Optimizing Cold Atmospheric Plasma Dosage to Enhance DESI-MS Signal Intensity in MDA-MB-231 Breast Cancer Cells: Mechanistic Insights and Workflow Development.

Triple-negative breast cancer (TNBC) harbors low-abundance lipid species that serve as critical molecular signatures, yet these remain difficult to detect with conventional mass spectrometry. To address this challenge, we developed a cold atmospheric plasma (CAP)-assisted desorption electrospray ionization mass spectrometry (DESI-MS) workflow to enhance the lipid ionization and detection sensitivity. MDA-MB-231 cell extracts were treated with three CAP doses, and lipid signals were systematically assessed in positive- and negative-ion modes with triplicate measurements to ensure reproducibility. Principal component analysis revealed clear separation between control and CAP-treated groups, with the intermediate dose (10 μM H2O2, Dose 2) showing the strongest statistical distinction. Under this condition, detection limits for key phospholipids improved ∼5-6-fold relative to control and ∼3-fold relative to Dose 1. For example, m/z 799.57 [PG (16:0/22:4)] and m/z 803.25 [PA (22:6/22:1)] exhibited the greatest gains, while Dose 2 also retained ∼1.4-1.5-fold advantages over Dose 3. This setting preserved structural integrity and peak stability, with aging assays showing sustained signals for 7 days, whereas higher doses caused rapid decay from overoxidation. Notably, very low-abundance lipids such as m/z 721.50 [PI (12:0/12:0)] became detectable, underscoring sensitivity gains at the intermediate dose. Mechanistically, argon-based CAP generates reactive oxygen species that induce mild hydroxylation, enhancing droplet-surface interactions and ionization efficiency while avoiding destructive degradation. Complementary MTT and flow cytometry assays confirmed that the intermediate dose maintained ∼25% metabolic activity and membrane integrity. Together, this study provides the first systematic evaluation of CAP dose effects in DESI-MS lipidomics and establishes a framework for improving the detection of low-abundance phospholipids in aggressive cancer models.