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ORIGINAL RESEARCH

Establishment and Validation of a Model for Disease-Free Survival Rate Prediction Using the Combination of microRNA-381 and Clinical Indicators in Patients with Breast Cancer

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Pages 375-389 | Received 20 Jul 2022, Accepted 15 Nov 2022, Published online: 04 Dec 2023

References

  • Bray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, Jemal A. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2018;68(6):394–424. doi:10.3322/caac.21492
  • Torre LA, Bray F, Siegel RL, Ferlay J, Lortet-Tieulent J, Jemal A. Global cancer statistics, 2012. CA Cancer J Clin. 2015;65(2):87–108. doi:10.3322/caac.21262
  • McGuire S. World Cancer Report 2014. Geneva, Switzerland: World Health Organization, International Agency for Research on Cancer, WHO Press; 2015.
  • Tan XF, Xia F. Long-term fatigue state in postoperative patients with breast cancer. Chin J Cancer Res. 2014;26(1):12–16. doi:10.3978/j.issn.1000-9604.2014.01.12
  • Saphner T, Tormey DC, Gray R. Annual hazard rates of recurrence for breast cancer after primary therapy. J Clin Oncol. 1996;14(10):2738–2746. doi:10.1200/JCO.1996.14.10.2738
  • Colleoni M, Sun Z, Price KN, et al. Annual hazard rates of recurrence for breast cancer during 24 years of follow-up: results from the international breast cancer study group trials I to V. J Clin Oncol. 2016;34(9):927–935. doi:10.1200/JCO.2015.62.3504
  • Bojesen SE, Pooley KA, Johnatty SE, et al. Multiple independent variants at the TERT locus are associated with telomere length and risks of breast and ovarian cancer. Nat Genet. 2013;45(4):371–84, 384e1–2. doi:10.1038/ng.2566
  • Cserni G, Chmielik E, Cserni B, Tot T. The new TNM-based staging of breast cancer. Virchows Arch. 2018;472(5):697–703. doi:10.1007/s00428-018-2301-9
  • Ming J, Zhou Y, Du J, et al. miR-381 suppresses C/EBPα-dependent Cx43 expression in breast cancer cells. Biosci Rep. 2015;35(6). doi:10.1042/BSR20150167
  • Xue Y, Xu W, Zhao W, Wang W, Zhang D, Wu P. miR-381 inhibited breast cancer cells proliferation, epithelial-to-mesenchymal transition and metastasis by targeting CXCR4. Biomed Pharmacother. 2017;86:426–433. doi:10.1016/j.biopha.2016.12.051
  • Pan Z, Ding J, Yang Z, Li H, Ding H, Chen Q. LncRNA FLVCR1-AS1 promotes proliferation, migration and activates Wnt/β-catenin pathway through miR-381-3p/CTNNB1 axis in breast cancer. Cancer Cell Int. 2020;20:214. doi:10.1186/s12935-020-01247-2
  • Mi H, Wang X, Wang F, et al. miR-381 induces sensitivity of breast cancer cells to doxorubicin by inactivation of MAPK signaling via FYN. Eur J Pharmacol. 2018;839:66–75. doi:10.1016/j.ejphar.2018.09.024
  • Zhang M, Yang L, Hou L, Tang X. LncRNA SNHG1 promotes tumor progression and cisplatin resistance through epigenetically silencing miR-381 in breast cancer. Bioengineered. 2021;12(2):9239–9250. doi:10.1080/21655979.2021.1996305
  • Goetz MP, Gradishar WJ, Anderson BO, et al. NCCN guidelines insights: breast cancer, version 3.2018. J Natl Compr Canc Netw. 2019;17(2):118–126. doi:10.6004/jnccn.2019.0009
  • Singletary SE, Allred C, Ashley P, et al. Staging system for breast cancer: revisions for the 6th edition of the AJCC cancer staging manual. Surg Clin North Am. 2003;83(4):803–819. doi:10.1016/S0039-6109(03)00034-3
  • Wolff AC, Hammond ME, Hicks DG, et al. Recommendations for human epidermal growth factor receptor 2 testing in breast cancer: American society of clinical oncology/college of American pathologists clinical practice guideline update. J Clin Oncol. 2013;31(31):3997–4013. doi:10.1200/JCO.2013.50.9984
  • Perou CM, Sørlie T, Eisen MB, et al. Molecular portraits of human breast tumours. Nature. 2000;406(6797):747–752. doi:10.1038/35021093
  • Goldhirsch A, Wood WC, Coates AS, et al. Strategies for subtypes--dealing with the diversity of breast cancer: highlights of the St. Gallen international expert consensus on the primary therapy of early breast cancer 2011. Ann Oncol. 2011;22(8):1736–1747. doi:10.1093/annonc/mdr304
  • Park SY. Nomogram: an analogue tool to deliver digital knowledge. J Thorac Cardiovasc Surg. 2018;155(4):1793. doi:10.1016/j.jtcvs.2017.12.107
  • Li J, Ma S. Time-dependent ROC analysis under diverse censoring patterns. Stat Med. 2011;30(11):1266–1277. doi:10.1002/sim.4178
  • Pepe MS, Fan J, Feng Z, et al. The Net Reclassification Index (NRI): a misleading measure of prediction improvement even with independent test data sets. Stat Biosci. 2015;7(2):282–295. doi:10.1007/s12561-014-9118-0
