During the last decades a considerable amount of research has been focused on cancer. A number of genetic and signaling defects have been identified. This has allowed the design and screening of a number of anti-tumor drugs for therapeutic use. One of the main challenges of anti-cancer therapy is to specifically target these drugs to malignant cells. Recently, tumor cell metabolism has been considered as a possible target for cancer therapy. It is widely accepted that tumors display an enhanced glycolytic activity and oxidative phosphorylation down-regulation (Warburg effect). Therefore, it seems reasonable that disruption of glycolysis might be a promising candidate for specific anti-cancer therapy. Nonetheless, the concept of aerobic glycolysis as the paradigm of tumor cell metabolism has been challenged, as some tumor cells use oxidative phosphorylation. Mitochondria are of special interest in cancer cell energy metabolism, as their physiology is linked to the Warburg effect. Besides, their central role in apoptosis makes these organelles a promising "dual hit target" for selectively eliminate tumor cells. Thus, it is desirable to have an easy-to-use and reliable model in order to do the screening for energy metabolism-inhibiting drugs to be used in cancer therapy. From a metabolic point of view, the fermenting yeast Saccharomyces cerevisiae and tumor cells share several features. In this paper we will review these common metabolic properties and we will discuss the possibility of using S. cerevisiae as an early screening test in the research for novel anti-tumor compounds used for the inhibition of tumor cell metabolism.
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Evidence ID | Analyze ID | Gene/Complex | Systematic Name/Complex Accession | Qualifier | Gene Ontology Term ID | Gene Ontology Term | Aspect | Annotation Extension | Evidence | Method | Source | Assigned On | Reference |
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Evidence ID | Analyze ID | Gene | Gene Systematic Name | Phenotype | Experiment Type | Experiment Type Category | Mutant Information | Strain Background | Chemical | Details | Reference |
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Evidence ID | Analyze ID | Gene | Gene Systematic Name | Disease Ontology Term | Disease Ontology Term ID | Qualifier | Evidence | Method | Source | Assigned On | Reference |
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Evidence ID | Analyze ID | Regulator | Regulator Systematic Name | Target | Target Systematic Name | Direction | Regulation of | Happens During | Regulator Type | Direction | Regulation Of | Happens During | Method | Evidence | Strain Background | Reference |
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Site | Modification | Modifier | Source | Reference |
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Evidence ID | Analyze ID | Interactor | Interactor Systematic Name | Interactor | Interactor Systematic Name | Allele | Assay | Annotation | Action | Phenotype | SGA score | P-value | Source | Reference | Note |
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Evidence ID | Analyze ID | Interactor | Interactor Systematic Name | Interactor | Interactor Systematic Name | Assay | Annotation | Action | Modification | Source | Reference | Note |
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Complement ID | Locus ID | Gene | Species | Gene ID | Strain background | Direction | Details | Source | Reference |
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Evidence ID | Analyze ID | Dataset | Description | Keywords | Number of Conditions | Reference |
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