Indolepropionic Acid, a Metabolite of the Microbiome, Has Cytostatic Properties in Breast Cancer by Activating AHR and PXR Receptors and Inducing Oxidative Stress
Abstract
:1. Introduction
2. Materials and Methods
2.1. Chemicals
2.2. Cell Culture
2.3. In Vitro Cell Proliferation Assays
2.4. Detection of Cell Death
2.5. Electric Cell–Substrate Impedance Sensing (ECIS)
2.6. Immunocytochemisry
2.7. mRNA Preparation and Quantitation
2.8. Bacterial TnaA DNA Quantitation
2.9. Quantitation of Fecal E. coli TnaA Protein
2.10. Aldefluor Assay
2.11. SDS-PAGE and Western Blotting
2.12. Determination of Lipid Peroxidation
2.13. Animal Study
2.14. Human Studies
2.14.1. Cohort 1
2.14.2. Cohort 2
2.14.3. Cohort 3
2.15. Tissue Microarray, Immunohistochemistry and Analysis
2.16. Database Screening
2.17. Statistical Analysis
3. Results
3.1. Indolepropionic Acid Reduces the Progression of Breast Cancer In Vivo
3.2. Indolepropionic Acid Inhibits Hallmarks of Cancer
3.3. IPA-Induced Cytostatic and Antineoplastic Effects Are Mediated by Reactive Species Production
3.4. IPA Exerts Its Effects through Aryl-Hydrocarbon Peceptor (AHR) and Pregnane X Receptor (PXR)
3.5. Microbial Indole Biosynthesis by the Gut Microbiome Is Repressed in Early Stages of Breast Cancer
3.6. Fecal Protein Expression of E. coli TnaA Correlates with the Number of Tumor Infiltrating Lymphocytes
4. Discussion
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
- Flores, R.; Shi, J.; Fuhrman, B.; Xu, X.; Veenstra, T.D.; Gail, M.H.; Gajer, P.; Ravel, J.; Goedert, J.J. Fecal microbial determinants of fecal and systemic estrogens and estrogen metabolites: A cross-sectional study. J. Transl. Med. 2012, 10, 253. [Google Scholar] [CrossRef][Green Version]
- Fuhrman, B.J.; Feigelson, H.S.; Flores, R.; Gail, M.H.; Xu, X.; Ravel, J.; Goedert, J.J. Associations of the fecal microbiome with urinary estrogens and estrogen metabolites in postmenopausal women. J. Clin. Endocrinol. Metab. 2014, 99, 4632–4640. [Google Scholar] [CrossRef]
- Goedert, J.J.; Jones, G.; Hua, X.; Xu, X.; Yu, G.; Flores, R.; Falk, R.T.; Gail, M.H.; Shi, J.; Ravel, J.; et al. Investigation of the association between the fecal microbiota and breast cancer in postmenopausal women: A population-based case-control pilot study. J. Natl. Cancer Inst. 2015, 107, djv147. [Google Scholar] [CrossRef]
- Goedert, J.J.; Hua, X.; Bielecka, A.; Okayasu, I.; Milne, G.L.; Jones, G.S.; Fujiwara, M.; Sinha, R.; Wan, Y.; Xu, X.; et al. Postmenopausal breast cancer and oestrogen associations with the IgA-coated and IgA-noncoated faecal microbiota. Br. J. Cancer 2018, 23, 435. [Google Scholar] [CrossRef][Green Version]
- Jones, G.S.; Spencer Feigelson, H.; Falk, R.T.; Hua, X.; Ravel, J.; Yu, G.; Flores, R.; Gail, M.H.; Shi, J.; Xu, X.; et al. Mammographic breast density and its association with urinary estrogens and the fecal microbiota in postmenopausal women. PLoS ONE 2019, 14, e0216114. [Google Scholar] [CrossRef]
- Fruge, A.D.; Van der Pol, W.; Rogers, L.Q.; Morrow, C.D.; Tsuruta, Y.; Demark-Wahnefried, W. Fecal Akkermansia muciniphila Is Associated with Body Composition and Microbiota Diversity in Overweight and Obese Women with Breast Cancer Participating in a Presurgical Weight Loss Trial. J. Acad. Nutr. Diet. 2018, 9, 164. [Google Scholar] [CrossRef][Green Version]
- Luu, T.H.; Michel, C.; Bard, J.M.; Dravet, F.; Nazih, H.; Bobin-Dubigeon, C. Intestinal Proportion of Blautia sp. is Associated with Clinical Stage and Histoprognostic Grade in Patients with Early-Stage Breast Cancer. Nutr. Cancer 2017, 69, 267–275. [Google Scholar] [CrossRef]
- Zhu, J.; Liao, M.; Yao, Z.; Liang, W.; Li, Q.; Liu, J.; Yang, H.; Ji, Y.; Wei, W.; Tan, A.; et al. Breast cancer in postmenopausal women is associated with an altered gut metagenome. Microbiome 2018, 6, 136. [Google Scholar] [CrossRef][Green Version]
- Banerjee, S.; Tian, T.; Wei, Z.; Shih, N.; Feldman, M.D.; Peck, K.N.; DeMichele, A.M.; Alwine, J.C.; Robertson, E.S. Distinct Microbial Signatures Associated With Different Breast Cancer Types. Front. Microbiol. 2018, 9, 951. [Google Scholar] [CrossRef][Green Version]
- Kwa, M.; Plottel, C.S.; Blaser, M.J.; Adams, S. The Intestinal Microbiome and Estrogen Receptor-Positive Female Breast Cancer. J. Natl. Cancer Inst. 2016, 108, djw029. [Google Scholar]
