Oil for the cancer engine: The cross-talk between oncogenic signaling and polyamine metabolism

Arruabarrena-Aristorena, Amaia; Zabala-Letona, Amaia; Carracedo, Arkaitz

doi:10.1126/sciadv.aar2606

Cited by 91 publications

(86 citation statements)

References 115 publications

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“…(2020) 10:3490 | https://doi.org/10.1038/s41598-020-60384-w www.nature.com/scientificreports www.nature.com/scientificreports/ prostate cancer 60 . Alternatively, arginine is also important for biosynthesis, which creates a competition for polyamine synthesis (Fig.…”

Section: Scientific Reports |mentioning

confidence: 99%

Spatial modeling of prostate cancer metabolic gene expression reveals extensive heterogeneity and selective vulnerabilities

Wang

Ruzzo

2020

Sci Rep

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Spatial heterogeneity is a fundamental feature of the tumor microenvironment (TME), and tackling spatial heterogeneity in neoplastic metabolic aberrations is critical for tumor treatment. Genomescale metabolic network models have been used successfully to simulate cancer metabolic networks. However, most models use bulk gene expression data of entire tumor biopsies, ignoring spatial heterogeneity in the TME. To account for spatial heterogeneity, we performed spatially-resolved metabolic network modeling of the prostate cancer microenvironment. We discovered novel malignantcell-specific metabolic vulnerabilities targetable by small molecule compounds. We predicted that inhibiting the fatty acid desaturase SCD1 may selectively kill cancer cells based on our discovery of spatial separation of fatty acid synthesis and desaturation. We also uncovered higher prostaglandin metabolic gene expression in the tumor, relative to the surrounding tissue. Therefore, we predicted that inhibiting the prostaglandin transporter SLCO2A1 may selectively kill cancer cells. Importantly, SCD1 and SLCO2A1 have been previously shown to be potently and selectively inhibited by compounds such as CAY10566 and suramin, respectively. We also uncovered cancer-selective metabolic liabilities in central carbon, amino acid, and lipid metabolism. Our novel cancer-specific predictions provide new opportunities to develop selective drug targets for prostate cancer and other cancers where spatial transcriptomics datasets are available.Cancer cells reprogram their metabolism to fulfill the energetic and biosynthetic needs of proliferation, invasion and migration 1 . This is exemplified in prostate cancer, the second most common cancer in American men after melanoma 2 . Previous studies have uncovered profound metabolic dysregulation in multiple pathways, particularly in fatty acid and lipid metabolism 3,4 . Discovering novel cancer-specific metabolic aberrations has significant translational applications, because cancer-associated metabolic dysfunctions can be exploited to advance cancer detection (e.g., 18 F-FDG (Fludeoxyglucose) imaging based on elevated glycolysis in cancer 5 ) and treatment (e.g., L-asparaginase in treating acute lymphoblastic leukemia 6 ).Cancer metabolic reprograming is profoundly impacted by spatial heterogeneity, a fundamental feature of the tumor microenvironment (TME) 7 . Heterogeneous distributions of blood vessels and stromal tissues create uneven spatial gradients of nutrients and metabolic byproducts, which significantly shape the phenotypes of many cell types in the TME 8 . Recent technologies, such as spatial transcriptomics 9,10 and Slide-seq 11 have enabled transcriptomic profiling of hundreds of locations within tissue sections with high spatial resolution (2-100 μm), and have been used to study multiple types of malignancies, including prostate cancer, breast cancer, pancreatic cancer, and melanoma 9,10,12-14 . These spatially-resolved datasets provide novel opportunities to dissect spatial metabolic heterogeneity i...

