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Published in: Breast Cancer Research 1/2018

Open Access 01-12-2018 | Research Article

Increased circulating resistin levels in early-onset breast cancer patients of normal body mass index correlate with lymph node negative involvement and longer disease free survival: a multi-center POSH cohort serum proteomics study

Authors: Bashar Zeidan, Antigoni Manousopoulou, Diana J. Garay-Baquero, Cory H. White, Samantha E. T. Larkin, Kathleen N. Potter, Theodoros I. Roumeliotis, Evangelia K. Papachristou, Ellen Copson, Ramsey I. Cutress, Stephen A. Beers, Diana Eccles, Paul A. Townsend, Spiros D. Garbis

Published in: Breast Cancer Research | Issue 1/2018

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Abstract

Background

Early-onset breast cancer (EOBC) affects about one in 300 women aged 40 years or younger and is associated with worse outcomes than later onset breast cancer. This study explored novel serum proteins as surrogate markers of prognosis in patients with EOBC.

Methods

Serum samples from EOBC patients (stages 1–3) were analysed using agnostic high-precision quantitative proteomics. Patients received anthracycline-based chemotherapy. The discovery cohort (n = 399) either had more than 5-year disease-free survival (DFS) (good outcome group, n = 203) or DFS of less than 2 years (poor outcome group, n = 196). Expressed proteins were assessed for differential expression between the two groups. Bioinformatics pathway and network analysis in combination with literature research were used to determine clinically relevant proteins. ELISA analysis against an independent sample set from the Prospective study of Outcomes in Sporadic versus Hereditary breast cancer (POSH) cohort (n = 181) was used to validate expression levels of the selected target. Linear and generalized linear modelling was applied to determine the effect of target markers, body mass index (BMI), lymph node involvement (LN), oestrogen receptor (ER), progesterone receptor and human epidermal growth factor receptor 2 status on patients’ outcome.

Results

A total of 5346 unique proteins were analysed (peptide FDR p ≤ 0.05). Of these, 812 were differentially expressed in the good vs poor outcome groups and showed significant enrichment for the insulin signalling (p = 0.01) and the glycolysis/gluconeogenesis (p = 0.01) pathways. These proteins further correlated with interaction networks involving glucose and fatty acid metabolism. A consistent nodal protein to these metabolic networks was resistin (upregulated in the good outcome group, p = 0.009). ELISA validation demonstrated resistin to be upregulated in the good outcome group (p = 0.04), irrespective of BMI and ER status. LN involvement was the only covariate with a significant association with resistin measurements (p = 0.004). An ancillary in-silico observation was the induction of the inflammatory response, leucocyte infiltration, lymphocyte migration and recruitment of phagocytes (p < 0.0001, z-score > 2). Survival analysis showed that resistin overexpression was associated with improved DFS.