- Howe, C.; Kim, S.J.; Mitchell, J.; Im, E.; Kim, Y.S.; Kim, Y.S.; Rhee, S.H. Differential expression of tumor-associated genes and altered gut microbiome with decreased Akkermansia muciniphila confer a tumor-preventive microenvironment in intestinal epithelial Pten-deficient mice. Biochim. Biophys. Acta Mol. Basis Dis. 2018, 1864, 3746–3758. [Google Scholar] [CrossRef] [PubMed]
- Parida, S.; Sharma, D. The power of small changes: Comprehensive analyses of microbial dysbiosis in breast cancer. Biochim. Biophys. Acta Rev. Cancer 2019, 11, 30042–30043. [Google Scholar] [CrossRef] [PubMed]
- Dakubo, G.D. Body Fluid Microbiome as Cancer Biomarkers. In Cancer Biomarkers in Body Fluids; Springer: Cham, Switzerland, 2019. [Google Scholar]
- Kirkup, B.; McKee, A.; Makin, K.; Paveley, J.; Caim, S.; Alcon-Giner, C.; Leclaire, C.; Dalby, M.; Le Gall, G.; Andrusaite, A.; et al. Perturbation of the gut microbiota by antibiotics results in accelerated breast tumour growth and metabolic dysregulation. BioRxiv 2019. [Google Scholar] [CrossRef]
- Velicer, C.M.; Heckbert, S.R.; Lampe, J.W.; Potter, J.D.; Robertson, C.A.; Taplin, S.H. Antibiotic use in relation to the risk of breast cancer. JAMA 2004, 291, 827–835. [Google Scholar] [CrossRef] [PubMed][Green Version]
- Tamim, H.M.; Hanley, J.A.; Hajeer, A.H.; Boivin, J.F.; Collet, J.P. Risk of breast cancer in relation to antibiotic use. Pharmacoepidemiol. Drug Saf. 2008, 17, 144–150. [Google Scholar] [CrossRef]
- Sergentanis, T.N.; Zagouri, F.; Zografos, G.C. Is antibiotic use a risk factor for breast cancer? A meta-analysis. Pharmacoepidemiol. Drug Saf. 2010, 19, 1101–1107. [Google Scholar] [CrossRef]
- Satram-Hoang, S.; Moran, E.M.; Anton-Culver, H.; Burras, R.W.; Heimann, T.M.; Boggio, I.; Dykstra-Long, G.R.; Wood, P.A.; Zulka, R.; Hufnagel, G.; et al. A pilot study of male breast cancer in the Veterans Affairs healthcare system. J. Environ. Pathol. Toxicol. Oncol. 2010, 29, 235–244. [Google Scholar] [CrossRef]
- Wirtz, H.S.; Buist, D.S.; Gralow, J.R.; Barlow, W.E.; Gray, S.; Chubak, J.; Yu, O.; Bowles, E.J.; Fujii, M.; Boudreau, D.M. Frequent antibiotic use and second breast cancer events. Cancer Epidemiol. Biomark. Prev. 2013, 22, 1588–1599. [Google Scholar] [CrossRef][Green Version]
- Elkrief, A.; Derosa, L.; Kroemer, G.; Zitvogel, L.; Routy, B. The negative impact of antibiotics on outcomes in cancer patients treated with immunotherapy: A new independent prognostic factor? Ann. Oncol. 2019, 30, 1572–1579. [Google Scholar] [CrossRef][Green Version]
- Friedman, G.D.; Oestreicher, N.; Chan, J.; Quesenberry, C.P., Jr.; Udaltsova, N.; Habel, L.A. Antibiotics and risk of breast cancer: Up to 9 years of follow-up of 2.1 million women. Cancer Epidemiol. Biomark. Prev. 2006, 15, 2102–2106. [Google Scholar] [CrossRef][Green Version]
- Velicer, C.M.; Heckbert, S.R.; Rutter, C.; Lampe, J.W.; Malone, K. Association between antibiotic use prior to breast cancer diagnosis and breast tumour characteristics (United States). Cancer Causes Control 2006, 17, 307–313. [Google Scholar] [CrossRef] [PubMed]
- Aragon, F.; Carino, S.; Perdigon, G.; de Moreno de LeBlanc, A. The administration of milk fermented by the probiotic Lactobacillus casei CRL 431 exerts an immunomodulatory effect against a breast tumour in a mouse model. Immunobiology 2014, 219, 457–464. [Google Scholar] [CrossRef] [PubMed]
- Hassan, Z.; Mustafa, S.; Rahim, R.A.; Isa, N.M. Anti-breast cancer effects of live, heat-killed and cytoplasmic fractions of Enterococcus faecalis and Staphylococcus hominis isolated from human breast milk. In Vitro Cell. Dev. Biol. Anim. 2016, 52, 337–348. [Google Scholar] [CrossRef]
- Mendoza, L. Potential effect of probiotics in the treatment of breast cancer. Oncol. Rev. 2019, 13, 422. [Google Scholar] [CrossRef] [PubMed][Green Version]
- Ranjbar, S.; Seyednejad, S.A.; Azimi, H.; Rezaeizadeh, H.; Rahimi, R. Emerging Roles of Probiotics in Prevention and Treatment of Breast Cancer: A Comprehensive Review of Their Therapeutic Potential. Nutr. Cancer 2019, 71, 1–12. [Google Scholar] [CrossRef]
- Miko, E.; Vida, A.; Kovacs, T.; Ujlaki, G.; Trencsenyi, G.; Marton, J.; Sari, Z.; Kovacs, P.; Boratko, A.; Hujber, Z.; et al. Lithocholic acid, a bacterial metabolite reduces breast cancer cell proliferation and aggressiveness. Biochim. Biophys. Acta 2018, 1859, 958–974. [Google Scholar] [CrossRef]
- Kovács, T.; Mikó, E.; Vida, A.; Sebő, É.; Toth, J.; Csonka, T.; Boratkó, A.; Ujlaki, G.; Lente, G.; Kovács, P.; et al. Cadaverine, a metabolite of the microbiome, reduces breast cancer aggressiveness through trace amino acid receptors. Sci. Rep. 2019, 9, 1300. [Google Scholar] [CrossRef][Green Version]
