Why the Gold Standard Approach by Mammography Demands Extension by Multiomics? Application of Liquid Biopsy miRNA Profiles to Breast Cancer Disease Management
Abstract
:1. Introduction
2. Breast Cancer in the Context of Global Cancer Mortality
3. Breast Cancer Screening by Mammography: An Evolution
4. Breast Cancer Screening by Mammography and Profiling of Genetic Risk
4.1. Low- and Intermediate-Risk Women
4.2. High-Risk Women
4.3. Genetic Profiling as a Tool for the Risk Assessment
4.4. Proteomic Profiling as a Tool for Screening Guidelines
5. Liquid Biopsy as Marker for Breast Cancer Control and Management
Extracellular miRNA Molecules as an Important Tool of Liquid Biopsy in BC Screening
6. Circulating miRNA
7. miRNAs as Potential Blood-Based Biomarkers for Early Breast Cancer Detection
8. Tumor vs Serum miRNA Profile as a Background for miRNAs Based Screening
9. The Role of Circulating miRNAs in Profiling of BC at the Time of Sampling for Screening
10. Pros and Cons for miRNAs in BC Screening and Management
11. Conclusions and Expert Recommendations
- -
- unmet needs of young populations such as innovative screening programs for early and predictive diagnosis, for example in case of planned pregnancies to avoid pregnancy associated BC [213]
- -
- -
Funding
Acknowledgments
Conflicts of Interest
References
- Ferlay, J.; Colombet, M.; Soerjomataram, I.; Mathers, C.; Parkin, D.M.; Piñeros, M.; Znaor, A.; Bray, F. Estimating the global cancer incidence and mortality in 2018: GLOBOCAN sources and methods. Int. J. Cancer 2018, 144, 1941–1953. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Golubnitschaja, O.; Sridhar, K.C. Liver metastatic disease: New concepts and biomarker panels to improve individual outcomes. Clin. Exp. Metastasis 2016, 33, 743–755. [Google Scholar] [CrossRef] [PubMed]
- Golubnitschaja, O. Feeling cold and other underestimated symptoms in breast cancer: Anecdotes or individual profiles for advanced patient stratification? EPMA J. 2017, 8, 17–22. [Google Scholar] [CrossRef]
- Zubor, P.; Gondova, A.; Polivka, J.; Kasajova, P.; Konieczka, K.; Danko, J.; Golubnitschaja, O. Breast cancer and Flammer syndrome: Any symptoms in common for prediction, prevention and personalised medical approach? EPMA J. 2017, 8, 129–140. [Google Scholar] [CrossRef] [PubMed]
- Fröhlich, H.; Patjoshi, S.; Yeghiazaryan, K.; Kehrer, C.; Kuhn, W.; Golubnitschaja, O. Premenopausal breast cancer: Potential clinical utility of a multi-omics based machine learning approach for patient stratification. EPMA J. 2018, 9, 175–186. [Google Scholar] [CrossRef]
- Zubor, P.; Kubatka, P.; Dankova, Z.; Gondova, A.; Kajo, K.; Hatok, J.; Samec, M.; Jagelkova, M.; Krivus, S.; Holubekova, V.; et al. miRNA in a multiomic context for diagnosis, treatment monitoring and personalized management of metastatic breast cancer. Future Oncol. 2018, 14, 1847–1867. [Google Scholar] [CrossRef]
- Golubnitschaja, O.; Polivka, J.; Yeghiazaryan, K.; Berliner, L. Liquid biopsy and multiparametric analysis in management of liver malignancies: New concepts of the patient stratification and prognostic approach. EPMA J. 2018, 9, 271–285. [Google Scholar] [CrossRef]
- Statistical Office of the European Communities; Kotzeva, M.; Brandmüller, T.; Önnerfors, Å. Eurostat Regional Yearbook 2014; Publications Office of the European Union: Luxembourg, 2014; ISBN 978-92-79-38906-1. [Google Scholar]
- Ferlay, J.; Steliarova-Foucher, E.; Lortet-Tieulent, J.; Rosso, S.; Coebergh, J.W.W.; Comber, H.; Forman, D.; Bray, F. Cancer incidence and mortality patterns in Europe: Estimates for 40 countries in 2012. Eur. J. Cancer 2013, 49, 1374–1403. [Google Scholar] [CrossRef] [Green Version]
- Ferlay, J.; Soerjomataram, I.; Dikshit, R.; Eser, S.; Mathers, C.; Rebelo, M.; Parkin, D.M.; Forman, D.; Bray, F. Cancer incidence and mortality worldwide: Sources, methods and major patterns in GLOBOCAN 2012: Globocan 2012. Int. J. Cancer 2015, 136, E359–E386. [Google Scholar] [CrossRef]
- Golubnitschaja, O.; Debald, M.; Yeghiazaryan, K.; Kuhn, W.; Pešta, M.; Costigliola, V.; Grech, G. Breast cancer epidemic in the early twenty-first century: Evaluation of risk factors, cumulative questionnaires and recommendations for preventive measures. Tumor Biol. 2016, 37, 12941–12957. [Google Scholar] [CrossRef]
- DeSantis, C.E.; Ma, J.; Goding Sauer, A.; Newman, L.A.; Jemal, A. Breast cancer statistics, 2017, racial disparity in mortality by state: Breast Cancer Statistics, 2017. CA Cancer J. Clin. 2017, 67, 439–448. [Google Scholar] [CrossRef] [PubMed]
- Malvezzi, M.; Carioli, G.; Bertuccio, P.; Boffetta, P.; Levi, F.; La Vecchia, C.; Negri, E. European cancer mortality predictions for the year 2019 with focus on breast cancer. Ann. Oncol. 2019, 30, 781–787. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Altobelli, E.; Lattanzi, A. Breast cancer in European Union: An update of screening programmes as of March 2014 (Review). Int. J. Oncol. 2014, 45, 1785–1792. [Google Scholar] [CrossRef]
- Breast Cancer Breast Screening Programme, England Statistics for 2014–2015, Health and Social Care Information Centre. Available online: https://digital.nhs.uk/data-and-information/publications/statistical/breast-screening-programme/breast-screening-programme-england-2014-15 (accessed on 4 June 2019).
- Programme de Dépistage du Cancer du sein en France: Résultats 2006; Institut de Veille Sanitaire: Saint-Maurice, France, 2009; Available online: http://invs.santepubliquefrance.fr/publications/2009/plaquette_depistage_cancer_sein_2006/depistage_cancer_sein_2006.pdf (accessed on 4 June 2019).
- Giordano, L.; Castagno, R.; Giorgi, D.; Piccinelli, C.; Ventura, L.; Segnan, N.; Zappa, M. Breast cancer screening in Italy: Evaluating key performance indicators for time trends and activity volumes. Epidemiol. Prev. 2015, 39, 30–39. [Google Scholar] [PubMed]
- Marnach-Kopp, B. Mammographie-Screening in Deutschland, Informationen und Adressen. Kooperationsgemeinschaft Mammographie 2008. Available online: http://www.zentralestelle-bayern.de/downloads/info_adressen.pdf (accessed on 4 June 2019).
- Laat je Borsten Zien: Doen of Niet? Resultaten Screening. Available online: https://www.zol.be/sites/default/files/deelsites/medische-beeldvorming/verwijzers/sympoisa/20140920/dr.-van-steen-laat-je-borsten-zien-doen-of-niet.pdf (accessed on 4 June 2019).
