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Cell Metabolism

ISSN: 1550-4131

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Datasets associated with articles published in Cell Metabolism

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1970
2024
1970 2024
51 results
  • Chiche J et al, GAPDH expression predicts the response to R-CHOP, the tumor metabolic status and the response of DLBCL patients to metabolic inhibitors , Cell Metabolism 2019
    This repository contains the R code used in our analysis of the Lenz et al (NEJM 2008) dataset. The processed data and metadata are available, to allow reproduction of the figures of the present publication. All details and references for these analyses are available in the method section of our manuscript.
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  • raw and processed data
    link between activation of anxiogenic circuits and hypermetabolism
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  • Data from Cellular metabolism is a major determinant of HIV-1 reservoir seeding in CD4+ T cells and offers an opportunity to tackle infection
    Relative mRNA expression (RT-qPCR) in naive, central memory, transitional memory and effector memory CD4+ T cells from 6 healthy human donors non activated or after three or five days of activation with soluble anti-CD3. Data related to BECN1 expression. Data from failed reactions were removed
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  • Obesity-Induced Cellular Senescence Drives Anxiety-Like Behavior And Impairment of Neurogenesis
    These CyTOF raw data were collected from brain cells of DIO mice and DBDB mice. Some were Veh treated and some were senolytics treated.
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  • RNA-seq profiling of 368T1 murine KP NSCLC cells deleted for AMPK with AMPKa1 add-back subjected to no glucose conditions, Replicate 1
    This dataset was generated for the paper, "Genetic analysis reveals AMPK is required to support tumor growth in murine Kras-dependent lung cancer models." Murine Kras mutant, p53 null (KP) 368T1 NSCLC cells were deleted for AMPK using the CRISPR/Cas9 system and subsequently stably infected with control vector ("KO") or AMPKalpha1 cDNA ("A1") add-back. These cells were subjected to no glucose (0mM, "NG") conditions for 12 or 18 hours, and profiled by RNA-sequencing. Replicate 1 High Glucose (HG) and No Glucose (NG) conditions were generated simultaneously and analyzed together. Analysis of a single dataset was performed using Replicate 1 ("R1"), and both replicates ("R1" and "R2") were analyzed together as indicated.
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  • RNA-seq profiling of 368T1 murine KP NSCLC cells deleted for AMPK with AMPKa1 add-back subjected to no glucose conditions, Replicate 2
    This dataset was generated for the paper, "Genetic analysis reveals AMPK is required to support tumor growth in murine Kras-dependent lung cancer models." Murine Kras mutant, p53 null (KP) 368T1 NSCLC cells were deleted for AMPK using the CRISPR/Cas9 system and subsequently stably infected with control vector ("KO") or AMPKalpha1 cDNA ("A1") add-back. These cells were subjected to no glucose (0mM, "NG") conditions for 12 or 18 hours, and profiled by RNA-sequencing. Replicate 2 High Glucose (HG) and No Glucose (NG) conditions were generated simultaneously and analyzed together. Analysis of a single dataset was performed using Replicate 1 ("R1"), and both replicates ("R1" and "R2") were analyzed together as indicated.
    • Dataset
  • RNA-seq profiling of 368T1 murine KP NSCLC cells deleted for AMPK with AMPKa1 add-back subjected to high glucose conditions, Replicate 2
    This dataset was generated for the paper, "Genetic analysis reveals AMPK is required to support tumor growth in murine Kras-dependent lung cancer models." Murine Kras mutant, p53 null (KP) 368T1 NSCLC cells were deleted for AMPK using the CRISPR/Cas9 system and subsequently stably infected with control vector ("KO") or AMPKalpha1 cDNA ("A1") add-back. These cells were subjected to high glucose (25mM, "HG") conditions for 12 or 18 hours, and profiled by RNA-sequencing. Replicate 2 High Glucose (HG) and No Glucose (NG) conditions were generated simultaneously and analyzed together. Analysis of a single dataset was performed using Replicate 1 ("R1"), and both replicates ("R1" and "R2") were analyzed together as indicated.
    • Dataset
  • RNASeq data from primary breast cancer clinical study pre- and post- two weeks treatment with metformin
    A clinical study that measured transcriptomics from biopsies of primary breast cancer taken at paired time points two weeks apart to profile the bioactivity of metformin breast cancer. Next generation sequencing of ‘Poly (A) targeted’ mRNA, including library preparation, was carried out by the Oxford Genomics Centre core facility at the Welcome Trust Centre for Human Genetics. The NEBNext mRNA Library Prep Master Mix Set (New England Biolabs) was used for preparation of the expression libraries and the Illumina HiSeq 2000 system used to carry out the sequencing. Paired-read were aligned to human reference genome GRCh38, including transcriptomic information, by Bowtie 2.2.6 and Tophat v2.1. The fold change of normalized expression level, FPKM (Fragments Per Kilobase of transcript per Million mapped reads), for each gene was then estimated from those aligned reads using Cuffdiff 2.2.1.
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  • PML-regulated mitochondrial metabolism enhances chemosensitivity in human ovarian cancers
    High-grade serous ovarian cancer (HGSOC) remains an unmet medical challenge. Here, we unravel an unanticipated metabolic heterogeneity in HGSOC. By combining proteomic, metabolomic, and bioergenetic analyses, we identify two molecular subgroups, low- and high-OXPHOS. While low-OXPHOS exhibit a glycolytic metabolism, high-OXPHOS HGSOCs rely on oxidative phosphorylation, supported by glutamine and fatty acid oxidation, and show chronic oxidative stress. We identify an important role for the PML-PGC-1α axis in the metabolic features of high-OXPHOS HGSOC. In high-OXPHOS tumors, chronic oxidative stress promotes aggregation of PML-nuclear bodies, resulting in activation of the transcriptional co-activator PGC-1α. Active PGC-1α increases synthesis of electron transport chain complexes, thereby promoting mitochondrial respiration. Importantly, high-OXPHOS HGSOCs exhibit increased response to conventional chemotherapies, in which increased oxidative stress, PML, and potentially ferroptosis play key functions. Collectively, our data establish a stress-mediated PML-PGC-1α-dependent mechanism that promotes OXPHOS metabolism and chemosensitivity in ovarian cancer.
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  • Increased lactate secretion by cancer cells sustains non-cell-autonomous adaptive resistance to MET and EGFR targeted therapies. Apicella et al.
    Microenvironment is known to influence cancer drug response and sustain resistance to therapies targeting receptor-tyrosine kinases. However if and how tumor microenvironment can be altered during treatment, contributing to resistance onset is not known. Here we show that, under prolonged treatment with tyrosine kinase inhibitors (TKIs), EGFR- or MET-addicted cancer cells displayed a metabolic shift towards increased glycolysis and lactate production. We identified secreted lactate as the key molecule able to instruct Cancer Associated Fibroblasts (CAFs) to produce Hepatocyte Growth Factor (HGF) in a NF-KB dependent manner. Increased HGF, activating MET-dependent signaling in cancer cells, sustained resistance to TKIs. Functional or pharmacological targeting of molecules involved in the lactate axis, such as lactate dehydrogenase or the lactate transporters MCT4 and MCT1, abrogated in vivo resistance, demonstrating the crucial role of this metabolite in the adaptive process. This non-cell-autonomous, adaptive resistance mechanism was observed in NSCLC patients progressed on EGFR TKIs, demonstrating the clinical relevance of our findings and opening novel scenarios in the challenge to drug resistance.
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