Conclusions

Higher circulating resistin correlated with node-negative patients and longer DFS independent of BMI and ER status in women with EOBC. Overexpression of serum resistin in EOBC may be a surrogate indicator of improved prognosis.
Appendix
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Literature
1.
go back to reference Eccles D, Gerty S, Simmonds P, Hammond V, Ennis S, Altman DG, POSH. Steering Group. Prospective study of Outcomes in Sporadic versus Hereditary breast cancer (POSH): study protocol. BMC Cancer. 2007;7:160.CrossRefPubMedPubMedCentral Eccles D, Gerty S, Simmonds P, Hammond V, Ennis S, Altman DG, POSH. Steering Group. Prospective study of Outcomes in Sporadic versus Hereditary breast cancer (POSH): study protocol. BMC Cancer. 2007;7:160.CrossRefPubMedPubMedCentral
2.
go back to reference Copson E, Eccles B, Maishman T, Gerty S, Stanton L, Cutress RI, Altman DG, Durcan L, Simmonds P, Lawrence G, et al. Prospective observational study of breast cancer treatment outcomes for UK women aged 18-40 years at diagnosis: the POSH study. J Natl Cancer Inst. 2013;105(13):978–88.CrossRefPubMed Copson E, Eccles B, Maishman T, Gerty S, Stanton L, Cutress RI, Altman DG, Durcan L, Simmonds P, Lawrence G, et al. Prospective observational study of breast cancer treatment outcomes for UK women aged 18-40 years at diagnosis: the POSH study. J Natl Cancer Inst. 2013;105(13):978–88.CrossRefPubMed
3.
go back to reference Candido Dos Reis FJ, Wishart GC, Dicks EM, Greenberg D, Rashbass J, Schmidt MK, van den Broek AJ, Ellis IO, Green A, Rakha E, et al. An updated PREDICT breast cancer prognostication and treatment benefit prediction model with independent validation. Breast Cancer Res. 2017;19(1):58.CrossRefPubMedPubMedCentral Candido Dos Reis FJ, Wishart GC, Dicks EM, Greenberg D, Rashbass J, Schmidt MK, van den Broek AJ, Ellis IO, Green A, Rakha E, et al. An updated PREDICT breast cancer prognostication and treatment benefit prediction model with independent validation. Breast Cancer Res. 2017;19(1):58.CrossRefPubMedPubMedCentral
4.
go back to reference Zeidan BA, Townsend PA, Garbis SD, Copson E, Cutress RI. Clinical proteomics and breast cancer. Surgeon. 2015;13(5):271–8.CrossRefPubMed Zeidan BA, Townsend PA, Garbis SD, Copson E, Cutress RI. Clinical proteomics and breast cancer. Surgeon. 2015;13(5):271–8.CrossRefPubMed
7.
go back to reference Meng R, Gormley M, Bhat VB, Rosenberg A, Quong AA. Low abundance protein enrichment for discovery of candidate plasma protein biomarkers for early detection of breast cancer. J Proteomics. 2011;75(2):366–74.CrossRefPubMed Meng R, Gormley M, Bhat VB, Rosenberg A, Quong AA. Low abundance protein enrichment for discovery of candidate plasma protein biomarkers for early detection of breast cancer. J Proteomics. 2011;75(2):366–74.CrossRefPubMed
8.
go back to reference Opstal-van Winden AW, Krop EJ, Karedal MH, Gast MC, Lindh CH, Jeppsson MC, Jonsson BA, Grobbee DE, Peeters PH, Beijnen JH, et al. Searching for early breast cancer biomarkers by serum protein profiling of pre-diagnostic serum; a nested case-control study. BMC Cancer. 2011;11:381.CrossRefPubMedPubMedCentral Opstal-van Winden AW, Krop EJ, Karedal MH, Gast MC, Lindh CH, Jeppsson MC, Jonsson BA, Grobbee DE, Peeters PH, Beijnen JH, et al. Searching for early breast cancer biomarkers by serum protein profiling of pre-diagnostic serum; a nested case-control study. BMC Cancer. 2011;11:381.CrossRefPubMedPubMedCentral
9.
