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A circulating miRNA signature as a diagnostic biomarker for non-invasive early detection of breast cancer

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Abstract

Novel, non-invasive biomarkers to diagnose breast cancer with high sensitivity and specificity are greatly desired. Circulating microRNAs (miRNAs) show potential for breast cancer detection, but the existing results appear to be mixed. Using microscale serum, we established a novel serum-direct multiplex detection assay based on RT-PCR (SdM-RT-PCR). Ninety-three miRNAs dysregulated or with functions in breast cancer were selected as candidates, and additional 3 miRNAs were chosen as endogenous controls. We first conducted miRNA profiling of these 96 miRNAs by SdM-RT-PCR using the sera of 25 breast cancer patients at diagnosis prior to treatment and 20 age-matched healthy controls. miRNAs showing significantly different expression levels between patients and controls were further analyzed using a logistic regression model. A miRNA signature was validated in an independent set of 128 serum samples composed of 76 breast cancer patients and 52 healthy controls. In the discovery stage, we identified 23 miRNAs as significantly dysregulated in breast cancer patients compared with healthy controls. Of these, 10 miRNAs were previously identified as dysregulated in breast cancer; 14 miRNAs remained significant after P-values were adjusted by both correction methods. Principal component analysis and hierarchical clustering of these miRNAs separated patients from controls. Furthermore, the 3-miRNA signature (miR-199a, miR-29c, and miR-424) with the highest diagnostic accuracy for distinguishing breast cancer patients from controls by ROC curve analysis (AUC = 0.888) was successfully confirmed in the validation set (AUC = 0.901). Our data demonstrate that the SdM-RT-PCR assay is an effective breast cancer profiling method that utilizes very small volumes and is compatible with Biobank. Furthermore, the identified 3-miRNA signature is a promising circulating biomarker for breast cancer diagnosis.

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Abbreviations

AUC:

Area under curve

ER:

Estrogen receptor

HER2:

Human epidermal factor 2

LN:

Lymph node

PR:

Progesterone receptor

ROC:

Receiver operating characteristic

References

  1. Bertos NR, Park M (2011) Breast cancer—one term, many entities? J Clin Invest 121(10):3789–3796

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  2. Jemal A, Bray F, Center MM et al (2011) Global cancer statistics. CA Cancer J Clin 61(2):69–90

    Article  PubMed  Google Scholar 

  3. Maxmen A (2012) The hard facts. Nature 485(7400):S50–S51

    Article  PubMed  Google Scholar 

  4. Mandelblatt JS, Cronin KA, Bailey S et al (2009) Effects of mammography screening under different screening schedules: model estimates of potential benefits and harms. Ann Intern Med 151(10):738–747

    Article  PubMed Central  PubMed  Google Scholar 

  5. Bleyer A, Welch HG (2012) Effect of three decades of screening mammography on breast-cancer incidence. N Engl J Med 367(21):1998–2005

    Article  CAS  PubMed  Google Scholar 

  6. Harris L, Fritsche H, Mennel R et al (2007) American society of clinical oncology 2007 update of recommendations for the use of tumor markers in breast cancer. J Clin Oncol 25(33):5287–5312

    Article  CAS  PubMed  Google Scholar 

  7. Duffy MJ, Evoy D, McDermott EW (2010) CA 15-3: uses and limitation as a biomarker for breast cancer. Clin Chim Acta 411(23–24):1869–1874

    Article  CAS  PubMed  Google Scholar 

  8. Patani N, Martin LA, Dowsett M (2013) Biomarkers for the clinical management of breast cancer: international perspective. Int J Cancer 133(1):1–13

    Article  CAS  PubMed  Google Scholar 

  9. Carney PA, Miglioretti DL, Yankaskas BC et al (2003) Individual and combined effects of age, breast density, and hormone replacement therapy use on the accuracy of screening mammography. Ann Intern Med 138(3):168–175

