Multiparametric ECIS Profiling Complements Metabolic Endpoint Screening of Complex Plant Extracts in HNSCC Models

Metabolic endpoint assays enable rapid screening but provide limited information on treatment kinetics, heterogeneity, and recovery. Here, we established a multistep workflow combining MTS-based metabolic screening with electric cell–substrate impedance sensing (ECIS), a label-free cell-based biosensor, to functionally prioritize complex plant extracts in head and neck squamous cell carcinoma (HNSCC) models. Seventeen soluble extracts were screened at 50 µg/mL for 24 h in four HNSCC cell lines and human adipose-derived stem cells. Selected candidates were subsequently characterized by real-time impedance monitoring, multifrequency analysis, and model-derived barrier resistance. Extract 16 showed the most favorable metabolic selectivity profile. ECIS resolved no growth-inhibitory effects, sustained impedance suppression, heterogeneous responses, and transient suppression followed by partial recovery. Cross-model analysis identified distinct barrier-resistance dynamics, particularly in CAL-33 and Detroit 562. Comparison with the PI3Kα inhibitor Inavolisib revealed partially overlapping but non-identical metabolic response profiles and no consistent enhancement by combination treatment. Extract 16 was further associated with junctional redistribution, F-actin remodeling, and PARP processing, whereas reproducible caspase 3/7 activation was not detected. Thus, integrating metabolic endpoint screening with multiparametric ECIS monitoring provides greater functional resolution and supports the prioritization of complex bioactive samples for subsequent chemical and mechanistic investigation.