The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.
Circulating Micro-RNAs as Potential Blood-Based Markers for Early Stage Breast Cancer Detection
Open accessAbstract
INTRODUCTION: MicroRNAs (miRNAs, miRs) are a class of small, non-coding RNA molecules with relevance as regulators of gene expression thereby affecting crucial processes in cancer development. MiRNAs offer great potential as biomarkers for cancer detection due to their remarkable stability in blood and their characteristic expression in many different diseases. We investigated whether microarray-based miRNA profiling on whole blood could discriminate between early stage breast cancer patients and healthy controls. METHODS: We performed microarray-based miRNA profiling on whole blood of 48 early stage breast cancer patients at diagnosis along with 57 healthy individuals as controls. This was followed by a real-time semi-quantitative Polymerase Chain Reaction (RT-qPCR) validation in a separate cohort of 24 early stage breast cancer patients from a breast cancer screening unit and 24 age matched controls using two differentially expressed miRNAs (miR-202, miR-718). RESULTS: Using the significance level of p<0.05, we found that 59 miRNAs were differentially expressed in whole blood of early stage breast cancer patients compared to healthy controls. 13 significantly up-regulated miRNAs and 46 significantly down-regulated miRNAs in our microarray panel of 1100 miRNAs and miRNA star sequences could be detected. A set of 240 miRNAs that was evaluated by radial basis function kernel support vector machines and 10-fold cross validation yielded a specificity of 78.8%, and a sensitivity of 92.5%, as well as an accuracy of 85.6%. Two miRNAs were validated by RT-qPCR in an independent cohort. The relative fold changes of the RT-qPCR validation were in line with the microarray data for both miRNAs, and statistically significant differences in miRNA-expression were found for miR-202. CONCLUSIONS: MiRNA profiling in whole blood has potential as a novel method for early stage breast cancer detection, but there are still challenges that need to be addressed to establish these new biomarkers in clinical use.
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The C. elegans heterochronic gene lin-4 encodes small RNAs with antisense complementarity to lin-14
Lee, R. C., Feinbaum, R. L., & Ambros, V. (1993) · Cell · doi:10.1016/0092-8674(93)90529-y · Cited by 12,948
Jemal, A., Siegel, R., Ward, E., Hao, Y., Xu, J., & Thun, M. J. (2009) · CA: A Cancer Journal for Clinicians · doi:10.3322/caac.20006 · Cited by 9,709
MicroRNA Gene Expression Deregulation in Human Breast Cancer
Iorio, M. V., Ferracin, M., Liu, C.-G., Veronese, A., Spizzo, R., Sabbioni, S., Magri, E., Pedriali, M., Fabbri, M., Campiglio, M., et al. (2005) · Cancer Research · doi:10.1158/0008-5472.can-05-1783 · Cited by 4,053
miRBase: integrating microRNA annotation and deep-sequencing data
Kozomara, A., & Griffiths-Jones, S. (2011) · Nucleic Acids Research · doi:10.1093/nar/gkq1027 · Cited by 3,634
The impact of microRNAs on protein output
Baek, D., Villén, J., Shin, C., Camargo, F. D., Gygi, S. P., & Bartel, D. P. (2008) · Nature · doi:10.1038/nature07242 · Cited by 3,592
Huber, W., von Heydebreck, A., Sültmann, H., Poustka, A., & Vingron, M. (2002) · Bioinformatics · doi:10.1093/bioinformatics/18.suppl_1.s96 · Cited by 2,440
A Pilot Study of Circulating miRNAs as Potential Biomarkers of Early Stage Breast Cancer
Zhao, H., Shen, J., Medico, L., Wang, D., Ambrosone, C. B., & Liu, S. (2010) · PLoS ONE · doi:10.1371/journal.pone.0013735 · Cited by 398
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Sugimachi, K., Matsumura, T., Hirata, H., Uchi, R., Ueda, M., Ueo, H., Shinden, Y., Iguchi, T., Eguchi, H., Shirabe, K., et al. (2015) · British Journal of Cancer · doi:10.1038/bjc.2014.621 · Cited by 263
Plasma MicroRNAs as Novel Biomarkers for Endometriosis and Endometriosis-Associated Ovarian Cancer
Suryawanshi, S., Vlad, A. M., Lin, H.-M., Mantia-Smaldone, G., Laskey, R., Lee, M., Lin, Y., Donnellan, N., Klein-Patel, M., Lee, T., et al. (2013) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-12-2726 · Cited by 197
Yong, F. L., Law, C. W., & Wang, C. W. (2013) · BMC Cancer · doi:10.1186/1471-2407-13-280 · Cited by 176
Epigenetics as a Therapeutic Target in Breast Cancer
Connolly, R., & Stearns, V. (2012) · Journal of Mammary Gland Biology and Neoplasia · doi:10.1007/s10911-012-9263-3 · Cited by 117
Müller, M., Kuiperij, H. B., Versleijen, A. A. M., Chiasserini, D., Farotti, L., Baschieri, F., Parnetti, L., Struyfs, H., De Roeck, N., Luyckx, J., et al. (2016) · Journal of Alzheimer’s Disease · doi:10.3233/jad-160038 · Cited by 41
Metadata
- Authors
- 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., Bayer, C. M., Bani, M. R., Richter, S., Adamietz, B. R., Wenkel, E., Rauh, C., Beckmann, M. W., & Fasching, P. A.
- Venue
- PLoS ONE
- Publisher
- Public Library of Science (PLoS)
- Published
- 2012-01-05
- Volume
- 7
- Issue
- 1
- Pages
- e29770
- ISSN
- 1932-6203 (ISSN-L)
- OpenAlex
- W2026866676
- Cited by
- 250
- References
- 7
- FWCI
- 10.46
- Type
- journal article
- Language
- en
- Open access
- gold
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- 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., Bayer, C. M., Bani, M. R., Richter, S., Adamietz, B. R., Wenkel, E., Rauh, C., Beckmann, M. W., & Fasching, P. A. (2012). Circulating Micro-RNAs as Potential Blood-Based Markers for Early Stage Breast Cancer Detection. PLoS ONE. https://doi.org/10.1371/journal.pone.0029770
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