    Article  PubMed  Google Scholar 

  10. Lewis BP, Burge CB, Bartel DP (2005) Conserved seed pairing, often flanked by adenosines, indicates that thousands of human genes are microRNA targets. Cell 120(1):15–20

    Article  CAS  PubMed  Google Scholar 

  11. Friedman RC, Farh KK, Burge CB et al (2009) Most mammalian mRNAs are conserved targets of microRNAs. Genome Res 19(1):92–105

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  12. Karp X, Ambros V (2005) Developmental biology. Encountering microRNAs in cell fate signaling. Science 310(5752):1288–1289

    Article  CAS  PubMed  Google Scholar 

  13. Lu J, Getz G, Miska EA et al (2005) MicroRNA expression profiles classify human cancers. Nature 435(7043):834–838

    Article  CAS  PubMed  Google Scholar 

  14. Mulrane L, McGee SF, Gallagher WM et al (2013) miRNA dysregulation in breast cancer. Cancer Res 73(22):6554–6562

    Article  CAS  PubMed  Google Scholar 

  15. Volinia S, Galasso M, Sana ME et al (2012) Breast cancer signatures for invasiveness and prognosis defined by deep sequencing of microRNA. Proc Natl Acad Sci USA 109(8):3024–3029

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  16. Andorfer CA, Necela BM, Thompson EA et al (2011) MicroRNA signatures: clinical biomarkers for the diagnosis and treatment of breast cancer. Trends Mol Med 17(6):313–319

    Article  CAS  PubMed  Google Scholar 

  17. Chen X, Ba Y, Ma L et al (2008) Characterization of microRNAs in serum: a novel class of biomarkers for diagnosis of cancer and other diseases. Cell Res 18(10):997–1006

    Article  CAS  PubMed  Google Scholar 

  18. Lawrie CH, Gal S, Dunlop HM et al (2008) Detection of elevated levels of tumour-associated microRNAs in serum of patients with diffuse large B-cell lymphoma. Br J Haematol 141(5):672–675

    Article  PubMed  Google Scholar 

  19. Mitchell PS, Parkin RK, Kroh EM et al (2008) Circulating microRNAs as stable blood-based markers for cancer detection. Proc Natl Acad Sci USA 105(30):10513–10518

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  20. Le HB, Zhu WY, Chen DD et al (2012) Evaluation of dynamic change of serum miR-21 and miR-24 in pre- and post-operative lung carcinoma patients. Med Oncol 29(5):3190–3197

    Article  CAS  PubMed  Google Scholar 

  21. Zen K, Zhang CY (2012) Circulating microRNAs: a novel class of biomarkers to diagnose and monitor human cancers. Med Res Rev 32(2):326–348

    Article  PubMed  Google Scholar 

  22. Heneghan HM, Miller N, Kelly R et al (2010) Systemic miRNA-195 differentiates breast cancer from other malignancies and is a potential biomarker for detecting noninvasive and early stage disease. Oncologist 15(7):673–682

    Article  PubMed Central  PubMed  Google Scholar 

  23. Sun Y, Wang M, Lin G et al (2012) Serum microRNA-155 as a potential biomarker to track disease in breast cancer. PLoS One 7(10):e47003

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  24. Roth C, Rack B, Muller V et al (2010) Circulating microRNAs as blood-based markers for patients with primary and metastatic breast cancer. Breast Cancer Res 12(6):R90

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  25. Asaga S, Kuo C, Nguyen T et al (2011) Direct serum assay for microRNA-21 concentrations in early and advanced breast cancer. Clin Chem 57(1):84–91

    Article  CAS  PubMed  Google Scholar 

  26. Schwarzenbach H, Milde-Langosch K, Steinbach B et al (2012) Diagnostic potential of PTEN-targeting miR-214 in the blood of breast cancer patients. Breast Cancer Res Treat 134(3):933–941

