Abstract
Improved diagnostic screening has led to earlier detection of many tumors, but screening may still miss many aggressive tumor types. Proteomic and genomic profiling studies of breast cancer samples have identified tumor markers that may help improve screening for more aggressive, rapidly growing breast cancers. To identify potential blood-based biomarkers for the early detection of breast cancer, we assayed serum samples via matrix-assisted laser desorption ionization–time of flight mass spectrometry from a rat model of mammary carcinogenesis. We found elevated levels of a fragment of the protein dermcidin (DCD) to be associated with early progression of N-methylnitrosourea-induced breast cancer, demonstrating significance at weeks 4 (p = 0.045) and 5 (p = 0.004), a time period during which mammary pathologies rapidly progress from ductal hyperplasia to adenocarcinoma. The highest serum concentrations were observed in rats bearing palpable mammary carcinomas. Increased DCD was also detected with immunoblotting methods in 102 serum samples taken from women just prior to breast cancer diagnosis. To validate these findings in a larger population, we applied a 32-gene in vitro DCD response signature to a dataset of 295 breast tumors and assessed correlation with intrinsic breast cancer subtypes and overall survival. The DCD-derived gene signature was significantly associated with subtype (p < 0.001) and poorer overall survival [HR (95 % CI) = 1.60 (1.01–2.51), p = 0.044]. In conclusion, these results present novel evidence that DCD levels may increase in early carcinogenesis, particularly among more aggressive forms of breast cancer.
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Buist D, Bosco J, Silliman RA, Gold HT (2013) Long-term surveillance mammography and mortality in older women with a history of early stage invasive breast cancer. Breast Cancer Res 142(1):153–63. doi:10.1080/10810730.2013.825673
Anderson WF, Chen BE, Brinton LA, Devesa SS (2007) Qualitative age interactions (or effect modification) suggest different cancer pathways for early-onset and late-onset breast cancers. Cancer Causes Control 18:1187–1198. doi:10.1007/s10552-007-9057-x
Collett K, Stefansson IM, Eide J et al (2005) A basal epithelial phenotype is more frequent in interval breast cancers compared with screen detected tumors. Cancer Epidemiol Biomarkers Prev 14:1108–1112. doi:10.1158/1055-9965.EPI-04-0394
Saunders NA, Simpson F, Thompson EW et al (2012) Role of intratumoural heterogeneity in cancer drug resistance: molecular and clinical perspectives. EMBO Mol Med 4:675–684. doi:10.1002/emmm.201101131
Marić P, Ozretić P, Levanat S et al (2011) Tumor markers in breast cancer-evaluation of their clinical usefulness. Coll Antropol 35:241–247
Mannello F, Medda V, Tonti GA (2009) Protein profile analysis of the breast microenvironment to differentiate healthy women from breast cancer patients. Expert Rev Proteomics 6:43–60. doi:10.1586/14789450.6.1.43
Ebeling FG, Stieber P, Untch M et al (2002) Serum CEA and CA 15-3 as prognostic factors in primary breast cancer. Br J Cancer 86:1217–1222. doi:10.1038/sj/bjc/6600248
Gion M, Mione R, Leon AE, Dittadi R (1999) Comparison of the diagnostic accuracy of CA27.29 and CA15.3 in primary breast cancer. Clin Chem 45:630–637
Brauer HA, Libby TE, Mitchell BL et al (2011) Cruciferous vegetable supplementation in a controlled diet study alters the serum peptidome in a GSTM1-genotype dependent manner. Nutr J 10:11. doi:10.1186/1475-2891-10-11
Mitchell BL, Yasui Y, Lampe JW et al (2005) Evaluation of matrix-assisted laser desorption/ionization-time of flight mass spectrometry proteomic profiling: identification of alpha 2-HS glycoprotein B-chain as a biomarker of diet. Proteomics 5:2238–2246. doi:10.1002/pmic.200401099
Bertucci F, Goncalves A (2008) Clinical proteomics and breast cancer: strategies for diagnostic and therapeutic biomarker discovery. Future Oncol 4:271–287. doi:10.2217/14796694.4.2.271
Li J, Orlandi R, White CN et al (2005) Independent validation of candidate breast cancer serum biomarkers identified by mass spectrometry. Clin Chem 51:2229–2235. doi:10.1373/clinchem.2005.052878
Belluco C, Petricoin EF, Mammano E et al (2007) Serum proteomic analysis identifies a highly sensitive and specific discriminatory pattern in stage 1 breast cancer. Ann Surg Oncol 14:2470–2476. doi:10.1245/s10434-007-9354-3
van Winden AW, Gast M-CW, Beijnen JH et al (2009) Validation of previously identified serum biomarkers for breast cancer with SELDI-TOF MS: a case control study. BMC Med Genomics 2:4. doi:10.1186/1755-8794-2-4
