Research of novel anticancer agents targeting arginase inhibition

Pham, Thanh-Nhat; Liagre, Bertrand; Girard, Christian; Demougeot, Céline

doi:10.1016/j.drudis.2018.01.046

Cited by 37 publications

(20 citation statements)

References 60 publications

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“…The arginase inhibitor, nor-NOHA, was approved for human use and has been used in various cancers 24 and in an I/R injury trial. 25 We investigated whether arginase inhibition by nor-NOHA is effective for renal I/R injury.…”

Section: Arg2 Mediates Renal I/r Injury By Increasing Nitrosative Stressmentioning

confidence: 99%

Arginase 2 is a mediator of ischemia–reperfusion injury in the kidney through regulation of nitrosative stress

Hara

Torisu

Tomita

et al. 2020

Kidney International

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Section: Arg2 Mediates Renal I/r Injury By Increasing Nitrosative Stressmentioning

confidence: 99%

Arginase 2 is a mediator of ischemia–reperfusion injury in the kidney through regulation of nitrosative stress

Hara

Torisu

Tomita

et al. 2020

Kidney International

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“…range of cancers, and arginase is an attractive drug target 57 . One product of arginase is urea, and we found that the urea transporter SLC14A1 is selectively depleted in the malignant region in both tissue sections 1.2 and 2.4 (Fig.…”

Section: Spatial Patterns Of Arginine and Urea Metabolism Arginine Mmentioning

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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“…The binuclear manganese‐dependent metalloenzyme arginase catalyzes the catabolism of l ‐arginine to l ‐ornithine and urea. Through this hydrolytic reaction, it regulates the polyamine biosynthetic pathway, T‐cell–mediated immune response, and nitric oxide production pathways, which are involved in growth and proliferation of normal cells and control of diseases like cancer, cardiovascular diseases, and diseases related to the immune system . In the last few decades, polyamine biosynthetic pathway has been therapeutically targeted for the development of potential drugs against parasitic protozoan diseases including leishmaniasis, giardiasis, and African sleeping sickness .…”

Section: Introductionmentioning

confidence: 99%

“…Due to indispensable role of polyamines in cell growth, proliferation, and differentiation, polyamine biosynthesis is also a suitable target for therapeutic intervention in various other human diseases like cancer. Therefore, the lead compounds identified using the rational strategy in this study can not only be used for the development of anti‐amoebic drugs but also their efficacy can be tested against human arginases which might lead to the development of novel drugs against diseases like cancer through arginase inhibition approach .…”

Section: Introductionmentioning

confidence: 99%

Structural insights into Entamoeba histolytica arginase and structure‐based identification of novel non‐amino acid based inhibitors as potential antiamoebic molecules

et al. 2019

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Arginase, the binuclear metalloenzyme, is a potential target for therapeutic intervention in protozoan infections. Entamoeba histolytica infection causes amebiasis which is the second most common cause of protozoan‐related human deaths after malaria. Here, we report the crystal structure of E. histolytica arginase (EhArg) in complex with two known inhibitors Nω‐hydroxy‐l‐arginine (l‐NOHA) and l‐norvaline, and its product l‐ornithine at 1.7, 2.0, and 2.4 Å, respectively. Structural and comparative analysis of EhArg–inhibitor complexes with human arginase revealed that despite only 33% sequence identity, the structural determinants of inhibitor recognition and binding are highly conserved in arginases with variation in oligomerization motifs. Knowledge regarding the spatial organization of residues making molecular contacts with inhibitory compounds enabled in the identification of four novel non‐amino acid inhibitors, namely irinotecan, argatroban, cortisone acetate, and sorafenib. In vitro testing of the in silico‐identified inhibitors using purified enzyme proved that irinotecan, argatroban, cortisone acetate, and sorafenib inhibit EhArg with IC50 value (mm) of 1.99, 2.40, 0.91, and 2.75, respectively, as compared to the known inhibitors l‐NOHA and l‐norvaline with IC50 value (mm) of 1.57 and 17.9, respectively. The identification of structure‐based non‐amino acid inhibitory molecules against arginase will be constructive in design and discovery of novel chemical modulators for treating amebiasis by directed therapeutics.

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Research of novel anticancer agents targeting arginase inhibition

Cited by 37 publications

References 60 publications

Arginase 2 is a mediator of ischemia–reperfusion injury in the kidney through regulation of nitrosative stress

Arginase 2 is a mediator of ischemia–reperfusion injury in the kidney through regulation of nitrosative stress

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

Structural insights into Entamoeba histolytica arginase and structure‐based identification of novel non‐amino acid based inhibitors as potential antiamoebic molecules

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