Advertisement

Cancer and Metastasis Reviews

, Volume 32, Issue 1–2, pp 289–302 | Cite as

Hide and seek: tell-tale signs of breast cancer lurking in the blood

  • David S. Guttery
  • Kevin Blighe
  • Karen Page
  • Stephanie D. Marchese
  • Allison Hills
  • R. Charles Coombes
  • Justin Stebbing
  • Jacqueline A. Shaw
NON-THEMATIC REVIEW

Abstract

Breast cancer treatment is improving due to the introduction of new drugs, guided by molecular testing of the primary tumour for mutations/oncogenic drivers (e.g. HER2 gene amplification). However, tumour tissue is not always available for molecular analysis, intra-tumoural heterogeneity is common and the “cancer genome” is known to evolve with time, particularly following treatment as resistance develops. After resection, those patients with only residual micrometastases are likely to be cured but those with radiologically detectable overt disease are not. Thus, the discovery of blood test(s) that could (1) alert clinicians to early primary or recurrent disease and (2) monitor response to treatment could impact significantly on mortality. Towards this, we and others have focused on molecular profiling of circulating nucleic acids isolated from plasma, both cell-free DNA (cfDNA) and microRNAs, and the relationship of these to circulating tumour cells (CTCs). This review considers the utility of each as circulating biomarkers in breast cancer with particular emphasis on the bioinformatic tools available to support molecular profiling.

Keywords

Breast cancer Circulating nucleic acids Cell-free DNA Circulating miRNA Principal component analysis 

Notes

Conflicts of interest

The authors declare that they have no conflict of interest.

