Serum protein levels following surgery in breast cancer patients: A protein microarray approach

Perez-Rivas,Luis  G.; Jerez,Jose  M.; Fernandez-De Sousa,Cristina  E.; de Luque,Vanessa; Quero,Cristina; Pajares,Bella; Franco,Leonardo; Sanchez-Muñoz,Alfonso; Ribelles,Nuria; Alba,Emilio

doi:10.3892/ijo.2012.1667

Serum protein levels following surgery in breast cancer patients: A protein microarray approach

Authors:
- Luis G. Perez-Rivas
- Jose M. Jerez
- Cristina E. Fernandez-De Sousa
- Vanessa de Luque
- Cristina Quero
- Bella Pajares
- Leonardo Franco
- Alfonso Sanchez-Muñoz
- Nuria Ribelles
- Emilio Alba
View Affiliations

Affiliations: Department of Medical Oncology, Hospital Universitario Virgen de la Victoria, Campus de Teatinos s/n, 29010 Malaga, Spain, Department of Languages and Computer Science, University of Malaga, Campus de Teatinos s/n, 29071 Malaga, Spain
Published online on: October 16, 2012 https://doi.org/10.3892/ijo.2012.1667
Pages: 2200-2206

Metrics: Total Views: 0 (Spandidos Publications: | PMC Statistics: )

Metrics: Total PDF Downloads: 0 (Spandidos Publications: | PMC Statistics: )

Cited By (CrossRef): 0 citations Loading Articles...

Abstract

Surgery is the primary treatment for non-metastatic breast cancer. However, the risk of early recurrence remains after surgical removal of the primary tumor. Recurrence is suggested to result from hidden micrometastatic foci, which are triggered to escape from dormancy by surgical resection of the primary tumor. In this study, we focused on the differential impact of breast surgery on the serum profiles of early breast cancer patients and healthy women. Serum samples from invasive breast cancer patients, in situ carcinoma breast cancer patients and healthy women were analyzed using reverse phase protein array technology. Samples were collected prior to breast surgery and 24 h following breast surgery. Both the expression level and the velocity of 42 serum proteins were quantified and compared among groups. We found that surgery increased the concentration of several proteins (CSF1, THSB2, IL6, IL7, IL16, FasL and VEGF-B) in the overall population. Compared with healthy women and patients with non-invasive tumors, invasive tumor patients exhibited higher preoperative levels of several serum proteins, such as αFP, IFNβ1, VEGF-A, IL18, E-cadherin or CD31, and lower postoperative levels of TNFα and IL5. Similarly, we detected significant surgery-induced changes in the velocity of VEGF-A and IL16 accumulation in samples derived from invasive breast cancer patients. In conclusion, breast surgery induced distinct changes in the concentrations and dynamics of serum proteins in invasive breast cancer patients compared with healthy women and non-invasive tumor patients.

