Metabolomics: a promising diagnostic and therapeutic implement for breast cancer

Figures & data

Table 1 Molecular subtypes of BC based on metabolomics

Category	Biomarker	Sample	Alteration	Ref
Subtype
HER2-positive	Carnitine, lysophosphatidylcholine (20:4), proline, valine, and 2-octenedioic acid	plasma	up	^Citation38
HER2-negative	-
ER-positive	Glycochenodeoxycholic acid	plasma	up	^Citation38
Alanine, lysophosphatidylcholine (16:1), valine and 2-octenedioic acid.	down
	Glutamine biosynthesis and glutamine secretion	cell	up	^Citation39
	4-aminobutyrate aminotransferase expression	tissue	down	^Citation40
ER-negative	Serine metabolism and glutamine utilization	cell	up	^Citation39
	Beta-alanine	Tissue	Up	^Citation40
Triple-negative	De novo lipid synthesis	Cell	Down	^Citation42
Metabolism of triacylglycerols (TAGs)	Up
Reclassification
Breast cancer cells		Cell		^Citation43
MDA-MB-468 and MCF7	^13C-aspartate production from [U^13C]-glucose or [U-^13C]-glutamine lactate (media)		Low High
BT474 and MDA-MB-231	Lactate (media) ^13C-aspartate production from [U^13C]-glucose or [U-^13C]-glutamine		Low High
BT474 and MDA-MB-468	^13C-glycine production from media [U-^13C]-glucose		High
MCF-7 and MDA-MB-231	^13C-glycine production from media [U-^13C]-glucose		Low
Luminal A		Tissue		^Citation44
A1	Lipid residues a-H amino acid and myo-inositol		High Low
A2	Glucose alanine and lactate		Low High
A3	a-H amino acid		High
Luminal A		Tissue		^Citation45
Cluster 1	Glycerophosphocholine, phosphocholine and lactate glucose		High Low
Cluster 2	Glucose lactate and alanine		High Low
Cluster 3	Lactate and alanine glucose		High Low

Abbreviations: HER2, human epidermal growth factor receptor 2; ER, estrogen receptor.

Table 2 The application of metabolomics in the risk factors, diagnosis, treatment and prognosis of breast cancer