References

  1. 1.
    Taplin, S., Abraham, L., Barlow, W. E., Fenton, J. J., Berns, E. A., Carney, P. A., et al. (2008). Mammography facility characteristics associated with interpretive accuracy of screening mammography. Journal of the National Cancer Institute, 100(12), 876–887.PubMedCrossRefGoogle Scholar
  2. 2.
    Harris, L., Fritsche, H., Mennel, R., Norton, L., Ravdin, P., Taube, S., et al. (2007). American Society of Clinical Oncology 2007 update of recommendations for the use of tumor markers in breast cancer. Journal of Clinical Oncology, 25(33), 5287–5312.PubMedCrossRefGoogle Scholar
  3. 3.
    O'Hanlon, D. M., Kerin, M. J., Kent, P., Maher, D., Grimes, H., & Given, H. F. (1995). An evaluation of preoperative CA 15-3 measurement in primary breast carcinoma. British Journal of Cancer, 71(6), 1288–1291.PubMedCrossRefGoogle Scholar
  4. 4.
    Piccart-Gebhart, M. J., Procter, M., Leyland-Jones, B., Goldhirsch, A., Untch, M., Smith, I., et al. (2005). Trastuzumab after adjuvant chemotherapy in HER2-positive breast cancer. The New England Journal of Medicine, 353(16), 1659–1672.PubMedCrossRefGoogle Scholar
  5. 5.
    Uehara, M., Kinoshita, T., Hojo, T., Akashi-Tanaka, S., Iwamoto, E., & Fukutomi, T. (2008). Long-term prognostic study of carcinoembryonic antigen (CEA) and carbohydrate antigen 15-3 (CA 15-3) in breast cancer. International Journal of Clinical Oncology, 13(5), 447–451.PubMedCrossRefGoogle Scholar
  6. 6.
    Weigel, M. T., & Dowsett, M. (2010). Current and emerging biomarkers in breast cancer: prognosis and prediction. Endocrine-Related Cancer, 17(4), R245–R262.PubMedCrossRefGoogle Scholar
  7. 7.
    Karrison, T. G., Ferguson, D. J., & Meier, P. (1999). Dormancy of mammary carcinoma after mastectomy. Journal of the National Cancer Institute, 91(1), 80–85.PubMedCrossRefGoogle Scholar
  8. 8.
    Fisher, B., Jeong, J.H., Dignam, J., Anderson, S., Mamounas, E., Wickerham, D. L., et al. (2001). Findings from recent National Surgical Adjuvant Breast and Bowel Project adjuvant studies in stage I breast cancer. Journal of National Cancer Institute Monographs, 2001(30), 62–66.Google Scholar
  9. 9.
    Wallgren, A., Bonetti, M., Gelber, R. D., Goldhirsch, A., Castiglione-Gertsch, M., Holmberg, S. B., et al. (2003). Risk factors for locoregional recurrence among breast cancer patients: results from International Breast Cancer Study Group Trials I through VII. Journal of Clinical Oncology, 21(7), 1205–1213.PubMedCrossRefGoogle Scholar
  10. 10.
    Meltzer, A. (1990). Dormancy and breast cancer. Journal of Surgical Oncology, 43(3), 181–188.PubMedCrossRefGoogle Scholar
  11. 11.
    Murray, C. (1995). Tumour dormancy: not so sleepy after all. Nature Medicine, 1(2), 117–118.PubMedCrossRefGoogle Scholar
  12. 12.
    Kuukasjarvi, T., Karhu, R., Tanner, M., Kahkonen, M., Schaffer, A., Nupponen, N., et al. (1997). Genetic heterogeneity and clonal evolution underlying development of asynchronous metastasis in human breast cancer. Cancer Research, 57(8), 1597–1604.PubMedGoogle Scholar
  13. 13.
    Gangnus, R., Langer, S., Breit, E., Pantel, K., & Speicher, M. R. (2004). Genomic profiling of viable and proliferative micrometastatic cells from early-stage breast cancer patients. Clinical Cancer Research, 10(10), 3457–3464.PubMedCrossRefGoogle Scholar
  14. 14.
    Stoecklein, N. H., & Klein, C. A. (2010). Genetic disparity between primary tumours, disseminated tumour cells, and manifest metastasis. International Journal of Cancer, 126(3), 589–598.CrossRefGoogle Scholar
  15. 15.
    Levenson, V. V. (2007). Biomarkers for early detection of breast cancer: what, when, and where? Biochimica et Biophysica Acta, 1770(6), 847–856.PubMedCrossRefGoogle Scholar
  16. 16.
    Mandel, P., & Metais, P. (1948). Les acides nucléiques du plasma sanguin chez l'homme. Comptes Rendus de l'Académie des Sciences de Paris, 142, 241–243.Google Scholar
  17. 17.
    Leon, S. A., Shapiro, B., Sklaroff, D. M., & Yaros, M. J. (1977). Free DNA in the serum of cancer patients and the effect of therapy. Cancer Research, 37(3), 646–650.PubMedGoogle Scholar
  18. 18.
    Stroun, M., Anker, P., Lyautey, J., Lederrey, C., & Maurice, P. A. (1987). Isolation and characterization of DNA from the plasma of cancer patients. European Journal of Cancer & Clinical Oncology, 23(6), 707–712.CrossRefGoogle Scholar
  19. 19.
    Cherepanova, A. V., Tamkovich, S. N., Bryzgunova, O. E., Vlassov, V. V., & Laktionov, P. P. (2008). Deoxyribonuclease activity and circulating DNA concentration in blood plasma of patients with prostate tumors. Annals of the New York Academy of Sciences, 1137, 218–221.PubMedCrossRefGoogle Scholar
  20. 20.
    Huang, Z. H., Li, L. H., & Hua, D. (2006). Quantitative analysis of plasma circulating DNA at diagnosis and during follow-up of breast cancer patients. Cancer Letters, 243(1), 64–70.PubMedCrossRefGoogle Scholar
  21. 21.
    Page, K., Powles, T., Slade, M. J., Tamburo de Bella, M., Walker, R. A., Coombes, R. C., et al. (2006). The importance of careful blood processing in isolation of cell-free DNA. Annals of the New York Academy of Sciences, 1075, 313–317.PubMedCrossRefGoogle Scholar
  22. 22.
    Wang, B. G., Huang, H. Y., Chen, Y. C., Bristow, R. E., Kassauei, K., Cheng, C. C., et al. (2003). Increased plasma DNA integrity in cancer patients. Cancer Research, 63(14), 3966–3968.PubMedGoogle Scholar
  23. 23.
    Gong, B., Xue, J., Yu, J., Li, H., Hu, H., Yen, H., et al. (2012). Cell-free DNA in blood is a potential diagnostic biomarker of breast cancer. Oncology Letters, 3(4), 897–900.PubMedGoogle Scholar
  24. 24.
    Zanetti-Dallenbach, R., Wight, E., Fan, A. X., Lapaire, O., Hahn, S., Holzgreve, W., et al. (2008). Positive correlation of cell-free DNA in plasma/serum in patients with malignant and benign breast disease. Anticancer Research, 28(2A), 921–925.PubMedGoogle Scholar
  25. 25.
    Pathak, A. K., Bhutani, M., Kumar, S., Mohan, A., & Guleria, R. (2006). Circulating cell-free DNA in plasma/serum of lung cancer patients as a potential screening and prognostic tool. Clinical Chemistry, 52(10), 1833–1842.PubMedGoogle Scholar
  26. 26.
    Anker, P., Stroun, M., & Maurice, P. A. (1975). Spontaneous release of DNA by human blood lymphocytes as shown in an in vitro system. Cancer Research, 35(9), 2375–2382.PubMedGoogle Scholar
  27. 27.
    Nawroz, H., Koch, W., Anker, P., Stroun, M., & Sidransky, D. (1996). Microsatellite alterations in serum DNA of head and neck cancer patients. Nature Medicine, 2(9), 1035–1037.PubMedCrossRefGoogle Scholar
  28. 28.
