Global analysis of osteosarcoma lipidomes reveal altered lipid profiles in metastatic versus nonmetastatic cells.
Roy Jahnabi,Dibaeinia Payam,Fan Timothy M,Sinha Saurabh,Das Aditi
Journal of lipid research
Osteosarcoma (OS) is the most common form of primary bone cancer in humans. The early detection and subsequent control of metastasis has been challenging in OS. Lipids are important constituents of cells that maintain structural integrity that can be converted into lipid-signaling molecules and are reprogrammed in cancerous states. Here, we investigate the global lipidomic differences in metastatic (143B) and nonmetastatic (HOS) human OS cells as compared with normal fetal osteoblast cells (FOB) using lipidomics. We detect 15 distinct lipid classes in all three cell lines that included over 1,000 lipid species across various classes including phospholipids, sphingolipids and ceramides, glycolipids, and cholesterol. We identify a key class of lipids, diacylglycerols, which are overexpressed in metastatic OS cells as compared with their nonmetastatic or nontumorigenic counterparts. As a proof of concept, we show that blocking diacylglycerol synthesis reduces cellular viability and reduces cell migration in metastatic OS cells. Thus, the differentially regulated lipids identified in this study might aid in biomarker discovery, and the synthesis and metabolism of specific lipids could serve as future targets for therapeutic development.
Discovery of potential biomarkers in human melanoma cells with different metastatic potential by metabolic and lipidomic profiling.
Kim Hye-Youn,Lee Hwanhui,Kim So-Hyun,Jin Hanyong,Bae Jeehyeon,Choi Hyung-Kyoon
Malignant melanoma, characterized by its ability to metastasize to other organs, is responsible for 90% of skin cancer mortality. To investigate alterations in the cellular metabolome and lipidome related to melanoma metastasis, gas chromatography-mass spectrometry (GC-MS) and direct infusion-mass spectrometry (DI-MS)-based metabolic and lipidomic profiling were performed on extracts of normal human melanocyte (HEMn-LP), low metastatic melanoma (A375, G361), and highly metastatic melanoma (A2058, SK-MEL-28) cell lines. In this study, metabolomic analysis identified aminomalonic acid as a novel potential biomarker to discriminate between different stages of melanoma metastasis. Uptake and release of major metabolites as hallmarks of cancer were also measured between high and low metastatic melanoma cells. Lipid analysis showed a progressive increase in phosphatidylinositol (PI) species with saturated and monounsaturated fatty acyl chains, including 16:0/18:0, 16:0/18:1, 18:0/18:0, and 18:0/18:1, with increasing metastatic potential of melanoma cells, defining these lipids as possible biomarkers. In addition, a partial-least-squares projection to latent structure regression (PLSR) model for the prediction of metastatic properties of melanoma was established, and central metabolic and lipidomic pathways involved in the increased motility and metastatic potential of melanoma cells were identified as therapeutic targets. These results could be used to diagnose and control of melanoma metastasis.