    Article  CAS  PubMed  Google Scholar 

  27. Cuk K, Zucknick M, Heil J et al (2012) Circulating microRNAs in plasma as early detection markers for breast cancer. Int J Cancer 132(7):1602–1612

    Article  PubMed  Google Scholar 

  28. Chan M, Liaw CS, Ji SM et al (2013) Identification of circulating microRNA signatures for breast cancer detection. Clin Cancer Res 19(16):4477–4487

    Article  CAS  PubMed  Google Scholar 

  29. Schwarzenbach H, Hoon DS, Pantel K (2011) Cell-free nucleic acids as biomarkers in cancer patients. Nat Rev Cancer 11(6):426–437

    Article  CAS  PubMed  Google Scholar 

  30. Hu Z, Dong J, Wang LE et al (2012) Serum microRNA profiling and breast cancer risk: the use of miR-484/191 as endogenous controls. Carcinogenesis 33(4):828–834

    Article  CAS  PubMed  Google Scholar 

  31. Zhou J, Yu L, Gao X et al (2011) Plasma microRNA panel to diagnose hepatitis B virus-related hepatocellular carcinoma. J Clin Oncol 29(36):4781–4788

    Article  CAS  PubMed  Google Scholar 

  32. Xiang M, Zeng Y, Yang R et al (2014) U6 is not a suitable endogenous control for the quantification of circulating microRNAs. Biochem Biophys Res Commun 454(1):210–214

    Article  CAS  PubMed  Google Scholar 

  33. Godfrey AC, Xu Z, Weinberg CR et al (2013) Serum microRNA expression as an early marker for breast cancer risk in prospectively collected samples from the Sister Study cohort. Breast Cancer Res 15(3):R42

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  34. Foekens JA, Sieuwerts AM, Smid M et al (2008) Four miRNAs associated with aggressiveness of lymph node-negative, estrogen receptor-positive human breast cancer. Proc Natl Acad Sci USA 105(35):13021–13026

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  35. Redova M, Sana J, Slaby O (2013) Circulating miRNAs as new blood-based biomarkers for solid cancers. Futur Oncol 9(3):387–402

    Article  CAS  Google Scholar 

  36. Hu Z, Dong J, Wang LE et al (2012) Serum microRNA profiling and breast cancer risk: the use of miR-484/191 as endogenous controls. Carcinogenesis

  37. Andersen CL, Jensen JL, Orntoft TF (2004) Normalization of real-time quantitative reverse transcription-PCR data: a model-based variance estimation approach to identify genes suited for normalization, applied to bladder and colon cancer data sets. Cancer Res 64(15):5245–5250

    Article  CAS  PubMed  Google Scholar 

  38. Vandesompele J, De Preter K, Pattyn F et al (2002) Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes. Genome Biol 3 (7):RESEARCH0034

  39. Wang SM, Ooi LL, Hui KM (2007) Identification and validation of a novel gene signature associated with the recurrence of human hepatocellular carcinoma. Clin Cancer Res 13(21):6275–6283

    Article  CAS  PubMed  Google Scholar 

  40. Taplin S, Abraham L, Barlow WE et al (2008) Mammography facility characteristics associated with interpretive accuracy of screening mammography. J Natl Cancer Inst 100(12):876–887

    Article  PubMed Central  PubMed  Google Scholar 

  41. Checka CM, Chun JE, Schnabel FR et al (2012) The relationship of mammographic density and age: implications for breast cancer screening. AJR Am J Roentgenol 198(3):W292–W295

    Article  PubMed  Google Scholar 

  42. Britton P, Warwick J, Wallis MG et al (2012) Measuring the accuracy of diagnostic imaging in symptomatic breast patients: team and individual performance. Br J Radiol 85(1012):415–422

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  43. Kirschner MB, Kao SC, Edelman JJ et al (2011) Haemolysis during sample preparation alters microRNA content of plasma. PLoS One 6(9):e24145

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  44. Witwer KW (2015) Circulating microRNA biomarker studies: pitfalls and potential solutions. Clin Chem 61(1):56–63