- Vergara, D.; Simeone, P.; Damato, M.; Maffia, M.; Lanuti, P.; Trerotola, M. The Cancer Microbiota: EMT and Inflammation as Shared Molecular Mechanisms Associated with Plasticity and Progression. J. Oncol. 2019, 2019, 1253727. [Google Scholar] [CrossRef]
- Kovács, P.; Csonka, T.; Kovács, T.; Sári, Z.; Ujlaki, G.; Sipos, A.; Karányi, Z.; Szeőcs, D.; Hegedűs, C.; Uray, K.; et al. Lithocholic acid, a metabolite of the microbiome, increases oxidative stress in breast cancer. Cancers 2019, 11, 1255. [Google Scholar] [CrossRef][Green Version]
- Buchta Rosean, C.; Bostic, R.R.; Ferey, J.C.M.; Feng, T.Y.; Azar, F.N.; Tung, K.S.; Dozmorov, M.G.; Smirnova, E.; Bos, P.D.; Rutkowski, M.R. Preexisting Commensal Dysbiosis Is a Host-Intrinsic Regulator of Tissue Inflammation and Tumor Cell Dissemination in Hormone Receptor-Positive Breast Cancer. Cancer Res. 2019, 79, 3662–3675. [Google Scholar] [CrossRef][Green Version]
- Ingman, W.V. The Gut Microbiome: A New Player in Breast Cancer Metastasis. Cancer Res. 2019, 79, 3539–3541. [Google Scholar] [CrossRef][Green Version]
- Yager, J.D. Mechanisms of estrogen carcinogenesis: The role of E2/E1-quinone metabolites suggests new approaches to preventive intervention—A review. Steroids 2015, 99, 56–60. [Google Scholar] [CrossRef] [PubMed][Green Version]
- Miko, E.; Kovacs, T.; Sebo, E.; Toth, J.; Csonka, T.; Ujlaki, G.; Sipos, A.; Szabo, J.; Mehes, G.; Bai, P. Microbiome-Microbial Metabolome-Cancer Cell Interactions in Breast Cancer-Familiar, but Unexplored. Cells 2019, 8, 293. [Google Scholar] [CrossRef][Green Version]
- Zitvogel, L.; Ayyoub, M.; Routy, B.; Kroemer, G. Microbiome and Anticancer Immunosurveillance. Cell 2016, 165, 276–287. [Google Scholar] [CrossRef][Green Version]
- Zitvogel, L.; Daillere, R.; Roberti, M.P.; Routy, B.; Kroemer, G. Anticancer effects of the microbiome and its products. Nat. Rev. Microbiol. 2017, 15, 465–478. [Google Scholar] [CrossRef]
- Viaud, S.; Daillere, R.; Boneca, I.G.; Lepage, P.; Pittet, M.J.; Ghiringhelli, F.; Trinchieri, G.; Goldszmid, R.; Zitvogel, L. Harnessing the intestinal microbiome for optimal therapeutic immunomodulation. Cancer Res. 2014, 74, 4217–4221. [Google Scholar] [CrossRef][Green Version]
- Routy, B.; Le Chatelier, E.; Derosa, L.; Duong, C.P.M.; Alou, M.T.; Daillere, R.; Fluckiger, A.; Messaoudene, M.; Rauber, C.; Roberti, M.P.; et al. Gut microbiome influences efficacy of PD-1-based immunotherapy against epithelial tumors. Science 2018, 359, 91–97. [Google Scholar] [CrossRef][Green Version]
- Tang, W.; Putluri, V.; Ambati, C.R.; Dorsey, T.H.; Putluri, N.; Ambs, S. Liver- and Microbiome-derived Bile Acids Accumulate in Human Breast Tumors and Inhibit Growth and Improve Patient Survival. Clin. Cancer Res. 2019, 25, 5972–5983. [Google Scholar] [CrossRef][Green Version]
- Roager, H.M.; Licht, T.R. Microbial tryptophan catabolites in health and disease. Nat. Commun. 2018, 9, 3294. [Google Scholar] [CrossRef][Green Version]
- Yokoyama, M.T.; Carlson, J.R. Microbial metabolites of tryptophan in the intestinal tract with special reference to skatole. Am. J. Clin. Nutr. 1979, 32, 173–178. [Google Scholar] [CrossRef]
- Wikoff, W.R.; Anfora, A.T.; Liu, J.; Schultz, P.G.; Lesley, S.A.; Peters, E.C.; Siuzdak, G. Metabolomics analysis reveals large effects of gut microflora on mammalian blood metabolites. Proc. Natl. Acad. Sci. USA 2009, 106, 3698–3703. [Google Scholar] [CrossRef] [PubMed][Green Version]
- Browne, C.A.; Clarke, G.; Dinan, T.G.; Cryan, J.F. An effective dietary method for chronic tryptophan depletion in two mouse strains illuminates a role for 5-HT in nesting behaviour. Neuropharmacology 2012, 62, 1903–1915. [Google Scholar] [CrossRef] [PubMed]
- El Aidy, S.; Kunze, W.; Bienenstock, J.; Kleerebezem, M. The microbiota and the gut-brain axis: Insights from the temporal and spatial mucosal alterations during colonisation of the germfree mouse intestine. Benef. Microbes. 2012, 3, 251–259. [Google Scholar] [CrossRef] [PubMed]
- Mardinoglu, A.; Shoaie, S.; Bergentall, M.; Ghaffari, P.; Zhang, C.; Larsson, E.; Backhed, F.; Nielsen, J. The gut microbiota modulates host amino acid and glutathione metabolism in mice. Mol. Syst. Biol. 2015, 11, 834. [Google Scholar] [CrossRef] [PubMed]
- Gao, J.; Xu, K.; Liu, H.; Liu, G.; Bai, M.; Peng, C.; Li, T.; Yin, Y. Impact of the Gut Microbiota on Intestinal Immunity Mediated by Tryptophan Metabolism. Front. Cell. Infect. Microbiol. 2018. [Google Scholar] [CrossRef][Green Version]