- Skol, A.D.; Sasaki, M.M.; Onel, K. The genetics of breast cancer risk in the post-genome era: Thoughts on study design to move past BRCA and towards clinical relevance. Breast Cancer Res. 2016, 18, 99. [Google Scholar] [CrossRef] [PubMed]
- Chetlen, A.; Mack, J.; Chan, T. Breast cancer screening controversies: Who, when, why, and how? Clin. Imaging 2016, 40, 279–282. [Google Scholar] [CrossRef] [PubMed]
- Pérez-Solis, M.A.; Maya-Nuñez, G.; Casas-González, P.; Olivares, A.; Aguilar-Rojas, A. Effects of the lifestyle habits in breast cancer transcriptional regulation. Cancer Cell Int. 2016, 16, 7. [Google Scholar] [CrossRef] [PubMed]
- Drukteinis, J.S.; Mooney, B.P.; Flowers, C.I.; Gatenby, R.A. Beyond Mammography: New Frontiers in Breast Cancer Screening. Am. J. Med. 2013, 126, 472–479. [Google Scholar] [CrossRef] [PubMed]
- Wilczek, B.; Wilczek, H.E.; Rasouliyan, L.; Leifland, K. Adding 3D automated breast ultrasound to mammography screening in women with heterogeneously and extremely dense breasts: Report from a hospital-based, high-volume, single-center breast cancer screening program. Eur. J. Radiol. 2016, 85, 1554–1563. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Lebron-Zapata, L.; Jochelson, M.S. Overview of Breast Cancer Screening and Diagnosis. PET Clin. 2018, 13, 301–323. [Google Scholar] [CrossRef] [PubMed]
- Polivka, J.; Kralickova, M.; Polivka, J.; Kaiser, C.; Kuhn, W.; Golubnitschaja, O. Mystery of the brain metastatic disease in breast cancer patients: Improved patient stratification, disease prediction and targeted prevention on the horizon? EPMA J. 2017, 8, 119–127. [Google Scholar] [CrossRef] [PubMed]
- Yung, R.L.; Ligibel, J.A. Obesity and breast cancer: Risk, outcomes, and future considerations. Clin. Adv. Hematol. Oncol. 2016, 14, 790–797. [Google Scholar] [PubMed]
- Golubnitschaja, O.; Filep, N.; Yeghiazaryan, K.; Blom, H.J.; Hofmann-Apitius, M.; Kuhn, W. Multi-omic approach decodes paradoxes of the triple-negative breast cancer: Lessons for predictive, preventive and personalised medicine. Amino Acids 2018, 50, 383–395. [Google Scholar] [CrossRef] [PubMed]
- Golubnitschaja, O.; Yeghiazaryan, K.; Abraham, J.-A.; Schild, H.H.; Costigliola, V.; Debald, M.; Kuhn, W. Breast cancer risk assessment: A non-invasive multiparametric approach to stratify patients by MMP-9 serum activity and RhoA expression patterns in circulating leucocytes. Amino Acids 2017, 49, 273–281. [Google Scholar] [CrossRef] [PubMed]
- Hinkson, I.V.; Davidsen, T.M.; Klemm, J.D.; Chandramouliswaran, I.; Kerlavage, A.R.; Kibbe, W.A. A Comprehensive Infrastructure for Big Data in Cancer Research: Accelerating Cancer Research and Precision Medicine. Front. Cell Dev. Biol. 2017, 5, 83. [Google Scholar] [CrossRef] [PubMed]
- Koch, H. Mammography as a method for diagnosing breast cancer. Radiol. Bras. 2016, 49, VII. [Google Scholar] [CrossRef] [PubMed]
- Gay, H.; Pietrosanu, R.; George, S.; Tzias, D.; Mehta, R.; Patel, C.; Heller, S.; Wilkinson, L. PB.13: Comparison between analogue and digital mammography: A reader’s perspective. Breast Cancer Res. 2013, 15, P13. [Google Scholar] [CrossRef]
- Van Ravesteyn, N.T. Tipping the Balance of Benefits and Harms to Favor Screening Mammography Starting at Age 40 Years: A Comparative Modeling Study of Risk. Ann. Intern. Med. 2012, 156, 609. [Google Scholar] [CrossRef] [PubMed]
- Helvie, M.A. Digital Mammography Imaging: Breast Tomosynthesis and Advanced Applications. Radiol. Clin. N. Am. 2010, 48, 917–929. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Niklason, L.T.; Christian, B.T.; Niklason, L.E.; Kopans, D.B.; Castleberry, D.E.; Opsahl-Ong, B.H.; Landberg, C.E.; Slanetz, P.J.; Giardino, A.A.; Moore, R.; et al. Digital tomosynthesis in breast imaging. Radiology 1997, 205, 399–406. [Google Scholar] [CrossRef] [PubMed]
- Uchiyama, N.; Kikuchi, M.; Machida, M.; Arai, Y.; Murakami, R.; Otsuka, K.; Jerebko, A.; Kelm, M.; Mertelmeier, T. Diagnostic Usefulness of Synthetic MMG (SMMG) with DBT (Digital Breast Tomosynthesis) for Clinical Setting in Breast Cancer Screening. In Breast Imaging; Tingberg, A., Lång, K., Timberg, P., Eds.; Springer International Publishing: Cham, Switzerland, 2016; Volume 9699, pp. 59–67. ISBN 978-3-319-41545-1. [Google Scholar]
- Takahashi, T.A.; Lee, C.I.; Johnson, K.M. Breast cancer screening: Does tomosynthesis augment mammography? Cleve Clin. J. Med. 2017, 84, 522–527. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Tonelli, M.; Connor Gorber, S.; Joffres, M.; Dickinson, J.; Singh, H.; Lewin, G.; Birtwhistle, R.; Fitzpatrick-Lewis, D.; Hodgson, N.; Ciliska, D.; et al. Recommendations on screening for breast cancer in average-risk women aged 40–74 years. CMAJ Can. Med. Assoc. J. J. Assoc. Medicale Can. 2011, 183, 1991–2001. [Google Scholar]
- Olsen, O.; Gøtzsche, P.C. Cochrane review on screening for breast cancer with mammography. Lancet 2001, 358, 1340–1342. [Google Scholar] [CrossRef]
- Miller, A.B. The role of screening mammography in the era of modern breast cancer treatment. Climacteric 2018, 21, 204–208. [Google Scholar] [CrossRef] [PubMed]
- Redmond, C.E.; Healy, G.M.; Murphy, C.F.; O’Doherty, A.; Foster, A. The use of ultrasonography and digital mammography in women under 40 years with symptomatic breast cancer: A 7-year Irish experience. Ir. J. Med. Sci. (1971-) 2017, 186, 63–67. [Google Scholar] [CrossRef] [PubMed]
- Lehman, C.D.; Lee, C.I.; Loving, V.A.; Portillo, M.S.; Peacock, S.; DeMartini, W.B. Accuracy and Value of Breast Ultrasound for Primary Imaging Evaluation of Symptomatic Women 30–39 Years of Age. Am. J. Roentgenol. 2012, 199, 1169–1177. [Google Scholar] [CrossRef] [PubMed]
- Cho, N.; Han, W.; Han, B.-K.; Bae, M.S.; Ko, E.S.; Nam, S.J.; Chae, E.Y.; Lee, J.W.; Kim, S.H.; Kang, B.J.; et al. Breast Cancer Screening with Mammography Plus Ultrasonography or Magnetic Resonance Imaging in Women 50 Years or Younger at Diagnosis and Treated with Breast Conservation Therapy. JAMA Oncol. 2017, 3, 1495. [Google Scholar] [CrossRef]
- Wellings, E.; Vassiliades, L.; Abdalla, R. Breast Cancer Screening for High-Risk Patients of Different Ages and Risk—Which Modality Is Most Effective? Cureus 2016. [Google Scholar] [CrossRef]
- Anders, C.K.; Hsu, D.S.; Broadwater, G.; Acharya, C.R.; Foekens, J.A.; Zhang, Y.; Wang, Y.; Marcom, P.K.; Marks, J.R.; Febbo, P.G.; et al. Young Age at Diagnosis Correlates with Worse Prognosis and Defines a Subset of Breast Cancers with Shared Patterns of Gene Expression. J. Clin. Oncol. 2008, 26, 3324–3330. [Google Scholar] [CrossRef]
- Meisel, S.F.; Pashayan, N.; Rahman, B.; Side, L.; Fraser, L.; Gessler, S.; Lanceley, A.; Wardle, J. Adjusting the frequency of mammography screening on the basis of genetic risk: Attitudes among women in the UK. Breast 2015, 24, 237–241. [Google Scholar] [CrossRef] [Green Version]
- Pashayan, N.; Duffy, S.W.; Chowdhury, S.; Dent, T.; Burton, H.; Neal, D.E.; Easton, D.F.; Eeles, R.; Pharoah, P. Polygenic susceptibility to prostate and breast cancer: Implications for personalised screening. Br. J. Cancer 2011, 104, 1656–1663. [Google Scholar] [CrossRef] [PubMed]
- Gagnon, J.; Lévesque, E.; Borduas, F.; Chiquette, J.; Diorio, C.; Duchesne, N.; Dumais, M.; Eloy, L.; Foulkes, W.; Gervais, N.; et al. Recommendations on breast cancer screening and prevention in the context of implementing risk stratification: Impending changes to current policies. Curr. Oncol. 2016, 23, 615. [Google Scholar] [CrossRef] [PubMed]
- Nelson, H.D.; Pappas, M.; Cantor, A.; Griffin, J.; Daeges, M.; Humphrey, L. Harms of Breast Cancer Screening: Systematic Review to Update the 2009 U.S. Preventive Services Task Force Recommendation. Ann. Intern. Med. 2016, 164, 256. [Google Scholar] [CrossRef] [PubMed]
- Hellquist, B.N.; Czene, K.; Hjälm, A.; Nyström, L.; Jonsson, H. Effectiveness of population-based service screening with mammography for women ages 40 to 49 years with a high or low risk of breast cancer: Socioeconomic status, parity, and age at birth of first child: Mammography Effectiveness in Risk Groups. Cancer 2015, 121, 251–258. [Google Scholar] [CrossRef] [PubMed]
- Moss, S.M.; Cuckle, H.; Evans, A.; Johns, L.; Waller, M.; Bobrow, L. Effect of mammographic screening from age 40 years on breast cancer mortality at 10 years’ follow-up: A randomised controlled trial. Lancet 2006, 368, 2053–2060. [Google Scholar] [CrossRef]
- The Canadian National Breast Screening Study-1: Breast Cancer Mortality after 11 to 16 Years of Follow-Up. A Randomized Screening Trial of Mammography in Women Age 40 to 49 Years. Available online: https://www.ncbi.nlm.nih.gov/pubmed/12204013 (accessed on 4 June 2019).
