Journal of Cancer Research and Clinical Oncology

, Volume 136, Issue 8, pp 1243–1254 | Cite as

Detection and identification of potential biomarkers of breast cancer

  • Yuxia Fan
  • Jiachen Wang
  • Yang Yang
  • Qiuliang Liu
  • Yingzhong Fan
  • Jiekai Yu
  • Shu Zheng
  • Mengquan Li
  • Jiaxiang Wang
Original Paper

Abstract

Purpose

Noninvasive and convenient biomarkers for early diagnosis of breast cancer remain an urgent need. The aim of this study was to discover and identify potential protein biomarkers specific for breast cancer.

Methods

Two hundred and eighty-two (282) serum samples with 124 breast cancer and 158 controls were randomly divided into a training set and a blind-testing set. Serum proteomic profiles were analyzed using SELDI-TOF-MS. Candidate biomarkers were purified by HPLC, identified by LC-MS/MS and validated using ProteinChip immunoassays and western blot technique.

Results

A total of 3 peaks (m/z with 6,630, 8,139 and 8,942 Da) were screened out by support vector machine to construct the classification model with high discriminatory power in the training set. The sensitivity and specificity of the model were 96.45 and 94.87%, respectively, in the blind-testing set. The candidate biomarker with m/z of 6,630 Da was found to be down-regulated in breast cancer patients, and was identified as apolipoprotein C-I. Another two candidate biomarkers (8,139, 8,942 Da) were found up-regulated in breast cancer and identified as C-terminal-truncated form of C3a and complement component C3a, respectively. In addition, the level of apolipoprotein C-I progressively decreased with the clinical stages I, II, III and IV, and the expression of C-terminal-truncated form of C3a and complement component C3a gradually increased in higher stages.

Conclusions

We have identified a set of biomarkers that could discriminate breast cancer from non-cancer controls. An efficient strategy, including SELDI-TOF-MS analysis, HPLC purification, MALDI-TOF-MS trace and LC-MS/MS identification, has been proved very successful.