    Alix-Panabieres, C., Schwarzenbach, H., & Pantel, K. (2012). Circulating tumor cells and circulating tumor DNA. Annual Review of Medicine, 63, 199–215.PubMedCrossRefGoogle Scholar
  29. 29.
    Jung, K., Fleischhacker, M., & Rabien, A. (2010). Cell-free DNA in the blood as a solid tumor biomarker—a critical appraisal of the literature. Clinica Chimica Acta, 411(21–22), 1611–1624.CrossRefGoogle Scholar
  30. 30.
    Higgins, M. J., Jelovac, D., Barnathan, E., Blair, B., Slater, S., Powers, P., et al. (2012). Detection of tumor PIK3CA status in metastatic breast cancer using peripheral blood. Clinical Cancer Research, 18(12), 3462–3469.PubMedCrossRefGoogle Scholar
  31. 31.
    Board, R. E., Wardley, A. M., Dixon, J. M., Armstrong, A. C., Howell, S., Renshaw, L., et al. (2010). Detection of PIK3CA mutations in circulating free DNA in patients with breast cancer. Breast Cancer Research and Treatment, 120(2), 461–467.PubMedCrossRefGoogle Scholar
  32. 32.
    Silva, J. M., Gonzalez, R., Dominguez, G., Garcia, J. M., Espana, P., & Bonilla, F. (1999). TP53 gene mutations in plasma DNA of cancer patients. Genes, Chromosomes & Cancer, 24(2), 160–161.CrossRefGoogle Scholar
  33. 33.
    Schwarzenbach, H., Muller, V., Stahmann, N., & Pantel, K. (2004). Detection and characterization of circulating microsatellite-DNA in blood of patients with breast cancer. Annals of the New York Academy of Sciences, 1022, 25–32.PubMedCrossRefGoogle Scholar
  34. 34.
    Shaw, J. A., Smith, B. M., Walsh, T., Johnson, S., Primrose, L., Slade, M. J., et al. (2000). Microsatellite alterations plasma DNA of primary breast cancer patients. Clinical Cancer Research, 6(3), 1119–1124.PubMedGoogle Scholar
  35. 35.
    Schwarzenbach, H., Eichelser, C., Kropidlowski, J., Janni, W., Rack, B., & Pantel, K. (2012). Loss of heterozygosity at tumor suppressor genes detectable on fractionated circulating cell-free tumor DNA as indicator of breast cancer progression. Clinical Cancer Research Google Scholar
  36. 36.
    Yamamoto, N., Nakayama, T., Kajita, M., Miyake, T., Iwamoto, T., Kim, S. J., et al. (2012). Detection of aberrant promoter methylation of GSTP1, RASSF1A, and RARbeta2 in serum DNA of patients with breast cancer by a newly established one-step methylation-specific PCR assay. Breast Cancer Research and Treatment, 132(1), 165–173.PubMedCrossRefGoogle Scholar
  37. 37.
    Hoque, M. O., Feng, Q., Toure, P., Dem, A., Critchlow, C. W., Hawes, S. E., et al. (2006). Detection of aberrant methylation of four genes in plasma DNA for the detection of breast cancer. Journal of Clinical Oncology, 24(26), 4262–4269.PubMedCrossRefGoogle Scholar
  38. 38.
    Sharma, G., Mirza, S., Parshad, R., Gupta, S. D., & Ralhan, R. (2012). DNA methylation of circulating DNA: a marker for monitoring efficacy of neoadjuvant chemotherapy in breast cancer patients. Tumour Biology. doi: 10.1007/s13277-012-0443-y.
  39. 39.
    Page, K., Hava, N., Ward, B., Brown, J., Guttery, D. S., Ruangpratheep, C., et al. (2011). Detection of HER2 amplification in circulating free DNA in patients with breast cancer. British Journal of Cancer, 104(8), 1342–1348.PubMedCrossRefGoogle Scholar
  40. 40.
    Diaz, L. A., Jr., Williams, R. T., Wu, J., Kinde, I., Hecht, J. R., Berlin, J., et al. (2012). The molecular evolution of acquired resistance to targeted EGFR blockade in colorectal cancers. Nature, 486(7404), 537–540.PubMedGoogle Scholar
  41. 41.
    Shaw, J. A., Page, K., Blighe, K., Hava, N., Guttery, D., Ward, B., et al. (2012). Genomic analysis of circulating cell-free DNA infers breast cancer dormancy. Genome Research, 22(2), 220–231.PubMedCrossRefGoogle Scholar
  42. 42.
    Beck, J., Urnovitz, H. B., Mitchell, W. M., & Schutz, E. (2010). Next generation sequencing of serum circulating nucleic acids from patients with invasive ductal breast cancer reveals differences to healthy and nonmalignant controls. Molecular Cancer Research, 8(3), 335–342.PubMedCrossRefGoogle Scholar
  43. 43.
    van de Wiel, M. A., Picard, F., van Wieringen, W. N., & Ylstra, B. (2011). Preprocessing and downstream analysis of microarray DNA copy number profiles. Briefings in Bioinformatics, 12(1), 10–21.PubMedCrossRefGoogle Scholar
  44. 44.
    Ong, M., Mateo, J., Pope, L., Cassidy, A. M., Yap, T. A., Perkins, G., et al. (2012). Prospective study of oncogenic mutations in circulating cell-free DNA (cfDNA) using a multiplex sequencing platform for patient (pt) allocation to phase I clinical trials. Paper presented at the 2012 ASCO Annual MeetingGoogle Scholar
  45. 45.
    Lam, H. Y. K., Clark, M. J., Chen, R., Chen, R., Natsoulis, G., O’Huallachain, M., et al. (2012). Performance comparison of whole-genome sequencing platforms. Nature Biotechnology, 30(1), 78–82.CrossRefGoogle Scholar
  46. 46.
    Archer, J., Baillie, G., Watson, J., Kellam, P., Rambaut, A., & Robertson, D. (2011). Characterizing Next Generation Sequencing Error and the Consequences for the Study of Intra-Patient Viral Diversity. Paper presented at the Eighteenth International Workshop on HIV Dynamics and Evolution, Galway, Republic of Ireland,Google Scholar
  47. 47.
    Li, H., Handsaker, B., Wysoker, A., Fennell, T., Ruan, J., Homer, N., et al. (2009). The sequence alignment/map format and SAMtools. Bioinformatics, 25(16), 2078–2079.PubMedCrossRefGoogle Scholar
  48. 48.
    He, L., & Hannon, G. J. (2004). MicroRNAs: small RNAs with a big role in gene regulation. Nature Reviews Genetics, 5(7), 522–531.PubMedCrossRefGoogle Scholar
  49. 49.
    Miranda, K. C., Huynh, T., Tay, Y., Ang, Y. S., Tam, W. L., Thomson, A. M., et al. (2006). A pattern-based method for the identification of microRNA binding sites and their corresponding heteroduplexes. Cell, 126(6), 1203–1217.PubMedCrossRefGoogle Scholar
  50. 50.
    Bullrich, F., Fujii, H., Calin, G., Mabuchi, H., Negrini, M., Pekarsky, Y., et al. (2001). Characterization of the 13q14 tumor suppressor locus in CLL: identification of ALT1, an alternative splice variant of the LEU2 gene. Cancer Research, 61(18), 6640–6648.PubMedGoogle Scholar
  51. 51.
    Cummins, J. M., He, Y., Leary, R. J., Pagliarini, R., Diaz, L. A., Jr., Sjoblom, T., et al. (2006). The colorectal microRNAome. Proceedings of the National Academy of Sciences of the United States of America, 103(10), 3687–3692.PubMedCrossRefGoogle Scholar
  52. 52.
    Schetter, A. J., Leung, S. Y., Sohn, J. J., Zanetti, K. A., Bowman, E. D., Yanaihara, N., et al. (2008). MicroRNA expression profiles associated with prognosis and therapeutic outcome in colon adenocarcinoma. Journal of the American Medical Association, 299(4), 425–436.PubMedCrossRefGoogle Scholar