- Moss, S.M.; Wale, C.; Smith, R.; Evans, A.; Cuckle, H.; Duffy, S.W. Effect of mammographic screening from age 40 years on breast cancer mortality in the UK Age trial at 17 years’ follow-up: A randomised controlled trial. Lancet Oncol. 2015, 16, 1123–1132. [Google Scholar] [CrossRef]
- Nelson, H.D. Screening for Breast Cancer: An Update for the U.S. Preventive Services Task Force. Ann. Intern. Med. 2009, 151, 727. [Google Scholar] [CrossRef]
- Sutton, T.; Reilly, P.; Johnson, N.; Garreau, J.R. Breast cancer in women under 50: Most are not high risk. Am. J. Surg. 2018, 215, 848–851. [Google Scholar] [CrossRef]
- Sung, J.S.; Stamler, S.; Brooks, J.; Kaplan, J.; Huang, T.; Dershaw, D.D.; Lee, C.H.; Morris, E.A.; Comstock, C.E. Breast Cancers Detected at Screening MR Imaging and Mammography in Patients at High Risk: Method of Detection Reflects Tumor Histopathologic Results. Radiology 2016, 280, 716–722. [Google Scholar] [CrossRef]
- Ford, D.; Easton, D.F.; Stratton, M.; Narod, S.; Goldgar, D.; Devilee, P.; Bishop, D.T.; Weber, B.; Lenoir, G.; Chang-Claude, J.; et al. Genetic heterogeneity and penetrance analysis of the BRCA1 and BRCA2 genes in breast cancer families. The Breast Cancer Linkage Consortium. Am. J. Hum. Genet. 1998, 62, 676–689. [Google Scholar] [CrossRef]
- Roa, B.B.; Boyd, A.A.; Volcik, K.; Richards, C.S. Ashkenazi Jewish population frequencies for common mutations in BRCA1 and BRCA2. Nat. Genet. 1996, 14, 185–187. [Google Scholar] [CrossRef] [PubMed]
- Lord, S.J.; Lei, W.; Craft, P.; Cawson, J.N.; Morris, I.; Walleser, S.; Griffiths, A.; Parker, S.; Houssami, N. A systematic review of the effectiveness of magnetic resonance imaging (MRI) as an addition to mammography and ultrasound in screening young women at high risk of breast cancer. Eur. J. Cancer 2007, 43, 1905–1917. [Google Scholar] [CrossRef] [PubMed]
- Hartman, A.-R.; Daniel, B.L.; Kurian, A.W.; Mills, M.A.; Nowels, K.W.; Dirbas, F.M.; Kingham, K.E.; Chun, N.M.; Herfkens, R.J.; Ford, J.M.; et al. Breast magnetic resonance image screening and ductal lavage in women at high genetic risk for breast carcinoma. Cancer 2004, 100, 479–489. [Google Scholar] [CrossRef] [PubMed]
- Lowry, K.P.; Lee, J.M.; Kong, C.Y.; McMahon, P.M.; Gilmore, M.E.; Cott Chubiz, J.E.; Pisano, E.D.; Gatsonis, C.; Ryan, P.D.; Ozanne, E.M.; et al. Annual screening strategies in BRCA1 and BRCA2 gene mutation carriers: A comparative effectiveness analysis. Cancer 2012, 118, 2021–2030. [Google Scholar] [CrossRef] [PubMed]
- Phi, X.-A.; Saadatmand, S.; De Bock, G.H.; Warner, E.; Sardanelli, F.; Leach, M.O.; Riedl, C.C.; Trop, I.; Hooning, M.J.; Mandel, R.; et al. Contribution of mammography to MRI screening in BRCA mutation carriers by BRCA status and age: Individual patient data meta-analysis. Br. J. Cancer 2016, 114, 631–637. [Google Scholar] [CrossRef] [PubMed]
- Van Zelst, J.C.M.; Mus, R.D.M.; Woldringh, G.; Rutten, M.J.C.M.; Bult, P.; Vreemann, S.; de Jong, M.; Karssemeijer, N.; Hoogerbrugge, N.; Mann, R.M. Surveillance of Women with the BRCA 1 or BRCA 2 Mutation by Using Biannual Automated Breast US, MR Imaging, and Mammography. Radiology 2017, 285, 376–388. [Google Scholar] [CrossRef]
- Autier, P.; Boniol, M. Mammography screening: A major issue in medicine. Eur. J. Cancer 2018, 90, 34–62. [Google Scholar] [CrossRef]
- The Independent UK Panel on Breast Cancer Screening; Marmot, M.G.; Altman, D.G.; Cameron, D.A.; Dewar, J.A.; Thompson, S.G.; Wilcox, M. The benefits and harms of breast cancer screening: An independent review: A report jointly commissioned by Cancer Research UK and the Department of Health (England) October 2012. Br. J. Cancer 2013, 108, 2205–2240. [Google Scholar] [CrossRef]
- Théberge, I.; Chang, S.-L.; Vandal, N.; Daigle, J.-M.; Guertin, M.-H.; Pelletier, É.; Brisson, J. Radiologist Interpretive Volume and Breast Cancer Screening Accuracy in a Canadian Organized Screening Program. JNCI J. Natl. Cancer Inst. 2014, 106. [Google Scholar] [CrossRef]
- Frères, P.; Wenric, S.; Boukerroucha, M.; Fasquelle, C.; Thiry, J.; Bovy, N.; Struman, I.; Geurts, P.; Collignon, J.; Schroeder, H.; et al. Circulating microRNA-based screening tool for breast cancer. Oncotarget 2016, 7, 5416. [Google Scholar] [CrossRef]
- Fu, S.W.; Lee, W.; Coffey, C.; Lean, A.; Wu, X.; Tan, X.; Man, Y.; Brem, R.F. miRNAs as potential biomarkers in early breast cancer detection following mammography. Cell Biosci. 2016, 6, 6. [Google Scholar] [CrossRef] [PubMed]
- Health Quality Ontario Ultrasound as an Adjunct to Mammography for Breast Cancer Screening: A Health Technology Assessment. Ont. Health Technol. Assess. Ser. 2016, 16, 1–71.
- Hooley, R.J.; Andrejeva, L.; Scoutt, L.M. Breast Cancer Screening and Problem Solving Using Mammography, Ultrasound, and Magnetic Resonance Imaging. Ultrasound Q. 2011, 27, 23–47. [Google Scholar] [CrossRef] [PubMed]
- Biswas, S.; Atienza, P.; Chipman, J.; Hughes, K.; Barrera, A.M.G.; Amos, C.I.; Arun, B.; Parmigiani, G. Simplifying clinical use of the genetic risk prediction model BRCAPRO. Breast Cancer Res. Treat. 2013, 139, 571–579. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- The Consortium of Investigators of Modifiers of BRCA1/2; The Breast Cancer Association Consortium; Lee, A.J.; Cunningham, A.P.; Kuchenbaecker, K.B.; Mavaddat, N.; Easton, D.F.; Antoniou, A.C. BOADICEA breast cancer risk prediction model: Updates to cancer incidences, tumour pathology and web interface. Br. J. Cancer 2014, 110, 535–545. [Google Scholar] [CrossRef] [PubMed]
- Mealiffe, M.E.; Stokowski, R.P.; Rhees, B.K.; Prentice, R.L.; Pettinger, M.; Hinds, D.A. Assessment of Clinical Validity of a Breast Cancer Risk Model Combining Genetic and Clinical Information. JNCI J. Natl. Cancer Inst. 2010, 102, 1618–1627. [Google Scholar] [CrossRef] [PubMed]
- McCarthy, A.M.; Armstrong, K.; Handorf, E.; Boghossian, L.; Jones, M.; Chen, J.; Demeter, M.B.; McGuire, E.; Conant, E.F.; Domchek, S.M. Incremental impact of breast cancer SNP panel on risk classification in a screening population of white and African American women. Breast Cancer Res. Treat. 2013, 138, 889–898. [Google Scholar] [CrossRef] [PubMed]
- Dite, G.S.; Mahmoodi, M.; Bickerstaffe, A.; Hammet, F.; Macinnis, R.J.; Tsimiklis, H.; Dowty, J.G.; Apicella, C.; Phillips, K.-A.; Giles, G.G.; et al. Using SNP genotypes to improve the discrimination of a simple breast cancer risk prediction model. Breast Cancer Res. Treat. 2013, 139, 887–896. [Google Scholar] [CrossRef]
- Cuzick, J.; Brentnall, A.R.; Segal, C.; Byers, H.; Reuter, C.; Detre, S.; Lopez-Knowles, E.; Sestak, I.; Howell, A.; Powles, T.J.; et al. Impact of a Panel of 88 Single Nucleotide Polymorphisms on the Risk of Breast Cancer in High-Risk Women: Results from Two Randomized Tamoxifen Prevention Trials. J. Clin. Oncol. 2017, 35, 743–750. [Google Scholar] [CrossRef]
- Wu, Y.; Abbey, C.K.; Liu, J.; Ong, I.; Peissig, P.; Onitilo, A.A.; Fan, J.; Yuan, M.; Burnside, E.S. Discriminatory Power of Common Genetic Variants in Personalized Breast Cancer Diagnosis. Proc. SPIE Int. Soc. Opt. Eng. 2016, 9787, 978706. [Google Scholar]
- Wacholder, S.; Hartge, P.; Prentice, R.; Garcia-Closas, M.; Feigelson, H.S.; Diver, W.R.; Thun, M.J.; Cox, D.G.; Hankinson, S.E.; Kraft, P.; et al. Performance of Common Genetic Variants in Breast-Cancer Risk Models. N. Engl. J. Med. 2010, 362, 986–993. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Liu, J.; Page, D.; Nassif, H.; Shavlik, J.; Peissig, P.; McCarty, C.; Onitilo, A.A.; Burnside, E. Genetic variants improve breast cancer risk prediction on mammograms. AMIA Annu. Symp. Proc. 2013, 2013, 876–885. [Google Scholar] [PubMed]
- Lee, C.P.L.; Choi, H.; Soo, K.C.; Tan, M.-H.; Chay, W.Y.; Chia, K.S.; Liu, J.; Li, J.; Hartman, M. Mammographic Breast Density and Common Genetic Variants in Breast Cancer Risk Prediction. PLoS ONE 2015, 10, e0136650. [Google Scholar] [CrossRef] [PubMed]
- Burnside, E.S.; Liu, J.; Wu, Y.; Onitilo, A.A.; McCarty, C.A.; Page, C.D.; Peissig, P.L.; Trentham-Dietz, A.; Kitchner, T.; Fan, J.; et al. Comparing Mammography Abnormality Features to Genetic Variants in the Prediction of Breast Cancer in Women Recommended for Breast Biopsy. Acad. Radiol. 2016, 23, 62–69. [Google Scholar] [CrossRef] [PubMed]
- Henderson, M.C.; Hollingsworth, A.B.; Gordon, K.; Silver, M.; Mulpuri, R.; Letsios, E.; Reese, D.E. Integration of Serum Protein Biomarker and Tumor Associated Autoantibody Expression Data Increases the Ability of a Blood-Based Proteomic Assay to Identify Breast Cancer. PLoS ONE 2016, 11, e0157692. [Google Scholar] [CrossRef] [PubMed]
- Horne, H.N.; Sherman, M.E.; Pfeiffer, R.M.; Figueroa, J.D.; Khodr, Z.G.; Falk, R.T.; Pollak, M.; Patel, D.A.; Palakal, M.M.; Linville, L.; et al. Circulating insulin-like growth factor-I, insulin-like growth factor binding protein-3 and terminal duct lobular unit involution of the breast: A cross-sectional study of women with benign breast disease. Breast Cancer Res. 2016, 18, 24. [Google Scholar] [CrossRef]
- Reese, D.E.; Henderson, M.C.; Silver, M.; Mulpuri, R.; Letsios, E.; Tran, Q.; Wolf, J.K. Breast density does not impact the ability of Videssa® Breast to detect breast cancer in women under age 50. PLoS ONE 2017, 12, e0186198. [Google Scholar] [CrossRef] [PubMed]
- Lourenco, A.P.; Benson, K.L.; Henderson, M.C.; Silver, M.; Letsios, E.; Tran, Q.; Gordon, K.J.; Borman, S.; Corn, C.; Mulpuri, R.; et al. A Noninvasive Blood-based Combinatorial Proteomic Biomarker Assay to Detect Breast Cancer in Women Under the Age of 50 Years. Clin. Breast Cancer 2017, 17, 516–525.e6. [Google Scholar] [CrossRef] [Green Version]
- Liquid Biopsy: The Future Work for Clinical Pathologist. Available online: https://www.austinpublishinggroup.com/clinical-pathology/fulltext/ajcp-v2-id1034.php (accessed on 4 June 2019).