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Section: Scientific Reports |mentioning

confidence: 99%

Spatial modeling of prostate cancer metabolic gene expression reveals extensive heterogeneity and selective vulnerabilities

Wang

Ruzzo

2020

Sci Rep

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“…The reprogramming of cancer metabolism represents a biochemical process that sustains cancer growth and proliferation, while also exerting a profound influence in the tumor microenvironment. [ 2–4 ] Several lines of evidence support the notion that symbiotic and competitive mechanisms exist, stemming from distinct metabolite‐based communication, which support tumor growth and hinder antitumor immunity. Consequently, the assessment of tumor‐secreted metabolites becomes instrumental for monitoring the response of tumors upon therapeutic challenges, the stratification of cancer patients, and the identification of novel therapeutic strategies.…”

Section: Introductionmentioning

confidence: 99%

Multiplex SERS Detection of Metabolic Alterations in Tumor Extracellular Media

Plou

Garcı́a

Charconnet

et al. 2020

Adv Funct Materials

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The composition and intercellular interactions of tumor cells in the tissues dictate the biochemical and metabolic properties of the tumor microenvironment. The metabolic rewiring has a profound impact on the properties of the microenvironment, to an extent that monitoring such perturbations could harbor diagnostic and therapeutic relevance. A growing interest in these phenomena has inspired the development of novel technologies with sufficient sensitivity and resolution to monitor metabolic alterations in the tumor microenvironment. In this context, surface-enhanced Raman scattering (SERS) can be used for the label-free detection and imaging of diverse molecules of interest among extracellular components. Herein, the application of nanostructured plasmonic substrates comprising Au nanoparticles, self-assembled as ordered superlattices, to the precise SERS detection of selected tumor metabolites, is presented. The potential of this technology is first demonstrated through the analysis of kynurenine, a secreted immunomodulatory derivative of the tumor metabolism and the related molecules tryptophan and purine derivatives. SERS facilitates the unambiguous identification of trace metabolites and allows the multiplex detection of their characteristic fingerprints under different conditions. Finally, the effective plasmonic SERS substrate is combined with a hydrogel-based three-dimensional cancer model, which recreates the tumor microenvironment, for the real-time imaging of metabolite alterations and cytotoxic effects on tumor cells.

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“…These results add to the multiplicity of known effects of polyamines in cells , and they may be important under conditions of activated polyamine synthesis as occurs in cancer cells . Finally, a useful observation is that therapeutical inhibition of the UPS at the level of either the proteasome or the ubiquitin ligases (present work) may be rescued with amino acid supplementation.…”

Section: Resultsmentioning

confidence: 70%

Polyamines interfere with protein ubiquitylation and cause depletion of intracellular amino acids: a possible mechanism for cell growth inhibition

et al. 2018

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Spermidine is a polyamine present in eukaryotes with essential functions in protein synthesis. At high concentrations spermidine and norspermidine inhibit growth by unknown mechanisms. Transcriptomic analysis of the effect of norspermidine on the plant Arabidopsis thaliana indicates upregulation of the response to heat stress and denatured proteins. Accordingly, these polyamines inhibit protein ubiquitylation, both in vivo (in yeast, Arabidopsis, and human Hela cells) and in vitro (with recombinant ubiquitin ligase). This interferes with protein degradation by the proteasome, a situation known to deplete cells of amino acids. Norspermidine treatment of yeast cells induces amino acid depletion, and supplementation of media with amino acids counteracts growth inhibition and cellular amino acid depletion but not inhibition of protein polyubiquitylation.

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Oil for the cancer engine: The cross-talk between oncogenic signaling and polyamine metabolism

Abstract: Polyamine metabolism exhibits tight cross-talk with oncogenic signaling, thus playing a central role in cancer dynamics.

Cited by 91 publications

References 115 publications

Spatial modeling of prostate cancer metabolic gene expression reveals extensive heterogeneity and selective vulnerabilities

Spatial modeling of prostate cancer metabolic gene expression reveals extensive heterogeneity and selective vulnerabilities

Multiplex SERS Detection of Metabolic Alterations in Tumor Extracellular Media

Polyamines interfere with protein ubiquitylation and cause depletion of intracellular amino acids: a possible mechanism for cell growth inhibition

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