  53. 53.
    Lu, J., Getz, G., Miska, E. A., Alvarez-Saavedra, E., Lamb, J., Peck, D., et al. (2005). MicroRNA expression profiles classify human cancers. Nature, 435(7043), 834–838.PubMedCrossRefGoogle Scholar
  54. 54.
    Rosenfeld, N., Aharonov, R., Meiri, E., Rosenwald, S., Spector, Y., Zepeniuk, M., et al. (2008). MicroRNAs accurately identify cancer tissue origin. Nature Biotechnology, 26(4), 462–469.PubMedCrossRefGoogle Scholar
  55. 55.
    Rosenwald, S., Gilad, S., Benjamin, S., Lebanony, D., Dromi, N., Faerman, A., et al. (2010). Validation of a microRNA-based qRT-PCR test for accurate identification of tumor tissue origin. Modern Pathology, 23(6), 814–823.PubMedCrossRefGoogle Scholar
  56. 56.
    Mostert, B., Sieuwerts, A. M., Martens, J. W., & Sleijfer, S. (2011). Diagnostic applications of cell-free and circulating tumor cell-associated miRNAs in cancer patients. Expert Review of Molecular Diagnostics, 11(3), 259–275.PubMedGoogle Scholar
  57. 57.
    Ferracin, M., Veronese, A., & Negrini, M. (2010). Micromarkers: miRNAs in cancer diagnosis and prognosis. Expert Review of Molecular Diagnostics, 10(3), 297–308.PubMedCrossRefGoogle Scholar
  58. 58.
    Lodes, M. J., Caraballo, M., Suciu, D., Munro, S., Kumar, A., & Anderson, B. (2009). Detection of cancer with serum miRNAs on an oligonucleotide microarray. PLoS One, 4(7), e6229.PubMedCrossRefGoogle Scholar
  59. 59.
    Mitchell, P. S., Parkin, R. K., Kroh, E. M., Fritz, B. R., Wyman, S. K., Pogosova-Agadjanyan, E. L., et al. (2008). Circulating microRNAs as stable blood-based markers for cancer detection. Proceedings of the National Academy of Sciences of the United States of America, 105(30), 10513–10518.PubMedCrossRefGoogle Scholar
  60. 60.
    Ji, X., Takahashi, R., Hiura, Y., Hirokawa, G., Fukushima, Y., & Iwai, N. (2009). Plasma miR-208 as a biomarker of myocardial injury. Clinical Chemistry, 55(11), 1944–1949.PubMedCrossRefGoogle Scholar
  61. 61.
    Hunter, M. P., Ismail, N., Zhang, X., Aguda, B. D., Lee, E. J., Yu, L., et al. (2008). Detection of microRNA expression in human peripheral blood microvesicles. PLoS One, 3(11), e3694.PubMedCrossRefGoogle Scholar
  62. 62.
    Kosaka, N., Iguchi, H., Yoshioka, Y., Takeshita, F., Matsuki, Y., & Ochiya, T. (2010). Secretory mechanisms and intercellular transfer of microRNAs in living cells. Journal of Biological Chemistry, 285(23), 17442–17452.PubMedCrossRefGoogle Scholar
  63. 63.
    Valadi, H., Ekstrom, K., Bossios, A., Sjostrand, M., Lee, J. J., & Lotvall, J. O. (2007). Exosome-mediated transfer of mRNAs and microRNAs is a novel mechanism of genetic exchange between cells. Nature Cell Biology, 9(6), 654–659.PubMedCrossRefGoogle Scholar
  64. 64.
    Brase, J. C., Wuttig, D., Kuner, R., & Sultmann, H. (2010). Serum microRNAs as non-invasive biomarkers for cancer. Molecular Cancer, 9, 306.PubMedCrossRefGoogle Scholar
  65. 65.
    Turchinovich, A., Weiz, L., & Burwinkel, B. (2012). Extracellular miRNAs: the mystery of their origin and function. Trends in Biochemical Sciences.Google Scholar
  66. 66.
    Pigati, L., Yaddanapudi, S. C., Iyengar, R., Kim, D. J., Hearn, S. A., Danforth, D., et al. (2010). Selective release of microRNA species from normal and malignant mammary epithelial cells. PLoS One, 5(10), e13515.PubMedCrossRefGoogle Scholar
  67. 67.
    Pritchard, C. C., Kroh, E., Wood, B., Arroyo, J. D., Dougherty, K. J., Miyaji, M. M., et al. (2012). Blood cell origin of circulating microRNAs: a cautionary note for cancer biomarker studies. Cancer Prevention Research (Philadelphia, Pa.), 5(3), 492–497.CrossRefGoogle Scholar
  68. 68.
    Wittmann, J., & Jack, H. M. (2010). Serum microRNAs as powerful cancer biomarkers. Biochimica et Biophysica Acta, 1806(2), 200–207.PubMedGoogle Scholar
  69. 69.
    Heneghan, H. M., Miller, N., Lowery, A. J., Sweeney, K. J., Newell, J., & Kerin, M. J. (2010). Circulating microRNAs as novel minimally invasive biomarkers for breast cancer. Annals of Surgery, 251(3), 499–505.PubMedCrossRefGoogle Scholar
  70. 70.
    Zhu, W., Qin, W., Atasoy, U., & Sauter, E. R. (2009). Circulating microRNAs in breast cancer and healthy subjects. BMC Research Notes, 2, 89.PubMedCrossRefGoogle Scholar
  71. 71.
    Roth, C., Rack, B., Muller, V., Janni, W., Pantel, K., & Schwarzenbach, H. (2010). Circulating microRNAs as blood-based markers for patients with primary and metastatic breast cancer. Breast Cancer Research, 12(6), R90.PubMedCrossRefGoogle Scholar
  72. 72.
    van Schooneveld, E., Wouters, M. C., Van der Auwera, I., Peeters, D. J., Wildiers, H., Van Dam, P. A., et al. (2012). Expression profiling of cancerous and normal breast tissues identifies microRNAs that are differentially expressed in serum from patients with (metastatic) breast cancer and healthy volunteers. Breast Cancer Research, 14(1), R34.PubMedCrossRefGoogle Scholar
  73. 73.
    Wu, X., Somlo, G., Yu, Y., Palomares, M. R., Li, A. X., Zhou, W., et al. (2012). De novo sequencing of circulating miRNAs identifies novel markers predicting clinical outcome of locally advanced breast cancer. Journal of Translational Medicine, 10, 42.PubMedCrossRefGoogle Scholar
  74. 74.
    Schrauder, M. G., Strick, R., Schulz-Wendtland, R., Strissel, P. L., Kahmann, L., Loehberg, C. R., et al. (2012). Circulating micro-RNAs as potential blood-based markers for early stage breast cancer detection. PLoS One, 7(1), e29770.PubMedCrossRefGoogle Scholar
  75. 75.
    Carlsson, J., Helenius, G., Karlsson, M., Lubovac, Z., Andrén, O., Olsson, B., et al. (2010). Validation of suitable endogenous control genes for expression studies of miRNA in prostate cancer tissues. Cancer Genetics and Cytogenetics, 202(2), 71–75.PubMedCrossRefGoogle Scholar
  76. 76.
    Appaiah, H. N., Goswami, C. P., Mina, L. A., Badve, S., Sledge, G. W., Jr., Liu, Y., et al. (2011). Persistent upregulation of U6:SNORD44 small RNA ratio in the serum of breast cancer patients. Breast Cancer Research, 13(5), R86.PubMedCrossRefGoogle Scholar
  77. 77.
    Cogswell, J. P., Ward, J., Taylor, I. A., Waters, M., Shi, Y., Cannon, B., et al. (2008). Identification of miRNA changes in Alzheimer's disease brain and CSF yields putative biomarkers and insights into disease pathways. Journal of Alzheimer's Disease, 14(1), 27–41.PubMedGoogle Scholar
  78. 78.
    Mizuguchi, Y., Mishima, T., Yokomuro, S., Arima, Y., Kawahigashi, Y., Shigehara, K., et al. (2011). Sequencing and bioinformatics-based analyses of the microRNA transcriptome in hepatitis B–related hepatocellular carcinoma. PLoS One, 6(1), e15304.PubMedCrossRefGoogle Scholar