go back to reference Garbis SD, Roumeliotis TI, Tyritzis SI, Zorpas KM, Pavlakis K, Constantinides CA. A novel multidimensional protein identification technology approach combining protein size exclusion prefractionation, peptide zwitterion-ion hydrophilic interaction chromatography, and nano-ultraperformance RP chromatography/nESI-MS2 for the in-depth analysis of the serum proteome and phosphoproteome: application to clinical sera derived from humans with benign prostate hyperplasia. Anal Chem. 2011;83(3):708–18.CrossRefPubMed Garbis SD, Roumeliotis TI, Tyritzis SI, Zorpas KM, Pavlakis K, Constantinides CA. A novel multidimensional protein identification technology approach combining protein size exclusion prefractionation, peptide zwitterion-ion hydrophilic interaction chromatography, and nano-ultraperformance RP chromatography/nESI-MS2 for the in-depth analysis of the serum proteome and phosphoproteome: application to clinical sera derived from humans with benign prostate hyperplasia. Anal Chem. 2011;83(3):708–18.CrossRefPubMed
10.
go back to reference Copson ER, Cutress RI, Maishman T, Eccles BK, Gerty S, Stanton L, Altman DG, Durcan L, Wong C, Simmonds PD, et al. Obesity and the outcome of young breast cancer patients in the UK: the POSH study. Ann Oncol. 2015;26(1):101–12.CrossRefPubMed Copson ER, Cutress RI, Maishman T, Eccles BK, Gerty S, Stanton L, Altman DG, Durcan L, Wong C, Simmonds PD, et al. Obesity and the outcome of young breast cancer patients in the UK: the POSH study. Ann Oncol. 2015;26(1):101–12.CrossRefPubMed
11.
go back to reference Johnston HE, Carter MJ, Cox KL, Dunscombe M, Manousopoulou A, Townsend PA, Garbis SD, Cragg MS. Integrated cellular and plasma proteomics of contrasting B-cell cancers reveals common, unique and systemic signatures. Mol Cell Proteomics. 2017;16(3):386–406.CrossRefPubMedPubMedCentral Johnston HE, Carter MJ, Cox KL, Dunscombe M, Manousopoulou A, Townsend PA, Garbis SD, Cragg MS. Integrated cellular and plasma proteomics of contrasting B-cell cancers reveals common, unique and systemic signatures. Mol Cell Proteomics. 2017;16(3):386–406.CrossRefPubMedPubMedCentral
12.
go back to reference Al-Daghri NM, Al-Attas OS, Johnston HE, Singhania A, Alokail MS, Alkharfy KM, Abd-Alrahman SH, Sabico SL, Roumeliotis TI, Manousopoulou-Garbis A, et al. Whole serum 3D LC-nESI-FTMS quantitative proteomics reveals sexual dimorphism in the milieu interieur of overweight and obese adults. J Proteome Res. 2014;13(11):5094–105.CrossRefPubMed Al-Daghri NM, Al-Attas OS, Johnston HE, Singhania A, Alokail MS, Alkharfy KM, Abd-Alrahman SH, Sabico SL, Roumeliotis TI, Manousopoulou-Garbis A, et al. Whole serum 3D LC-nESI-FTMS quantitative proteomics reveals sexual dimorphism in the milieu interieur of overweight and obese adults. J Proteome Res. 2014;13(11):5094–105.CrossRefPubMed
13.
go back to reference Al-Daghri NM, Alokail MS, Manousopoulou A, Heinson A, Al-Attas O, Al-Saleh Y, Sabico S, Yakout S, Woelk CH, Chrousos GP, et al. Sex-specific vitamin D effects on blood coagulation among overweight adults. Eur J Clin Invest. 2016;46(12):1031–40.CrossRefPubMed Al-Daghri NM, Alokail MS, Manousopoulou A, Heinson A, Al-Attas O, Al-Saleh Y, Sabico S, Yakout S, Woelk CH, Chrousos GP, et al. Sex-specific vitamin D effects on blood coagulation among overweight adults. Eur J Clin Invest. 2016;46(12):1031–40.CrossRefPubMed
14.
go back to reference Larkin SE, Johnston HE, Jackson TR, Jamieson DG, Roumeliotis TI, Mockridge CI, Michael A, Manousopoulou A, Papachristou EK, Brown MD, et al. Detection of candidate biomarkers of prostate cancer progression in serum: a depletion-free 3D LC/MS quantitative proteomics pilot study. Br J Cancer. 2016;115(9):1078–86.CrossRefPubMedPubMedCentral Larkin SE, Johnston HE, Jackson TR, Jamieson DG, Roumeliotis TI, Mockridge CI, Michael A, Manousopoulou A, Papachristou EK, Brown MD, et al. Detection of candidate biomarkers of prostate cancer progression in serum: a depletion-free 3D LC/MS quantitative proteomics pilot study. Br J Cancer. 2016;115(9):1078–86.CrossRefPubMedPubMedCentral
15.
