prostate-specific antigen (PSA), a glycoprotein secreted by prostate epithelial cells, serves as our proof-of-concept analyte. Our platform allows multiplex targeting of PSA multiplex glycosylation profiles of PSA at "gray zone" concentrations for prostate cancer diagnosis. We additionally show the use of SERS for glycan analysis in PSA secreted from prostate cancer cell lines after androgen-based treatment. Differences in PSA glycan profiles from resistant cell lines after androgen-based treatment may eventually improve cancer treatment.