  79. 79.
    Ge, Q., Li, H., Yang, Q., Lu, J., Tu, J., Bai, Y., et al. (2011). Sequencing circulating miRNA in maternal plasma with modified library preparation. Clinica Chimica Acta, 412(21–22), 1989–1994.CrossRefGoogle Scholar
  80. 80.
    Li, H., Guo, L., Wu, Q., Lu, J., Ge, Q., & Lu, Z. (2012). A comprehensive survey of maternal plasma miRNAs expression profiles using high-throughput sequencing. Clinica Chimica Acta, 413(5–6), 568–576.CrossRefGoogle Scholar
  81. 81.
    Griffiths-Jones, S., Grocock, R. J., van Dongen, S., Bateman, A., & Enright, A. J. (2006). miRBase: microRNA sequences, targets and gene nomenclature. Nucleic Acids Research, 34(suppl 1), D140–D144.PubMedCrossRefGoogle Scholar
  82. 82.
    Griffiths-Jones, S., Saini, H. K., van Dongen, S., & Enright, A. J. (2008). miRBase: tools for microRNA genomics. Nucleic Acids Research, 36(suppl 1), D154–D158.PubMedGoogle Scholar
  83. 83.
    Lewis, B. P., Burge, C. B., & Bartel, D. P. (2005). Conserved seed pairing, often flanked by adenosines, indicates that thousands of human genes are microRNA targets. Cell, 120(1), 15–20.PubMedCrossRefGoogle Scholar
  84. 84.
    Team, R. D. C. (2008). R: A language and environment for statistical computing. Vienna: R Foundation for Statistical Computing.Google Scholar
  85. 85.
    Quackenbush, J. (2002). Microarray data normalization and transformation. Nature Genetics, 32(Suppl), 496–501.PubMedCrossRefGoogle Scholar
  86. 86.
    Calza, S., Chen, S., & Pawitan, Y. (2010). LVSmiRNA: LVS normalization for Agilent miRNA data (R package version 1.4.0 ed.).Google Scholar
  87. 87.
    Calza, S., Valentini, D., & Pawitan, Y. (2008). Normalization of oligonucleotide arrays based on the least-variant set of genes. BMC Bioinformatics, 9(1), 140.PubMedCrossRefGoogle Scholar
  88. 88.
    López-Romero, P. AgiMicroRna: Processing and differential expression analysis of agilent microRNA chips (R package version 2.4.0 ed.).Google Scholar
  89. 89.
    Gubian, S., Sewer, A., & PMP, S. A. (2010). ExiMiR: R functions for the normalization of Exiqon miRNA array data (R package version 1.2.0 ed.).Google Scholar
  90. 90.
    Huovilainen, O. P., & Lahti, L. pint—R/Bioconductor package for pairwise integration of functional genomics data.Google Scholar
  91. 91.
    Gentleman, R., & Falcon, S. microRNA: Data and functions for dealing with microRNAs (R package version 1.12.0 ed.).Google Scholar
  92. 92.
    Favero, F. RmiR.Hs.miRNA: Various databases of microRNA Targets (R package version 1.0.6 ed.).Google Scholar
  93. 93.
    Griffiths-Jones, S. (2004). The microRNA registry. Nucleic Acids Research, 32(suppl 1), D109–D111.PubMedCrossRefGoogle Scholar
  94. 94.
    Kozomara, A., & Griffiths-Jones, S. (2011). miRBase: integrating microRNA annotation and deep-sequencing data. Nucleic Acids Research, 39(suppl 1), D152–D157.PubMedCrossRefGoogle Scholar
  95. 95.
    John, B., Enright, A. J., Aravin, A., Tuschl, T., Sander, C., & Marks, D. S. (2004). Human microRNA targets. PLoS Biology, 2(11), e363.PubMedCrossRefGoogle Scholar
  96. 96.
    Papadopoulos, G. L., Reczko, M., Simossis, V. A., Sethupathy, P., & Hatzigeorgiou, A. G. (2009). The database of experimentally supported targets: a functional update of TarBase. Nucleic Acids Research, 37(suppl 1), D155–D158.PubMedCrossRefGoogle Scholar
  97. 97.
    Wang, X., & El Naqa, I. M. (2008). Prediction of both conserved and nonconserved microRNA targets in animals. Bioinformatics, 24(3), 325–332.PubMedCrossRefGoogle Scholar
  98. 98.
    Krek, A., Grun, D., Poy, M. N., Wolf, R., Rosenberg, L., Epstein, E. J., et al. (2005). Combinatorial microRNA target predictions. Nature Genetics, 37(5), 495–500.PubMedCrossRefGoogle Scholar
  99. 99.
    Favero, F. RmiR: Package to work with miRNAs and miRNA targets with R (R package version 1.10.0 ed.).Google Scholar
  100. 100.
    Chambers, A. F., Groom, A. C., & MacDonald, I. C. (2002). Dissemination and growth of cancer cells in metastatic sites. Nature Reviews. Cancer, 2(8), 563–572.PubMedCrossRefGoogle Scholar
  101. 101.
    Bernards, R., & Weinberg, R. A. (2002). A progression puzzle. Nature, 418(6900), 823.PubMedCrossRefGoogle Scholar
  102. 102.
    Husemann, Y., Geigl, J. B., Schubert, F., Musiani, P., Meyer, M., Burghart, E., et al. (2008). Systemic spread is an early step in breast cancer. Cancer Cell, 13(1), 58–68.PubMedCrossRefGoogle Scholar
  103. 103.
    Stott, S. L., Hsu, C. H., Tsukrov, D. I., Yu, M., Miyamoto, D. T., Waltman, B. A., et al. (2010). Isolation of circulating tumor cells using a microvortex-generating herringbone-chip. Proceedings of the National Academy of Sciences of the United States of America, 107(43), 18392–18397.PubMedCrossRefGoogle Scholar
  104. 104.
    Hayashi, N., & Yamauchi, H. (2012). Role of circulating tumor cells and disseminated tumor cells in primary breast cancer. Breast Cancer, 19(2), 110–117.PubMedCrossRefGoogle Scholar
  105. 105.
    Yu, M., Stott, S., Toner, M., Maheswaran, S., & Haber, D. A. (2011). Circulating tumor cells: approaches to isolation and characterization. The Journal of Cell Biology, 192(3), 373–382.PubMedCrossRefGoogle Scholar
  106. 106.
    Powell, A. A., Talasaz, A. H., Zhang, H., Coram, M. A., Reddy, A., Deng, G., et al. (2012). Single cell profiling of circulating tumor cells: transcriptional heterogeneity and diversity from breast cancer cell lines. PLoS One, 7(5), e33788.PubMedCrossRefGoogle Scholar
  107. 107.
    Riethdorf, S., Fritsche, H., Muller, V., Rau, T., Schindlbeck, C., Rack, B., et al. (2007). Detection of circulating tumor cells in peripheral blood of patients with metastatic breast cancer: a validation study of the cell search system. Clinical Cancer Research, 13(3), 920–928.PubMedCrossRefGoogle Scholar
  108. 108.
    Vona, G., Sabile, A., Louha, M., Sitruk, V., Romana, S., Schutze, K., et al. (2000). Isolation by size of epithelial tumor cells: a new method for the immunomorphological and molecular characterization of circulating tumor cells. American Journal of Pathology, 156(1), 57–63.PubMedCrossRefGoogle Scholar
  109. 109.
    Farace, F., Massard, C., Vimond, N., Drusch, F., Jacques, N., Billiot, F., et al. (2011). A direct comparison of cell search and ISET for circulating tumour-cell detection in patients with metastatic carcinomas. British Journal of Cancer, 105(6), 847–853.PubMedCrossRefGoogle Scholar
  110. 110.