go back to reference Manousopoulou A, Koutmani Y, Karaliota S, Woelk CH, Manolakos ES, Karalis K, Garbis SD. Hypothalamus proteomics from mouse models with obesity and anorexia reveals therapeutic targets of appetite regulation. Nutr Diabetes. 2016;6:e204.CrossRefPubMedPubMedCentral Manousopoulou A, Koutmani Y, Karaliota S, Woelk CH, Manolakos ES, Karalis K, Garbis SD. Hypothalamus proteomics from mouse models with obesity and anorexia reveals therapeutic targets of appetite regulation. Nutr Diabetes. 2016;6:e204.CrossRefPubMedPubMedCentral
16.
go back to reference Papachristou EK, Roumeliotis TI, Chrysagi A, Trigoni C, Charvalos E, Townsend PA, Pavlakis K, Garbis SD. The shotgun proteomic study of the human ThinPrep cervical smear using iTRAQ mass-tagging and 2D LC-FT-Orbitrap-MS: the detection of the human papillomavirus at the protein level. J Proteome Res. 2013;12(5):2078–89.CrossRefPubMed Papachristou EK, Roumeliotis TI, Chrysagi A, Trigoni C, Charvalos E, Townsend PA, Pavlakis K, Garbis SD. The shotgun proteomic study of the human ThinPrep cervical smear using iTRAQ mass-tagging and 2D LC-FT-Orbitrap-MS: the detection of the human papillomavirus at the protein level. J Proteome Res. 2013;12(5):2078–89.CrossRefPubMed
17.
go back to reference Giannogonas P, Apostolou A, Manousopoulou A, Theocharis S, Macari SA, Psarras S, Garbis SD, Pothoulakis C, Karalis KP. Identification of a novel interaction between corticotropin releasing hormone (Crh) and macroautophagy. Sci Rep. 2016;6:23342.CrossRefPubMedPubMedCentral Giannogonas P, Apostolou A, Manousopoulou A, Theocharis S, Macari SA, Psarras S, Garbis SD, Pothoulakis C, Karalis KP. Identification of a novel interaction between corticotropin releasing hormone (Crh) and macroautophagy. Sci Rep. 2016;6:23342.CrossRefPubMedPubMedCentral
18.
go back to reference Manousopoulou A, Gatherer M, Smith C, Nicoll JAR, Woelk CH, Johnson M, Kalaria R, Attems J, Garbis SD, Carare RO. Systems proteomic analysis reveals that clusterin and tissue inhibitor of metalloproteinases 3 increase in leptomeningeal arteries affected by cerebral amyloid angiopathy. Neuropathol Appl Neurobiol. 2017;43(6):492–504.CrossRefPubMed Manousopoulou A, Gatherer M, Smith C, Nicoll JAR, Woelk CH, Johnson M, Kalaria R, Attems J, Garbis SD, Carare RO. Systems proteomic analysis reveals that clusterin and tissue inhibitor of metalloproteinases 3 increase in leptomeningeal arteries affected by cerebral amyloid angiopathy. Neuropathol Appl Neurobiol. 2017;43(6):492–504.CrossRefPubMed
19.
go back to reference Concato J, Peduzzi P, Holford TR, Feinstein AR. Importance of events per independent variable in proportional hazards analysis. I. Background, goals, and general strategy. J Clin Epidemiol. 1995;48(12):1495–501.CrossRefPubMed Concato J, Peduzzi P, Holford TR, Feinstein AR. Importance of events per independent variable in proportional hazards analysis. I. Background, goals, and general strategy. J Clin Epidemiol. 1995;48(12):1495–501.CrossRefPubMed
20.
go back to reference Peduzzi P, Concato J, Feinstein AR, Holford TR. Importance of events per independent variable in proportional hazards regression analysis. II. Accuracy and precision of regression estimates. J Clin Epidemiol. 1995;48(12):1503–10.CrossRefPubMed Peduzzi P, Concato J, Feinstein AR, Holford TR. Importance of events per independent variable in proportional hazards regression analysis. II. Accuracy and precision of regression estimates. J Clin Epidemiol. 1995;48(12):1503–10.CrossRefPubMed
21.
go back to reference Peduzzi P, Concato J, Kemper E, Holford TR, Feinstein AR. A simulation study of the number of events per variable in logistic regression analysis. J Clin Epidemiol. 1996;49(12):1373–9.CrossRefPubMed Peduzzi P, Concato J, Kemper E, Holford TR, Feinstein AR. A simulation study of the number of events per variable in logistic regression analysis. J Clin Epidemiol. 1996;49(12):1373–9.CrossRefPubMed
22.
