J Breast Cancer.  2019 Dec;22(4):579-586. 10.4048/jbc.2019.22.e57.

A Validation Study of a Multiple Reaction Monitoring-Based Proteomic Assay to Diagnose Breast Cancer

• Kim Y
• Kang UB
• Kim S
• Lee HB
• Moon HG
• Han W
• Noh DY

• KMID: 2470894
• DOI: http://doi.org/10.4048/jbc.2019.22.e57

Abstract

PURPOSE
Currently, the standard screening tool for breast cancer is screening mammography. There have been many efforts to develop a blood-based diagnostic assay for breast cancer diagnosis; however, none have been approved for clinical use at this time. The purpose of this study was to determine the accuracy of a novel blood-based proteomic test for aiding breast cancer diagnosis in a relatively large cohort of cancer patients.
METHODS
A blood-based test using multiple reaction monitoring (MRM) measured by mass spectrometry to quantify 3 peptides (apolipoprotein C-1, carbonic anhydrase 1, and neural cell adhesion molecule L1-like protein) present in human plasma was investigated. A total of 1,129 blood samples from 575 breast cancer patients, 454 healthy controls, and 100 patients with other malignancies were used to verify and optimize the assay.
RESULTS
The diagnostic sensitivity, specificity, and accuracy of the MRM-based proteomic assay were 71.6%, 85.3%, and 77%, respectively; the area under the receiver operating characteristic curve was 0.8323. The proteomic assay did not demonstrate diagnostic accuracy in patients with other types of malignancies including thyroid, pancreatic, lung, and colon cancers. The diagnostic performance of the proteomic assay was not associated with the timing of blood sampling before or after anesthesia.
CONCLUSION
The data demonstrated that an MRM-based proteomic assay that measures plasma levels of three specific peptides can be a useful tool for breast cancer screening and its accuracy is cancer-type specific.

Keyword

Biomarkers; Breast neoplasms; Diagnosis; Blood proteins; Proteomics

MeSH Terms

Anesthesia
Biomarkers
Blood Proteins
Breast Neoplasms*
Breast*
Carbonic Anhydrases
Cohort Studies
Colonic Neoplasms
Diagnosis
Humans
Lung
Mammography
Mass Screening
Mass Spectrometry
Neural Cell Adhesion Molecules
Peptides
Plasma
Proteomics
ROC Curve
Sensitivity and Specificity
Thyroid Gland
Biomarkers
Blood Proteins
Carbonic Anhydrases
Neural Cell Adhesion Molecules
Peptides

Reference

1. GLOBOCAN. Estimated cancer incidence, mortality and prevalence worldwide in 2012. Lyon: International Agency for Research on Cancer;2012. Accessed September 1st, 2016. http://globocan.iarc.fr/Pages/fact_sheets_cancer.

2. Jung KW, Won YJ, Kong HJ, Lee ES. Community of Population-Based Regional Cancer Registries. Cancer statistics in Korea: incidence, mortality, survival, and prevalence in 2015. Cancer Res Treat. 2018; 50:303–316.

3. Statistics Korea. KOrean Statistical information Service. Daejeon: Statistics Korea;2019. Accessed August 14th, 2018. http://kosis.kr.

4. Humphrey LL, Helfand M, Chan BK, Woolf SH. Breast cancer screening: a summary of the evidence for the U.S. Preventive Services Task Force. Ann Intern Med. 2002; 137:347–360.

5. Berrington de González A. Estimates of the potential risk of radiation-related cancer from screening in the UK. J Med Screen. 2011; 18:163–164.

6. de Gelder R, Draisma G, Heijnsdijk EA, de Koning HJ. Population-based mammography screening below age 50: balancing radiation-induced vs prevented breast cancer deaths. Br J Cancer. 2011; 104:1214–1220.

7. Shin HJ, Ko ES, Yi A. Breast cancer screening in Korean woman with dense breast tissue. J Korean Soc Radiol. 2015; 73:279–286.