Application	Biomarker	Sample	Pathway	Alteration	Ref
Risk factor	Dehydroepiandrosterone sulfate; other androgens, estrogens, ethyl-glucuronide;a-hydroxyisovalerate, caprate (10:0), a medium-chain SFA, 10-undecenoate (11:1n–1), an odd-carbon MUFA, 2-hydroxyoctanoate, a hydroxy fatty acid; g-CEHC.)	Serum	Androgen pathway, estrogen pathway,	Up	^Citation50
			Vitamin E (a-tocopherol was inversely associated, whereas d-tocopherol and g- CEHC)	Down
	Valine, lysine, arginine, glutamine, creatine, creatinine, glucose	Plasma	Amino acids metabolism, glucose metabolism, glutamine metabolism, lipid metabolism	Up	^Citation47
			lipoproteins, lipids, glycoproteins, acetone, glycerol-derived compounds, unsaturated lipids	Down
	Methylation of catechol estrogen	Serum	Estrogen metabolism	Down	^Citation48
			Parent estrogens	Up
	16a-hydroxy-DHEA-3-sulfate,3-methylglutarylcarnitine, allo-isoleucine,2-methylbutyrylcarnitine	Serum	Steroid hormone metabolism, branched chain amino acid metabolism	Up	^Citation49
Diagnosis	Lysophosphatidylcholines, phosphatidylcholines	Serum	Phospholipid metabolism	Up	^Citation60
	Tryptophan	Serum and tissue	Amino acids metabolism	Down (serum)	^Citation57
	Tyrosine			Down (serum); up (tissue)
	Creatine			Down (serum); up (tissue)
	Adenine, N6-methyladenosine,1-methyladenosine	Plasma	Purine metabolism, nucleotide metabolism	Down (BRAC1 mutated)	^Citation70
	Lysophosphatidylcholine (18:1), lysophosphatidylcholine (22:6), monoacylglycerol	Saliva	Phospholipid catabolism, glycerolipids catabolism	Up	^Citation64
	Glutamine	Cell	Glutamine metabolism	Down	^Citation105
	Homovanillate,4-hydroxyphenylacetate,5-hydroxyindoleacetate	Urine	Tyrosine metabolism, tryptophan metabolism, pyrimidine metabolism, purine metabolism	Down	^Citation62
			Urea	Up
Treatment	3-hydroxy-butyrate	Plasma	Lipid metabolism	Up	^Citation83
	AC 14:0, AC 18:1, and AC 18:2
	Cysteine–cystine			Down
	Phosphatidylethanolamine 18:2
	Acetyl-l-alanine and indoxyl sulfate	Serum	Energy metabolism, amino acid metabolism	Up	^Citation84
	5-oxo-l-proline			Down
	Kynurenine and kynurenine/tryptophan ratios		Tryptophan/kynurenine pathways	Up
	Histidine, phenylalanine, and threonine	Whole blood	Amino acids metabolism	Down	^Citation85
	Glutathione	Cell	Glutathione biosynthesis	Down	^Citation106
	Serine, leucine, isoleucine	Serum	Amino acids metabolism	Up	^Citation81
	Ratio of GSH/GSSG, ATP/ADP and ATP/AMP	Cell	Glutamine metabolism, glucose metabolism (glycolysis/oxidative phosphorylation)	Up	^Citation76
	Spermidine	Serum	Spermidine and tryptophan metabolic pathways	Up	^Citation74
			Tryptophan	Down
Prognosis and metastasis	Xanthine, glucose-6-phosphate, mannose-6-phosphate	Cell	Purine metabolism, glucose metabolism,	Down	^Citation93
		Guanine, adenine	Purine metabolism	Up
	9cisRA	Serum, urine	Retinol metabolism	Down	^Citation58
	Cytidine monophosphate	Cell	Glucose metabolism (sialic acid metabolism)	Down	^Citation107
			Cytidine monophosphate-sialic acid, sialic acid	Up
	Putrescine, asymmetric dimethylarginine, total phosphatidylcholines, diester-bound phospholipid fraction, lysophospholipids	Plasma	Arginine, energy metabolism, lipid metabolism	Up	^Citation96
	Prometastatic arachidonic acid	Serum	Lipid metabolism	Up	^Citation98
			Antimetastatic lysophosphatidylcholines	Down
	27-hydroxycholesterol	Plasma	Lipid metabolism	Up	^Citation91
	Creatinine and allantoin	Urine	Uric acid metabolism, creatine metabolism, phospholipid metabolism	Down	^Citation97
			Trimethylamine, trimethylamine-N-oxide, creatine+phosphocreatine and taurine	Up
	Glucose, glycine, serine, acetate	Tissue	Glucose metabolism, amino acids metabolism	Down	^Citation99
	Z-4-hydroxy-tamoxifen, Z-endoxifen	Serum	Tamoxifen metabolism	Down	^Citation100
	Phenylalanine, glutamate	Serum	Phenylalanine metabolism, glutamine metabolism,	Up	^Citation79
	Ketones and lactates	Cell	Glucose metabolism	Up	^Citation88
	N-acetylneuraminic acid	Cell	Glucose metabolism (sialic acid metabolism)	Up	^Citation89

