Vitamin B 5 supports MYC oncogenic metabolism and tumor progression in breast cancer.
Peter A KreuzalerPaolo IngleseAvinash D GhanateErsa GjelajVincen WuYulia PaninaAndres Mendez-LucasCatherine MacLachlanNeill PataniCatherine B HubertHelen HuangGina GreenidgeOscar M RuedaAdam J TaylorEvdoxia KaraliEmine KazancAmy R Spicer-HadlingtonAlex DexterWei LinDaria ThompsonMariana Silva Dos SantosEnrica CalvaniNathalie M LegraveJames K EllisWendy GreenwoodMary GreenEmma NyeEmma Stillnull nullSimon T BarryRichard J A GoodwinAlejandra BrunaCarlos CaldasJames I MacRaeLuiz Pedro Sório de CarvalhoGeorge PoulogiannisGreg McMahonZoltán TakátsJosephine BunchMariia O YunevaPublished in: Nature metabolism (2023)
Tumors are intrinsically heterogeneous and it is well established that this directs their evolution, hinders their classification and frustrates therapy 1-3 . Consequently, spatially resolved omics-level analyses are gaining traction 4-9 . Despite considerable therapeutic interest, tumor metabolism has been lagging behind this development and there is a paucity of data regarding its spatial organization. To address this shortcoming, we set out to study the local metabolic effects of the oncogene c-MYC, a pleiotropic transcription factor that accumulates with tumor progression and influences metabolism 10,11 . Through correlative mass spectrometry imaging, we show that pantothenic acid (vitamin B 5 ) associates with MYC-high areas within both human and murine mammary tumors, where its conversion to coenzyme A fuels Krebs cycle activity. Mechanistically, we show that this is accomplished by MYC-mediated upregulation of its multivitamin transporter SLC5A6. Notably, we show that SLC5A6 over-expression alone can induce increased cell growth and a shift toward biosynthesis, whereas conversely, dietary restriction of pantothenic acid leads to a reversal of many MYC-mediated metabolic changes and results in hampered tumor growth. Our work thus establishes the availability of vitamins and cofactors as a potential bottleneck in tumor progression, which can be exploited therapeutically. Overall, we show that a spatial understanding of local metabolism facilitates the identification of clinically relevant, tractable metabolic targets.
Keyphrases
- transcription factor
- poor prognosis
- mass spectrometry
- long non coding rna
- high resolution
- endothelial cells
- machine learning
- liquid chromatography
- deep learning
- signaling pathway
- big data
- risk assessment
- young adults
- artificial intelligence
- bone marrow
- high performance liquid chromatography
- induced pluripotent stem cells
- photodynamic therapy
- data analysis
- childhood cancer