    Gertler, R., Rosenberg, R., Fuehrer, K., Dahm, M., Nekarda, H., & Siewert, J. R. (2003). Detection of circulating tumor cells in blood using an optimized density gradient centrifugation. Recent Results in Cancer Research, 162, 149–155.PubMedCrossRefGoogle Scholar
  111. 111.
    Sieuwerts, A. M., Kraan, J., Bolt, J., van der Spoel, P., Elstrodt, F., Schutte, M., et al. (2009). Anti-epithelial cell adhesion molecule antibodies and the detection of circulating normal-like breast tumor cells. Journal of the National Cancer Institute, 101(1), 61–66.PubMedCrossRefGoogle Scholar
  112. 112.
    Tibbe, A. G., Miller, M. C., & Terstappen, L. W. (2007). Statistical considerations for enumeration of circulating tumor cells. Cytometry. Part A, 71(3), 154–162.CrossRefGoogle Scholar
  113. 113.
    Goeminne, J. C., Guillaume, T., & Symann, M. (2000). Pitfalls in the detection of disseminated non-hematological tumor cells. Annals of Oncology, 11(7), 785–792.PubMedCrossRefGoogle Scholar
  114. 114.
    Konigsberg, R., Obermayr, E., Bises, G., Pfeiler, G., Gneist, M., Wrba, F., et al. (2011). Detection of EpCAM positive and negative circulating tumor cells in metastatic breast cancer patients. Acta Oncologica, 50(5), 700–710.PubMedCrossRefGoogle Scholar
  115. 115.
    Mikolajczyk, S. D., Millar, L. S., Tsinberg, P., Coutts, S. M., Zomorrodi, M., Pham, T., et al. (2011). Detection of EpCAM-negative and cytokeratin-negative circulating tumor cells in peripheral blood. Journal of Oncology, 2011, 252361.PubMedCrossRefGoogle Scholar
  116. 116.
    Park, J.M., Lee, J.Y., Lee, J.G., Jeong, H., Oh, J.M., Kim, Y.J., et al. (2012). Highly efficient assay of circulating tumor cells by selective sedimentation with a density gradient medium and microfiltration from whole blood. Analytical Chemistry Google Scholar
  117. 117.
    Barriere, G., Riouallon, A., Renaudie, J., Tartary, M., & Rigaud, M. (2012). Mesenchymal characterization: alternative to simple CTC detection in two clinical trials. Anticancer Research, 32(8), 3363–3369.PubMedGoogle Scholar
  118. 118.
    Friel, A. M., Corcoran, C., Crown, J., & O'Driscoll, L. (2010). Relevance of circulating tumor cells, extracellular nucleic acids, and exosomes in breast cancer. Breast Cancer Research and Treatment, 123(3), 613–625.PubMedCrossRefGoogle Scholar
  119. 119.
    Stathopoulou, A., Ntoulia, M., Perraki, M., Apostolaki, S., Mavroudis, D., Malamos, N., et al. (2006). A highly specific real-time RT-PCR method for the quantitative determination of CK-19 mRNA positive cells in peripheral blood of patients with operable breast cancer. International Journal of Cancer, 119(7), 1654–1659.CrossRefGoogle Scholar
  120. 120.
    de Albuquerque, A., Kubisch, I., Ernst, D., Breier, G., Stamminger, G., Fersis, N., et al. (2012). Development of a molecular multimarker assay for the analysis of circulating tumor cells in adenocarcinoma patients. Clinical Laboratory, 58(5–6), 373–384.PubMedGoogle Scholar
  121. 121.
    Pachmann, K., Camara, O., Kavallaris, A., Krauspe, S., Malarski, N., Gajda, M., et al. (2008). Monitoring the response of circulating epithelial tumor cells to adjuvant chemotherapy in breast cancer allows detection of patients at risk of early relapse. Journal of Clinical Oncology, 26(8), 1208–1215.PubMedCrossRefGoogle Scholar
  122. 122.
    Ignatiadis, M., Xenidis, N., Perraki, M., Apostolaki, S., Politaki, E., Kafousi, M., et al. (2007). Different prognostic value of cytokeratin-19 mRNA positive circulating tumor cells according to estrogen receptor and HER2 status in early-stage breast cancer. Journal of Clinical Oncology, 25(33), 5194–5202.PubMedCrossRefGoogle Scholar
  123. 123.
    Pierga, J. Y., Bidard, F. C., Mathiot, C., Brain, E., Delaloge, S., Giachetti, S., et al. (2008). Circulating tumor cell detection predicts early metastatic relapse after neoadjuvant chemotherapy in large operable and locally advanced breast cancer in a phase II randomized trial. Clinical Cancer Research, 14(21), 7004–7010.PubMedCrossRefGoogle Scholar
  124. 124.
    Chen, X., Bonnefoi, H., Diebold-Berger, S., Lyautey, J., Lederrey, C., Faltin-Traub, E., et al. (1999). Detecting tumor-related alterations in plasma or serum DNA of patients diagnosed with breast cancer. Clinical Cancer Research, 5(9), 2297–2303.PubMedGoogle Scholar
  125. 125.
    Schwarzenbach, H., Alix-Panabieres, C., Muller, I., Letang, N., Vendrell, J. P., Rebillard, X., et al. (2009). Cell-free tumor DNA in blood plasma as a marker for circulating tumor cells in prostate cancer. Clinical Cancer Research, 15(3), 1032–1038.PubMedCrossRefGoogle Scholar
  126. 126.
    Paris, P. L., Kobayashi, Y., Zhao, Q., Zeng, W., Sridharan, S., Fan, T., et al. (2009). Functional phenotyping and genotyping of circulating tumor cells from patients with castration resistant prostate cancer. Cancer Letters, 277(2), 164–173.PubMedCrossRefGoogle Scholar
  127. 127.
    Stathopoulou, A., Mavroudis, D., Perraki, M., Apostolaki, S., Vlachonikolis, I., Lianidou, E., et al. (2003). Molecular detection of cancer cells in the peripheral blood of patients with breast cancer: comparison of CK-19, CEA and maspin as detection markers. Anticancer Research, 23(2C), 1883–1890.PubMedGoogle Scholar
  128. 128.
    Stathopoulou, A., Vlachonikolis, I., Mavroudis, D., Perraki, M., Kouroussis, C., Apostolaki, S., et al. (2002). Molecular detection of cytokeratin-19-positive cells in the peripheral blood of patients with operable breast cancer: evaluation of their prognostic significance. Journal of Clinical Oncology, 20(16), 3404–3412.PubMedCrossRefGoogle Scholar
  129. 129.
    Xenidis, N., Ignatiadis, M., Apostolaki, S., Perraki, M., Kalbakis, K., Agelaki, S., et al. (2009). Cytokeratin-19 mRNA-positive circulating tumor cells after adjuvant chemotherapy in patients with early breast cancer. Journal of Clinical Oncology, 27(13), 2177–2184.PubMedCrossRefGoogle Scholar
  130. 130.
    Xenidis, N., Perraki, M., Kafousi, M., Apostolaki, S., Bolonaki, I., Stathopoulou, A., et al. (2006). Predictive and prognostic value of peripheral blood cytokeratin-19 mRNA-positive cells detected by real-time polymerase chain reaction in node-negative breast cancer patients. Journal of Clinical Oncology, 24(23), 3756–3762.PubMedCrossRefGoogle Scholar
  131. 131.
    Sieuwerts, A. M., Mostert, B., Bolt-de Vries, J., Peeters, D., de Jongh, F. E., Stouthard, J. M., et al. (2011). mRNA and microRNA expression profiles in circulating tumor cells and primary tumors of metastatic breast cancer patients. Clinical Cancer Research, 17(11), 3600–3618.PubMedCrossRefGoogle Scholar
  132. 132.