Abbreviations: BC, breast cancer; MS, mass spectrometry; GC, gas chromatography; LC, liquid chromatograph; CE, capillary electrophoresis; NMR, nuclear magnetic resonance; UPLC, ultra performance liquid chromatography; PCA, principal component analysis; HCA, hierarchical cluster analysis; PLS, partial least squares; SIMCA, soft independent modeling of class analogy; PLS-DA, partial least squares discriminant analysis; OPLS-DA, orthogonal PLS-DA; ER, estrogen receptor; PR, progesterone receptor; HER-2, human epidermal growth factor receptor 2; BMI, body mass index; IDC, invasive ductal carcinoma; LBC, localized breast cancers; MT, metastatic breast cancers; NC, normal controls; QTOF-MS/MS, liquid chromatography (UHPLC)-time-of-flight tandem mass spectrometer; LPCs, lysophosphatidylcholines; PCs, phosphatidylcholines; NAF, nipple aspirate fluids; UPLC-QTOF, ultra-performance liquid chromatography coupled with a quadrupole time-of-light; TNBC, triple negative breast cancer; LESA-MS, liquid extraction surface analysis with mass spectrometry; MDR, multidrug resistance; RT, radiotherapy; PN, psychoneurologic; Neu5Ac, N-acetylneuraminic acid; CMAS, N-acetylneuraminic acid synthetase; CMP, cytidine monophosphate; HFD, high-fat diet; 27HC, 27-hydroxycholesterol; MALDI MSI, matrix-assisted laser desorption/ionization mass spectrometry imaging; GC-MS, chromatography mass spectrometry; DI-MS, direct infusion mass spectrometry; Z-4OHtam, Z-4-hydroxy-tamoxifen; GC/MS, gas chromatography mass spectrometry; LC-MS/MS, liquid chromatography-tandem mass spectrometry; ARG, arginase; PG, phosphatidylglycerol; PA, phosphatidic acid; PE, phosphatidylethanolamine; PS, phosphatidylserine; PC, phosphatidylcholine; PI, phosphatidylinositol; SM, sphingomyelin; FA, fatty acids; CL, glycerophosphoglycerophosphoglycerols; SFA,saturated fatty acids; MUFA, monounsaturated fatty acids; CEHC, carboxyethyl hydrochroman; DHEA, dehydroepiandrosterone; AC, acylcarnitines; GSH, glutathione; GSSG, oxidized glutathione; ATP, adenosine triphosphate; ADP, adenosine diphosphate; AMP, adenosine monophosphate; 9cisRA, 9-cis-retinoic acid.

Fan Y, Zhou X, Xia TS, et al. Human plasma metabolomics for identifying differential metabolites and predicting molecular subtypes of breast cancer. Oncotarget. 2016;7(9):9925–9938. doi:10.18632/oncotarget.715526848530

 PubMedGoogle Scholar

Jerby L, Wolf L, Denkert C, et al. Metabolic associations of reduced proliferation and oxidative stress in advanced breast cancer. Cancer Res. 2012;72(22):5712–5720. doi:10.1158/0008-5472.CAN-12-221522986741

 PubMed Web of Science ®Google Scholar

Budczies J, Brockmoller SF, Muller BM, et al. Comparative metabolomics of estrogen receptor positive and estrogen receptor negative breast cancer: alterations in glutamine and beta-alanine metabolism. J Proteomics. 2013;94:279–288. doi:10.1016/j.jprot.2013.10.00224125731

 PubMed Web of Science ®Google Scholar

Giudetti AM, De Domenico S, Ragusa A, et al. A specific lipid metabolic profile is associated with the epithelial mesenchymal transition program. Biochimica Et Biophysica Acta Mol Cell Biol Lipids. 2019;1864(3):344–357. doi:10.1016/j.bbalip.2018.12.011

 PubMed Web of Science ®Google Scholar

Winnike JH, Stewart DA, Pathmasiri WW, McRitchie SL, Sumner SJ. Stable isotope-resolved metabolomic differences between hormone-responsive and triple-negative breast cancer cell lines. Int J Breast Cancer. 2018;2018:2063540. doi:10.1155/2018/206354030363973

 PubMed Web of Science ®Google Scholar

Borgan E, Sitter B, Lingjaerde OC, et al. Merging transcriptomics and metabolomics–advances in breast cancer profiling. BMC Cancer. 2010;10:628. doi:10.1186/1471-2407-10-66321080935

 PubMed Web of Science ®Google Scholar

Aure MR, Vitelli V, Jernstrom S, et al. Integrative clustering reveals a novel split in the luminal A subtype of breast cancer with impact on outcome. Breast Cancer Res. 2017;19(1):44. doi:10.1186/s13058-017-0812-y28356166

 PubMedGoogle Scholar

Playdon MC, Ziegler RG, Sampson JN, et al. Nutritional metabolomics and breast cancer risk in a prospective study. Am J Clin Nutr. 2017;106(2):637–649. doi:10.3945/ajcn.116.15091228659298

 PubMed Web of Science ®Google Scholar

Lecuyer L, Victor Bala A, Deschasaux M, et al. NMR metabolomic signatures reveal predictive plasma metabolites associated with long-term risk of developing breast cancer. Int J Epidemiol. 2018;47(2):484–494. doi:10.1093/ije/dyx27129365091

