Journal List > J Vet Sci > v.21(2) > 1144498

Valko-Rokytovská, Očenáš, Salayová, Titková, and Kostecká: Specific urinary metabolites in canine mammary gland tumors

Abstract

The identification of biomarkers that distinguish diseased from healthy individuals is of great interest in human and veterinary fields. In this research area, a metabolomic approach and its related statistical analyses can be useful for biomarker determination and allow non-invasive discrimination of healthy volunteers from breast cancer patients. In this study, we focused on the most common canine neoplasm, mammary gland tumor, and herein, we describe a simple method using ultra-high-performance liquid chromatography to determine the levels of tyrosine and its metabolites (epinephrine, 3,4-dihydroxy-L-phenylalanine, 3,4-dihydroxyphenylacetic acid, and vanillylmandelic acid), tryptophan and its metabolites (5-hydroxyindolacetic acid, indoxyl sulfate, serotonin, and kynurenic acid) in canine mammary cancer urine samples. Our results indicated significantly increased concentrations of three tryptophan metabolites, 5-hydroxyindolacetic acid (p < 0.001), serotonin, indoxyl sulfate (p < 0.01), and kynurenic acid (p < 0.05), and 2 tyrosine metabolites, 3,4-dihydroxy-L-phenylalanine (p < 0.001), and epinephrine (p < 0.05) in urine samples from the mammary gland tumor group compared to concentrations in urine samples from the healthy group. The results indicate that select urinary tyrosine and tryptophan metabolites may be useful as non-invasive diagnostic markers as well as in developing a therapeutic strategy for canine mammary gland tumors.

