Cells were lysed in 100?L buffer provided by the kit and centrifuged at 12,000??for 15?min to collect the cell supernatant. of receptor tyrosine kinases (RTK), the most well-defined cancer genotypes, may precisely direct metabolic intervention to a broad patient population. By integrating metabolomics and transcriptomics, we herein show that oncogenic RTK activation causes distinct metabolic preference. Specifically, EGFR activation branches glycolysis to the serine synthesis for nucleotide biosynthesis and redox homeostasis, whereas FGFR activation recycles lactate to fuel oxidative phosphorylation for energy generation. Genetic alterations of and stratify the responsive tumors to pharmacological inhibitors that target serine synthesis and lactate fluxes, respectively. Together, this study provides the molecular link between cancer genotypes and metabolic dependency, providing basis for patient stratification in metabolism-targeted therapies. mutation (L858R, exon 19 deletion, or exon 21 deletion), amplification, mutation etc., were exposed to small molecule inhibitors targeting enzymes in glucose and glutamine metabolism or fatty acid oxidation (Supplementary Fig.?1a)17. Hierarchical cluster analysis of the growth inhibition rate showed that cancer cells in the same genotype tended to present comparable metabolic vulnerabilities, especially for FGFR- and EGFR-aberrant cells that showed a trend of clustering (Supplementary Fig.?1a, Dataset 1). To confirm the clinical relevance of this obtaining, we extracted 740 lung adenocarcinoma from TCGA database, among which 54 patients were Bifemelane HCl confirmed with activating mutation (amplification (amplification (fusion ((EGFR-L858R-T790M), (TEL-FGFR1 fusion), (TPR-MET fusion) or (CCDC6-RET fusion) into BAF3 cells resulted Bifemelane HCl in the constitutively activated RTK signaling (Fig.?1a, Supplementary Fig.?1c), the IL3-independent cell growth (Fig.?1b), and the exquisite sensitivity to specific RTK inhibitors (Fig.?1c). We then characterized the metabolic profiles of these cell lines. It was noted that RTK activation resulted in the enhancement of both aerobic glycolysis and oxidative phosphorylation, as indicated by the extracellular acidification rate (ECAR) and oxygen consumption rate (OCR), but with striking difference between RTK genotypes (Fig.?1d). Given that Rabbit Polyclonal to CEBPD/E gene has four isoforms, we also introduced fusion into BAF3 cells, which resulted in IL3-impartial cell growth (Supplementary Fig.?1d) and the sensitivity to AZD4547 (Supplementary Fig.?1e). The comparison of the FGFR1- and FGFR3-driven BAF3 cells in parallel observed the equally enhanced ECAR and OCR (Supplementary Fig.?1f). We also tested the impact of IL3 around the metabolic phenotypes in these cells, as IL3 is very important for BAF3 cell model. As expected, deprivation of IL3 resulted in the striking change?in OCR in BAF3 parental cells, since the survival of these cells is highly dependent on IL3. BAF3-RTK cells were generally much less affected (Supplementary Fig.?1g). The metabolic effect appeared to correlate with the impact of IL3 on cell growth (Fig.?1b). Open in a separate window Fig. 1 Oncogenic Bifemelane HCl RTK differentially reprogram metabolic phenotypes. a Immunoblotting analysis. Cells were treated with indicated RTK inhibitors (100?nM) for 1?h. b Bifemelane HCl IL3 dependence analysis. Cell growth fold changes with or without IL3 were plotted by counting cell numbers. Data were means of triplicates; Bifemelane HCl error bars represented SD. c Cell sensitivity to RTK inhibition. Cells were treated with indicated RTK inhibitors for 72?h and cell viability was analyzed using CCK8 assay. Data were means of duplicates; error bars represented SD. d Oxygen consumption rate (OCR) and extracellular acidification rate (ECAR) measurement using Seahorse XF96 analyzer. Data were means of triplicates; error bars represented SD. e Heatmap depicting the metabolite intensities in the metabolomics data. Rows indicate different metabolites, and columns indicate different cells (value using Fisher’s exact? test (amplified cells did not show clear metabolic signature (Fig.?1h, Supplementary Dataset?4). We then asked whether the metabolic changes in RTK-driven cells could suggest their distinct metabolic dependency. Indeed, we discovered that the proliferation of BAF3-EGFR and BAF3-FGFR1 cells was heavily dependent on glucose supply, whereas the growth of BAF3-RET cells appeared relying on the glutamine supply (Fig.?1i). These findings were further confirmed in.