View Figures

View References

1.	Jemal A, Bray F, Center MM, Ferlay J, Ward E and Forman D: Global cancer statistics. CA Cancer J Clin. 61:69–90. 2011. View Article : Google Scholar
2.	Perou CM, Sørlie T, Eisen MB, van De Rijn M, Jeffrey SS, Rees CA, Pollack JR, Ross DT, Johnsen H, Akslen LA, et al: Molecular portraits of human breast tumours. Nature. 406:747–752. 2000. View Article : Google Scholar : PubMed/NCBI
3.	Anderson WF and Matsuno R: Breast cancer heterogeneity: a mixture of at least two main types? J Natl Cancer Inst. 98:948–951. 2006. View Article : Google Scholar : PubMed/NCBI
4.	Børresen-Dale AL, Sørlie T and Kristensen VN: On the molecular biology of breast cancer. Mol Oncol. 4:171–173. 2010.
5.	Sørlie T, Perou CM, Tibshirani R, Aas T, Geisler S, Johnsen H, Hastie T, Eisen MB, van De Rijn M, Jeffrey SS, et al: Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications. Proc Natl Acad Sci USA. 98:10869–10874. 2001.PubMed/NCBI
6.	Baum M, Demicheli R, Hrushesky W and Retsky MW: Does surgery unfavourably perturb the ‘natural history’ of early breast cancer by accelerating the appearance of distant metastases? Eur J Cancer. 41:508–515. 2005.PubMed/NCBI
7.	Demicheli R, Retsky MW, Hrushesky WJM, Baum M and Gukas ID: The effects of surgery on tumor growth: a century of investigations. Ann Oncol. 19:1821–1828. 2008. View Article : Google Scholar : PubMed/NCBI
8.	Fehm T, Mueller V, Marches R, Klein G, Gueckel B, Neubauer H, Solomayer E and Becker S: Tumor cell dormancy: implications for the biology and treatment of breast cancer. Acta Pathol Microbiol Immunol Scand. 116:742–753. 2008. View Article : Google Scholar : PubMed/NCBI
9.	Tseng WW, Fadaki N and Leong SP: Metastatic tumor dormancy in cutaneous melanoma: Does surgery induce escape? Cancers. 3:730–746. 2011. View Article : Google Scholar : PubMed/NCBI
10.	Retsky MW, Demicheli R, Hrushesky W, Baum M and Gukas I: Surgery triggers outgrowth of latent distant disease in breast cancer: An inconvenient truth? Cancers. 2:305–337. 2010. View Article : Google Scholar : PubMed/NCBI
11.	Uhr JW and Pantel K: Controversies in clinical cancer dormancy. Proc Natl Acad Sci USA. 108:1–5. 2011.
12.	Demicheli R, Retsky MW, Hrushesky WJM and Baum M: Tumor dormancy and surgery-driven interruption of dormancy in breast cancer: learning from failures. Nat Clin Pract Oncol. 4:699–710. 2007. View Article : Google Scholar : PubMed/NCBI
13.	Aguirre-Ghiso JA: Models, mechanisms and clinical evidence for cancer dormancy. Nat Rev Cancer. 7:834–846. 2007. View Article : Google Scholar : PubMed/NCBI
14.	Coffey JC, Wang JH, Smith MJF, Bouchier-Hayes D, Cotter TG and Redmond HP: Excisional surgery for cancer cure: therapy at a cost. Lancet Oncol. 4:760–768. 2003. View Article : Google Scholar : PubMed/NCBI
15.	Spurrier B, Honkanen P, Holway A, Kumamoto K, Terashima M, Takenoshita S, Wakabayashi G, Austin J and Nishizuka S: Protein and lysate array technologies in cancer research. Biotechnol Adv. 26:361–369. 2008. View Article : Google Scholar : PubMed/NCBI
16.	Mueller C, La Liotta and Espina V: Reverse phase protein microarrays advance to use in clinical trials. Mol Oncol. 4:1–21. 2010. View Article : Google Scholar : PubMed/NCBI
17.	Sheehan KM, Calvert VS, Kay EW, Lu Y, Fishman D, Espina V, Aquino J, Speer R, Araujo R, Mills GB, et al: Use of reverse phase protein microarrays and reference standard development for molecular network analysis of metastatic ovarian carcinoma. Mol Cell Proteomics. 4:346–355. 2005. View Article : Google Scholar
18.	Tibes R, Qiu Y, Lu Y, Hennessy B, Andreeff M, Mills GB and Kornblau SM: Reverse phase protein array: validation of a novel proteomic technology and utility for analysis of primary leukemia specimens and hematopoietic stem cells. Mol Cancer Ther. 5:2512–2521. 2006. View Article : Google Scholar : PubMed/NCBI
19.	Brennan DJ, O’Connor DP, Rexhepaj E, Ponten F and Gallagher WM: Antibody-based proteomics: fast-tracking molecular diagnostics in oncology. Nat Rev Cancer. 10:605–617. 2010. View Article : Google Scholar : PubMed/NCBI
20.	Grote T, Siwak DR, Fritsche HA, Joy C, Mills GB, Simeone D, Whitcomb DC and Logsdon CD: Validation of reverse phase protein array for practical screening of potential biomarkers in serum and plasma: accurate detection of CA19-9 levels in pancreatic cancer. Proteomics. 8:3051–3060. 2008. View Article : Google Scholar : PubMed/NCBI
21.	Holdaway IM, Lethaby AE, Mason BH, Singh V, Harman JE, MacCormick M and Civil ID: Effect of breast surgery on serum levels of insulin-like growth factors (IGF-I, IGF-II, and IGF binding protein-3) in women with benign and malignant breast lesions. Ann Surg Oncol. 8:25–31. 2001. View Article : Google Scholar : PubMed/NCBI
22.	Smyth GK: Limma: linear models for microarray data. Bioinformatics and Computational Biology Solutions using R and Bioconductor. Gentleman R, Carey V, Dudoit S, Irizarry R and Huber W: Springer; New York, NY: pp. 397–420. 2005, View Article : Google Scholar
23.	Yang YH and Thorne NP: Normalization for two-color cDNA microarray data. Institute of Mathematical Statistics; 2003
