This dataset comprises label-free quantitative proteomics of the secretome from human THP-1 serglycin (SRGN) knock-out and wild-type macrophage-like cells differentiated with PMA (M0) and polarized to M1 (LPS + IFN-γ) or M2 (IL-4 + IL-13). The study investigates how macrophage activation states in the absence of serglycin reshape the composition of secreted proteins relevant to inflammatory signaling, vesicle biology, and metabolism. Conditioned media were collected after polarization, processed by bottom-up proteomics, and analyzed by nanoLC–MS/MS on an Orbitrap Fusion Lumos. The resulting protein abundance profiles provide a resource to compare resting (M0) versus pro-inflammatory (M1) and alternatively activated (M2) macrophage secretomes in a standardized cell system.