Data from: Defining metabolic flexibility in hair follicle stem cell induced squamous cell carcinoma
Data files
Mar 20, 2025 version files 9.47 MB
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Metabolomics_Galvan_et_al_2024.xlsx
768.86 KB
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README.md
790 B
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RNAseq_GLSKO_Galvan_et_al_2024.xlsx
4.59 MB
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RNAseq_LDHAKO_Galvan_et_al_2024.xlsx
4.11 MB
Abstract
Among the numerous changes associated with the transformation to cancer, cellular metabolism is one of the first discovered and most prominent. However, despite the knowledge that nearly every cancer is associated with the strong upregulation of various metabolic pathways, there has yet to be much clinical progress on the treatment of cancer by targeting a single metabolic enzyme directly. We previously showed that inhibition of glycolysis through lactate dehydrogenase (LDHA) deletion in cancer cells of origin had no effect on the initiation or progression of cutaneous squamous cell carcinoma, suggesting that these cancers are metabolically flexible enough to produce the necessary metabolites required for sustained growth in the absence of glycolysis. Here we focused on glutaminolysis, another metabolic pathway frequently implicated as important for tumorigenesis in correlative studies. We genetically blocked glutaminolysis through glutaminase (GLS) deletion in cancer cells of origin, and found that this had little effect on tumorigenesis, similar to what we previously showed for blocking glycolysis. Tumors with genetic deletion of glutaminolysis instead upregulated lactate consumption and utilization for the TCA cycle, providing further evidence of metabolic flexibility. We also found that the metabolic flexibility observed upon inhibition of glycolysis, pyruvate oxidation, or glutaminolysis is due to post-transcriptional changes in the levels of plasma membrane lactate, glucose, and glutamine transporters. To define the limits of metabolic flexibility in cancer initiating hair follicle stem cells, we genetically blocked both glycolysis and glutaminolysis simultaneously and found that frank carcinoma was not compatible with abrogation of both of these carbon utilization pathways. These data point towards metabolic flexibility mediated by regulation of nutrient consumption, and suggest that treatment of cancer through metabolic manipulation will require multiple interventions on distinct pathways.
https://doi.org/10.5061/dryad.73n5tb34q
For RNAseq, wild-type and knock out are labeled on respective files.
For metabolomics, data is organized based on the carbon labeled used, pool data, and genotype if indicated on sheet tab titles. Wild-type and knock out samples are labeled on the sheet itself or on the sheet title. Empty cells and “NA” labeled cells are values that were not detected for metabolites.
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pool = metabolic pool levels
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gls = glutaminase wt vs ko
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label = carbon 13 isotope labeling
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ldha = lactate dehydrogenase
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mpc = mitochondrial pyruvate carrier
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scc = squamous cell carcinoma