go back to reference Kuhnast C, Neuhauser M. A note on the use of the non-parametric Wilcoxon-Mann-Whitney test in the analysis of medical studies. Ger Med Sci. 2008;6:Doc02.PubMedPubMedCentral Kuhnast C, Neuhauser M. A note on the use of the non-parametric Wilcoxon-Mann-Whitney test in the analysis of medical studies. Ger Med Sci. 2008;6:Doc02.PubMedPubMedCentral
23.
go back to reference Lumley T, Diehr P, Emerson S, Chen L. The importance of the normality assumption in large public health data sets. Annu Rev Public Health. 2002;23:151–69.CrossRefPubMed Lumley T, Diehr P, Emerson S, Chen L. The importance of the normality assumption in large public health data sets. Annu Rev Public Health. 2002;23:151–69.CrossRefPubMed
24.
go back to reference Sawilowsky SS, Hillman SB. Power of the independent samples t test under a prevalent psychometric measure distribution. J Consult Clin Psychol. 1992;60(2):240–3.CrossRefPubMed Sawilowsky SS, Hillman SB. Power of the independent samples t test under a prevalent psychometric measure distribution. J Consult Clin Psychol. 1992;60(2):240–3.CrossRefPubMed
25.
go back to reference Gyorffy B, Lanczky A, Eklund AC, Denkert C, Budczies J, Li Q, Szallasi Z. An online survival analysis tool to rapidly assess the effect of 22,277 genes on breast cancer prognosis using microarray data of 1,809 patients. Breast Cancer Res Treat. 2010;123(3):725–31.CrossRefPubMed Gyorffy B, Lanczky A, Eklund AC, Denkert C, Budczies J, Li Q, Szallasi Z. An online survival analysis tool to rapidly assess the effect of 22,277 genes on breast cancer prognosis using microarray data of 1,809 patients. Breast Cancer Res Treat. 2010;123(3):725–31.CrossRefPubMed
26.
go back to reference Zimmerlin L, Donnenberg AD, Rubin JP, Basse P, Landreneau RJ, Donnenberg VS. Regenerative therapy and cancer: in vitro and in vivo studies of the interaction between adipose-derived stem cells and breast cancer cells from clinical isolates. Tissue Eng Part A. 2011;17(1–2):93–106.CrossRefPubMed Zimmerlin L, Donnenberg AD, Rubin JP, Basse P, Landreneau RJ, Donnenberg VS. Regenerative therapy and cancer: in vitro and in vivo studies of the interaction between adipose-derived stem cells and breast cancer cells from clinical isolates. Tissue Eng Part A. 2011;17(1–2):93–106.CrossRefPubMed
27.
go back to reference Koerner A, Kratzsch J, Kiess W. Adipocytokines: leptin—the classical, resistin—the controversical, adiponectin—the promising, and more to come. Best Pract Res Clin Endocrinol Metab. 2005;19(4):525–46.CrossRefPubMed Koerner A, Kratzsch J, Kiess W. Adipocytokines: leptin—the classical, resistin—the controversical, adiponectin—the promising, and more to come. Best Pract Res Clin Endocrinol Metab. 2005;19(4):525–46.CrossRefPubMed
28.
go back to reference Georgiou GP, Provatopoulou X, Kalogera E, Siasos G, Menenakos E, Zografos GC, Gounaris A. Serum resistin is inversely related to breast cancer risk in premenopausal women. Breast. 2016;29:163–9.CrossRefPubMed Georgiou GP, Provatopoulou X, Kalogera E, Siasos G, Menenakos E, Zografos GC, Gounaris A. Serum resistin is inversely related to breast cancer risk in premenopausal women. Breast. 2016;29:163–9.CrossRefPubMed
29.
go back to reference Lee JO, Kim N, Lee HJ, Lee YW, Kim SJ, Park SH, Kim HS. Resistin, a fat-derived secretory factor, promotes metastasis of MDA-MB-231 human breast cancer cells through ERM activation. Sci Rep. 2016;6:18923.CrossRefPubMedPubMedCentral Lee JO, Kim N, Lee HJ, Lee YW, Kim SJ, Park SH, Kim HS. Resistin, a fat-derived secretory factor, promotes metastasis of MDA-MB-231 human breast cancer cells through ERM activation. Sci Rep. 2016;6:18923.CrossRefPubMedPubMedCentral
30.
go back to reference Sun CA, Wu MH, Chu CH, Chou YC, Hsu GC, Yang T, Chou WY, Yu CP, Yu JC. Adipocytokine resistin and breast cancer risk. Breast Cancer Res Treat. 2010;123(3):869–76.CrossRefPubMed Sun CA, Wu MH, Chu CH, Chou YC, Hsu GC, Yang T, Chou WY, Yu CP, Yu JC. Adipocytokine resistin and breast cancer risk. Breast Cancer Res Treat. 2010;123(3):869–76.CrossRefPubMed
