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Zaghlool, S. B.

Publications and source records attributed to Zaghlool, S. B..

2 recordsLinked to original sources

Accelerated lipid catabolism and autophagy are cancer survival mechanisms under inhibited glutaminolysis

Suppressing glutaminolysis does not always induce cancer cell death in glutamine-dependent tumors because cells may switch to alternative energy sources. To reveal compensatory metabolic pathways, we investigated the metabolome-wide cellular response to inhibited glutaminolysis. We conducted metabolic profiling in the triple-negative breast cancer cell line MB-MDA-231, treated with different dosages of glutaminase inhibitor C.968 at multiple time points. We found that multiple molecules involved in lipid catabolism responded directly to glutamate deficiency as a presumed compensation for energy deficit. Accelerated lipid catabolism, together with oxidative stress induced by glutaminolysis inhibition, triggered autophagy. We therefore simultaneously inhibited glutaminolysis and autophagy, which induced cancer cell death. Our study emphasizes the potential of non-targeted metabolomics to characterize and identify metabolic escape mechanisms contributing to cancer cell survival under treatment. Our findings add to the increasing evidence that combined inhibition of glutaminolysis and autophagy may be effective in glutamine-addicted cancers.

cancer biology

PopPAnTe: population and pedigree association testing for quantitative data

Family-based designs, from twin studies to isolated populations with their complex genealogical data, are a valuable resource for genetic studies of heritable molecular biomarkers. Existing software for family-based studies have mainly focused on facilitating association between response phenotypes and genetic markers, and no user-friendly tools are at present available to straightforwardly extend association studies in related samples to large datasets of generic quantitative data, as those generated by current -omics technologies.\n\nWe developed PopPAnTe, a user-friendly Java program, which evaluates the association of quantitative data in related samples. Additionally, Pop-PAnTe implements data pre and post processing, region based testing, and empirical assessment of associations.\n\nPopPAnTe is an integrated and flexible framework for pairwise association testing in related samples with a large number of predictors and response variables. It works either with family data of any size and complexity, or, when the genealogical information is unknown, it uses genetic similarity information between individuals as those inferred from genome-wide genetic data. It can therefore be particularly useful in facilitating usage of biobank data collections from population isolates when extensive genealogical information is missing.

bioinformatics