- Siravegna, G.; Bardelli, A. Genotyping cell-free tumor DNA in the blood to detect residual disease and drug resistance. Genome Biol. 2014, 15, 449. [Google Scholar] [CrossRef] [Green Version]
- Cardoso, A.R.; Moreira, F.T.C.; Fernandes, R.; Sales, M.G.F. Novel and simple electrochemical biosensor monitoring attomolar levels of miRNA-155 in breast cancer. Biosens. Bioelectron. 2016, 80, 621–630. [Google Scholar] [CrossRef]
- Crowley, E.; Di Nicolantonio, F.; Loupakis, F.; Bardelli, A. Liquid biopsy: Monitoring cancer-genetics in the blood. Nat. Rev. Clin. Oncol. 2013, 10, 472–484. [Google Scholar] [CrossRef] [PubMed]
- Pantel, K.; Alix-Panabières, C. Liquid biopsy: Potential and challenges. Mol. Oncol. 2016, 10, 371–373. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Zhai, L.-Y.; Li, M.-X.; Pan, W.-L.; Chen, Y.; Li, M.-M.; Pang, J.-X.; Zheng, L.; Chen, J.-X.; Duan, W.-J. In Situ Detection of Plasma Exosomal MicroRNA-1246 for Breast Cancer Diagnostics by a Au Nanoflare Probe. ACS Appl. Mater. Interfaces 2018, 10, 39478–39486. [Google Scholar] [CrossRef] [PubMed]
- Kim, H.-Y.; Choi, H.-J.; Lee, J.-Y.; Kong, G. Cancer Target Gene Screening: A web application for breast cancer target gene screening using multi-omics data analysis. Brief. Bioinform. 2019. [Google Scholar] [CrossRef] [PubMed]
- Beaver, J.A.; Jelovac, D.; Balukrishna, S.; Cochran, R.L.; Croessmann, S.; Zabransky, D.J.; Wong, H.Y.; Valda Toro, P.; Cidado, J.; Blair, B.G.; et al. Detection of Cancer DNA in Plasma of Patients with Early-Stage Breast Cancer. Clin. Cancer Res. 2014, 20, 2643–2650. [Google Scholar] [CrossRef] [PubMed]
- Chera, B.S.; Kumar, S.; Beaty, B.T.; Marron, D.; Jefferys, S.R.; Green, R.L.; Goldman, E.C.; Amdur, R.; Sheets, N.; Dagan, R.; et al. Rapid Clearance Profile of Plasma Circulating Tumor HPV Type 16 DNA during Chemoradiotherapy Correlates with Disease Control in HPV-Associated Oropharyngeal Cancer. Clin. Cancer Res. Off. J. Am. Assoc. Cancer Res. 2019. [Google Scholar] [CrossRef] [PubMed]
- Ignatiadis, M.; Rack, B.; Rothé, F.; Riethdorf, S.; Decraene, C.; Bonnefoi, H.; Dittrich, C.; Messina, C.; Beauvois, M.; Trapp, E.; et al. Liquid biopsy-based clinical research in early breast cancer: The EORTC 90091-10093 Treat CTC trial. Eur. J. Cancer Oxf. Engl. 1990 2016, 63, 97–104. [Google Scholar] [CrossRef] [PubMed]
- Coombes, R.C.; Page, K.; Salari, R.; Hastings, R.K.; Armstrong, A.; Ahmed, S.; Ali, S.; Cleator, S.; Kenny, L.; Stebbing, J.; et al. Personalized Detection of Circulating Tumor DNA Antedates Breast Cancer Metastatic Recurrence. Clin. Cancer Res. Off. J. Am. Assoc. Cancer Res. 2019. [Google Scholar] [CrossRef] [PubMed]
- Li, X.; Chen, N.; Zhou, L.; Wang, C.; Wen, X.; Jia, L.; Cui, J.; Hoffman, A.R.; Hu, J.-F.; Li, W. Genome-wide target interactome profiling reveals a novel EEF1A1 epigenetic pathway for oncogenic lncRNA MALAT1 in breast cancer. Am. J. Cancer Res. 2019, 9, 714–729. [Google Scholar]
- Bidard, F.-C.; Proudhon, C.; Pierga, J.-Y. Circulating tumor cells in breast cancer. Mol. Oncol. 2016, 10, 418–430. [Google Scholar] [CrossRef] [Green Version]
- Hall, C.; Valad, L.; Lucci, A. Circulating Tumor Cells in Breast Cancer Patients. Crit. Rev. Oncog. 2016, 21, 125–139. [Google Scholar] [CrossRef] [PubMed]
- Mansouri, S.; Hesari, P.M.; Naghavi-al-Hosseini, F.; Majidzadeh-A, K.; Farahmand, L. The Prognostic Value of Circulating Tumor Cells in Primary Breast Cancer Prior to any Systematic Therapy: A Systematic Review. Curr. Stem Cell Res. Ther. 2019, 14. [Google Scholar] [CrossRef] [PubMed]
- Mego, M.; Karaba, M.; Minarik, G.; Benca, J.; Silvia, J.; Sedlackova, T.; Manasova, D.; Kalavska, K.; Pindak, D.; Cristofanilli, M.; et al. Circulating Tumor Cells with Epithelial–to–mesenchymal Transition Phenotypes Associated with Inferior Outcomes in Primary Breast Cancer. Anticancer Res. 2019, 39, 1829–1837. [Google Scholar] [CrossRef]
- Kumar, S.; Lindsay, D.; Chen, Q.B.; Garrett, A.L.; Tan, X.M.; Anders, C.K.; Carey, L.A.; Gupta, G.P. Tracking plasma DNA mutation dynamics in estrogen receptor positive metastatic breast cancer with dPCR-SEQ. NPJ Breast Cancer 2018, 4, 39. [Google Scholar] [CrossRef] [PubMed]
- Diaz, L.A.; Bardelli, A. Liquid Biopsies: Genotyping Circulating Tumor DNA. J. Clin. Oncol. 2014, 32, 579–586. [Google Scholar] [CrossRef]
- Bettegowda, C.; Sausen, M.; Leary, R.J.; Kinde, I.; Wang, Y.; Agrawal, N.; Bartlett, B.R.; Wang, H.; Luber, B.; Alani, R.M.; et al. Detection of Circulating Tumor DNA in Early- and Late-Stage Human Malignancies. Sci. Transl. Med. 2014, 6, 224ra24. [Google Scholar] [CrossRef] [PubMed]
- Diehl, F.; Schmidt, K.; Choti, M.A.; Romans, K.; Goodman, S.; Li, M.; Thornton, K.; Agrawal, N.; Sokoll, L.; Szabo, S.A.; et al. Circulating mutant DNA to assess tumor dynamics. Nat. Med. 2008, 14, 985–990. [Google Scholar] [CrossRef] [PubMed]
- Shigeyasu, K.; Toden, S.; Zumwalt, T.J.; Okugawa, Y.; Goel, A. Emerging Role of MicroRNAs as Liquid Biopsy Biomarkers in Gastrointestinal Cancers. Clin. Cancer Res. 2017, 23, 2391–2399. [Google Scholar] [CrossRef] [PubMed]
- Shah, M.Y.; Ferrajoli, A.; Sood, A.K.; Lopez-Berestein, G.; Calin, G.A. microRNA Therapeutics in Cancer—An Emerging Concept. EBioMedicine 2016, 12, 34–42. [Google Scholar] [CrossRef] [PubMed]
- Takahashi, R.; Miyazaki, H.; Ochiya, T. The Roles of MicroRNAs in Breast Cancer. Cancers 2015, 7, 598–616. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Van Schooneveld, E.; Wildiers, H.; Vergote, I.; Vermeulen, P.B.; Dirix, L.Y.; Van Laere, S.J. Dysregulation of microRNAs in breast cancer and their potential role as prognostic and predictive biomarkers in patient management. Breast Cancer Res. 2015, 17, 21. [Google Scholar] [CrossRef] [PubMed]
- Abba, M.L.; Patil, N.; Leupold, J.H.; Moniuszko, M.; Utikal, J.; Niklinski, J.; Allgayer, H. MicroRNAs as novel targets and tools in cancer therapy. Cancer Lett. 2017, 387, 84–94. [Google Scholar] [CrossRef] [PubMed]
- Mohr, A.; Mott, J. Overview of MicroRNA Biology. Semin. Liver Dis. 2015, 35, 003–011. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Hsu, P.W.C. miRNAMap: Genomic maps of microRNA genes and their target genes in mammalian genomes. Nucleic Acids Res. 2006, 34, D135–D139. [Google Scholar] [CrossRef] [PubMed]
- Fiorucci, G.; Chiantore, M.V.; Mangino, G.; Percario, Z.A.; Affabris, E.; Romeo, G. Cancer regulator microRNA: Potential relevance in diagnosis, prognosis and treatment of cancer. Curr. Med. Chem. 2012, 19, 461–474. [Google Scholar] [CrossRef] [PubMed]
- Lee, R.C.; Feinbaum, R.L.; Ambros, V. The C. elegans heterochronic gene lin-4 encodes small RNAs with antisense complementarity to lin-14. Cell 1993, 75, 843–854. [Google Scholar] [CrossRef]
- Iorio, M.V.; Croce, C.M. Commentary on microRNA Fingerprint in Human Epithelial Ovarian Cancer. Cancer Res. 2016, 76, 6143–6145. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Calin, G.A.; Dumitru, C.D.; Shimizu, M.; Bichi, R.; Zupo, S.; Noch, E.; Aldler, H.; Rattan, S.; Keating, M.; Rai, K.; et al. Nonlinear partial differential equations and applications: Frequent deletions and down-regulation of micro-RNA genes miR15 and miR16 at 13q14 in chronic lymphocytic leukemia. Proc. Natl. Acad. Sci. USA 2002, 99, 15524–15529. [Google Scholar] [CrossRef]
- Homo Sapiens miRNAs (1917 Sequences) [GRCh38]. Available online: http://www.mirbase.org/cgi-bin/mirna_summary.pl?org=hsa (accessed on 4 June 2019).