References

1. Peña L, Gama A, Goldschmidt MH, Abadie J, Benazzi C, Castagnaro M, Díez L, Gärtner F, Hellmén E, Kiupel M, Millán Y, Miller MA, Nguyen F, Poli A, Sarli G, Zappulli V, de las Mulas JM. Canine mammary tumors: a review and consensus of standard guidelines on epithelial and myoepithelial phenotype markers, HER2, and hormone receptor assessment using immunohistochemistry. Vet Pathol. 2014; 51:127–145.
2. Sorenmo K. Canine mammary gland tumors. Vet Clin North Am Small Anim Pract. 2003; 33:573–596.
crossref
3. Concannon PW, Spraker TR, Casey HW, Hansel W. Gross and histopathologic effects of medroxyprogesterone acetate and progesterone on the mammary glands of adult beagle bitches. Fertil Steril. 1981; 36:373–387.
crossref
4. Sorenmo KU, Kristiansen VM, Cofone MA, Shofer FS, Breen AM, Langeland M, Mongil CM, Grondahl AM, Teige J, Goldschmidt MH. Canine mammary gland tumours; a histological continuum from benign to malignant; clinical and histopathological evidence. Vet Comp Oncol. 2009; 7:162–172.
crossref
5. Moe L. Population-based incidence of mammary tumours in some dog breeds. J Reprod Fertil Suppl. 2001; 57:439–443.
6. Nguyen F, Peña L, Ibisch C, Loussouarn D, Gama A, Rieder N, Belousov A, Campone M, Abadie J. Canine invasive mammary carcinomas as models of human breast cancer. Part 1: natural history and prognostic factors. Breast Cancer Res Treat. 2018; 167:635–648.
crossref
7. Johnson CH, Manna SK, Krausz KW, Bonzo JA, Divelbiss RD, Hollingshead MG, Gonzalez FJ. Global metabolomics reveals urinary biomarkers of breast cancer in a mcf-7 xenograft mouse model. Metabolites. 2013; 3:658–672.
crossref
8. Wu G. Amino acids: metabolism, functions, and nutrition. Amino Acids. 2009; 37:1–17.
crossref
9. Wiggins T, Kumar S, Markar SR, Antonowicz S, Hanna GB. Tyrosine, phenylalanine, and tryptophan in gastroesophageal malignancy: a systematic review. Cancer Epidemiol Biomarkers Prev. 2015; 24:32–38.
crossref
10. Oto J, Suzue A, Inui D, Fukuta Y, Hosotsubo K, Torii M, Nagahiro S, Nishimura M. Plasma proinflammatory and anti-inflammatory cytokine and catecholamine concentrations as predictors of neurological outcome in acute stroke patients. J Anesth. 2008; 22:207–212.
crossref
11. Heng B, Lim CK, Lovejoy DB, Bessede A, Gluch L, Guillemin GJ. Understanding the role of the kynurenine pathway in human breast cancer immunobiology. Oncotarget. 2016; 7:6506–6520.
crossref
12. Kuo TR, Chen JS, Chiu YC, Tsai CY, Hu CC, Chen CC. Quantitative analysis of multiple urinary biomarkers of carcinoid tumors through gold-nanoparticle-assisted laser desorption/ionization time-of-flight mass spectrometry. Anal Chim Acta. 2011; 699:81–86.
crossref
13. Chung KT, Gadupudi GS. Possible roles of excess tryptophan metabolites in cancer. Environ Mol Mutagen. 2011; 52:81–104.
crossref
14. Mulder EJ, Anderson GM, Kemperman RF, Oosterloo-Duinkerken A, Minderaa RB, Kema IP. Urinary excretion of 5-hydroxyindoleacetic acid, serotonin and 6-sulphatoxymelatonin in normoserotonemic and hyperserotonemic autistic individuals. Neuropsychobiology. 2010; 61:27–32.
crossref
15. Porto-Figueira P, Pereira JA, Câmara JS. Exploring the potential of needle trap microextraction combined with chromatographic and statistical data to discriminate different types of cancer based on urinary volatomic biosignature. Anal Chim Acta. 2018; 1023:53–63.
crossref
16. Chen Y, Zhang R, Song Y, He J, Sun J, Bai J, An Z, Dong L, Zhan Q, Abliz Z. RRLC-MS/MS-based metabonomics combined with in-depth analysis of metabolic correlation network: finding potential biomarkers for breast cancer. Analyst (Lond). 2009; 134:2003–2011.
crossref
17. Cascino A, Cangiano C, Ceci F, Franchi F, Mineo T, Mulieri M, Muscaritoli M, Rossi Fanelli F. Increased plasma free tryptophan levels in human cancer: a tumor related effect? Anticancer Res. 1991; 11:1313–1316.
18. Valko-Rokytovská M, Očenáš P, Salayová A, Kostecká Z. New developed UHPLC method for selected urine metabolites. J Chromatogr Sep Tech. 2018; 9:1000404.
crossref
19. Nam H, Chung BC, Kim Y, Lee K, Lee D. Combining tissue transcriptomics and urine metabolomics for breast cancer biomarker identification. Bioinformatics. 2009; 25:3151–3157.
crossref
20. Mishra P, Ambs S. Metabolic signatures of human breast cancer. Mol Cell Oncol. 2015; 2:e992217.
crossref
21. Prendergast GC. Cancer: why tumours eat tryptophan. Nature. 2011; 478:192–194.
22. Jose J, Tavares CD, Ebelt ND, Lodi A, Edupuganti R, Xie X, Devkota AK, Kaoud TS, Van Den Berg CL, Anslyn EV, Tiziani S, Bartholomeusz C, Dalby KN. Serotonin analogues as inhibitors of breast cancer cell growth. ACS Med Chem Lett. 2017; 8:1072–1076.
crossref
23. Miller AG, Brown H, Degg T, Allen K, Keevil BG. Measurement of plasma 5-hydroxyindole acetic acid by liquid chromatography tandem mass spectrometry–comparison with HPLC methodology. J Chromatogr B Analyt Technol Biomed Life Sci. 2010; 878:695–699.
crossref
24. Yamaguchi J, Tanaka T, Inagi R. Effect of AST-120 in chronic kidney disease treatment: still a controversy? Nephron. 2017; 135:201–206.
25. Sagan D, Kocki T, Patel S, Kocki J. Utility of kynurenic acid for non-invasive detection of metastatic spread to lymph nodes in non-small cell lung cancer. Int J Med Sci. 2015; 12:146–153.
crossref
26. Xie Z, Lorkiewicz P, Riggs DW, Bhatnagar A, Srivastava S. Comprehensive, robust, and sensitive UPLC-MS/MS analysis of free biogenic monoamines and their metabolites in urine. J Chromatogr B Analyt Technol Biomed Life Sci. 2018; 1099:83–91.
crossref
27. Muthuswamy R, Okada NJ, Jenkins FJ, McGuire K, McAuliffe PF, Zeh HJ, Bartlett DL, Wallace C, Watkins S, Henning JD, Bovbjerg DH, Kalinski P. Epinephrine promotes COX-2-dependent immune suppression in myeloid cells and cancer tissues. Brain Behav Immun. 2017; 62:78–86.
crossref
28. Barollo S, Bertazza L, Watutantrige-Fernando S, Censi S, Cavedon E, Galuppini F, Pennelli G, Fassina A, Citton M, Rubin B, Pezzani R, Benna C, Opocher G, Iacobone M, Mian C. Overexpression of L-Type amino acid transporter 1 (LAT1) and 2 (LAT2): Novel markers of neuroendocrine tumors. PLoS One. 2016; 11:e0156044.
crossref
29. Zhang A, Sun H, Wang P, Han Y, Wang X. Recent and potential developments of biofluid analyses in metabolomics. J Proteomics. 2012; 75:1079–1088.
crossref
30. McCartney A, Vignoli A, Biganzoli L, Love R, Tenori L, Luchinat C, Di Leo A. Metabolomics in breast cancer: a decade in review. Cancer Treat Rev. 2018; 67:88–96.
crossref

