Abstract
Epithelial-mesenchymal-transition promotes intra-tumoral heterogeneity, by enhancing tumor cell invasiveness and promoting drug resistance. We integrated transcriptomic data for two clonal subpopulations from a prostate cancer cell line (PC-3) into a genome-scale metabolic network model to explore their metabolic differences and potential vulnerabilities. In this dual cell model, PC-3/S cells express Epithelial-mesenchymal-transition markers and display high invasiveness and low metastatic potential, while PC-3/M cells present the opposite phenotype and higher proliferative rate. Model-driven analysis and experimental validations unveiled a marked metabolic reprogramming in long-chain fatty acids metabolism. While PC-3/M cells showed an enhanced entry of long-chain fatty acids into the mitochondria, PC-3/S cells used long-chain fatty acids as precursors of eicosanoid metabolism. We suggest that this metabolic reprogramming endows PC-3/M cells with augmented energy metabolism for fast proliferation and PC-3/S cells with increased eicosanoid production impacting angiogenesis, cell adhesion and invasion. PC-3/S metabolism also promotes the accumulation of docosahexaenoic acid, a long-chain fatty acid with antiproliferative effects. The potential therapeutic significance of our model was supported by a differential sensitivity of PC-3/M cells to etomoxir, an inhibitor of long-chain fatty acid transport to the mitochondria.
Highlights
Prostate cancer (PC) is the most commonly diagnosed non-cutaneous malignancy among Western men and accounts for the second leading cause of cancer-related death [1]
Model-driven discovery of long-chain fatty acids (LCFA) metabolic reprogramming in heterogeneous PC cells excellent cellular model to study how intra-tumoral heterogeneity and the different phenotypes endowed by the different subpopulations provides advantages to the tumor in terms of metastatic capability and drug resistance
To infer the activity states of the metabolic networks of PC-3/S and PC-3/M subpopulations, we used previously generated transcriptomic data for PC-3/S and PC-3/M cells based on microarray technology [9] which was integrated into a genome-scale reconstruction of the human metabolic network [11]
Summary
Prostate cancer (PC) is the most commonly diagnosed non-cutaneous malignancy among Western men and accounts for the second leading cause of cancer-related death [1]. The coexistence within the same tumor of a variety of cell subpopulations, featuring different phenotypes (intra-tumoral heterogeneity) associated with tumor evolution and progression reflects extreme plasticity and adaptation capability of neoplastic cells This diversity is reached through genetic evolution of neoplastic cells and epigenetic and metabolic reprogramming of neoplastic and non-neoplastic tumor components that enhance tumor progression and represent a challenge for targeted therapies [3,4]. EMT-mediated molecular and cellular changes have been widely studied, the EMT-induced metabolic changes remain poorly understood In this sense, it is widely accepted that metabolic reprogramming is one of the ten hallmarks of cancer [6] which endows cancer cells with a phenotype characterized by a rapid and continuous proliferation, metastasis, invasion, and treatment resistance. Study of the metabolism in these heterogeneous cellular populations is of special interest and must be approached from a global perspective integrating global metabolism with consideration of different subpopulations
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