- Agus, A.; Planchais, J.; Sokol, H. Gut Microbiota Regulation of Tryptophan Metabolism in Health and Disease. Cell Host Microbe 2018, 23, 716–724. [Google Scholar] [CrossRef][Green Version]
- Smith, E.A.; Macfarlane, G.T. Dissimilatory amino Acid metabolism in human colonic bacteria. Anaerobe 1997, 3, 327–337. [Google Scholar] [CrossRef]
- Danaceau, J.P.; Anderson, G.M.; McMahon, W.M.; Crouch, D.J. A liquid chromatographic-tandem mass spectrometric method for the analysis of serotonin and related indoles in human whole blood. J. Anal. Toxicol. 2003, 27, 440–444. [Google Scholar] [CrossRef][Green Version]
- Rosas, H.D.; Doros, G.; Bhasin, S.; Thomas, B.; Gevorkian, S.; Malarick, K.; Matson, W.; Hersch, S.M. A systems-level “misunderstanding”: The plasma metabolome in Huntington’s disease. Ann. Clin. Transl. Neurol. 2015, 2, 756–768. [Google Scholar] [CrossRef]
- Huang, H.; Wang, H.; Sinz, M.; Zoeckler, M.; Staudinger, J.; Redinbo, M.R.; Teotico, D.G.; Locker, J.; Kalpana, G.V.; Mani, S. Inhibition of drug metabolism by blocking the activation of nuclear receptors by ketoconazole. Oncogene 2007, 26, 258–268. [Google Scholar] [CrossRef][Green Version]
- Cancilla, M.T.; He, M.M.; Viswanathan, N.; Simmons, R.L.; Taylor, M.; Fung, A.D.; Cao, K.; Erlanson, D.A. Discovery of an Aurora kinase inhibitor through site-specific dynamic combinatorial chemistry. Bioorg. Med. Chem. Lett. 2008, 18, 3978–3981. [Google Scholar] [CrossRef] [PubMed]
- Fodor, T.; Szanto, M.; Abdul-Rahman, O.; Nagy, L.; Der, A.; Kiss, B.; Bai, P. Combined Treatment of MCF-7 Cells with AICAR and Methotrexate, Arrests Cell Cycle and Reverses Warburg Metabolism through AMP-Activated Protein Kinase (AMPK) and FOXO1. PLoS ONE 2016, 11, e0150232. [Google Scholar] [CrossRef] [PubMed][Green Version]
- Rueden, C.T.; Schindelin, J.; Hiner, M.C.; DeZonia, B.E.; Walter, A.E.; Arena, E.T.; Eliceiri, K.W. ImageJ2: ImageJ for the next generation of scientific image data. BMC Bioinform. 2017, 18, 529. [Google Scholar] [CrossRef] [PubMed]
- Bai, P.; Bakondi, E.; Szabo, E.; Gergely, P.; Szabo, C.; Virag, L. Partial protection by poly (ADP-ribose) polymerase inhibitors from nitroxyl-induced cytotoxity in thymocytes. Free Radic. Biol. Med. 2001, 31, 1616–1623. [Google Scholar] [CrossRef]
- Szántó, M.; Brunyánszki, A.; Márton, J.; Vámosi, G.; Nagy, L.; Fodor, T.; Kiss, B.; Virag, L.; Gergely, P.; Bai, P. Deletion of PARP-2 induces hepatic cholesterol accumulation and decrease in HDL levels. Biochim. Biophys. Acta—Mol. Basis Dis. 2014, 1842, 594–602. [Google Scholar] [CrossRef][Green Version]
- Sári, Z.; Kovács, T.; Csonka, T.; Török, M.; Sebő, É.; Toth, J.; Tóth, D.; Mikó, E.; Kiss, B.; Szeőcs, D.; et al. Fecal expression of E. coli lysine decarboxylase (LdcC) is downregulated in E-cadherin negative lobular breast carcinoma. Physiol. Int. 2020. [Google Scholar] [CrossRef]
- Dai, Z.; Wu, Z.; Hang, S.; Zhu, W.; Wu, G. Amino acid metabolism in intestinal bacteria and its potential implications for mammalian reproduction. Mol. Hum. Reprod. 2015, 21, 389–409. [Google Scholar] [CrossRef][Green Version]
- Fiorillo, M.; Peiris-Pages, M.; Sanchez-Alvarez, R.; Bartella, L.; Di Donna, L.; Dolce, V.; Sindona, G.; Sotgia, F.; Cappello, A.R.; Lisanti, M.P. Bergamot natural products eradicate cancer stem cells (CSCs) by targeting mevalonate, Rho-GDI-signalling and mitochondrial metabolism. Biochim. Biophys. Acta 2018, 4, 30061–30066. [Google Scholar] [CrossRef]
- Nagy, L.; Marton, J.; Vida, A.; Kis, G.; Bokor, E.; Kun, S.; Gonczi, M.; Docsa, T.; Toth, A.; Antal, M.; et al. Glycogen phosphorylase inhibition improves beta cell function. Br. J. Pharmacol. 2018, 175, 301–319. [Google Scholar] [CrossRef][Green Version]
- Mabley, J.G.; Pacher, P.; Bai, P.; Wallace, R.; Goonesekera, S.; Virag, L.; Southan, G.J.; Szabo, C. Suppression of intestinal polyposis in Apcmin/+ mice by targeting the nitric oxide or poly(ADP-ribose) pathways. Mutat. Res. 2004, 548, 107–116. [Google Scholar] [CrossRef]
- Csonka, T.; Murnyák, B.; Szepesi, R.; Bencze, J.; Bognár, L.; Klekner, Á.; Hortobágyi, T. Assessment of candidate immunohistochemical prognostic markers of meningioma recurrence. Folia Neuropathologica 2016, 54, 114–126. [Google Scholar] [CrossRef] [PubMed][Green Version]
- Stenger, M. Calculating H-Score. Available online: http://www.ascopost.com/issues/april-10-2015/calculating-h-score/ (accessed on 1 July 2019).