31.
go back to reference Adeghate E. An update on the biology and physiology of resistin. Cell Mol Life Sci. 2004;61(19–20):2485–96.CrossRefPubMed Adeghate E. An update on the biology and physiology of resistin. Cell Mol Life Sci. 2004;61(19–20):2485–96.CrossRefPubMed
32.
go back to reference Lee YC, Chen YJ, Wu CC, Lo S, Hou MF, Yuan SS. Resistin expression in breast cancer tissue as a marker of prognosis and hormone therapy stratification. Gynecol Oncol. 2012;125(3):742–50.CrossRefPubMed Lee YC, Chen YJ, Wu CC, Lo S, Hou MF, Yuan SS. Resistin expression in breast cancer tissue as a marker of prognosis and hormone therapy stratification. Gynecol Oncol. 2012;125(3):742–50.CrossRefPubMed
33.
go back to reference Qatanani M, Szwergold NR, Greaves DR, Ahima RS, Lazar MA. Macrophage-derived human resistin exacerbates adipose tissue inflammation and insulin resistance in mice. J Clin Invest. 2009;119(3):531–9.CrossRefPubMedPubMedCentral Qatanani M, Szwergold NR, Greaves DR, Ahima RS, Lazar MA. Macrophage-derived human resistin exacerbates adipose tissue inflammation and insulin resistance in mice. J Clin Invest. 2009;119(3):531–9.CrossRefPubMedPubMedCentral
34.
go back to reference Lu LJ, Gan L, Hu JB, Ran L, Cheng QF, Wang RJ, Jin LB, Ren GS, Li HY, Wu KN, et al. On the status of beta-cell dysfunction and insulin resistance of breast cancer patient without history of diabetes after systemic treatment. Med Oncol. 2014;31(5):956.CrossRefPubMed Lu LJ, Gan L, Hu JB, Ran L, Cheng QF, Wang RJ, Jin LB, Ren GS, Li HY, Wu KN, et al. On the status of beta-cell dysfunction and insulin resistance of breast cancer patient without history of diabetes after systemic treatment. Med Oncol. 2014;31(5):956.CrossRefPubMed
35.
go back to reference Coskun T, Kosova F, Ari Z, Sakarya A, Kaya Y. Effect of oncological treatment on serum adipocytokine levels in patients with stage II-III breast cancer. Mol Clin Oncol. 2016;4(5):893–7.CrossRefPubMedPubMedCentral Coskun T, Kosova F, Ari Z, Sakarya A, Kaya Y. Effect of oncological treatment on serum adipocytokine levels in patients with stage II-III breast cancer. Mol Clin Oncol. 2016;4(5):893–7.CrossRefPubMedPubMedCentral
36.
go back to reference Liu Z, Shi A, Song D, Han B, Zhang Z, Ma L, Liu D, Fan Z. Resistin confers resistance to doxorubicin-induced apoptosis in human breast cancer cells through autophagy induction. Am J Cancer Res. 2017;7(3):574–83.PubMedPubMedCentral Liu Z, Shi A, Song D, Han B, Zhang Z, Ma L, Liu D, Fan Z. Resistin confers resistance to doxorubicin-induced apoptosis in human breast cancer cells through autophagy induction. Am J Cancer Res. 2017;7(3):574–83.PubMedPubMedCentral
37.
go back to reference Schott AF, Hayes DF. Defining the benefits of neoadjuvant chemotherapy for breast cancer. J Clin Oncol. 2012;30(15):1747–9.CrossRefPubMed Schott AF, Hayes DF. Defining the benefits of neoadjuvant chemotherapy for breast cancer. J Clin Oncol. 2012;30(15):1747–9.CrossRefPubMed
39.
go back to reference Mandusic V, Dimitrijevic B, Nikolic-Vukosavljevic D, Neskovic-Konstantinovic Z, Kanjer K, Hamann U. Different associations of estrogen receptor beta isoforms, ERbeta1 and ERbeta2, expression levels with tumor size and survival in early- and late-onset breast cancer. Cancer Lett. 2012;321(1):73–9.CrossRefPubMed Mandusic V, Dimitrijevic B, Nikolic-Vukosavljevic D, Neskovic-Konstantinovic Z, Kanjer K, Hamann U. Different associations of estrogen receptor beta isoforms, ERbeta1 and ERbeta2, expression levels with tumor size and survival in early- and late-onset breast cancer. Cancer Lett. 2012;321(1):73–9.CrossRefPubMed
40.