- Griffiths-Jones, S. miRBase: microRNA sequences, targets and gene nomenclature. Nucleic Acids Res. 2006, 34, D140–D144. [Google Scholar] [CrossRef]
- Iorio, M.V.; Ferracin, M.; Liu, C.-G.; Veronese, A.; Spizzo, R.; Sabbioni, S.; Magri, E.; Pedriali, M.; Fabbri, M.; Campiglio, M.; et al. MicroRNA Gene Expression Deregulation in Human Breast Cancer. Cancer Res. 2005, 65, 7065–7070. [Google Scholar] [CrossRef]
- Lu, J.; Getz, G.; Miska, E.A.; Alvarez-Saavedra, E.; Lamb, J.; Peck, D.; Sweet-Cordero, A.; Ebert, B.L.; Mak, R.H.; Ferrando, A.A.; et al. MicroRNA expression profiles classify human cancers. Nature 2005, 435, 834–838. [Google Scholar] [CrossRef] [PubMed]
- Jia, W.; Wu, Y.; Zhang, Q.; Gao, G.; Zhang, C.; Xiang, Y. Expression profile of circulating microRNAs as a promising fingerprint for cervical cancer diagnosis and monitoring. Mol. Clin. Oncol. 2015, 3, 851–858. [Google Scholar] [CrossRef] [Green Version]
- Keller, A.; Leidinger, P.; Borries, A.; Wendschlag, A.; Wucherpfennig, F.; Scheffler, M.; Huwer, H.; Lenhof, H.-P.; Meese, E. miRNAs in lung cancer—Studying complex fingerprints in patient’s blood cells by microarray experiments. BMC Cancer 2009, 9, 353. [Google Scholar] [CrossRef] [PubMed]
- Iorio, M.V.; Visone, R.; Di Leva, G.; Donati, V.; Petrocca, F.; Casalini, P.; Taccioli, C.; Volinia, S.; Liu, C.-G.; Alder, H.; et al. MicroRNA Signatures in Human Ovarian Cancer. Cancer Res. 2007, 67, 8699–8707. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Raychaudhuri, M.; Bronger, H.; Buchner, T.; Kiechle, M.; Weichert, W.; Avril, S. MicroRNAs miR-7 and miR-340 predict response to neoadjuvant chemotherapy in breast cancer. Breast Cancer Res. Treat. 2017, 162, 511–521. [Google Scholar] [CrossRef] [PubMed]
- Sohel, M.H. Extracellular/Circulating MicroRNAs: Release Mechanisms, Functions and Challenges. Achiev. Life Sci. 2016, 10, 175–186. [Google Scholar] [CrossRef] [Green Version]
- Turchinovich, A.; Tonevitsky, A.G.; Burwinkel, B. Extracellular miRNA: A Collision of Two Paradigms. Trends Biochem. Sci. 2016, 41, 883–892. [Google Scholar] [CrossRef] [PubMed]
- Weber, J.A.; Baxter, D.H.; Zhang, S.; Huang, D.Y.; How Huang, K.; Jen Lee, M.; Galas, D.J.; Wang, K. The MicroRNA Spectrum in 12 Body Fluids. Clin. Chem. 2010, 56, 1733–1741. [Google Scholar] [CrossRef] [PubMed]
- Mo, M.-H.; Chen, L.; Fu, Y.; Wang, W.; Fu, S.W. Cell-free Circulating miRNA Biomarkers in Cancer. J. Cancer 2012, 3, 432–448. [Google Scholar] [CrossRef]
- Shah, M.Y.; Calin, G.A. The Mix of Two Worlds: Non-Coding RNAs and Hormones. Nucleic Acid Ther. 2013, 23, 2–8. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Cocucci, E.; Racchetti, G.; Meldolesi, J. Shedding microvesicles: Artefacts no more. Trends Cell Biol. 2009, 19, 43–51. [Google Scholar] [CrossRef] [PubMed]
- Sourvinou, I.S.; Markou, A.; Lianidou, E.S. Quantification of Circulating miRNAs in Plasma. J. Mol. Diagn. 2013, 15, 827–834. [Google Scholar] [CrossRef]
- Boon, R.A.; Vickers, K.C. Intercellular Transport of MicroRNAs. Arterioscler. Thromb. Vasc. Biol. 2013, 33, 186–192. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Matamala, N.; Vargas, M.T.; Gonzalez-Campora, R.; Minambres, R.; Arias, J.I.; Menendez, P.; Andres-Leon, E.; Gomez-Lopez, G.; Yanowsky, K.; Calvete-Candenas, J.; et al. Tumor MicroRNA Expression Profiling Identifies Circulating MicroRNAs for Early Breast Cancer Detection. Clin. Chem. 2015, 61, 1098–1106. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Arroyo, J.D.; Chevillet, J.R.; Kroh, E.M.; Ruf, I.K.; Pritchard, C.C.; Gibson, D.F.; Mitchell, P.S.; Bennett, C.F.; Pogosova-Agadjanyan, E.L.; Stirewalt, D.L.; et al. Argonaute2 complexes carry a population of circulating microRNAs independent of vesicles in human plasma. Proc. Natl. Acad. Sci. USA 2011, 108, 5003–5008. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Théry, C. Exosomes: Secreted vesicles and intercellular communications. F1000 Biol. Rep. 2011, 3, 15. [Google Scholar] [CrossRef]
- Kahlert, C.; Kalluri, R. Exosomes in tumor microenvironment influence cancer progression and metastasis. J. Mol. Med. 2013, 91, 431–437. [Google Scholar] [CrossRef] [Green Version]
- Pigati, L.; Yaddanapudi, S.C.S.; Iyengar, R.; Kim, D.-J.; Hearn, S.A.; Danforth, D.; Hastings, M.L.; Duelli, D.M. Selective Release of MicroRNA Species from Normal and Malignant Mammary Epithelial Cells. PLoS ONE 2010, 5, e13515. [Google Scholar] [CrossRef]
- Chen, X.; Ba, Y.; Ma, L.; Cai, X.; Yin, Y.; Wang, K.; Guo, J.; Zhang, Y.; Chen, J.; Guo, X.; et al. Characterization of microRNAs in serum: A novel class of biomarkers for diagnosis of cancer and other diseases. Cell Res. 2008, 18, 997–1006. [Google Scholar] [CrossRef]
- Schrauder, M.G.; Strick, R.; Schulz-Wendtland, R.; Strissel, P.L.; Kahmann, L.; Loehberg, C.R.; Lux, M.P.; Jud, S.M.; Hartmann, A.; Hein, A.; et al. Circulating Micro-RNAs as Potential Blood-Based Markers for Early Stage Breast Cancer Detection. PLoS ONE 2012, 7, e29770. [Google Scholar] [CrossRef]
- Witwer, K.W. Circulating MicroRNA Biomarker Studies: Pitfalls and Potential Solutions. Clin. Chem. 2015, 61, 56–63. [Google Scholar] [CrossRef] [PubMed]
- Witwer, K.W.; Buzás, E.I.; Bemis, L.T.; Bora, A.; Lässer, C.; Lötvall, J.; Nolte-‘t Hoen, E.N.; Piper, M.G.; Sivaraman, S.; Skog, J.; et al. Standardization of sample collection, isolation and analysis methods in extracellular vesicle research. J. Extracell. Vesicles 2013, 2, 20360. [Google Scholar] [CrossRef] [PubMed]
- Piva, R.; Spandidos, D.A.; Gambari, R. From microRNA functions to microRNA therapeutics: Novel targets and novel drugs in breast cancer research and treatment. Int. J. Oncol. 2013, 43, 985–994. [Google Scholar] [CrossRef] [PubMed]
- Armand-Labit, V.; Pradines, A. Circulating cell-free microRNAs as clinical cancer biomarkers. Biomol. Concepts 2017, 8, 61–81. [Google Scholar] [CrossRef] [PubMed]
- Khoury, S.; Tran, N. Circulating microRNAs: Potential Biomarkers for Common Malignancies. Biomark. Med. 2015, 9, 131–151. [Google Scholar] [CrossRef] [PubMed]
- NCI Dictionary of Cancer Terms. Available online: https://www.cancer.gov/publications/dictionaries/cancer-terms (accessed on 4 June 2019).
