Functional lipidomics: Palmitic acid impairs hepatocellular carcinoma development by modulating membrane fluidity and glucose metabolism

Abstract

These data collectively demonstrate the biomedical potential of using altered lipid metabolism as a diagnostic marker for cancerous cells and open an opportunity for treating aggressive HCCs by targeting altered C16:0 metabolism. (Hepatology 2017;66:432-448).

Functional impairment triggered by altertoxin II (ATXII) in intestinal cells in vitro: cross-talk between cytotoxicity and mechanotransduction

“…Interestingly, the effects of ATXII on the cell membrane appeared in a low concentration range, being the toxin tested routinely in vitro up to 20 µM (Vejdovszky et al 2017b). It was recently reported that alteration of membrane fluidity could be directly correlated to cell migratory/metastatic capabilities both in vitro and in vivo (Edmond et al 2015; Lin et al 2017). In line, the evaluation of the oxidative status of the membrane is gaining more and more importance in the comprehension of the complex loss/gain of functional landscapes associated with the progression of cancer malignancy (Van der Paal et al 2016), as well as representing a promising target for future therapeutic strategies (Peetla et al 2013; Suganuma et al 2016).…”

LION/web: a web-based ontology enrichment tool for lipidomic data analysis

“…S2 C ). Next, values predicted by the obtained model of all applicable lipid species present in LION were divided into quintiles with limits based on four reported lipidomics datasets (Andreyev et al, 2010; Haraszti et al, 2016; Köberlin et al, 2015; Lin et al, 2017) and categorized into five representative classes: ‘very low’, ‘low’, ‘average’, ‘high’ or ‘very high’ chain-melting transition temperature (a flow-chart of this procedure is depicted in Fig. S2 E ).…”

“…S2 A-B ). We followed the same procedure as used for transition temperatures; extrapolated results for both properties were divided into quintiles (based on values of reported datasets (Andreyev et al, 2010; Haraszti et al, 2016; Köberlin et al, 2015; Lin et al, 2017), predicted by our models) and categorized into five representative classes: ‘very low’, ‘low’, ‘average’, ‘high’ or ‘very high’.…”

“…Subsequently, all numerical datapoints for each biophysical property were categorized into five pre-defined groups (‘very low’, ‘low’, ‘average’, ‘high’, ‘very high’). The limits of each group were determined based on the presence of lipid species reported in four lipidomics publications (Andreyev et al, 2010; Haraszti et al, 2016; Köberlin et al, 2015; Lin et al, 2017). These values were subsequently used to categorize all applicable lipid species present in LION ( Fig.…”

Lipidomics: a promising cancer biomarker

“…Some cancer cells were found to stay alive through energy from fatty acid oxidation. Several studies found many lipids increased in cancer, such as the lysophospholipids in ovarian cancer, glycerophospholipids in hepatocellular carcinoma, acylcarnitines, glycerophospholipids and arginine in prostate cancer, sphingolipid 1-phosphate in ovarian or glioma and breast cancer [3][4][5][6][7][8]. Studies also suggested the choline-containing lipids and phospholipids could increase during the metastasis of cancer cells.…”