van Winden AO, Rodenburg W, Pennings JLA et al (2012) A bead-based multiplexed immunoassay to evaluate breast cancer biomarkers for early detection in pre-diagnostic serum. IJMS 13:13587–13604. doi:10.3390/ijms131013587
Thompson HJ, McGinley JN, Rothhammer K, Singh M (1995) Rapid induction of mammary intraductal proliferations, ductal carcinoma in situ and carcinomas by the injection of sexually immature female rats with 1-methyl-1-nitrosourea. Carcinogenesis 16:2407–2411
Thompson HJ, Adlakha H (1991) Dose-responsive induction of mammary gland carcinomas by the intraperitoneal injection of 1-methyl-1-nitrosourea. Cancer Res 51:3411–3415
Randolph TW, Yasui Y (2006) Multiscale processing of mass spectrometry data. Biometrics 62:589–597. doi:10.1111/j.1541-0420.2005.00504.x
Yasui Y, Pepe M, Thompson ML et al (2003) A data-analytic strategy for protein biomarker discovery: profiling of high-dimensional proteomic data for cancer detection. Biostatistics 4:449–463. doi:10.1093/biostatistics/4.3.449
Yasui Y, McLerran D, Adam B-L et al (2003) An automated peak identification/calibration procedure for high-dimensional protein measures from mass spectrometers. J Biomed Biotechnol 2003:242–248
Liska J, Galbavy S, Macejova D, Zlatos J (2000) Histopathology of mammary tumours in female rats treated with 1-methyl-1-nitrosourea. Endocr Regul 34(2):91–96
Lowrie AG, Dickinson P, Wheelhouse N et al (2011) Proteolysis-inducing factor core peptide mediates dermcidin-induced proliferation of hepatic cells through multiple signalling networks. Int J Oncol 39:709–718. doi:10.3892/ijo 2011.1064
Creighton CJ, Casa A, Lazard Z et al (2008) Insulin-like growth factor-I activates gene transcription programs strongly associated with poor breast cancer prognosis. J Clin Oncol 26:4078–4085. doi:10.1200/JCO.2007.13.4429
Fan C, Prat A, Parker JS et al (2011) Building prognostic models for breast cancer patients using clinical variables and hundreds of gene expression signatures. BMC Med Genomics 4:3. doi:10.1186/1755-8794-4-3
Anderson WF, Matsuno R (2006) Breast cancer heterogeneity: a mixture of at least two main types? JNCI J Natl Cancer Inst 98:948–951. doi:10.1093/jnci/djj295
Anders CK, Carey LA (2009) Biology, metastatic patterns, and treatment of patients with triple-negative breast cancer. Clin Breast Cancer 9:S73–S81. doi:10.3816/CBC.2009.s.008
Stewart GD, Skipworth RJE, Pennington CJ et al (2008) Variation in dermcidin expression in a range of primary human tumours and in hypoxic/oxidatively stressed human cell lines. Br J Cancer 99:126–132. doi:10.1038/sj.bjc.6604458
Stewart GD, Lowrie AG, Riddick ACP et al (2007) Dermcidin expression confers a survival advantage in prostate cancer cells subjected to oxidative stress or hypoxia. Prostate 67:1308–1317. doi:10.1002/pros.20618
Porter D, Weremowicz S, Chin K et al (2003) A neural survival factor is a candidate oncogene in breast cancer. Proc Natl Acad Sci USA 100:10931–10936. doi:10.1073/pnas.1932980100
Perou CM, Sørlie T, Eisen MB, van de Rijn M et al (2000) Molecular portraits of human breast tumours. Nature 406:747–752. doi:10.1038/35021093
Acknowledgments
This work was supported by the National Institutes of Health through the following grants: Women's Health Initiative (U01 CA152637), Early Detection Research Network (N01-WH-74313), and Cardiovascular Health Study (R01-CA116393). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
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The authors declare that they have no conflict of interest or financial relationship with the organizations that sponsored the research.
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10549_2014_2880_MOESM1_ESM.eps
Supplemental Fig. 1 (A) Map of DCD sequence and known peptide sequence, brackets indicate unique peptides identified using TOF/TOF methods. (B) Schematic of carboxypeptidase digestion of peak 4452.42 m/z demonstrates each stage of the cleavage, leaving three fragments (4338.32 m/z, 4209.2 m/z, and 4081.03 m/z) that are consistent with the loss of asparagine, glutamic acid and lysine from the C-terminus. The peak of interest identified by MALDI-TOF MS (4209.2 m/z) appeared as an intermediate fragment and the sequence identified is also present in DCD, overlapping with one of the TOF/TOF peptides. (C) Proposed DCD peptide sequence based on molecular weight, TOF/TOF and carboxypeptidase digestion
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Brauer, H.A., D’Arcy, M., Libby, T.E. et al. Dermcidin expression is associated with disease progression and survival among breast cancer patients. Breast Cancer Res Treat 144, 299–306 (2014). https://doi.org/10.1007/s10549-014-2880-3
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DOI: https://doi.org/10.1007/s10549-014-2880-3