- Susana Campuzano; María Pedrero; José Pingarrón Non-Invasive Breast Cancer Diagnosis through Electrochemical Biosensing at Different Molecular Levels. Sensors 2017, 17, 1993. [CrossRef] [PubMed]
- Hamam, R.; Ali, A.M.; Alsaleh, K.A.; Kassem, M.; Alfayez, M.; Aldahmash, A.; Alajez, N.M. microRNA expression profiling on individual breast cancer patients identifies novel panel of circulating microRNA for early detection. Sci. Rep. 2016, 6, 25997. [Google Scholar] [CrossRef] [Green Version]
- Heneghan, H.M.; Miller, N.; Lowery, A.J.; Sweeney, K.J.; Newell, J.; Kerin, M.J. Circulating microRNAs as Novel Minimally Invasive Biomarkers for Breast Cancer. Ann. Surg. 2010, 251, 499–505. [Google Scholar] [CrossRef]
- Cookson, V.J.; Bentley, M.A.; Hogan, B.V.; Horgan, K.; Hayward, B.E.; Hazelwood, L.D.; Hughes, T.A. Circulating microRNA profiles reflect the presence of breast tumours but not the profiles of microRNAs within the tumours. Cell. Oncol. 2012, 35, 301–308. [Google Scholar] [CrossRef]
- Zhu, J.; Zheng, Z.; Wang, J.; Sun, J.; Wang, P.; Cheng, X.; Fu, L.; Zhang, L.; Wang, Z.; Li, Z. Different miRNA expression profiles between human breast cancer tumors and serum. Front. Genet. 2014, 5, 149. [Google Scholar] [CrossRef] [Green Version]
- Zhao, H.; Shen, J.; Medico, L.; Wang, D.; Ambrosone, C.B.; Liu, S. A Pilot Study of Circulating miRNAs as Potential Biomarkers of Early Stage Breast Cancer. PLoS ONE 2010, 5, e13735. [Google Scholar] [CrossRef]
- Cuk, K.; Zucknick, M.; Madhavan, D.; Schott, S.; Golatta, M.; Heil, J.; Marmé, F.; Turchinovich, A.; Sinn, P.; Sohn, C.; et al. Plasma MicroRNA Panel for Minimally Invasive Detection of Breast Cancer. PLoS ONE 2013, 8, e76729. [Google Scholar] [CrossRef] [PubMed]
- Chen, W.; Cai, F.; Zhang, B.; Barekati, Z.; Zhong, X.Y. The level of circulating miRNA-10b and miRNA-373 in detecting lymph node metastasis of breast cancer: Potential biomarkers. Tumor Biol. 2013, 34, 455–462. [Google Scholar] [CrossRef] [PubMed]
- Inns, J.; James, V. Circulating microRNAs for the prediction of metastasis in breast cancer patients diagnosed with early stage disease. Breast 2015, 24, 364–369. [Google Scholar] [CrossRef] [PubMed]
- Madhavan, D.; Peng, C.; Wallwiener, M.; Zucknick, M.; Nees, J.; Schott, S.; Rudolph, A.; Riethdorf, S.; Trumpp, A.; Pantel, K.; et al. Circulating miRNAs with prognostic value in metastatic breast cancer and for early detection of metastasis. Carcinogenesis 2016, 37, 461–470. [Google Scholar] [CrossRef] [Green Version]
- Wang, P.-Y.; Gong, H.-T.; Li, B.-F.; Lv, C.-L.; Wang, H.-T.; Zhou, H.-H.; Li, X.-X.; Xie, S.-Y.; Jiang, B.-F. Higher expression of circulating miR-182 as a novel biomarker for breast cancer. Oncol. Lett. 2013, 6, 1681–1686. [Google Scholar] [CrossRef] [PubMed]
- Sun, Y.; Wang, M.; Lin, G.; Sun, S.; Li, X.; Qi, J.; Li, J. Serum MicroRNA-155 as a Potential Biomarker to Track Disease in Breast Cancer. PLoS ONE 2012, 7, e47003. [Google Scholar] [CrossRef] [PubMed]
- Fang, R.; Zhu, Y.; Hu, L.; Khadka, V.S.; Ai, J.; Zou, H.; Ju, D.; Jiang, B.; Deng, Y.; Hu, X. Plasma MicroRNA Pair Panels as Novel Biomarkers for Detection of Early Stage Breast Cancer. Front. Physiol. 2019, 9, 1879. [Google Scholar] [CrossRef] [Green Version]
- Li, S.; Yang, X.; Yang, J.; Zhen, J.; Zhang, D. Serum microRNA-21 as a potential diagnostic biomarker for breast cancer: A systematic review and meta-analysis. Clin. Exp. Med. 2016, 16, 29–35. [Google Scholar] [CrossRef]
- Schwarzenbach, H. Circulating nucleic acids as biomarkers in breast cancer. Breast Cancer Res. 2013, 15, 211. [Google Scholar] [CrossRef]
- Markou, A.; Zavridou, M.; Sourvinou, I.; Yousef, G.; Kounelis, S.; Malamos, N.; Georgoulias, V.; Lianidou, E. Direct Comparison of Metastasis-Related miRNAs Expression Levels in Circulating Tumor Cells, Corresponding Plasma, and Primary Tumors of Breast Cancer Patients. Clin. Chem. 2016, 62, 1002–1011. [Google Scholar] [CrossRef] [PubMed]
- Wang, F.; Hou, J.; Jin, W.; Li, J.; Yue, Y.; Jin, H.; Wang, X. Increased Circulating MicroRNA-155 as a Potential Biomarker for Breast Cancer Screening: A Meta-Analysis. Molecules 2014, 19, 6282–6293. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Moldovan, L.; Batte, K.; Wang, Y.; Wisler, J.; Piper, M. Analyzing the Circulating MicroRNAs in Exosomes/Extracellular Vesicles from Serum or Plasma by qRT-PCR. In Circulating MicroRNAs; Kosaka, N., Ed.; Humana Press: Totowa, NJ, USA, 2013; Volume 1024, pp. 129–145. ISBN 978-1-62703-452-4. [Google Scholar]
- Chen, X.; Liang, H.; Zhang, J.; Zen, K.; Zhang, C.-Y. Horizontal transfer of microRNAs: Molecular mechanisms and clinical applications. Protein Cell 2012, 3, 28–37. [Google Scholar] [CrossRef] [PubMed]
- Bahrami, A.; Aledavood, A.; Anvari, K.; Hassanian, S.M.; Maftouh, M.; Yaghobzade, A.; Salarzaee, O.; ShahidSales, S.; Avan, A. The prognostic and therapeutic application of microRNAs in breast cancer: Tissue and circulating microRNAs. J. Cell. Physiol. 2018, 233, 774–786. [Google Scholar] [CrossRef] [PubMed]
- Kleivi Sahlberg, K.; Bottai, G.; Naume, B.; Burwinkel, B.; Calin, G.A.; Borresen-Dale, A.-L.; Santarpia, L. A Serum MicroRNA Signature Predicts Tumor Relapse and Survival in Triple-Negative Breast Cancer Patients. Clin. Cancer Res. 2015, 21, 1207–1214. [Google Scholar] [CrossRef] [PubMed]
- Anfossi, S.; Giordano, A.; Gao, H.; Cohen, E.N.; Tin, S.; Wu, Q.; Garza, R.J.; Debeb, B.G.; Alvarez, R.H.; Valero, V.; et al. High Serum miR-19a Levels Are Associated with Inflammatory Breast Cancer and Are Predictive of Favorable Clinical Outcome in Patients with Metastatic HER2+ Inflammatory Breast Cancer. PLoS ONE 2014, 9, e83113. [Google Scholar] [CrossRef] [PubMed]
- Bertoli, G.; Cava, C.; Castiglioni, I. MicroRNAs: New Biomarkers for Diagnosis, Prognosis, Therapy Prediction and Therapeutic Tools for Breast Cancer. Theranostics 2015, 5, 1122–1143. [Google Scholar] [CrossRef] [PubMed]
- Kodahl, A.R.; Lyng, M.B.; Binder, H.; Cold, S.; Gravgaard, K.; Knoop, A.S.; Ditzel, H.J. Novel circulating microRNA signature as a potential non-invasive multi-marker test in ER-positive early-stage breast cancer: A case control study. Mol. Oncol. 2014, 8, 874–883. [Google Scholar] [CrossRef]
- Godfrey, A.C.; Xu, Z.; Weinberg, C.R.; Getts, R.C.; Wade, P.A.; DeRoo, L.A.; Sandler, D.P.; Taylor, J.A. Serum microRNA expression as an early marker for breast cancer risk in prospectively collected samples from the Sister Study cohort. Breast Cancer Res. 2013, 15, R42. [Google Scholar] [CrossRef]
- Guo, L.-J.; Zhang, Q.-Y. Decreased serum miR-181a is a potential new tool for breast cancer screening. Int. J. Mol. Med. 2012, 30, 680–686. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Mar-Aguilar, F.; Mendoza-Ramírez, J.A.; Malagón-Santiago, I.; Espino-Silva, P.K.; Santuario-Facio, S.K.; Ruiz-Flores, P.; Rodríguez-Padilla, C.; Reséndez-Pérez, D. Serum Circulating microRNA Profiling for Identification of Potential Breast Cancer Biomarkers. Dis. Markers 2013, 34, 163–169. [Google Scholar] [CrossRef] [PubMed]
- Sochor, M.; Basova, P.; Pesta, M.; Dusilkova, N.; Bartos, J.; Burda, P.; Pospisil, V.; Stopka, T. Oncogenic MicroRNAs: miR-155, miR-19a, miR-181b, and miR-24 enable monitoring of early breast cancer in serum. BMC Cancer 2014, 14, 448. [Google Scholar] [CrossRef] [PubMed]
- Roth, C.; Rack, B.; Müller, V.; Janni, W.; Pantel, K.; Schwarzenbach, H. Circulating microRNAs as blood-based markers for patients with primary and metastatic breast cancer. Breast Cancer Res. 2010, 12, R90. [Google Scholar] [CrossRef] [PubMed]
- Wang, F.; Zheng, Z.; Guo, J.; Ding, X. Correlation and quantitation of microRNA aberrant expression in tissues and sera from patients with breast tumor. Gynecol. Oncol. 2010, 119, 586–593. [Google Scholar] [CrossRef] [PubMed]
- Zhang, L.; Dong, B.; Ren, P.; Ye, H.; Shi, J.; Qin, J.; Wang, K.; Wang, P.; Zhang, J. Circulating plasma microRNAs in the detection of esophageal squamous cell carcinoma. Oncol. Lett. 2018, 16, 3303–3318. [Google Scholar] [CrossRef] [Green Version]
- Zhao, S.; Wu, Q.; Gao, F.; Zhang, C.; Yang, X. Serum microRNA-155 as a potential biomarker for breast cancer screening. Chin. Sci. Bull. 2012, 57, 3466–3468. [Google Scholar] [CrossRef] [Green Version]