- Lanczky, A.; Nagy, A.; Bottai, G.; Munkacsy, G.; Szabo, A.; Santarpia, L.; Gyorffy, B. miRpower: A web-tool to validate survival-associated miRNAs utilizing expression data from 2178 breast cancer patients. Breast Cancer Res. Treat. 2016, 160, 439–446. [Google Scholar] [CrossRef] [PubMed]
- Goldberg, A.A.; Beach, A.; Davies, G.F.; Harkness, T.A.; Leblanc, A.; Titorenko, V.I. Lithocholic bile acid selectively kills neuroblastoma cells, while sparing normal neuronal cells. Oncotarget 2011, 2, 761–782. [Google Scholar] [CrossRef] [PubMed][Green Version]
- Luo, M.; Shang, L.; Brooks, M.D.; Jiagge, E.; Zhu, Y.; Buschhaus, J.M.; Conley, S.; Fath, M.A.; Davis, A.; Gheordunescu, E.; et al. Targeting Breast Cancer Stem Cell State Equilibrium through Modulation of Redox Signaling. Cell. Metab. 2018, 28, 69–86. [Google Scholar] [CrossRef] [PubMed][Green Version]
- Pacher, P.; Beckman, J.S.; Liaudet, L. Nitric oxide and peroxynitrite in health and disease. Physiol. Rev. 2007, 87, 315–424. [Google Scholar] [CrossRef] [PubMed][Green Version]
- Szabo, C.; Ischiropoulos, H.; Radi, R. Peroxynitrite: Biochemistry, pathophysiology and development of therapeutics. Nat. Rev. Drug Discov. 2007, 6, 662–680. [Google Scholar] [CrossRef]
- Davila-Gonzalez, D.; Choi, D.S.; Rosato, R.R.; Granados-Principal, S.M.; Kuhn, J.G.; Li, W.F.; Qian, W.; Chen, W.; Kozielski, A.J.; Wong, H.; et al. Pharmacological Inhibition of NOS Activates ASK1/JNK Pathway Augmenting Docetaxel-Mediated Apoptosis in Triple-Negative Breast Cancer. Clin. Cancer Res. 2018, 24, 1152–1162. [Google Scholar] [CrossRef][Green Version]
- Pons, D.G.; Nadal-Serrano, M.; Torrens-Mas, M.; Valle, A.; Oliver, J.; Roca, P. UCP2 inhibition sensitizes breast cancer cells to therapeutic agents by increasing oxidative stress. Free Radic. Biol. Med. 2015, 86, 67–77. [Google Scholar] [CrossRef]
- Ozsvari, B.; Fiorillo, M.; Bonuccelli, G.; Cappello, A.R.; Frattaruolo, L.; Sotgia, F.; Trowbridge, R.; Foster, R.; Lisanti, M.P. Mitoriboscins: Mitochondrial-based therapeutics targeting cancer stem cells (CSCs), bacteria and pathogenic yeast. Oncotarget 2017, 8, 67457–67472. [Google Scholar] [CrossRef][Green Version]
- Bao, B.; Azmi, A.S.; Li, Y.; Ahmad, A.; Ali, S.; Banerjee, S.; Kong, D.; Sarkar, F.H. Targeting CSCs in tumor microenvironment: The potential role of ROS-associated miRNAs in tumor aggressiveness. Curr. Stem Cell Res. Ther. 2014, 9, 22–35. [Google Scholar] [CrossRef][Green Version]
- Tang, S.; Yang, L.; Tang, X.; Liu, M. The role of oxidized ATM in the regulation of oxidative stress-induced energy metabolism reprogramming of CAFs. Cancer Lett. 2014, 353, 133–144. [Google Scholar] [CrossRef] [PubMed]
- Fujii-Kuriyama, Y.; Mimura, J. Molecular mechanisms of AhR functions in the regulation of cytochrome P450 genes. Biochem. Biophysic. Res. Commun. 2005, 338, 311–317. [Google Scholar] [CrossRef] [PubMed]
- Migliaccio, A.; Castoria, G.; de Falco, A.; Bilancio, A.; Giovannelli, P.; Di Donato, M.; Marino, I.; Yamaguchi, H.; Appella, E.; Auricchio, F. Polyproline and Tat transduction peptides in the study of the rapid actions of steroid receptors. Steroids 2012, 77, 974–978. [Google Scholar] [CrossRef] [PubMed]
- Guarnieri, T. Aryl Hydrocarbon Receptor Connects Inflammation to Breast Cancer. Int. J. Mol. Sci. 2020, 21, 5264. [Google Scholar] [CrossRef]
- Kim, C.H. Immune regulation by microbiome metabolites. Immunology 2018, 154, 220–229. [Google Scholar] [CrossRef]
- Smith, A.; Pierre, J.F.; Makowski, L.; Tolley, E.; Lyn-Cook, B.; Lu, L.; Vidal, G.; Starlard-Davenport, A. Distinct microbial communities that differ by race, stage, or breast-tumor subtype in breast tissues of non-Hispanic Black and non-Hispanic White women. Sci. Rep. 2019, 9, 11940. [Google Scholar] [CrossRef][Green Version]
- Banerjee, S.; Wei, Z.; Tan, F.; Peck, K.N.; Shih, N.; Feldman, M.; Rebbeck, T.R.; Alwine, J.C.; Robertson, E.S. Distinct microbiological signatures associated with triple negative breast cancer. Sci. Rep. 2015, 5, 15162. [Google Scholar] [CrossRef] [PubMed]
- Xuan, C.; Shamonki, J.M.; Chung, A.; Dinome, M.L.; Chung, M.; Sieling, P.A.; Lee, D.J. Microbial dysbiosis is associated with human breast cancer. PLoS ONE 2014, 9, e83744. [Google Scholar] [CrossRef][Green Version]
- Fernandez, M.F.; Reina-Perez, I.; Astorga, J.M.; Rodriguez-Carrillo, A.; Plaza-Diaz, J.; Fontana, L. Breast Cancer and Its Relationship with the Microbiota. Int. J. Environ. Res. Public Health 2018, 15, 1747. [Google Scholar] [CrossRef][Green Version]
