3D growth of cancer cells elicits sensitivity to kinase inhibitors but not lipid metabolism modifiers

Journal article

Tumor cells exhibit altered lipid metabolism compared with normal cells. Cell signaling kinases are important for regulating lipid synthesis and energy storage. How upstream kinases regulate lipid content, versus direct targeting of lipid-metabolizing enzymes, is currently unexplored. We evaluated intracellular lipid concentrations in prostate and breast tumor spheroids, treated with drugs directly inhibiting metabolic enzymes fatty acid synthase (FASN), acetyl-CoA carboxylase (ACC), diacylglyceride acyltransferase (DGAT), and pyruvate dehydrogenase kinase (PDHK), or cell signaling kinase enzymes PI3K, AKT, and mTOR with lipidomic analysis. We assessed whether baseline lipid profiles corresponded to inhibitors' effectiveness in modulating lipid profiles in three-dimensional (3D) growth and their relationship to therapeutic activity. Inhibitors against PI3K, AKT, and mTOR significantly inhibited MDA-MB-468 and PC3 cell growth in two-dimensional (2D) and 3D spheroid growth, while moderately altering lipid content. Conversely, metabolism inhibitors against FASN and DGAT altered lipid content most effectively, while only moderately inhibiting growth compared with kinase inhibitors. The FASN and ACC inhibitors' effectiveness in MDA-MB-468, versus PC3, suggested the former depended more on synthesis, whereas the latter may salvage lipids. Although baseline lipid profiles did not predict growth effects, lipid changes on therapy matched the growth effects of FASN and DGAT inhibitors. Several phospholipids, including phosphatidylcholine, were also upregulated following treatment, possibly via the Kennedy pathway. As this promotes tumor growth, combination studies should include drugs targeting it. Two-dimensional drug screening may miss important metabolism inhibitors or underestimate their potency. Clinical studies should consider serial measurements of tumor lipids to prove target modulation. Pretherapy tumor classification by de novo lipid synthesis versus uptake may help demonstrate efficacy.

Authors: Jones, DT; Valli, A; Haider, S; Zhang, Q; Smethurst, EA

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: American Association for Cancer Research
• Journal: Molecular Cancer Therapeutics
• Volume: 18
• Issue: 2
• Pages: 376-388
• Publication date: 2018-11-26
• Acceptance date: 2018-11-09
• DOI: 10.1158/1535-7163.mct-17-0857
• EISSN: 1538-8514
• ISSN: 1535-7163
• Pmid: 30478149
• Language: English
• Keywords: FFR