- Chan, M.; Liaw, C.S.; Ji, S.M.; Tan, H.H.; Wong, C.Y.; Thike, A.A.; Tan, P.H.; Ho, G.H.; Lee, A.S.-G. Identification of Circulating MicroRNA Signatures for Breast Cancer Detection. Clin. Cancer Res. 2013, 19, 4477–4487. [Google Scholar] [CrossRef] [Green Version]
- Shen, J.; Hu, Q.; Schrauder, M.; Yan, L.; Wang, D.; Medico, L.; Guo, Y.; Yao, S.; Zhu, Q.; Liu, B.; et al. Circulating miR-148b and miR-133a as biomarkers for breast cancer detection. Oncotarget 2014, 5, 5284. [Google Scholar] [CrossRef]
- Cuk, K.; Zucknick, M.; Heil, J.; Madhavan, D.; Schott, S.; Turchinovich, A.; Arlt, D.; Rath, M.; Sohn, C.; Benner, A.; et al. Circulating microRNAs in plasma as early detection markers for breast cancer. Int. J. Cancer 2013, 132, 1602–1612. [Google Scholar] [CrossRef]
- Ng, E.K.O.; Li, R.; Shin, V.Y.; Jin, H.C.; Leung, C.P.H.; Ma, E.S.K.; Pang, R.; Chua, D.; Chu, K.-M.; Law, W.L.; et al. Circulating microRNAs as Specific Biomarkers for Breast Cancer Detection. PLoS ONE 2013, 8, e53141. [Google Scholar] [CrossRef]
- Hu, Z.; Dong, J.; Wang, L.-E.; Ma, H.; Liu, J.; Zhao, Y.; Tang, J.; Chen, X.; Dai, J.; Wei, Q.; et al. Serum microRNA profiling and breast cancer risk: The use of miR-484/191 as endogenous controls. Carcinogenesis 2012, 33, 828–834. [Google Scholar] [CrossRef] [PubMed]
- Gao, J.; Zhang, Q.; Xu, J.; Guo, L.; Li, X. Clinical significance of serum miR-21 in breast cancer compared with CA153 and CEA. Chin. J. Cancer Res. 2013, 25, 743–748. [Google Scholar]
- Asaga, S.; Kuo, C.; Nguyen, T.; Terpenning, M.; Giuliano, A.E.; Hoon, D.S.B. Direct Serum Assay for MicroRNA-21 Concentrations in Early and Advanced Breast Cancer. Clin. Chem. 2011, 57, 84–91. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Chen, H.; Liu, H.; Zou, H.; Chen, R.; Dou, Y.; Sheng, S.; Dai, S.; Ai, J.; Melson, J.; Kittles, R.A.; et al. Evaluation of Plasma miR-21 and miR-152 as Diagnostic Biomarkers for Common Types of Human Cancers. J. Cancer 2016, 7, 490–499. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Zearo, S.; Kim, E.; Zhu, Y.; Zhao, J.T.; Sidhu, S.B.; Robinson, B.G.; Soon, P.S. MicroRNA-484 is more highly expressed in serum of early breast cancer patients compared to healthy volunteers. BMC Cancer 2014, 14, 200. [Google Scholar] [CrossRef] [PubMed]
- Shimomura, A.; Shiino, S.; Kawauchi, J.; Takizawa, S.; Sakamoto, H.; Matsuzaki, J.; Ono, M.; Takeshita, F.; Niida, S.; Shimizu, C.; et al. Novel combination of serum microRNA for detecting breast cancer in the early stage. Cancer Sci. 2016, 107, 326–334. [Google Scholar] [CrossRef] [PubMed]
- Zhang, L.; Xu, Y.; Jin, X.; Wang, Z.; Wu, Y.; Zhao, D.; Chen, G.; Li, D.; Wang, X.; Cao, H.; et al. A circulating miRNA signature as a diagnostic biomarker for non-invasive early detection of breast cancer. Breast Cancer Res. Treat. 2015, 154, 423–434. [Google Scholar] [CrossRef] [PubMed]
- Li, X.-X.; Gao, S.-Y.; Wang, P.-Y.; Zhou, X.; Li, Y.-J.; Yu, Y.; Yan, Y.-F.; Zhang, H.-H.; Lv, C.-J.; Zhou, H.-H.; et al. Reduced expression levels of let-7c in human breast cancer patients. Oncol. Lett. 2015, 9, 1207–1212. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Zhu, W.; Qin, W.; Atasoy, U.; Sauter, E.R. Circulating microRNAs in breast cancer and healthy subjects. BMC Res. Notes 2009, 2, 89. [Google Scholar] [CrossRef] [PubMed]
- McDermott, A.M.; Miller, N.; Wall, D.; Martyn, L.M.; Ball, G.; Sweeney, K.J.; Kerin, M.J. Identification and Validation of Oncologic miRNA Biomarkers for Luminal A-like Breast Cancer. PLoS ONE 2014, 9, e87032. [Google Scholar] [CrossRef]
- Stückrath, I.; Rack, B.; Janni, W.; Jäger, B.; Pantel, K.; Schwarzenbach, H. Aberrant plasma levels of circulating miR-16, miR-107, miR-130a and miR-146a are associated with lymph node metastasis and receptor status of breast cancer patients. Oncotarget 2015, 6, 13387. [Google Scholar] [CrossRef] [PubMed]
- Eichelser, C.; Flesch-Janys, D.; Chang-Claude, J.; Pantel, K.; Schwarzenbach, H. Deregulated Serum Concentrations of Circulating Cell-Free MicroRNAs miR-17, miR-34a, miR-155, and miR-373 in Human Breast Cancer Development and Progression. Clin. Chem. 2013, 59, 1489–1496. [Google Scholar] [CrossRef] [PubMed]
- Swellam, M.; El Magdoub, H.M.; Hassan, N.M.; Hefny, M.M.; Sobeih, M.E. Potential diagnostic role of circulating MiRNAs in breast cancer: Implications on clinicopathological characters. Clin. Biochem. 2018, 56, 47–54. [Google Scholar] [CrossRef] [PubMed]
- Mishra, S.; Srivastava, A.K.; Suman, S.; Kumar, V.; Shukla, Y. Circulating miRNAs revealed as surrogate molecular signatures for the early detection of breast cancer. Cancer Lett. 2015, 369, 67–75. [Google Scholar] [CrossRef] [PubMed]
- Shin, V.Y.; Siu, J.M.; Cheuk, I.; Ng, E.K.O.; Kwong, A. Circulating cell-free miRNAs as biomarker for triple-negative breast cancer. Br. J. Cancer 2015, 112, 1751–1759. [Google Scholar] [CrossRef] [PubMed]
- Zhang, J.; Jiang, C.; Shi, X.; Yu, H.; Lin, H.; Peng, Y. Diagnostic value of circulating miR-155, miR-21, and miR-10 b as promising biomarkers in human breast cancer. Int. J. Clin. Exp. Pathol. 2016, 9, 10258–10265. [Google Scholar]
- Taslim, C.; Weng, D.Y.; Brasky, T.M.; Dumitrescu, R.G.; Huang, K.; Kallakury, B.V.S.; Krishnan, S.; Llanos, A.A.; Marian, C.; McElroy, J.; et al. Discovery and replication of microRNAs for breast cancer risk using genome-wide profiling. Oncotarget 2016, 7, 86457. [Google Scholar] [CrossRef]
- Kurozumi, S.; Yamaguchi, Y.; Kurosumi, M.; Ohira, M.; Matsumoto, H.; Horiguchi, J. Recent trends in microRNA research into breast cancer with particular focus on the associations between microRNAs and intrinsic subtypes. J. Hum. Genet. 2017, 62, 15–24. [Google Scholar] [CrossRef]
- McGuire, A.; Brown, J.A.L.; Kerin, M.J. Metastatic breast cancer: The potential of miRNA for diagnosis and treatment monitoring. Cancer Metastasis Rev. 2015, 34, 145–155. [Google Scholar] [CrossRef]
- Komatsu, S.; Ichikawa, D.; Takeshita, H.; Morimura, R.; Hirajima, S.; Tsujiura, M.; Kawaguchi, T.; Miyamae, M.; Nagata, H.; Konishi, H.; et al. Circulating miR-18a: A sensitive cancer screening biomarker in human cancer. Vivo Athens Greece 2014, 28, 293–297. [Google Scholar]
- Hamam, R.; Hamam, D.; Alsaleh, K.A.; Kassem, M.; Zaher, W.; Alfayez, M.; Aldahmash, A.; Alajez, N.M. Circulating microRNAs in breast cancer: Novel diagnostic and prognostic biomarkers. Cell Death Dis. 2017, 8, e3045. [Google Scholar] [CrossRef] [PubMed]
- Luengo-Gil, G.; Gonzalez-Billalabeitia, E.; Perez-Henarejos, S.A.; Navarro Manzano, E.; Chaves-Benito, A.; Garcia-Martinez, E.; Garcia-Garre, E.; Vicente, V.; Ayala de la Peña, F. Angiogenic role of miR-20a in breast cancer. PLoS ONE 2018, 13, e0194638. [Google Scholar] [CrossRef] [PubMed]
- Schwarzenbach, H.; Milde-Langosch, K.; Steinbach, B.; Müller, V.; Pantel, K. Diagnostic potential of PTEN-targeting miR-214 in the blood of breast cancer patients. Breast Cancer Res. Treat. 2012, 134, 933–941. [Google Scholar] [CrossRef] [PubMed]
- Wang, S.E.; Lin, R.-J. MicroRNA and HER2-overexpressing cancer. MicroRNA 2013, 2, 137–147. [Google Scholar] [CrossRef] [PubMed]
- Graveel, C.R.; Calderone, H.M.; Westerhuis, J.J.; Winn, M.E.; Sempere, L.F. Critical analysis of the potential for microRNA biomarkers in breast cancer management. Breast Cancer 2015, 7, 59–79. [Google Scholar] [Green Version]
- Wang, H.; Peng, R.; Wang, J.; Qin, Z.; Xue, L. Circulating microRNAs as potential cancer biomarkers: The advantage and disadvantage. Clin. Epigenetics 2018, 10, 59. [Google Scholar] [CrossRef]
- Castro-Giner, F.; Gkountela, S.; Donato, C.; Alborelli, I.; Quagliata, L.; Ng, C.K.Y.; Piscuoglio, S.; Aceto, N. Cancer Diagnosis Using a Liquid Biopsy: Challenges and Expectations. Diagnostics 2018, 8, 31. [Google Scholar] [CrossRef]
- Liu, T.; Zhang, Q.; Zhang, J.; Li, C.; Miao, Y.-R.; Lei, Q.; Li, Q.; Guo, A.-Y. EVmiRNA: A database of miRNA profiling in extracellular vesicles. Nucleic Acids Res. 2019, 47, D89–D93. [Google Scholar] [CrossRef]