8. Kim SH, Kim MH, Oh KK. Analysis and comparison of breast density according to age on mammogram between Korean and western women. J Korean Radiol Soc. 2000; 42:1009–1014.

9. Nam SJ. Screening and diagnosis for breast cancers. J Korean Med Assoc. 2009; 52:946–951.

10. Mandelson MT, Oestreicher N, Porter PL, White D, Finder CA, Taplin SH, et al. Breast density as a predictor of mammographic detection: comparison of interval- and screen-detected cancers. J Natl Cancer Inst. 2000; 92:1081–1087.

11. Bleyer A, Welch HG. Effect of three decades of screening mammography on breast-cancer incidence. N Engl J Med. 2012; 367:1998–2005.

12. Welch HG, Passow HJ. Quantifying the benefits and harms of screening mammography. JAMA Intern Med. 2014; 174:448–454.

13. Lee HB, Kang UB, Moon HG, Lee J, Lee KM, Yi M, et al. Development and validation of a novel plasma protein signature for breast cancer diagnosis by using multiple reaction monitoring-based mass spectrometry. Anticancer Res. 2015; 35:6271–6279.

14. Li J, Shi K, Sabet ZF, Fu W, Zhou H, Xu S, et al. New power of self-assembling carbonic anhydrase inhibitor: short peptide-constructed nanofibers inspire hypoxic cancer therapy. Sci Adv. 2019; 5:eaax0937.

15. Supuran CT, Winum JY. Carbonic anhydrase IX inhibitors in cancer therapy: an update. Future Med Chem. 2015; 7:1407–1414.

16. Drummond F, Sowden J, Morrison K, Edwards YH. The caudal-type homeobox protein Cdx-2 binds to the colon promoter of the carbonic anhydrase 1 gene. Eur J Biochem. 1996; 236:670–681.

17. He LH, Ma Q, Shi YH, Ge J, Zhao HM, Li SF, et al. CHL1 is involved in human breast tumorigenesis and progression. Biochem Biophys Res Commun. 2013; 438:433–438.

18. Cohen M, Yossef R, Erez T, Kugel A, Welt M, Karpasas MM, et al. Serum apolipoproteins C-I and C-III are reduced in stomach cancer patients: results from MALDI-based peptidome and immuno-based clinical assays. PLoS One. 2011; 6:e14540.

19. Sun Y, Zhang J, Guo F, Zhao W, Zhan Y, Liu C, et al. Identification of apolipoprotein C-I peptides as a potential biomarker and its biological roles in breast cancer. Med Sci Monit. 2016; 22:1152–1160.

20. Yang Y, Zhao S, Fan Y, Zhao F, Liu Q, Hu W, et al. Detection and identification of potential biomarkers of non-small cell lung cancer. Technol Cancer Res Treat. 2009; 8:455–466.

21. Takano S, Yoshitomi H, Togawa A, Sogawa K, Shida T, Kimura F, et al. Apolipoprotein C-1 maintains cell survival by preventing from apoptosis in pancreatic cancer cells. Oncogene. 2008; 27:2810–2822.

22. Weigel S, Heindel W, Heidrich J, Hense HW, Heidinger O. Digital mammography screening: sensitivity of the programme dependent on breast density. Eur Radiol. 2017; 27:2744–2751.

23. Carney PA, Miglioretti DL, Yankaskas BC, Kerlikowske K, Rosenberg R, Rutter CM, et al. Individual and combined effects of age, breast density, and hormone replacement therapy use on the accuracy of screening mammography. Ann Intern Med. 2003; 138:168–175.

24. Rafferty EA, Durand MA, Conant EF, Copit DS, Friedewald SM, Plecha DM, et al. Breast cancer screening using tomosynthesis and digital mammography in dense and nondense breasts. JAMA. 2016; 315:1784–1786.

25. Youn I, Choi S, Kook SH, Choi YJ. Mammographic breast density evaluation in Korean Women using fully automated volumetric assessment. J Korean Med Sci. 2016; 31:457–462.

26. Núñez C. Blood-based protein biomarkers in breast cancer. Clin Chim Acta. 2019; 490:113–127.