    Article  CAS  PubMed  Google Scholar 

  45. Shiao SL, Ganesan AP, Rugo HS et al (2011) Immune microenvironments in solid tumors: new targets for therapy. Genes Dev 25(24):2559–2572

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  46. Tan GW, Khoo AS, Tan LP (2015) Evaluation of extraction kits and RT-qPCR systems adapted to high-throughput platform for circulating miRNAs. Sci Rep 5:9430

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  47. Ono S, Oyama T, Lam S et al (2015) A direct plasma assay of circulating microRNA-210 of hypoxia can identify early systemic metastasis recurrence in melanoma patients. Oncotarget 6(9):7053–7064

    Article  PubMed Central  PubMed  Google Scholar 

  48. Wang Y, Gao X, Wei F et al (2014) Diagnostic and prognostic value of circulating miR-21 for cancer: a systematic review and meta-analysis. Gene 533(1):389–397

    Article  CAS  PubMed  Google Scholar 

  49. Shimono Y, Zabala M, Cho RW et al (2009) Downregulation of miRNA-200c links breast cancer stem cells with normal stem cells. Cell 138(3):592–603

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  50. Yan LX, Huang XF, Shao Q et al (2008) MicroRNA miR-21 overexpression in human breast cancer is associated with advanced clinical stage, lymph node metastasis and patient poor prognosis. RNA 14(11):2348–2360

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  51. Drasin DJ, Guarnieri AL, Neelakantan D et al (2015) TWIST1-Induced miR-424 Reversibly Drives Mesenchymal Programming while Inhibiting Tumor Initiation. Cancer Res 75(9):1908–1921

    Article  CAS  PubMed  Google Scholar 

  52. Yi H, Liang B, Jia J et al (2013) Differential roles of miR-199a-5p in radiation-induced autophagy in breast cancer cells. FEBS Lett 587(5):436–443

    Article  CAS  PubMed  Google Scholar 

  53. Nygren MK, Tekle C, Ingebrigtsen VA et al (2014) Identifying microRNAs regulating B7-H3 in breast cancer: the clinical impact of microRNA-29c. Br J Cancer 110(8):2072–2080

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  54. Turchinovich A, Burwinkel B (2012) Distinct AGO1 and AGO2 associated miRNA profiles in human cells and blood plasma. RNA Biol 9(8):1066–1075

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  55. Turchinovich A, Weiz L, Langheinz A et al (2011) Characterization of extracellular circulating microRNA. Nucleic Acids Res 39(16):7223–7233

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  56. Pigati L, Yaddanapudi SC, Iyengar R et al (2010) Selective release of microRNA species from normal and malignant mammary epithelial cells. PLoS One 5(10):e13515

    Article  PubMed Central  PubMed  Google Scholar 

  57. Palma J, Yaddanapudi SC, Pigati L et al (2012) MicroRNAs are exported from malignant cells in customized particles. Nucleic Acids Res 40(18):9125–9138

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  58. Eichelser C, Stuckrath I, Muller V et al (2014) Increased serum levels of circulating exosomal microRNA-373 in receptor-negative breast cancer patients. Oncotarget 5(20):9650–9663

    Article  PubMed Central  PubMed  Google Scholar 

  59. Wang F, Zheng Z, Guo J et al (2010) Correlation and quantitation of microRNA aberrant expression in tissues and sera from patients with breast tumor. Gynecol Oncol 119(3):586–593

    Article  CAS  PubMed  Google Scholar 

  60. Girardi C, De Pitta C, Casara S et al (2014) Integration analysis of microRNA and mRNA expression profiles in human peripheral blood lymphocytes cultured in modeled microgravity. Biomed Res Int 2014:296747

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  61. Wang H, Tan G, Dong L et al (2012) Circulating MiR-125b as a marker predicting chemoresistance in breast cancer. PLoS One 7(4):e34210