- Eichelser, C.; Stückrath, I.; Müller, V.; Milde-Langosch, K.; Wikman, H.; Pantel, K.; Schwarzenbach, H. Increased serum levels of circulating exosomal microRNA-373 in receptor-negative breast cancer patients. Oncotarget 2014, 5, 9650. [Google Scholar] [CrossRef]
- Filipów, S.; Łaczmański, Ł. Blood Circulating miRNAs as Cancer Biomarkers for Diagnosis and Surgical Treatment Response. Front. Genet. 2019, 10, 169. [Google Scholar] [CrossRef]
- Nassar, F.J.; Nasr, R.; Talhouk, R. MicroRNAs as biomarkers for early breast cancer diagnosis, prognosis and therapy prediction. Pharmacol. Ther. 2017, 172, 34–49. [Google Scholar] [CrossRef] [PubMed]
- Polivka, J.; Altun, I.; Golubnitschaja, O. Pregnancy-associated breast cancer: The risky status quo and new concepts of predictive medicine. EPMA J. 2018, 9, 1–13. [Google Scholar] [CrossRef] [PubMed]
- Avishai, E.; Yeghiazaryan, K.; Golubnitschaja, O. Impaired wound healing: Facts and hypotheses for multi-professional considerations in predictive, preventive and personalised medicine. EPMA J. 2017, 8, 23–33. [Google Scholar] [CrossRef] [PubMed]
- Kunin, A.; Polivka, J.; Moiseeva, N.; Golubnitschaja, O. “Dry mouth” and “Flammer” syndromes—neglected risks in adolescents and new concepts by predictive, preventive and personalised approach. EPMA J. 2018, 9, 307–317. [Google Scholar] [CrossRef] [PubMed]
- Girotra, S.; Yeghiazaryan, K.; Golubnitschaja, O. Potential biomarker panels in overall breast cancer management: Advancements by multilevel diagnostics. Pers. Med. 2016, 13, 469–484. [Google Scholar] [CrossRef] [PubMed]
- Golubnitschaja, O.; Baban, B.; Boniolo, G.; Wang, W.; Bubnov, R.; Kapalla, M.; Krapfenbauer, K.; Mozaffari, M.S.; Costigliola, V. Medicine in the early twenty-first century: Paradigm and anticipation—EPMA position paper 2016. EPMA J. 2016, 7, 23. [Google Scholar] [CrossRef]
Categories of Women | Applicability of Mammography |
---|---|
Postmenopausal with fatty breasts | The breast density gradually decreases after menopause, applicable every two years |
Young with very dense breast parenchyma | Low diagnostic sensitivity |
Pregnancy | Mammography is not contraindicated in the first and second trimesters (sufficient shading of the uterus is necessary); USG and MRI are predominant diagnostic methods |
Family history of BC | An annual mammography, supplemental imaging (MRI, USG) in dense breast tissue |
Genetic predisposition to BC | An annual mammogram starting at age 25 |
Diagnosis of atypical hyperplasia or lobular carcinoma in situ | An annual mammogram beginning at the time of diagnosis |
Average BC risk with no symptoms | An annual mammogram combined with USG in dense breast tissue |
miRNA | Expression (BC vs. Normal) | Sample Type | References |
---|---|---|---|
miR-15a | Upregulated | serum | [169] |
miR-18a | Upregulated | serum | [169,170,171] |
miR-107 | Upregulated | serum | [169] |
miR-425 | Upregulated | serum | [169] |
miR-139-5p | Downregulated | serum | [169] |
miR-143 | Downregulated | serum | [169] |
miR-145 | Downregulated | serum | [169,172] |
miR-365 | Downregulated | serum | [169] |
miR-155 | Upregulated | serum | [157,162,172,173,174,175,176,177] |
miR-1 | Upregulated | serum | [178] |
miR-133a | Upregulated | serum | [178,179] |
miR-133b | Upregulated | serum | [178] |
miR-92a | Upregulated | serum | [178] |
miR-148b | Upregulated | plasma | [152,179,180] |
miR-376c | Upregulated | plasma | [180] |
miR-409-3p | Upregulated | plasma | [152,179,180] |
miR-801 | Upregulated | plasma | [180] |
miR-16 | Upregulated | plasma | [181,182] |
miR-21 | Upregulated | plasma/serum | [133,175,176,181,183,184,185] |
miR-451 | Upregulated | plasma | [184] |
miR-145 | Downregulated | plasma | [184] |
miR-222 | Upregulated | serum | [170,182] |
miR-127 | Upregulated | plasma | [152] |
miR-376a | Upregulated | plasma | [152] |
miR-652 | Upregulated | plasma | [152] |
miR-801 | Upregulated | plasma | [152] |
miR-484 | Upregulated | serum | [186] |
miR-1246 | Upregulated | serum | [187] |
miR-1307 | Upregulated | serum | [187] |
miR-6861 | Upregulated | serum | [187] |
miR-4634 | Downregulated | serum | [187] |
miR-6875 | Downregulated | serum | [187] |
miR-181b | Upregulated | serum | [173] |
miR-24 | Upregulated | serum | [173] |
miR-505 | Upregulated | plasma | [133] |
miR-125 | Upregulated | plasma | [133] |
miR-96 | Upregulated | plasma | [133] |
miR-195 | Upregulated | serum | [148] |
miR-199a | Upregulated | serum | [188] |
Let-7a | Upregulated | serum | [148] |
miR-106a | Upregulated | serum | [175] |
miR-126 | Downregulated | serum | [175] |
miR-335 | Downregulated | serum | [175] |
Let-7c | Downregulated | serum | [189] |
miR-182 | Upregulated | serum | [156] |
miR-25 | Upregulated | serum | [182] |
miR-324 | Upregulated | serum | [182] |
miRNA | Expression | ER+/ER− | PR+/PR− | HER2+/HER2− | TNBC+/− | Nodal Affection | Stage of BC | References |
---|---|---|---|---|---|---|---|---|
miR-10b | up | − | − | − | + | yes | early | [153,199,200] |
miR-18a | up | − | − | − | + | [199,201] | ||
miR-18b | up | − | − | − | + | [199,202] | ||
miR-20a | up | + | − | yes | early | [200,203,204] | ||
miR-21 | up | − | − | + | − | yes | early/advanced | [184,200] |
miR-29a | down | + | + | − | − | early | [191] | |
miR-34a | up | − | − | + | − | yes | [200,205] | |
miR-103 | down | + | + | − | − | yes | [154,199] | |
miR-107 | down | + | + | − | yes | [154,199] | ||
miR-125a | down | − | − | + | − | early | [119,199] | |
miR-125b | down | − | − | + | − | early | [119,199] | |
miR-138 | up | + | yes | early | [206] | |||
miR-143 | down | − | − | − | + | early | [196,202] | |
miR-153 | up | − | − | − | + | [199] | ||
miR-155 | up | − | − | − | + | yes | early | [119,199,200] |
miR-181a | down | + | + | − | − | early | [191] | |
miR-193b | up | − | − | + | − | yes | [155,205] | |
miR-200a | up | + | − | yes | [200,205] | |||
miR-200b | up | + | − | yes | [200,205] | |||
miR-200c | up | + | − | yes | [200,205] | |||
miR-342 | up | + | + | + | − | early | [109,199] | |
miR-373 | up | + | − | yes | [193,200] | |||
miR-375 | up | − | − | + | − | yes | [154,205] | |
miR-429 | up | − | − | + | − | yes | [155,199] | |
miR-484 | up | + | yes | early | [206] | |||
miR-486-5p | up | + | + | − | − | yes | [155,191] | |
miR-642-3p | up | early | [207] | |||||
miR-652 | down | + | + | − | − | yes | early | [152,154,191] |
miR-801 | up | + | yes | early | [152,160,206] | |||
miR-1202-5p | up | early | [207] | |||||
miR-1207-5p | up | early | [207] |
© 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Share and Cite
Zubor, P.; Kubatka, P.; Kajo, K.; Dankova, Z.; Polacek, H.; Bielik, T.; Kudela, E.; Samec, M.; Liskova, A.; Vlcakova, D.; et al. Why the Gold Standard Approach by Mammography Demands Extension by Multiomics? Application of Liquid Biopsy miRNA Profiles to Breast Cancer Disease Management. Int. J. Mol. Sci. 2019, 20, 2878. https://doi.org/10.3390/ijms20122878
Zubor P, Kubatka P, Kajo K, Dankova Z, Polacek H, Bielik T, Kudela E, Samec M, Liskova A, Vlcakova D, et al. Why the Gold Standard Approach by Mammography Demands Extension by Multiomics? Application of Liquid Biopsy miRNA Profiles to Breast Cancer Disease Management. International Journal of Molecular Sciences. 2019; 20(12):2878. https://doi.org/10.3390/ijms20122878
Chicago/Turabian StyleZubor, Pavol, Peter Kubatka, Karol Kajo, Zuzana Dankova, Hubert Polacek, Tibor Bielik, Erik Kudela, Marek Samec, Alena Liskova, Dominika Vlcakova, and et al. 2019. "Why the Gold Standard Approach by Mammography Demands Extension by Multiomics? Application of Liquid Biopsy miRNA Profiles to Breast Cancer Disease Management" International Journal of Molecular Sciences 20, no. 12: 2878. https://doi.org/10.3390/ijms20122878
APA StyleZubor, P., Kubatka, P., Kajo, K., Dankova, Z., Polacek, H., Bielik, T., Kudela, E., Samec, M., Liskova, A., Vlcakova, D., Kulkovska, T., Stastny, I., Holubekova, V., Bujnak, J., Laucekova, Z., Büsselberg, D., Adamek, M., Kuhn, W., Danko, J., & Golubnitschaja, O. (2019). Why the Gold Standard Approach by Mammography Demands Extension by Multiomics? Application of Liquid Biopsy miRNA Profiles to Breast Cancer Disease Management. International Journal of Molecular Sciences, 20(12), 2878. https://doi.org/10.3390/ijms20122878