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Abstract

Detailed metabolic characterization of cancer cells provides an important cellular footprint in addition to well-­‐studied genomic features and could play an important role for understanding sensitivity of cancer cells to drug treatment. Thus, detailed understanding of metabolism and gene expression profiles of cancer cells could be an important guideline supporting the steps of drug selection and a determining factor for designing treatment strategies with available anticancer drugs. The aim of the presented study was to analyze the metabolic activities and cell-­‐cell interaction and cell-­‐matrix adhesion properties of a large number of cancer cell lines and correlate these cellular characteristics with drug sensitivity and compare this relation to established knowledge using gene expression and drug sensitivity prediction. For this, correlations among these different set of analytical information were analyzed to obtain cancer cell profiles linking metabolism, gene expression and drug IC50 values, by calculating Pearson correlation coefficients. The results obtained clearly corroborate well-­‐known relations but also provide important novel findings underlying the importance of cancer cell metabolism in drug sensitivity. As expected, the proliferation rate correlates well with the glycolytic activity of cancer cells (r = 0.71**) as well as with HOXA7 expression (r = 0.95***). The metabolism-­‐related candidate genes are PGLS, COX5B, RHBDL2, IFI16, GCN1L1, INPP5B, and LGALS8. Furthermore, the calculated Pearson product-­‐moment correlation coefficients show that the sensitivity of seven known drugs correlate with some of the analyzed cellular features of cancer cells. These compounds are elesclomol, Nutlin 3a, PF 4708671, EHT 1864, IPA3, RDEA119, and methotrexate. The detailed metabolic and electrochemical profiling of cancer cells carried out for this study reveals new relationships between genes expression, drug sensitivity/tolerance, and basic metabolic features of cancer cells. New insights are provided into cancer metabolism, genomic regulation, and a potential application to designing new chemotherapeutic strategies.