Data in Brief (Aug 2024)
Dataset for analysis of metabolic pathways and their reversibility associated with anti-proliferative effect of metformin in liver cancer cells
Abstract
Despite epidemiological indications, utility of metformin in liver cancer remains debated and the understanding of the mechanism underlying its anti-cancer effects remains incomplete. Particularly, whether it operates via similar mechanism under glucose-sufficient and glucose- deficient environments or whether these effects are reversible remains unexplored. This metabolomic dataset was collected from liver cancer (HepG2) cells treated with metformin or placebo over a period of 3 h to 48 h as well as from cells recovering after metformin withdrawal. Cells were exposed to placebo or 2.5 mM metformin with or without glucose (5 mM) supplementation. The cells were harvested at 3, 6, 12, 24, and 48 h post-treatment. Cells were also harvested after 24 h of treatment under one of these conditions followed by reversal of glucose and/or metformin exposure status for 48 h. Metabolites from six biological replicates of each experimental group were extracted using chilled monophasic metabolite extraction solvent (Water: Acetonitrile: Isopropanol= 2:3:3) containing homovanillic acid as an internal standard. Samples were derivatized using MOX reagent followed by MSTFA. Untargeted metabolomic profiling of derivatized samples were performed using an Agilent 7890B gas chromatograph coupled to a 5977B single quadrupole mass spectrometer. Analytes were injected through a splitless liner and separated on a HP-5MS ultra-inert column using ultrapure helium as the carrier gas. Peak alignment, annotation, and integration were done using Agilent MassHunter Quantitative analysis software. Multivariate analysis was performed using MetaboAnalyst 5.0. These experiments were performed to unravel the longitudinal evolution of cellular metabolome in response to metformin treatment, its glucose dependence, as well as to examine the reversibility of these changes. The dataset can help to identify glucose-independent pathways involved in anti-cancer effect of metformin. The dataset can be used to design experiments to develop novel therapeutic combinations synergistically acting with metformin to cripple the metabolic fitness of cancer cells. It can also help to develop experiments to test the effect of metformin withdrawal in liver cancer.