 PubMed Web of Science ®Google Scholar

Oh H, Coburn SB, Matthews CE, et al. Anthropometric measures and serum estrogen metabolism in postmenopausal women: the Women’s Health Initiative Observational Study. Breast Cancer Res. 2017;19(1):28. doi:10.1186/s13058-017-0810-028284224

 PubMedGoogle Scholar

Moore SC, Playdon MC, Sampson JN, et al. A metabolomics analysis of body mass index and postmenopausal breast cancer risk. J Natl Cancer Inst. 2018;110(6):588–597. doi:10.1093/jnci/djx24429325144

 PubMedGoogle Scholar

Okamoto Y, Aoki A, Ueda K, Jinno H. Metabolomic analysis uncovered an association of serum phospholipid levels with estrogen-induced mammary tumors in female ACI/Seg rats. Toxicol Lett. 2018;288:65–70. doi:10.1016/j.toxlet.2018.02.01729454887

 PubMed Web of Science ®Google Scholar

More TH, RoyChoudhury S, Christie J, et al. Metabolomic alterations in invasive ductal carcinoma of breast: a comprehensive metabolomic study using tissue and serum samples. Oncotarget. 2018;9(2):2678–2696. doi:10.18632/oncotarget.2362629416801

 PubMedGoogle Scholar

Roig B, Rodríguez-Balada M, Samino S, et al. Metabolomics reveals novel blood plasma biomarkers associated to the BRCA1-mutated phenotype of human breast cancer. Sci Rep. 2017;7. doi:10.1038/s41598-017-17897-828127057

 PubMedGoogle Scholar

Zhong L, Cheng F, Lu X, Duan Y, Wang X. Untargeted saliva metabonomics study of breast cancer based on ultra performance liquid chromatography coupled to mass spectrometry with HILIC and RPLC separations. Talanta. 2016;158:351–360. doi:10.1016/j.talanta.2016.04.04927343615

 PubMed Web of Science ®Google Scholar

Coloff JL, Murphy JP, Braun CR, et al. Differential glutamate metabolism in proliferating and quiescent mammary epithelial cells. Cell Metab. 2016;23(5):867–880. doi:10.1016/j.cmet.2016.03.01627133130

 PubMed Web of Science ®Google Scholar

Nam H, Chung BC, Kim Y, Lee K, Lee D. Combining tissue transcriptomics and urine metabolomics for breast cancer biomarker identification. Bioinformatics. 2009;25(23):3151–3157. doi:10.1093/bioinformatics/btp55819783829

 PubMed Web of Science ®Google Scholar

Ezaki T, Nishiumi S, Azuma T, Yoshida M. Metabolomics for the early detection of cisplatin-induced nephrotoxicity. Toxicol Res (Camb). 2017;6(6):843–853. doi:10.1039/c7tx00171a30090547

 PubMed Web of Science ®Google Scholar

Lyon DE, Starkweather A, Yao Y, et al. Pilot study of metabolomics and psychoneurological symptoms in women with early stage breast cancer. Biol Res Nurs. 2018;20(2):227–236. doi:10.1177/109980041774741129258398

 PubMed Web of Science ®Google Scholar

Sun Y, Kim JH, Vangipuram K, et al. Pharmacometabolomics reveals a role for histidine, phenylalanine, and threonine in the development of paclitaxel-induced peripheral neuropathy. Breast Cancer Res Treat. 2018;171(3):657–666. doi:10.1007/s10549-018-4862-329946863

 PubMed Web of Science ®Google Scholar

Beatty A, Fink LS, Singh T, et al. Metabolite profiling reveals the glutathione biosynthetic pathway as a therapeutic target in triple-negative breast cancer. Mol Cancer Ther. 2018;17(1):264–275. doi:10.1158/1535-7163.MCT-17-040729021292

 PubMed Web of Science ®Google Scholar

Arenas M, Rodriguez E, Garcia-Heredia A, et al. Metabolite normalization with local radiotherapy following breast tumor resection. PLoS One. 2018;13(11):e0207474. doi:10.1371/journal.pone.020747430444915

 PubMed Web of Science ®Google Scholar

Zong L, Pi Z, Liu S, Xing J, Liu Z, Song F. Liquid extraction surface analysis nanospray electrospray ionization based lipidomics for in situ analysis of tumor cells with multidrug resistance. Rapid Commun Mass Spectrom. 2018;32(19):1683–1692. doi:10.1002/rcm.822930003601

