Our study discovered critical physicochemical properties to distinguish between 43 cell-line selective membranolytic anticancer peptides and their 95 nonselective counterparts. Hydrophobicity, net charge and the presence of small and aliphatic residues influenced the potency and selectivity of these mACPs across cancer cell lines in a cell-specific manner. In some cases, more hydrophobic and bulkier residues or an increase in positively charged residues led to more potent peptides against a cluster of cancer cell lines. In others, the presence of successive small residues helped mACPs to gain in cell-line selectivity. Interestingly, some cancer cell lines responded similarly against a defined set of mACPs -homologues or sharing physicochemical properties -suggesting these clusters might present comparable lipid compositions on their cell surfaces. Lipidomic studies are needed to support or reject this hypothesis. Despite these observations, the limited number of mACPs provided insufficient ground to generalise for designing mACPs or developing cell line-specific machine learning models. Medium-large libraries of mACP homologues (with varying amino acid composition and physicochemical properties) should be evaluated across the widest range of cancer cell lines pairing with lipidomic studies.