  • Van Calster B, Wynants L, Verbeek J, et al. Reporting and interpreting decision curve analysis: a guide for investigators. Eur Urol. 2018;74(6):796–804. doi:10.1016/j.eururo.2018.08.038
  • Lánczky A, Győrffy B. Web-based survival analysis tool tailored for medical research (KMplot): development and implementation. J Med Internet Res. 2021;23(7):e27633. doi:10.2196/27633
  • Soldatos CR, Dikeos DG, Paparrigopoulos TJ. Athens insomnia scale: validation of an instrument based on ICD-10 criteria. J Psychosom Res. 2000;48(6):555–560. doi:10.1016/S0022-3999(00)00095-7
  • Friedman J, Hastie T, Tibshirani R. Regularization paths for generalized linear models via coordinate descent. J Stat Softw. 2010;33(1):1–22. doi:10.18637/jss.v033.i01
  • Sauerbrei W, Boulesteix AL, Binder H. Stability investigations of multivariable regression models derived from low- and high-dimensional data. J Biopharm Stat. 2011;21(6):1206–1231. doi:10.1080/10543406.2011.629890
  • Huitzil-Melendez FD, Capanu M, O’Reilly EM, et al. Advanced hepatocellular carcinoma: which staging systems best predict prognosis? J Clin Oncol. 2010;28(17):2889–2895. doi:10.1200/JCO.2009.25.9895
  • Burstein HJ, Temin S, Anderson H, et al. Adjuvant endocrine therapy for women with hormone receptor-positive breast cancer: American society of clinical oncology clinical practice guideline focused update. J Clin Oncol. 2014;32(21):2255–2269. doi:10.1200/JCO.2013.54.2258
  • Voduc KD, Cheang MC, Tyldesley S, et al. Breast cancer subtypes and the risk of local and regional relapse. J Clin Oncol. 2010;28(10):1684–1691. doi:10.1200/JCO.2009.24.9284
  • Tang H, Liu X, Wang Z, et al. Interaction of hsa-miR-381 and glioma suppressor LRRC4 is involved in glioma growth. Brain Res. 2011;1390:21–32. doi:10.1016/j.brainres.2011.03.034
  • Liang Y, Zhao Q, Fan L, et al. Down-regulation of MicroRNA-381 promotes cell proliferation and invasion in colon cancer through up-regulation of LRH-1. Biomed Pharmacother. 2015;75:137–141. doi:10.1016/j.biopha.2015.07.020
  • Yu YZ, Mu Q, Ren Q, et al. miR-381-3p suppresses breast cancer progression by inhibition of epithelial-mesenchymal transition. World J Surg Oncol. 2021;19(1):230. doi:10.1186/s12957-021-02344-w
  • Deng P, Tan M, Zhou W, et al. Bisphenol A promotes breast cancer cell proliferation by driving miR-381-3p-PTTG1-dependent cell cycle progression. Chemosphere. 2021;268:129221. doi:10.1016/j.chemosphere.2020.129221
  • Mohammadi-Yeganeh S, Hosseini V, Paryan M. Wnt pathway targeting reduces triple-negative breast cancer aggressiveness through miRNA regulation in vitro and in vivo. J Cell Physiol. 2019;234(10):18317–18328. doi:10.1002/jcp.28465
  • Wang D-Y, Gendoo D, Ben-David Y, et al. A subgroup of microRNAs defines PTEN-deficient, triple-negative breast cancer patients with poorest prognosis and alterations in RB1, MYC, and Wnt signaling. Breast Cancer Res. 2019;21(1):18. doi:10.1186/s13058-019-1098-z
  • Lyu L, Wang M, Zheng Y, et al. Overexpression of FAM234B predicts poor prognosis in patients with luminal breast cancer. Cancer Manag Res. 2020;12:12457–12471. doi:10.2147/CMAR.S280009
  • Pan Z, Ding J, Yang Z, Li H, Ding H, Chen Q. LncRNA FLVCR1-AS1 promotes proliferation, migration and activates Wnt/β-catenin pathway through miR-381-3p/CTNNB1 axis in breast cancer. Cancer Cell Int. 2020;20(1):214. PMID: 32518523, PMCID: PMC7275497. doi:10.1186/s12935-020-01247-2
  • Davey MG, Hynes SO, Kerin MJ, et al. Ki-67 as a prognostic biomarker in invasive breast cancer. Cancers. 2021;13(17):4455. doi:10.3390/cancers13174455
  • Kanyılmaz G, Yavuz BB, Aktan M, et al. Prognostic importance of Ki-67 in breast cancer and its relationship with other prognostic factors. Eur J Breast Health. 2019;15(4):256–261. doi:10.5152/ejbh.2019.4778
  • Menon SS, Guruvayoorappan C, Sakthivel KM, et al. Ki-67 protein as a tumour proliferation marker. Clin Chim Acta. 2019;491:39–45. doi:10.1016/j.cca.2019.01.011
  • Liang Q, Ma D, Gao R-F, et al. Effect of Ki-67 expression levels and histological grade on breast cancer early relapse in patients with different immunohistochemical-based subtypes. Sci Rep. 2020;10(1):7648. doi:10.1038/s41598-020-64523-1
  • Dihge L, Bendahl PO, Rydén L. Nomograms for preoperative prediction of axillary nodal status in breast cancer. Br J Surg. 2017;104(11):1494–1505. doi:10.1002/bjs.10583