    Madhavan, D., Zucknick, M., Wallwiener, M., Cuk, K., Modugno, C., Scharpff, M., et al. (2012). Circulating microRNAs as surrogate markers for circulating tumour cells and prognostic markers in metastatic breast cancer. Clinical Cancer Research Google Scholar
  133. 133.
    Payne, R. E., Hava, N. L., Page, K., Blighe, K., Ward, B., Slade, M., et al. (2012). The presence of disseminated tumour cells in the bone marrow is inversely related to circulating free DNA in plasma in breast cancer dormancy. British Journal of Cancer, 106(2), 375–382.PubMedCrossRefGoogle Scholar
  134. 134.
    Mazlum, N., Özer, A., & Mazlum, S. (1999). Interpretation of water quality data by principal components. Turkish Journal of Engineering and Environmental Sciences, 23, 19–26.Google Scholar
  135. 135.
    Joliffe, I. T. (2002). Principal components analysis (2nd ed.). NY: Springer.Google Scholar
  136. 136.
    Chakravarty, M. M., Aleong, R., Leonard, G., Perron, M., Pike, G. B., Richer, L., et al. (2011). Automated analysis of craniofacial morphology using magnetic resonance images. PLoS One, 6(5), e20241.PubMedCrossRefGoogle Scholar
  137. 137.
    Bicciato, S., Luchini, A., & Di Bello, C. (2003). PCA disjoint models for multiclass cancer analysis using gene expression data. Bioinformatics, 19(5), 571–578.PubMedCrossRefGoogle Scholar
  138. 138.
    Meng, Z., Zaykin, D. V., Xu, C.-F., Wagner, M., & Ehm, M. G. (2003). Selection of genetic markers for association analyses, using linkage disequilibrium and haplotypes. The American Journal of Human Genetics, 73(1), 115–130.CrossRefGoogle Scholar
  139. 139.
    Lin, Z., & Altman, R. B. (2004). Finding haplotype tagging SNPs by use of principal components analysis. The American Journal of Human Genetics, 75(5), 850–861.CrossRefGoogle Scholar
  140. 140.
    Parsons, K. J., Cooper, W. J., & Albertson, R. C. (2009). Limits of principal components analysis for producing a common trait space: implications for inferring selection, contingency, and chance in evolution. PLoS One, 4(11), e7957.PubMedCrossRefGoogle Scholar
  141. 141.
    Chatfield, C., & Collins, A. J. (1980). Introduction to multivariate analysis. NY: Chapman and Hall.Google Scholar
  142. 142.
    Kaiser, H. (1960). The application of electronic computers to factor analysis. Educational and Psychological Measurement, 20(1), 141–151.CrossRefGoogle Scholar
  143. 143.
    Cattell, R. B. (1966). The scree test for the number of factors. Multivariate Behavioral Research, 1, 629–637.Google Scholar
  144. 144.
    Mahloch, J. L. (1974). Multivariate techniques for water quality analysis. Journal of the Environmental Engineering Division, 100(5), 1119–1132.Google Scholar
  145. 145.
    Madsen, T. (2007). Multivariate data analysis with PCA, CA and MS. http://www.archaeoinfo.dk/PDF%20files/Multivariate%20data%20analysis.pdf. Accessed 15 Oct 2012.
  146. 146.
    Greenberg, P. A., Hortobagyi, G. N., Smith, T. L., Ziegler, L. D., Frye, D. K., & Buzdar, A. U. (1996). Long-term follow-up of patients with complete remission following combination chemotherapy for metastatic breast cancer. Journal of Clinical Oncology, 14(8), 2197–2205.PubMedGoogle Scholar
  147. 147.
    Curtis, C., Shah, S. P., Chin, S. F., Turashvili, G., Rueda, O. M., Dunning, M. J., et al. (2012). The genomic and transcriptomic architecture of 2,000 breast tumours reveals novel subgroups. Nature, 486(7403), 346–352.PubMedGoogle Scholar
  148. 148.
    Ramaswamy, S., Ross, K. N., Lander, E. S., & Golub, T. R. (2003). A molecular signature of metastasis in primary solid tumors. Nature Genetics, 33(1), 49–54.PubMedCrossRefGoogle Scholar
  149. 149.
    van’t Veer, L. J., Dai, H., van de Vijver, M. J., He, Y. D., Hart, A. A., Mao, M., et al. (2002). Gene expression profiling predicts clinical outcome of breast cancer. Nature, 415(6871), 530–536.CrossRefGoogle Scholar
  150. 150.
    Weigelt, B., Peterse, J. L., & van't Veer, L. J. (2005). Breast cancer metastasis: markers and models. Nature Reviews. Cancer, 5(8), 591–602.PubMedCrossRefGoogle Scholar
  151. 151.
    Landemaine, T., Jackson, A., Bellahcene, A., Rucci, N., Sin, S., Abad, B. M., et al. (2008). A six-gene signature predicting breast cancer lung metastasis. Cancer Research, 68(15), 6092–6099.PubMedCrossRefGoogle Scholar
  152. 152.
    Driouch, K., Landemaine, T., Sin, S., Wang, S., & Lidereau, R. (2007). Gene arrays for diagnosis, prognosis and treatment of breast cancer metastasis. Clinical & Experimental Metastasis, 24(8), 575–585.CrossRefGoogle Scholar
  153. 153.
    van de Vijver, M. J., He, Y. D., van't Veer, L. J., Dai, H., Hart, A. A., Voskuil, D. W., et al. (2002). A gene-expression signature as a predictor of survival in breast cancer. The New England Journal of Medicine, 347(25), 1999–2009.PubMedCrossRefGoogle Scholar
  154. 154.
    Fidler, I. J. (2003). The pathogenesis of cancer metastasis: the ‘seed and soil’ hypothesis revisited. Nature Reviews. Cancer, 3(6), 453–458.PubMedCrossRefGoogle Scholar
  155. 155.
    Smid, M., Wang, Y., Klijn, J. G., Sieuwerts, A. M., Zhang, Y., Atkins, D., et al. (2006). Genes associated with breast cancer metastatic to bone. Journal of Clinical Oncology, 24(15), 2261–2267.PubMedCrossRefGoogle Scholar
  156. 156.
    Bae, Y. K., Shim, Y. R., Choi, J. H., Kim, M. J., Gabrielson, E., Lee, S. J., et al. (2005). Gene promoter hypermethylation in tumors and plasma of breast cancer patients. Cancer Research and Treatment, 37(4), 233–240.PubMedCrossRefGoogle Scholar
  157. 157.
    Urquidi, V., & Goodison, S. (2007). Genomic signatures of breast cancer metastasis. Cytogenetic and Genome Research, 118(2–4), 116–129.PubMedCrossRefGoogle Scholar
  158. 158.
    Kallioniemi, A., Kallioniemi, O. P., Piper, J., Tanner, M., Stokke, T., Chen, L., et al. (1994). Detection and mapping of amplified DNA sequences in breast cancer by comparative genomic hybridization. Proceedings of the National Academy of Sciences of the United States of America, 91(6), 2156–2160.PubMedCrossRefGoogle Scholar
  159. 159.
    Han, W., Han, M. R., Kang, J. J., Bae, J. Y., Lee, J. H., Bae, Y. J., et al. (2006). Genomic alterations identified by array comparative genomic hybridization as prognostic markers in tamoxifen-treated estrogen receptor-positive breast cancer. BMC Cancer, 6, 92.PubMedCrossRefGoogle Scholar
  160. 160.
    Iorio, M. V., Ferracin, M., Liu, C. G., Veronese, A., Spizzo, R., Sabbioni, S., et al. (2005). MicroRNA gene expression deregulation in human breast cancer. Cancer Research, 65(16), 7065–7070.PubMedCrossRefGoogle Scholar
  161. 161.