- Wilmanski, T.; Rappaport, N.; Earls, J.C.; Magis, A.T.; Manor, O.; Lovejoy, J.; Omenn, G.S.; Hood, L.; Gibbons, S.M.; Price, N.D. Blood metabolome predicts gut microbiome alpha-diversity in humans. Nat. Biotechnol. 2019, 37, 1217–1228. [Google Scholar] [CrossRef]
- Urbaniak, C.; Cummins, J.; Brackstone, M.; Macklaim, J.M.; Gloor, G.B.; Baban, C.K.; Scott, L.; O’Hanlon, D.M.; Burton, J.P.; Francis, K.P.; et al. Microbiota of human breast tissue. Appl. Environ. Microbiol. 2014, 80, 3007–3014. [Google Scholar] [CrossRef][Green Version]
- Chan, A.A.; Bashir, M.; Rivas, M.N.; Duvall, K.; Sieling, P.A.; Pieber, T.R.; Vaishampayan, P.A.; Love, S.M.; Lee, D.J. Characterization of the microbiome of nipple aspirate fluid of breast cancer survivors. Sci. Rep. 2016, 6, 28061. [Google Scholar] [CrossRef][Green Version]
- Hieken, T.J.; Chen, J.; Hoskin, T.L.; Walther-Antonio, M.; Johnson, S.; Ramaker, S.; Xiao, J.; Radisky, D.C.; Knutson, K.L.; Kalari, K.R.; et al. The Microbiome of Aseptically Collected Human Breast Tissue in Benign and Malignant Disease. Sci. Rep. 2016, 6, 30751. [Google Scholar] [CrossRef]
- Wang, H.; Altemus, J.; Niazi, F.; Green, H.; Calhoun, B.C.; Sturgis, C.; Grobmyer, S.R.; Eng, C. Breast tissue, oral and urinary microbiomes in breast cancer. Oncotarget 2017, 8, 88122–88138. [Google Scholar] [CrossRef][Green Version]
- Costantini, L.; Magno, S.; Albanese, D.; Donati, C.; Molinari, R.; Filippone, A.; Masetti, R.; Merendino, N. Characterization of human breast tissue microbiota from core needle biopsies through the analysis of multi hypervariable 16S-rRNA gene regions. Sci. Rep. 2018, 8, 16893. [Google Scholar] [CrossRef][Green Version]
- Meng, S.; Chen, B.; Yang, J.; Wang, J.; Zhu, D.; Meng, Q.; Zhang, L. Study of Microbiomes in Aseptically Collected Samples of Human Breast Tissue Using Needle Biopsy and the Potential Role of in situ Tissue Microbiomes for Promoting Malignancy. Front. Oncol. 2018, 8, 318. [Google Scholar] [CrossRef][Green Version]
- Viaud, S.; Saccheri, F.; Mignot, G.; Yamazaki, T.; Daillere, R.; Hannani, D.; Enot, D.P.; Pfirschke, C.; Engblom, C.; Pittet, M.J.; et al. The intestinal microbiota modulates the anticancer immune effects of cyclophosphamide. Science 2013, 342, 971–976. [Google Scholar] [CrossRef][Green Version]
- Xie, W.; Huang, Y.; Xie, W.; Guo, A.; Wu, W. Bacteria peptidoglycan promoted breast cancer cell invasiveness and adhesiveness by targeting toll-like receptor 2 in the cancer cells. PLoS ONE 2010, 5, e10850. [Google Scholar] [CrossRef][Green Version]
- Zelante, T.; Iannitti, R.G.; Cunha, C.; De Luca, A.; Giovannini, G.; Pieraccini, G.; Zecchi, R.; D’Angelo, C.; Massi-Benedetti, C.; Fallarino, F.; et al. Tryptophan catabolites from microbiota engage aryl hydrocarbon receptor and balance mucosal reactivity via interleukin-22. Immunity 2013, 39, 372–385. [Google Scholar] [CrossRef][Green Version]
- Venkatesh, M.; Mukherjee, S.; Wang, H.; Li, H.; Sun, K.; Benechet, A.P.; Qiu, Z.; Maher, L.; Redinbo, M.R.; Phillips, R.S.; et al. Symbiotic bacterial metabolites regulate gastrointestinal barrier function via the xenobiotic sensor PXR and Toll-like receptor 4. Immunity 2014, 41, 296–310. [Google Scholar] [CrossRef][Green Version]
- Lamas, B.; Richard, M.L.; Leducq, V.; Pham, H.P.; Michel, M.L.; Da Costa, G.; Bridonneau, C.; Jegou, S.; Hoffmann, T.W.; Natividad, J.M.; et al. CARD9 impacts colitis by altering gut microbiota metabolism of tryptophan into aryl hydrocarbon receptor ligands. Nat. Med. 2016, 22, 598–605. [Google Scholar] [CrossRef] [PubMed]
- Sonner, J.K.; Keil, M.; Falk-Paulsen, M.; Mishra, N.; Rehman, A.; Kramer, M.; Deumelandt, K.; Rowe, J.; Sanghvi, K.; Wolf, L.; et al. Dietary tryptophan links encephalogenicity of autoreactive T cells with gut microbial ecology. Nat. Commun. 2019, 10, 4877. [Google Scholar] [CrossRef] [PubMed]
- Zhang, L.; Nichols, R.G.; Patterson, A.D. The aryl hydrocarbon receptor as a moderator of host-microbiota communication. Curr. Opin. Toxicol. 2017, 2, 30–35. [Google Scholar] [CrossRef] [PubMed][Green Version]
- Sári, Z.; Mikó, E.; Kovács, T.; Boratkó, A.; Ujlaki, G.; Jankó, L.; Kiss, B.; Uray, K.; Bai, P. Indoxyl-sulphate, a metabolite of the microbiome, has cytostatic properties in breast cancer by activating AHR and PXR receptors and inducing oxidative stress. Cancers 2020. under evaluation. [Google Scholar]
- Smolková, K.; Mikó, E.; Kovács, T.; Leguina-Ruzzi, A.; Sipos, A.; Bai, P. NRF2 in regulating cancer metabolism. Antioxid. Redox Signal. 2020. [Google Scholar] [CrossRef][Green Version]