 PubMed Web of Science ®Google Scholar

Miolo G, Muraro E, Caruso D, et al. Pharmacometabolomics study identifies circulating spermidine and tryptophan as potential biomarkers associated with the complete pathological response to trastuzumab-paclitaxel neoadjuvant therapy in HER-2 positive breast cancer. Oncotarget. 2016;7(26):39809–39822. doi:10.18632/oncotarget.948927223427

 PubMedGoogle Scholar

Kim HY, Lee KM, Kim SH, Kwon YJ, Chun YJ, Choi HK. Comparative metabolic and lipidomic profiling of human breast cancer cells with different metastatic potentials. Oncotarget. 2016;7(41):67111–67128. doi:10.18632/oncotarget.1156027564096

 PubMedGoogle Scholar

Wu J, Yang R, Zhang L, et al. Metabolomics research on potential role for 9-cis-retinoic acid in breast cancer progression. Cancer Sci. 2018;109(7):2315–2326. doi:10.1111/cas.1362929737597

 PubMed Web of Science ®Google Scholar

Teoh ST, Ogrodzinski MP, Ross C, Hunter KW, Lunt SY. Sialic acid metabolism: a key player in breast cancer metastasis revealed by metabolomics. Front Oncol. 2018;8:174. doi:10.3389/fonc.2018.0017429892572

 PubMed Web of Science ®Google Scholar

Kus K, Kij A, Zakrzewska A, et al. Alterations in arginine and energy metabolism, structural and signalling lipids in metastatic breast cancer in mice detected in plasma by targeted metabolomics and lipidomics. Breast Cancer Res. 2018;20(1):148. doi:10.1186/s13058-018-1075-y30514398

 PubMedGoogle Scholar

Krzeszinski JY, Schwaid AG, Cheng WY, et al. Lipid osteoclastokines regulate breast cancer bone metastasis. Endocrinology. 2017;158(3):477–489. doi:10.1210/en.2016-157027967239

 PubMed Web of Science ®Google Scholar

Baek AE, Yu YA, He S, et al. The cholesterol metabolite 27 hydroxycholesterol facilitates breast cancer metastasis through its actions on immune cells. Nat Commun. 2017;8(1):864. doi:10.1038/s41467-017-00910-z29021522

 PubMedGoogle Scholar

Larkin JR, Dickens AM, Claridge TD, et al. Early diagnosis of brain metastases using a biofluids-metabolomics approach in mice. Theranostics. 2016;6(12):2161–2169. doi:10.7150/thno.1653827924154

 PubMed Web of Science ®Google Scholar

Auslander N, Yizhak K, Weinstock A, et al. A joint analysis of transcriptomic and metabolomic data uncovers enhanced enzyme-metabolite coupling in breast cancer. Sci Rep. 2016;6:29662. doi:10.1038/srep2966227406679

 PubMed Web of Science ®Google Scholar

Helland T, Henne N, Bifulco E, et al. Serum concentrations of active tamoxifen metabolites predict long-term survival in adjuvantly treated breast cancer patients. Breast Cancer Res. 2017;19(1):125. doi:10.1186/s13058-017-0916-429183390

 PubMedGoogle Scholar

Hart CD, Vignoli A, Tenori L, et al. Serum metabolomic profiles identify ER-positive early breast cancer patients at increased risk of disease recurrence in a multicenter population. Clin Cancer Res. 2017;23(6):1422–1431. doi:10.1158/1078-0432.CCR-16-115328082280

 PubMed Web of Science ®Google Scholar

Martinez-Outschoorn UE, Prisco M, Ertel A, et al. Ketones and lactate increase cancer cell “stemness,” driving recurrence, metastasis and poor clinical outcome in breast cancer: achieving personalized medicine via metabolo-genomics. Cell Cycle. 2011;10(8):1271–1286. doi:10.4161/cc.10.8.1533021512313

 PubMed Web of Science ®Google Scholar

O’Day EM, Idos GE, Hill C, Chen JW, Wagner G. Cytidine monophosphate N-acetylneuraminic acid synthetase enhances invasion of human triple-negative breast cancer cells. Onco Targets Ther. 2018;11:6827–6838. doi:10.2147/OTT.S17763930349315

 PubMed Web of Science ®Google Scholar