ArticleData in brief2024
Dataset for analysis of metabolic pathways and their reversibility associated with anti-proliferative effect of metformin in liver cancer cells.
Article in Data in brief, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- A study of oral metformin for the intravesical treatment of non-muscle-invasive bladder cancer.BJU international · 2025Trial
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2 authors.
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No grant is acknowledged in the PubMed record.
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.
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