    Calin, G. A., & Croce, C. M. (2006). MicroRNA signatures in human cancers. Nature Reviews. Cancer, 6(11), 857–866.PubMedCrossRefGoogle Scholar
  162. 162.
    Ma, L., Teruya-Feldstein, J., & Weinberg, R. A. (2007). Tumour invasion and metastasis initiated by microRNA-10b in breast cancer. Nature, 449(7163), 682–688.PubMedCrossRefGoogle Scholar
  163. 163.
    Shi, M., Liu, D., Duan, H., Shen, B., & Guo, N. (2010). Metastasis-related miRNAs, active players in breast cancer invasion, and metastasis. Cancer and Metastasis Reviews, 29(4), 785–799.PubMedCrossRefGoogle Scholar
  164. 164.
    Molloy, T. J., Roepman, P., Naume, B., & van't Veer, L. J. (2012). A prognostic gene expression profile that predicts circulating tumor cell presence in breast cancer patients. PLoS One, 7(2), e32426.PubMedCrossRefGoogle Scholar
  165. 165.
    Alitalo, A., & Detmar, M. (2012). Interaction of tumor cells and lymphatic vessels in cancer progression. Oncogene, 31(42), 4499–4508.Google Scholar
  166. 166.
    Montel, V., Huang, T. Y., Mose, E., Pestonjamasp, K., & Tarin, D. (2005). Expression profiling of primary tumors and matched lymphatic and lung metastases in a xenogeneic breast cancer model. American Journal of Pathology, 166(5), 1565–1579.PubMedCrossRefGoogle Scholar
  167. 167.
    Pandis, N., Teixeira, M. R., Adeyinka, A., Rizou, H., Bardi, G., Mertens, F., et al. (1998). Cytogenetic comparison of primary tumors and lymph node metastases in breast cancer patients. Genes, Chromosomes & Cancer, 22(2), 122–129.CrossRefGoogle Scholar
  168. 168.
    Smeets, A., Daemen, A., Vanden Bempt, I., Gevaert, O., Claes, B., Wildiers, H., et al. (2011). Prediction of lymph node involvement in breast cancer from primary tumor tissue using gene expression profiling and miRNAs. Breast Cancer Research and Treatment, 129(3), 767–776.PubMedCrossRefGoogle Scholar
  169. 169.
    Schwarzenbach, H., Milde-Langosch, K., Steinbach, B., Muller, V., & Pantel, K. (2012). Diagnostic potential of PTEN-targeting miR-214 in the blood of breast cancer patients. Breast Cancer Res Treat, 134(3), 933–941.Google Scholar
  170. 170.
    Schwarzenbach, H., Muller, V., Beeger, C., Gottberg, M., Stahmann, N., & Pantel, K. (2007). A critical evaluation of loss of heterozygosity detected in tumor tissues, blood serum and bone marrow plasma from patients with breast cancer. Breast Cancer Research, 9(5), R66.PubMedCrossRefGoogle Scholar
  171. 171.
    Barekati, Z., Radpour, R., Lu, Q., Bitzer, J., Zheng, H., Toniolo, P., et al. (2012). Methylation signature of lymph node metastases in breast cancer patients. BMC Cancer, 12, 244.PubMedCrossRefGoogle Scholar
  172. 172.
    Gobel, G., Auer, D., Gaugg, I., Schneitter, A., Lesche, R., Muller-Holzner, E., et al. (2011). Prognostic significance of methylated RASSF1A and PITX2 genes in blood- and bone marrow plasma of breast cancer patients. Breast Cancer Research and Treatment, 130(1), 109–117.PubMedCrossRefGoogle Scholar
  173. 173.
    Matuschek, C., Bolke, E., Lammering, G., Gerber, P. A., Peiper, M., Budach, W., et al. (2010). Methylated APC and GSTP1 genes in serum DNA correlate with the presence of circulating blood tumor cells and are associated with a more aggressive and advanced breast cancer disease. European Journal of Medical Research, 15(7), 277–286.PubMedGoogle Scholar
  174. 174.
    Van der Auwera, I., Elst, H. J., Van Laere, S. J., Maes, H., Huget, P., van Dam, P., et al. (2009). The presence of circulating total DNA and methylated genes is associated with circulating tumour cells in blood from breast cancer patients. British Journal of Cancer, 100(8), 1277–1286.PubMedCrossRefGoogle Scholar
  175. 175.
    Dulaimi, E., Hillinck, J., Ibanez de Caceres, I., Al-Saleem, T., & Cairns, P. (2004). Tumor suppressor gene promoter hypermethylation in serum of breast cancer patients. Clinical Cancer Research, 10(18 Pt 1), 6189–6193.PubMedCrossRefGoogle Scholar
  176. 176.
    Martinez-Galan, J., Torres, B., Del Moral, R., Munoz-Gamez, J. A., Martin-Oliva, D., Villalobos, M., et al. (2008). Quantitative detection of methylated ESR1 and 14-3-3-sigma gene promoters in serum as candidate biomarkers for diagnosis of breast cancer and evaluation of treatment efficacy. Cancer Biology & Therapy, 7(6), 958–965.CrossRefGoogle Scholar
  177. 177.
    Papadopoulou, E., Davilas, E., Sotiriou, V., Georgakopoulos, E., Georgakopoulou, S., Koliopanos, A., et al. (2006). Cell-free DNA and RNA in plasma as a new molecular marker for prostate and breast cancer. Annals of the New York Academy of Sciences, 1075, 235–243.PubMedCrossRefGoogle Scholar
  178. 178.
    Cuk, K., Zucknick, M., Heil, J., Madhavan, D., Schott, S., Turchinovich, A., et al. (2012). Circulating microRNAs in plasma as early detection markers for breast cancer. International Journal of Cancer.Google Scholar
  179. 179.
    Cookson, V. J., Bentley, M. A., Hogan, B. V., Horgan, K., Hayward, B. E., Hazelwood, L. D., et al. (2012). Circulating microRNA profiles reflect the presence of breast tumours but not the profiles of microRNAs within the tumours. Cell Oncology (Dordrecht), 35(4), 301–308.CrossRefGoogle Scholar
  180. 180.
    Wang, H., Tan, G., Dong, L., Cheng, L., Li, K., Wang, Z., et al. (2012). Circulating MiR-125b as a marker predicting chemoresistance in breast cancer. PLoS One, 7(4), e34210.PubMedCrossRefGoogle Scholar
  181. 181.
    Jung, E. J., Santarpia, L., Kim, J., Esteva, F. J., Moretti, E., Buzdar, A. U., et al. (2012). Plasma microRNA 210 levels correlate with sensitivity to trastuzumab and tumor presence in breast cancer patients. Cancer, 118(10), 2603–2614.PubMedCrossRefGoogle Scholar
  182. 182.
    Zhao, R., Wu, J., Jia, W., Gong, C., Yu, F., Ren, Z., et al. (2011). Plasma miR-221 as a predictive biomarker for chemoresistance in breast cancer patients who previously received neoadjuvant chemotherapy. Onkologie, 34(12), 675–680.PubMedCrossRefGoogle Scholar
  183. 183.
    Zhao, H., Shen, J., Medico, L., Wang, D., Ambrosone, C. B., & Liu, S. (2010). A pilot study of circulating miRNAs as potential biomarkers of early stage breast cancer. PLoS One, 5(10), e13735.PubMedCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2012

Authors and Affiliations

  • David S. Guttery
    • 1
  • Kevin Blighe
    • 1
  • Karen Page
    • 1
  • Stephanie D. Marchese
    • 2
  • Allison Hills
    • 2
  • R. Charles Coombes
    • 2
  • Justin Stebbing
    • 2
  • Jacqueline A. Shaw
    • 1
  1. 1.Department of Cancer Studies and Molecular MedicineLeicester Royal InfirmaryLeicesterUK
  2. 2.Division of CancerImperial CollegeLondonUK

Personalised recommendations