We collected 138 membranolytic anticancer peptides (mACPs) from DBAASP (Database of Antimicrobial Activity and Structure of Peptide, ) using the Ranking Search option and specific filters. Each peptide exhibited inhibition against more than two specific cell lines, as expressed by their IC50 values. Alongside the sequences, we identified 11 normal healthy cell lines (HCLs, Figure ) and 77 distinct cancer cell lines (CCLs). Among the 138 peptides, only 0.7% were evaluated against seven or more CCLs; 12.3% against five CCLs; 18.8% against four CCLs; and 65.9% against three CCLs (Figure ). The synthetic peptide named Buforin-2(5-13) [17-20]3 (DBAASP ID 887) was the most evaluated peptide against 23 cancer cell lines. We analysed the ratios across all evaluated cancer cell lines per peptide from biological experiments. Figure lists the 77 cancer cell lines across 15 cancer types. Each bar represents the number of tested peptides against one cell line. The three most tested CCLs are related to blood disorders; K562, CCRF-CEM, and Jurkat E6-1 against 48, 30, and 29 peptides. Blood cancers are the most represented type of cancer in this analysis, with 11 cell lines. Besides blood cancer, mACPs have equally inhibited cell lines from other organs; brain (U251-MG), breast (MDA-MB-361), cervix (HeLa S3), colon (SW480 CCL-228), lung (NCI-H157, A549), and prostate (PC-3) -see Supporting information Lists S1-S2 for their full names. In contrast, kidney, oral, ovary, pancreatic, skin and stomach cancers were the least investigated cell lines. Subsequently, we determined the selectivity index (SI) for each sequence, which is traditionally defined as the ratio between cytotoxic activities (expressed with the IC50 values) of a single compound (e.g., peptide) against one HCL and one CCL (Eq.1). In our dataset, roughly a third of the sequences (47) were reported against one of the HCLs (List S1). In the absence of SI values and to support the design of cancer cell-specific mACPs, we studied how the peptide physicochemical descriptors and other features contribute to discriminating between cancer cell membranes. We developed our in-house cancer cell-line selectivity index, CCSI. We hypothesised that the differences in cytotoxicity of a peptide against more than two CCLs could be linked to their differences in lipid composition. Following the same reasoning, an untested mACP might display different cytotoxic values against one or more HCLs. Like SI, CCSI resulted from the difference in cytotoxic activity between two cell lines, using the highest and the lowest pIC50 values from two CCLs for a single peptide (Eq. 1-2). A higher pIC50 value denotes a more potent mACP. A cell-line selective mACP (ACP-S) has a CCSI equal to or superior to 0.5; otherwise, the peptide is labelled as non-selective (ACP-NS). Our dataset included 43 ACP-S and 95 ACP-NS. We illustrated their cytotoxic activity (expressed with pIC50 values) towards three or more of the 77 cancer cell lines for both ACP-S (Figure ) and ACP-NS (Figure ). In both figures, the rows represent all tested peptides, whereas the columns indicate all 77 cancer cell lines. The pIC50 values are depicted with a gradient from yellow (low) to red (high). In Out of curiosity, we compared our CCSI values with identified SI values. We first reported the SI values for the 47 peptides showing cytotoxic activity against at least 3 of the 27 CCLs and for each of the 11 HCLs, as illustrated in Figures . The figures depicted the selectivity on a negative logarithmic scale -log10(SI) for visualization purposes, where higher values indicated greater selectivity. In general, many peptides exhibited lower selectivity against some of the 27 CCLs when compared to the following four healthy cell lines; PNT1A (prostate cells), GES-1 (human gastric epithelial cells), HMEC-1 (human microvascular endothelial cells) and HUVEC (human umbilical vein endothelial cells). For example, the non-selective mACP Arminin-1a(40-70)-NH2 (ID: 12161) was tested against five CCLs (THP-1, K562/ADM, K562, Jurkat, and HL-60) and three human HCLs; PBMC (peripheral blood mononuclear cells), HEK293 (human embryonic kidney cells), and HUVEC (human umbilical vein endothelial cell). Irrespective of the CCLs, we noted that SI values were moderated (e.g., -log10(SI) ~ 0, SIHL-60: 4.41, purple) against HEK293 or HUVEC, and they were elevated (e.g., -log10(SI) > 0.5 or SI > 2, SIHL-60: 23.99, dark purple-black) against PBMC. However, the SI values corresponding to the five CCLs appeared in the same colour tones for a given HCL, suggesting similar cell-line selectivity indices and the peptide's non-selective nature. The peptide can selectively inhibit the growth of these cancer cell lines compared to these healthy ones, but it cannot differentiate across cancer cell lines. Similar observations could be made for most peptides listed in Figures except for a handful of selective mACPs (e.g., IDs: 1195, 3414, 3418, 3427, 3429, 11805, and 11807). CCSI indicated cell-line selectivity across CCLs, whereas SI denoted the selectivity between one CCL and one HCL. We performed linear regression analyses between our CCSI and SI values. The results in Figure summarised eight dispersion graphs with sufficient data for analysis between each cancer cell line against two healthy endothelial cell lines (HMEC-1, HUVEC). The linear relationships are quasiinexistent with R 2 ~ 0 for four CCLs; MCF-7, MDA-MB-435S, U251-MG against HMEC-1, and the human colon cancer cell line SW480 CCL-228 against HUVEC. In contrast, the other four cancer cell lines presented apparent (weak-moderate) positive correlations between the respective CCSI and SI values. For example, we observed an R 2 ~0.33 for the T lymphoblastoid cell line CCRF-CEM, R 2 ~0.45 for cervical adenocarcinoma HeLa S3, and R 2 ~0.67-0.68 for NCI-H157 and PC-3. What could explain the different responses between all cancer cell lines is unclear. To know if the cut used in our CCSI-based classification was adequate, we used the equations derived from the regression analyses of the last four cell lines (NCI-H157, PC-3, CCRF-CEM, HeLa S3). We substituted each x with a CCSI value of 0.5 (used to define a selective ACP), and we reported the corresponding SI values (y) greater than 2, in agreement with the definition of selectivity index . Noteworthy, the coefficients of determination (R 2 ) were relatively low, indicating high variability in the data and limited precision for the predicted SI values, whereas the low p-values supported the positive relationships between CCSI and SI values.