Fig. 1.
Urinary metabolite to creatinine ratios in mammary gland cancer and healthy control dogs. Horizontal lines represent median values. TYR, tyrosine; E, epinephrine; L-DOPA, 3,4-dihydroxy-L-phenylalanine; DOPAC, 3,4-dihydroxyphenylacetic acid; VMA, vanillylmandelic acid; TRP, tryptophan; 5-HIAA, 5-hydroxyindolacetic acid; IS, indoxyl sulfate; 5-HT, serotonin; KYNA, kynurenic acid.
jvs-21-e23f1.tif
Table 1.
Morphological characteristics of mammary gland tumors in patients (n = 14)
Histopathological type Stage Grade Size (cm) Consistency Localization Age (yr)
Adenocarcinoma I II 3 × 4 × 3 Solid M3, 4 – right side 13
Adenocarcinoma I III 3 × 2 × 2 Solid M3, 4, 5 – bilateral 16
Adenocarcinoma I III 3 × 2 × 2 Solid M4, 5 – bilateral 9
Adenocarcinoma I III 3 × 2 × 2 Solid M3, 4, 5 – bilateral 11
Adenocarcinoma II III 2 × 3 × 2 Solid M4, 5 – bilateral 9
Adenocarcinoma II III 1 × 1 × 1 Solid M2 – left side 14
Adenocarcinoma III III 10 × 5 × 6 Solid M3, 4, 5 – bilateral 6
Cystic papillar adenocarcinoma I I 1 × 1 × 1 Solid M3 – left side 10
Cystic papillar adenocarcinoma I III 0.5 (diameter) Solid M4 – left side 7
Fibrosarcoma III III 10 × 10 × 10 Solid M4 – left side 10
Low differentiated carcinoma III III 10 × 10 × 3 Solid M5 – right side 7
Mixed carcinoma (with osteoid and myxoid tissue) II III 2 × 2 × 2 Elastic M5 – right side 9
Mixed tumor II II 2 × 2 × 2 Elastic M2 – right side 6
Necrotizing carcinoma III III 3 × 4 × 4 Solid M3, 4, 5 – bilateral 6
Table 2.
Chromatographic parameters for urine metabolites derived via DAD or FLD
Detection Metabolite Retention time (min) Regression equation Standard curve linearity (R2)
DAD Creatinine 0.717 y = 0.3889x 0.9997
  DOPAC 6.917 y = 0.6198x 0.9997
  KYNA 9.427 y = 1.0333x 0.9998
FLD E 1.039 y = 38550.0444x 0.9991
  L-DOPA 1.599 y = 16747.3489x 0.9991
  TYR 2.425 y = 4590.4682x 0.9988
  VMA 3.762 y = 2118.4295x 0.9985
  5-HT 4.139 y = 658758.7562x 0.9994
  IS 6.752 y = 183019.6362x 0.9993
  TRP 7.485 y = 241663.4940x 0.9990
  5-HIAA 8.665 y = 17127.7056x 0.9993

DAD, diode array detector; FLD, fluorescence detector; DOPAC, 3,4-dihydroxyphenylacetic acid; KYNA, kynurenic acid; E, epinephrine; L-DOPA, 3,4-dihydroxy-L-phenylalanine; TYR, tyrosine; VMA, vanillylmandelic acid; 5-HT, serotonin; IS, indoxyl sulfate; TRP, tryptophan; 5-HIAA, 5-hydroxyindolacetic acid.

Table 3.
Levels of metabolites in the urine of study groups as determined by UHPLC and presented as median and interquartile range values (expressed as µmol/mmol creatinine)
Metabolite Canine mammary gland tumor (n = 14) Healthy control (n = 16)
Median Interquartile range Median Interquartile range
TYR 7.85 7.32 5.50 4.98
  p = 0.1079      
E 30.47 34.27 0.37 0.35
  p = 0.0303*      
L-DOPA 40.96 32.95 3.53 3.74
  p = 0.0003***      
DOPAC 2.39 6.61 4.78 5.78
  p = 0.4848      
VMA 2.50 3.35 4.27 3.07
  p = 0.5167      
TRP 1.20 1.08 1.51 0.82
  p = 0.3540      
5-HIAA 9.83 18.87 2.02 4.11
  p = 0.0003***      
IS 31.68 16.08 9.39 11.99
  p = 0.0091**      
5-HT 0.45 15.24 0.02 0.06
  p = 0.0019**      
KYNA 47.97 66.89 26.99 41.40
  p = 0.0227*      

The p value of Mann-Whitney U test of urine metabolites in canine mammary gland tumor patients versus healthy control. UHPLC, ultra-high-performance liquid chromatography; TYR, tyrosine; E, epinephrine; L-DOPA, 3,4-dihydroxy-L-phenylalanine; DOPAC, 3,4-dihydroxyphenylacetic acid; VMA, vanillylmandelic acid; TRP, tryptophan; 5-HIAA, 5-hydroxyindolacetic acid; IS, indoxyl sulfate; 5-HT, serotonin; KYNA, kynurenic acid.

* Correlation is significant at the 0.05 level;

** Correlation is significant at the 0.01 level;

*** Correlation is significant at the 0.001 level.

TOOLS
Similar articles