Keywords

Biomarker Breast cancer LC-MS/MS MALDI-TOF-MS Proteomics SELDI-TOF-MS 

References

  1. Agyei Frempong MT, Darko E, Addai BW (2008) The use of carbohydrate antigen (CA) 15-3 as a tumor marker in detecting breast cancer. Pak J Biol Sci 11:1945–1948CrossRefPubMedGoogle Scholar
  2. Belluco C, Petricoin EF, Mammano E, Facchiano F, Ross-Rucker S, Nitti D, Di Maggio C, Liu C, Lise M, Liotta LA, Whiteley G (2007) Serum proteomic analysis identifies a highly sensitive and specific discriminatory pattern in stage 1 breast cancer. Ann Surg Oncol 14:2470–2476CrossRefPubMedGoogle Scholar
  3. Bjorge L, Hakulinen J, Vintermyr OK, Jarva H, Jensen TS, Iversen OE, Meri S (2005) Ascitic complement system in ovarian cancer. Br J Cancer 92:895–905CrossRefPubMedGoogle Scholar
  4. Cherel P, Hagay C, Benaim B, De Maulmont C, Engerand S, Langer A, Talma V (2008) Mammographic evaluation of dense breasts: techniques and limits. J Radiol 89:1156–1168CrossRefPubMedGoogle Scholar
  5. De Gelder R, van As E, Tilanus-Linthorst MM, Bartels CC, Boer R, Draisma G, de Koning HJ (2008) Breast cancer screening: evidence for false reassurance? Int J Cancer 123:680–686CrossRefPubMedGoogle Scholar
  6. Ding J, Warren R, Warsi I, Day N, Thompson D, Brady M, Tromans C, Highnam R, Easton D (2008) Evaluating the effectiveness of using standard mammogram form to predict breast cancer risk: case-control study. Cancer Epidemiol Biomarkers Prev 17:1074–1081CrossRefPubMedGoogle Scholar
  7. Fang J, Dong Y, Williams TD, Lushington GH (2008) Feature selection in validating mass spectrometry database search results. J Bioinform Comput Biol 6:223–240CrossRefPubMedGoogle Scholar
  8. Grabiec M, Nowicki P, Walentowicz M, Grezlikowska U, Mierzwa T, Chmielewska W (2005) Role of Ca-125 in the differential diagnosis of adnexal mass in breast cancer patients. Ginekol Pol 76:371–376PubMedGoogle Scholar
  9. Hansh SM, Pitteri SJ, Faca VM (2008) Mining the plasma proteome for cancer biomarkers. Nature 452:571–579CrossRefGoogle Scholar
  10. Hu Y, Zhang SZ, Yu JK, Liu J, Zheng S (2005a) SELDI-TOF-MS: the proteomics and bioinformatics approaches in the diagnosis of breast cancer. Breast 14:250–255CrossRefPubMedGoogle Scholar
  11. Hu Y, Zhang SZ, Yu JK, Liu J, Zheng S, Hu X (2005b) Diagnostic application of serum protein pattern and artificial neural network software in breast cancer. Ai Zheng 24:67–71PubMedGoogle Scholar
  12. Hundt S, Haug U, Brenner H (2007) Blood markers for early detection of colorectal cancer: a systematic review. Cancer Epidemiol Biomarkers Prev 16:1935–1953CrossRefPubMedGoogle Scholar
  13. Jemal A, Siegel R, Ward E, Hao Y, Xu J, Murray T, Thun MJ (2008) Cancer statistics, 2008. CA Cancer J Clin 58:71–96CrossRefPubMedGoogle Scholar
  14. Kroman NT, Grinsted P, Nielsen NS (2007) Symptoms and diagnostic work-up in breast cancer. Ugeskr Laeger 169:2980–2981PubMedGoogle Scholar
  15. Laronga C, Becker S, Watson P, Gregory B, Cazares L, Lynch H, Perry RR, Wright GL Jr, Drake RR, Semmes OJ (2003) SELDI-TOF serum profiling for prognostic and diagnostic classification of breast cancers. Dis Markers 19:229–238PubMedGoogle Scholar
  16. Lee IN, Chen CH, Sheu JC, Lee HS, Huang GT, Chen DS, Yu CY, Wen CL, Lu FJ, Chow LP (2006) Identification of complement C3a as a candidate biomarker in human chronic hepatitis C and HCV-related hepatocellular carcinoma using a proteomics approach. Proteomics 6:2865–2873CrossRefPubMedGoogle Scholar
  17. Li J, Zhang Z, Rosenzweig J, Wang YY, Chan DW (2002) Proteomics and bioinformatics approaches for identification of serum biomarkers to detect breast cancer. Clin Chem 48:1296–1304PubMedGoogle Scholar
  18. Liu D, Cao L, Yu J, Que R, Jiang W, Zhou Y, Zhu L (2008) Diagnosis of pancreatic adenocarcinoma using Protein Chip technology. Pancreatology 9:127–135CrossRefPubMedGoogle Scholar
  19. Luo J, Qian JH, Yu JK, Zheng S, Xie X, Lu WG (2008) Discovery of altered protein profiles in epithelial ovarian carcinogenesis by SELDI mass spectrometry. Eur J Gynaecol Oncol 29:233–238PubMedGoogle Scholar
  20. Markiewski MM, Mastellos D, Tudoran R, De Angelis RA, Strey CW, Franchini S, Wetsel RA, Erdei A, Lambris JD (2004) C3a and C3b activation products of the third component of complement (C3) are critical for normal liver recovery after toxic injury. J Immunol 173:747–754PubMedGoogle Scholar
  21. Matheny ME, Resnic FS, Arora N, Ohno-Machado L (2007) Effects of SVM parameter optimization on discrimination and calibration for post-procedural PCI mortality. J Biomed Inform 40:688–697CrossRefPubMedGoogle Scholar
  22. Maurya P, Meleady P, Dowling P, Clynes M (2007) Proteomic approaches for serum biomarker discovery in cancer. Anticancer Res 27:1247–1255PubMedGoogle Scholar
  23. Redondo M, Rivas-Ruiz F, Guzman-Soler MC, Labajos C (2008) Monitoring indicators of health care quality by means of a hospital register of tumours. J Eval Clin Pract 14:1026–1030CrossRefPubMedGoogle Scholar
  24. Sahu A, Lambris JD (2001) Structure and biology of complement protein C3, a connecting link between innate and acquired immunity. Immunol Rev 180:35–48CrossRefPubMedGoogle Scholar
  25. Skytt A, Thysell E, Stattin P, Stenman UH, Antti H, Wikstrom P (2007) SELDI-TOF MS versus prostate specific antigen analysis of prospective plasma samples in a nested case-control study of prostate cancer. Int J Cancer 121:615–620CrossRefPubMedGoogle Scholar
  26. Somorjai RL, Dolenko B, Baumgartner R (2003) Class prediction and discovery using gene microarray and proteomics mass spectroscopy data: curses, caveats, cautions. Bioinformatics 19:1484–1491CrossRefPubMedGoogle Scholar
  27. Song G, Ouyang G, Bao S (2005) The activation of Akt/PKB signaling pathway and cell survival. J Cell Mol Med 9:59–71CrossRefPubMedGoogle Scholar
  28. Tomosugi N (2004) Discovery of disease biomarkers by ProteinChip system; clinical proteomics as noninvasive diagnostic tool. Rinsho Byori 52:973–979PubMedGoogle Scholar
  29. Wang XD, Wang JQ (2004) A survey on support vector machines training and testing algorithms. Comput Eng Appl 13:75–79Google Scholar
  30. Wang J, Zhang X, Ge X, Guo H, Xiong G, Zhu Y (2008) Proteomic studies of early-stage and advanced ovarian cancer patients. Gynecol Oncol 111:111–119CrossRefPubMedGoogle Scholar
  31. Zheng H, Luo RC (2005) Diagnostic value of combined detection of TPS, CA153 and CEA in breast cancer. Di Yi Jun Yi Da Xue Xue Bao 25:1293–1298PubMedGoogle Scholar
  32. Zhu W, Michael CW (2007) WT1, monoclonal CEA, TTF1, and CA125 antibodies in the differential diagnosis of lung, breast, and ovarian adenocarcinomas in serous effusions. Diagn Cytopathol 35:370–375CrossRefPubMedGoogle Scholar

Copyright information

© Springer-Verlag 2010

Authors and Affiliations

  • Yuxia Fan
    • 1
  • Jiachen Wang
    • 1
  • Yang Yang
    • 2
  • Qiuliang Liu
    • 1
  • Yingzhong Fan
    • 1
  • Jiekai Yu
    • 3
  • Shu Zheng
    • 3
  • Mengquan Li
    • 1
  • Jiaxiang Wang
    • 1
  1. 1.Department of General Surgery, The First Affiliated HospitalZhengzhou UniversityZhengzhouPeople’s Republic of China
  2. 2.Department of Thoracic Surgery, Union Hospital, Tongji Medical CollegeHuazhong University of Science and TechnologyWuhanPeople’s Republic of China
  3. 3.Institute of Cancer, The Second Affiliated Hospital, College of MedicineZhejiang UniversityHangzhouPeople’s Republic of China

Personalised recommendations