24.	Smyth GK: Linear models and empirical bayes methods for assessing differential expression in microarray experiments. Stat Appl Gen Mol Biol. 3:Article3, Feb 12, 2004 (Epub ahead of print).
25.	Benjamini Y and Hochberg Y: Controlling the false discovery rate: A practical and powerful approach to multiple testing. J Roy Stat Soc Ser B (Stat Method). 57:289–300. 1995.
26.	Carlsson A, Wingren C, Kristensson M, Rose C, Fernö M, Olsson H, Jernström H, Ek S, Gustavsson E, Ingvar C, et al: Molecular serum portraits in patients with primary breast cancer predict the development of distant metastases. Proc Natl Acad Sci USA. 108:14252–14257. 2011. View Article : Google Scholar : PubMed/NCBI
27.	Gurtner GC, Werner S, Barrandon Y and Longaker MT: Wound repair and regeneration. Nature. 453:314–321. 2008. View Article : Google Scholar : PubMed/NCBI
28.	Hamilton JA: Colony-stimulating factors in inflammation and autoimmunity. Nat Rev Immunol. 8:533–544. 2008. View Article : Google Scholar : PubMed/NCBI
29.	Lin Z-Q, Kondo T, Ishida Y, Takayasu T and Mukaida N: Essential involvement of IL-6 in the skin wound-healing process as evidenced by delayed wound healing in IL-6-deficient mice. J Leukoc Biol. 73:713–721. 2003. View Article : Google Scholar : PubMed/NCBI
30.	Oshika Y, Masuda K, Tokunaga T, Hatanaka H, Kamiya T, Abe Y, Ozeki Y, Kijima H, Yamazaki H, Tamaoki N, et al: Thrombospondin 2 gene expression is correlated with decreased vascularity in non-small cell lung cancer. Clin Cancer Res. 4:1785–1788. 1998.PubMed/NCBI
31.	Tokunaga T, Nakamura M, Oshika Y, Abe Y, Ozeki Y, Fukushima Y, Hatanaka H, Sadahiro S, Kijima H, Tsuchida T, et al: Thrombospondin 2 expression is correlated with inhibition of angiogenesis and metastasis of colon cancer. Br J Cancer. 79:354–359. 1999. View Article : Google Scholar : PubMed/NCBI
32.	Maclauchlan S, Skokos EA, Agah A, Zeng J, Tian W, Davidson JM, Bornstein P and Kyriakides TR: Enhanced angiogenesis and reduced contraction in thrombospondin-2-null wounds is associated with increased levels of matrix metalloproteinases-2 and -9, and soluble VEGF. J Histochem Cytochem. 57:301–313. 2009. View Article : Google Scholar : PubMed/NCBI
33.	Kyriakides TR, Tam JW and Bornstein P: Accelerated wound healing in mice with a disruption of the thrombospondin 2 gene. J Invest Dermatol. 113:782–787. 1999. View Article : Google Scholar : PubMed/NCBI
34.	Jameson J and Havran WL: Skin gammadelta T-cell functions in homeostasis and wound healing. Immunol Rev. 215:114–122. 2007. View Article : Google Scholar : PubMed/NCBI
35.	Al-Rawi MAA, Watkins G, Mansel RE and Jiang WG: The effects of interleukin-7 on the lymphangiogenic properties of human endothelial cells. Int J Oncol. 27:721–730. 2005.PubMed/NCBI
36.	Cruikshank W and Little F: lnterleukin-16: the ins and outs of regulating T-cell activation. Crit Rev Immunol. 28:467–483. 2008. View Article : Google Scholar : PubMed/NCBI
37.	Stabile E, Kinnaird T, la Sala A, Hanson SK, Watkins C, Campia U, Shou M, Zbinden S, Fuchs S, Kornfeld H, et al: CD8⁺ T lymphocytes regulate the arteriogenic response to ischemia by infiltrating the site of collateral vessel development and recruiting CD4⁺ mononuclear cells through the expression of interleukin-16. Circulation. 113:118–124. 2006.
38.	Al-Rawi MAA, Rmali K, Watkins G, Mansel RE and Jiang WG: Aberrant expression of interleukin-7 (IL-7) and its signalling complex in human breast cancer. Eur J Cancer. 40:494–502. 2004. View Article : Google Scholar : PubMed/NCBI
39.	Germano G, Allavena P and Mantovani A: Cytokines as a key component of cancer-related inflammation. Cytokine. 43:374–379. 2008. View Article : Google Scholar : PubMed/NCBI
40.	Studebaker AW, Storci G, Werbeck JL, Sansone P, Sasser AK, Tavolari S, Huang T, Chan MWY, Marini FC, Rosol TJ, et al: Fibroblasts isolated from common sites of breast cancer metastasis enhance cancer cell growth rates and invasiveness in an interleukin-6-dependent manner. Cancer Res. 68:9087–9095. 2008. View Article : Google Scholar
41.	Hanahan D and Weinberg RA: The hallmarks of cancer. Cell. 100:57–70. 2000. View Article : Google Scholar
42.	Carlsson A, Wingren C, Ingvarsson J, Ellmark P, Borrebaeck CAK, Baldertorp B, Fernö M and Olsson H: Serum proteome profiling of metastatic breast cancer using recombinant antibody microarrays. Eur J Cancer. 44:472–480. 2008. View Article : Google Scholar : PubMed/NCBI
43.	Gast M-CW, Zapatka M, van Tinteren H, Bontenbal M, Span PN, Tjan-Heijnen VCG, Knol JC, Jimenez CR, Schellens JHM and Beijnen JH: Postoperative serum proteomic profiles may predict recurrence-free survival in high-risk primary breast cancer. J Cancer Res Clin Oncol. 137:1773–1783. 2011. View Article : Google Scholar : PubMed/NCBI
44.	Pietrowska M, Polanska J, Marczak L, Behrendt K, Nowicka E, Stobiecki M, Polanski A, Tarnawski R and Widlak P: Mass spectrometry-based analysis of therapy-related changes in serum proteome patterns of patients with early-stage breast cancer. J Transl Med. 8:662010. View Article : Google Scholar : PubMed/NCBI