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  62. Mar-Aguilar F, Mendoza-Ramirez JA, Malagon-Santiago I et al (2013) Serum circulating microRNA profiling for identification of potential breast cancer biomarkers. Dis Markers 34(3):163–169

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  63. Madhavan D, Zucknick M, Wallwiener M et al (2012) Circulating microRNAs as surrogate markers for circulating tumour cells and prognostic markers in metastatic breast cancer. Clin Cancer Res 18(21):5972–5982

    Article  CAS  PubMed  Google Scholar 

  64. Liu J, Mao Q, Liu Y et al (2013) Analysis of miR-205 and miR-155 expression in the blood of breast cancer patients. Chin J Cancer Res 25(1):46–54

    PubMed Central  PubMed  Google Scholar 

  65. Sochor M, Basova P, Pesta M et al (2014) Oncogenic microRNAs: miR-155, miR-19a, miR-181b, and miR-24 enable monitoring of early breast cancer in serum. BMC Cancer 14:448

    Article  PubMed Central  PubMed  Google Scholar 

  66. Shin VY, Siu JM, Cheuk I et al (2015) Circulating cell-free miRNAs as biomarker for triple-negative breast cancer. Br J Cancer 112(11):1751–1759

    Article  CAS  PubMed  Google Scholar 

  67. Shen J, Hu Q, Schrauder M et al (2014) Circulating miR-148b and miR-133a as biomarkers for breast cancer detection. Oncotarget 5(14):5284–5294

    Article  PubMed Central  PubMed  Google Scholar 

  68. Chen D, Goswami CP, Burnett RM et al (2014) Cancer affects microRNA expression, release, and function in cardiac and skeletal muscle. Cancer Res 74(16):4270–4281

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  69. Schrauder MG, Strick R, Schulz-Wendtland R et al (2012) Circulating Micro-RNAs as Potential Blood-Based Markers for Early Stage Breast Cancer Detection. PLoS One 7(1):e29770

    Article  PubMed Central  CAS  PubMed  Google Scholar 

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Acknowledgments

This study was supported by the National High-Tech R&D Program of China (2012AA022501), the National Natural Science Foundation of China (81170097, 81373070), the National Natural Science Foundation of Jiangsu (BK2011381), and the 985 Project of Peking University.

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Authors and Affiliations

  1. Institute of Molecular Medicine, Peking University, 5 Yiheyuan Rd., Beijing, 100871, People’s Republic of China

    Lei Zhang, Yidi Wu, Deyao Zhao, Xiaoxia Wang, Huiqing Cao & Zicai Liang

  2. Key Laboratory of Carcinogenesis and Translational Research, Breast Center, Peking University Cancer Hospital & Institute, 52 Fucheng Rd., Beijing, 100142, People’s Republic of China

    Ye Xu & Yuntao Xie

  3. Suzhou Ribo Life Science Co., Ltd, Suzhou, Jiangsu, People’s Republic of China

    Xingyu Jin

  4. Division of Prevention and Community Health, National Center for Cardiovascular Diseases, Beijing Fuwai Hospital, Beijing, People’s Republic of China

    Zengwu Wang

  5. siRNA Biotechnology Research Institute, Kunshan Industrial Technology Research Institute, Suzhou, Jiangsu, People’s Republic of China

    Gang Chen & Deyu Li

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  1. Lei Zhang
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  2. Ye Xu
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  3. Xingyu Jin
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  4. Zengwu Wang
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  5. Yidi Wu
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  7. Gang Chen
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  9. Xiaoxia Wang
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  10. Huiqing Cao
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  11. Yuntao Xie
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  12. Zicai Liang
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Correspondence to Yuntao Xie or Zicai Liang.

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Zhang, L., Xu, Y., Jin, X. et al. A circulating miRNA signature as a diagnostic biomarker for non-invasive early detection of breast cancer. Breast Cancer Res Treat 154, 423–434 (2015). https://doi.org/10.1007/s10549-015-3591-0

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