go back to reference Keerthikumar S, Chisanga D, Ariyaratne D, Al Saffar H, Anand S, Zhao K, Samuel M, Pathan M, Jois M, Chilamkurti N, et al. ExoCarta: a web-based compendium of exosomal cargo. J Mol Biol. 2016;428(4):688–92.CrossRefPubMed Keerthikumar S, Chisanga D, Ariyaratne D, Al Saffar H, Anand S, Zhao K, Samuel M, Pathan M, Jois M, Chilamkurti N, et al. ExoCarta: a web-based compendium of exosomal cargo. J Mol Biol. 2016;428(4):688–92.CrossRefPubMed
41.
go back to reference Simpson RJ, Kalra H, Mathivanan S. ExoCarta as a resource for exosomal research. J Extracell Vesicles. 2012;1:18374–80.CrossRef Simpson RJ, Kalra H, Mathivanan S. ExoCarta as a resource for exosomal research. J Extracell Vesicles. 2012;1:18374–80.CrossRef
42.
go back to reference Mathivanan S, Fahner CJ, Reid GE, Simpson RJ. ExoCarta 2012: database of exosomal proteins. RNA and lipids Nucleic Acids Res. 2012;40(Database issue):D1241–4.CrossRefPubMed Mathivanan S, Fahner CJ, Reid GE, Simpson RJ. ExoCarta 2012: database of exosomal proteins. RNA and lipids Nucleic Acids Res. 2012;40(Database issue):D1241–4.CrossRefPubMed
43.
go back to reference Christofk HR, Vander Heiden MG, Harris MH, Ramanathan A, Gerszten RE, Wei R, Fleming MD, Schreiber SL, Cantley LC. The M2 splice isoform of pyruvate kinase is important for cancer metabolism and tumour growth. Nature. 2008;452(7184):230–3.CrossRefPubMed Christofk HR, Vander Heiden MG, Harris MH, Ramanathan A, Gerszten RE, Wei R, Fleming MD, Schreiber SL, Cantley LC. The M2 splice isoform of pyruvate kinase is important for cancer metabolism and tumour growth. Nature. 2008;452(7184):230–3.CrossRefPubMed
44.
go back to reference Schwartz DR, Briggs ER, Qatanani M, Sawaya H, Sebag IA, Picard MH, Scherrer-Crosbie M, Lazar MA. Human resistin in chemotherapy-induced heart failure in humanized male mice and in women treated for breast cancer. Endocrinology. 2013;154(11):4206–14.CrossRefPubMedPubMedCentral Schwartz DR, Briggs ER, Qatanani M, Sawaya H, Sebag IA, Picard MH, Scherrer-Crosbie M, Lazar MA. Human resistin in chemotherapy-induced heart failure in humanized male mice and in women treated for breast cancer. Endocrinology. 2013;154(11):4206–14.CrossRefPubMedPubMedCentral
45.
go back to reference Shetty GK, Economides PA, Horton ES, Mantzoros CS, Veves A. Circulating adiponectin and resistin levels in relation to metabolic factors, inflammatory markers, and vascular reactivity in diabetic patients and subjects at risk for diabetes. Diabetes Care. 2004;27(10):2450–7.CrossRefPubMed Shetty GK, Economides PA, Horton ES, Mantzoros CS, Veves A. Circulating adiponectin and resistin levels in relation to metabolic factors, inflammatory markers, and vascular reactivity in diabetic patients and subjects at risk for diabetes. Diabetes Care. 2004;27(10):2450–7.CrossRefPubMed
46.
go back to reference Zuniga MC, Raghuraman G, Hitchner E, Weyand C, Robinson W, Zhou W. PKC-epsilon and TLR4 synergistically regulate resistin-mediated inflammation in human macrophages. Atherosclerosis. 2017;259:51–9.CrossRefPubMed Zuniga MC, Raghuraman G, Hitchner E, Weyand C, Robinson W, Zhou W. PKC-epsilon and TLR4 synergistically regulate resistin-mediated inflammation in human macrophages. Atherosclerosis. 2017;259:51–9.CrossRefPubMed
Metadata
Title
Increased circulating resistin levels in early-onset breast cancer patients of normal body mass index correlate with lymph node negative involvement and longer disease free survival: a multi-center POSH cohort serum proteomics study
Authors
Bashar Zeidan
Antigoni Manousopoulou
Diana J. Garay-Baquero
Cory H. White
Samantha E. T. Larkin
Kathleen N. Potter
Theodoros I. Roumeliotis
Evangelia K. Papachristou
Ellen Copson
Ramsey I. Cutress
Stephen A. Beers
Diana Eccles
Paul A. Townsend
Spiros D. Garbis
Publication date
01-12-2018
Publisher
BioMed Central
Published in
Breast Cancer Research / Issue 1/2018
Electronic ISSN: 1465-542X
DOI
https://doi.org/10.1186/s13058-018-0938-6

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