- De Francesco, E.M.; Sotgia, F.; Lisanti, M.P. Cancer stem cells (CSCs): Metabolic strategies for their identification and eradication. Biochem. J. 2018, 475, 1611–1634. [Google Scholar] [CrossRef][Green Version]
- Trachootham, D.; Alexandre, J.; Huang, P. Targeting cancer cells by ROS-mediated mechanisms: A radical therapeutic approach? Nat. Rev. Drug Discov. 2009, 8, 579–591. [Google Scholar] [CrossRef]
- Kai, K.; Arima, Y.; Kamiya, T.; Saya, H. Breast cancer stem cells. Breast Cancer 2010, 17, 80–85. [Google Scholar] [CrossRef]
- Vera-Ramirez, L.; Sanchez-Rovira, P.; Ramirez-Tortosa, M.C.; Ramirez-Tortosa, C.L.; Granados-Principal, S.; Lorente, J.A.; Quiles, J.L. Free radicals in breast carcinogenesis, breast cancer progression and cancer stem cells. Biological bases to develop oxidative-based therapies. Crit. Rev. Oncol. Hematol. 2011, 80, 347–368. [Google Scholar] [CrossRef]
- Yang, J.; Ding, C.; Dai, X.; Lv, T.; Xie, T.; Zhang, T.; Gao, W.; Gong, J.; Zhu, W.; Li, N.; et al. Soluble Dietary Fiber Ameliorates Radiation-Induced Intestinal Epithelial-to-Mesenchymal Transition and Fibrosis. JPEN J. Parenter. Enteral. Nutr. 2017, 41, 1399–1410. [Google Scholar] [CrossRef]
- Hardie, D.G. Molecular Pathways: Is AMPK a Friend or a Foe in Cancer? Clin. Cancer Res. 2015, 21, 3836–3840. [Google Scholar] [CrossRef][Green Version]
- Cheng, J.; Shuai, X.; Gao, J.; Cai, M.; Wang, G.; Tao, K. Prognostic significance of AMPK in human malignancies: A meta-analysis. Oncotarget 2016, 7, 75739–75748. [Google Scholar] [CrossRef][Green Version]
- Auslander, N.; Yizhak, K.; Weinstock, A.; Budhu, A.; Tang, W.; Wang, X.W.; Ambs, S.; Ruppin, E. A joint analysis of transcriptomic and metabolomic data uncovers enhanced enzyme-metabolite coupling in breast cancer. Sci. Rep. 2016, 6, 29662. [Google Scholar] [CrossRef] [PubMed][Green Version]
- Tang, X.; Lin, C.C.; Spasojevic, I.; Iversen, E.S.; Chi, J.T.; Marks, J.R. A joint analysis of metabolomics and genetics of breast cancer. Breast Cancer Res. 2014, 16, 415. [Google Scholar] [CrossRef] [PubMed][Green Version]
- Newman, T.M.; Vitolins, M.Z.; Cook, K.L. From the Table to the Tumor: The Role of Mediterranean and Western Dietary Patterns in Shifting Microbial-Mediated Signaling to Impact Breast Cancer Risk. Nutrients 2019, 11, 2565. [Google Scholar] [CrossRef] [PubMed][Green Version]
- Chiba, A.; Bawaneh, A.; Velazquez, C.; Clear, K.Y.J.; Wilson, A.S.; Howard-McNatt, M.; Levine, E.A.; Levi-Polyachenko, N.; Yates-Alston, S.A.; Diggle, S.P.; et al. Neoadjuvant Chemotherapy Shifts Breast Tumor Microbiota Populations to Regulate Drug Responsiveness and the Development of Metastasis. Mol. Cancer Res. 2019, 18, 1541–7786. [Google Scholar] [CrossRef] [PubMed][Green Version]
Gene Symbol | Murine Forward Primer (5′–3′) | Murine Reverse Primer (5′–3′) |
CAT | CCTTCAAGTTGGTTAATGCAGA | CAAGTTTTTGATGCCCTGGT |
VIM | CTCCAGAGAGAGGAAGCCGAAAG | CCTGGATCTCTTCATCGTGCAGT |
FgfBp1 | CAAGGTCCAAGAAGCTGTCTCCA | AGCTCCAAGATTCCCCACAGAAC |
Cyclophilin A | TGGAGAGCACCAAGACAGACA | TGCCGGAGTCGACAATGAT |
36B4 | AGATTCGGGATATGCTGTTGG | AAAGCCTGGAAGAAGGAGGTC |
Gene Symbol | Human Forward Primer (5′–3′) | Human Reverse Primer (5′–3′) |
AHR | TTGAACCATCCCCATACCCCAC | GAGGTTCTGGCTGGCACTGATA |
PXR | AGTGAAGGTTCCCGAGGACATG | TTGTCACAGAGCATACCCAGCA |
Cyclophilin A | GTCTCCTTTGAGCTGTTTGCAGAC | CTTGCCACCAGTGCCATTATG |
36B4 | CCATTGAAATCCTGAGTGATGTG | GTCGAACACCTGCTGGATGAC |
Gene Symbol | Forward Primer (5′–3′) | Reverse Primer (5′–3′) |
---|---|---|
Alistipes shahii | GCCTCGAAGACGATCAAGGAGAT | TCGAACATGATGCTGAACGACAT |
Providencia rettegri | CGTTTACGTGAGGGAGGGATTTC | ACCGCACGAACACCAGATTCTAA |
Bacteriodes xylanisolvens | AACTGGAAATCCCGTTCAAAGGA | GTACGGGTTTGCCGTATTTGTCA |
Clostridium sp. | GATGGAACGTCCAAACACTTTCG | ATATTTTCCGCCTTCCGGAACTT |
Antibody | Dilution | Vendor |
---|---|---|
4-HNE | 1:1000 | Abcam (ab46545) |
Nitrotyrosine | 1:1000 | Millipore (06–284) |
iNOS | 1:1000 | Novus (NB300–605) |
NRF2 | 1:1000 | Abcam (ab31163) |
LC3 | 1:1000 | Cell Signaling (#13082) |
Phospho-AMPKα (Thr172) | 1:1000 | Cell Signaling (#2535) |
AMPKα | 1:1000 | Cell Signaling (#5832) |
Phospho-ACC (Ser79) | 1:1000 | Cell Signaling (#3661) |
ACC | 1:1000 | Cell Signaling (#3676) |
FOXO1 | 1:1000 | Cell Signaling (#9454) |
PGC1β | 1:1000 | Abcam (ab176328) |
E-cadherin | 1:1000 | Cell signaling (#3195) |
Vimentin | 1:1000 | Cell signaling (#5741) |
Snail | 1:1000 | Cell signaling (#3879) |
β-Catenin | 1:1000 | Sigma-Aldrich (C7082) |
β-Actin | 1:20000 | Sigma-Aldrich (A3854) |
E. coli TnaA | 1:2000 | Assaypro (33517–05111) |
β-Actin | 1:20000 | Sigma-Aldrich (A3854) |
Anti-rabbit IgG, HRP-linked antibody | 1:2000 | Cell Signaling (#7074) |
Anti-Mouse IgG, Peroxidase antibody | 1:2000 | Sigma-Aldrich (A9044) |
Antibody | Dilution | Vendor |
---|---|---|
PXR | 1:1000 | Thermo Fisher Scientific (PA5–72551) |
AHR | 1:200 | Sigma-Aldrich (HPA029722) |
AHR (202820_at) | HR (Hazard Ratio) | p-Value (Log Rank Test) |
All breast Cancers N = 3951 | 0.91 | 0.079 |
ER(+), N = 3082 | 0.87 | 0.037 |
ER(−), N = 869 | 0.96 | 0.68 |
PR(+), N = 589 | 0.72 | 0.068 |
PR(−), N = 549 | 0.87 | 0.35 |
HER2(+), N = 252 | 0.97 | 0.87 |
HER2(−), N = 800 | 0.71 | 0.012 |
ER(+), PR(+), HER2(+), N = 76 | 1.15 | 0.78 |
ER(−), PR(−), HER2(−), N = 198 | 0.84 | 0.48 |
ER(+), PR(+), N = 577 | 0.67 | 0.029 |
ER(−), PR(−), N = 298 | 0.84 | 0.39 |
ER(−), PR(−), HER2(−) N = 198 | 0.84 | 0.48 |
ER(+), Luminal A, N = 1933 | 0.87 | 0.11 |
ER(+), Luminal A, Grade 1, N = 267 | 0.65 | 0.17 |
ER(+), Luminal B, N = 1149 | 1.16 | 0.12 |
ER(+), Luminal B, Grade 1 N = 56 | 1.45 | 0.55 |
Grade 1, N = 345 | 0.67 | 0.13 |
Grade 2, N = 901 | 0.67 | 0.001 |
Grade 3, N = 903 | 0.97 | 0.78 |
Basal subtype, N = 618 | 0.95 | 0.67 |
Luminal A, N = 1933 | 0.87 | 0.11 |
Luminal B, N = 1149 | 1,16 | 0.12 |
ER(+), HER2(+), N = 156 | 1.33 | 0.36 |
ER(−), HER2(+), N = 96 | 0.67 | 0.21 |
ER(+), PR(+), Lymph(+) N = 344 | 0.61 | 0.026 |
ER(+), PR(+), Lymph(−) N = 228 | 0.86 | 0.64 |
ER(−), PR(−), Lymph(+) N = 127 | 0.85 | 0.54 |
ER(−), PR(−), Lymph(−) N = 167 | 0.68 | 0.21 |
ER(+), Luminal A, Grade 2, N = 567 | 0.69 | 0.027 |
ER(+), Luminal B, Grade 2 N = 253 | 0.76 | 0.21 |
PXR (207202_s_at) | HR (Hazard Ratio) | p-Value (Log Rank Test) |
All breast Cancers N = 3951 | 0.8 | 0.00055 |
ER(+), N = 3082 | 0.84 | 0.0073 |
ER(−), N = 869 | 0.74 | 0.0056 |
PR(+), N = 589 | 1.02 | 0.91 |
PR(−), N = 549 | 0.9 | 0.49 |
HER2(+), N = 252 | 0.93 | 0.73 |
HER2(−), N = 800 | 1.01 | 0.93 |
ER(+), PR(+), HER2(+), N = 76 | 1.31 | 0.61 |
ER(−), PR(−), HER2(−), N = 198 | 1.08 | 0.75 |
ER(+), PR(+), N = 577 | 0.97 | 0.89 |
ER(−), PR(−), N = 298 | 0.93 | 0.73 |
ER(−), PR(−), HER2(−) N = 198 | 1.048 | 0.75 |
ER(+), Luminal A, N = 1933 | 0.77 | 0.0031 |
ER(+), Luminal A, Grade 1, N = 267 | 1.04 | 0.9 |
ER(+), Luminal B, N = 1149 | 0.81 | 0.031 |
ER(+), Luminal B, Grade1 N = 56 | 0.77 | 0.66 |
Grade 1, N = 345 | 0.97 | 0.92 |
Grade 2, N = 901 | 1.07 | 0.56 |
Grade 3, N = 903 | 0.98 | 0.83 |
Basal subtype, N = 618 | 0.78 | 0.053 |
Luminal A, N = 1933 | 0.77 | 0.0031 |
Luminal B, N = 1149 | 0.81 | 0.031 |
ER(+), HER2(+), N = 156 | 1.41 | 0.28 |
ER(−), HER2(+), N = 96 | 0.63 | 0.15 |
ER(+), PR(+), Lymph(+) N = 344 | 0.96 | 0.85 |
ER(+), PR(+), Lymph(−) N = 228 | 0.84 | 0.6 |
ER(−), PR(−), Lymph(+) N = 127 | 0.95 | 0.86 |
ER(−), PR(−), Lymph(−) N = 167 | 1.02 | 0.95 |
ER(+), Luminal A, Grade 2, N = 567 | 1.06 | 0.73 |
ER(+), Luminal B, Grade2 N = 253 | 1.23 | 0.34 |
© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Share and Cite
Sári, Z.; Mikó, E.; Kovács, T.; Jankó, L.; Csonka, T.; Lente, G.; Sebő, É.; Tóth, J.; Tóth, D.; Árkosy, P.; Boratkó, A.; Ujlaki, G.; Török, M.; Kovács, I.; Szabó, J.; Kiss, B.; Méhes, G.; Goedert, J.J.; Bai, P. Indolepropionic Acid, a Metabolite of the Microbiome, Has Cytostatic Properties in Breast Cancer by Activating AHR and PXR Receptors and Inducing Oxidative Stress. Cancers 2020, 12, 2411. https://doi.org/10.3390/cancers12092411
Sári Z, Mikó E, Kovács T, Jankó L, Csonka T, Lente G, Sebő É, Tóth J, Tóth D, Árkosy P, Boratkó A, Ujlaki G, Török M, Kovács I, Szabó J, Kiss B, Méhes G, Goedert JJ, Bai P. Indolepropionic Acid, a Metabolite of the Microbiome, Has Cytostatic Properties in Breast Cancer by Activating AHR and PXR Receptors and Inducing Oxidative Stress. Cancers. 2020; 12(9):2411. https://doi.org/10.3390/cancers12092411
Chicago/Turabian StyleSári, Zsanett, Edit Mikó, Tünde Kovács, Laura Jankó, Tamás Csonka, Gréta Lente, Éva Sebő, Judit Tóth, Dezső Tóth, Péter Árkosy, Anita Boratkó, Gyula Ujlaki, Miklós Török, Ilona Kovács, Judit Szabó, Borbála Kiss, Gábor Méhes, James J. Goedert, and Péter Bai. 2020. "Indolepropionic Acid, a Metabolite of the Microbiome, Has Cytostatic Properties in Breast Cancer by Activating AHR and PXR Receptors and Inducing Oxidative Stress" Cancers 12, no. 9: 2411. https://doi.org/10.3390/cancers12092411