Skip to main content

Small non-coding RNA profiling in breast cancer: plasma U6 snRNA, miR-451a and miR-548b-5p as novel diagnostic and prognostic biomarkers

Abstract

Background

Breast cancer is a leading cause of cancer-related death in women. Most cases are invasive ductal carcinomas of no special type (NST breast carcinomas).

Methods and Results

In this prospective, multicentric biomarker discovery study, we analyzed the expression of small non-coding RNAs (mainly microRNAs) in plasma by qPCR and evaluated their association with NST breast cancer. Large-scale expression profiling and subsequent validations have been performed in patient and control groups and compared with clinicopathological data. Small nuclear U6 snRNA, miR-548b-5p and miR-451a have been identified as candidate biomarkers. U6 snRNA was remarkably overexpressed in all the validations, miR-548b-5p levels were generally elevated and miR-451a expression was mostly downregulated in breast cancer groups. Combined U6 snRNA/miR-548b-5p signature demonstrated the best diagnostic performance based on the ROC curve analysis with AUC of 0.813, sensitivity 73.1% and specificity 82.6%. There was a trend towards increased expression of both miR-548b-5p and U6 snRNA in more advanced stages. Further, increased miR-548b-5p levels have been partially associated with higher grades, multifocality, Ki-67 positivity, and luminal B rather than luminal A samples. On the other hand, an association has been observed between high miR-451a expression and progesterone receptor positivity, lower grade, unifocal samples, Ki-67-negativity, luminal A rather than luminal B samples as well as improved progression-free survival and overall survival.

Conclusions

Our results indicated that U6 snRNA and miR-548b-5p may have pro-oncogenic functions, while miR-451a may act as tumor suppressor in breast cancer.

This is a preview of subscription content, access via your institution.

Fig. 1
Fig. 2
Fig. 3

References

  1. Sung H, Ferlay J, Siegel RL et al (2021) Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. https://doi.org/10.3322/caac.21660

    Article  PubMed  Google Scholar 

  2. Reis-Filho JS, Lakhani SR (2008) Breast cancer special types: why bother? J Pathol. https://doi.org/10.1002/path.2419

    Article  PubMed  Google Scholar 

  3. Shea EKH, Koh VCY, Tan PH (2020) Invasive breast cancer: current perspectives and emerging views. Pathol Int. https://doi.org/10.1111/pin.12910

    Article  PubMed  Google Scholar 

  4. Feng Y, Spezia M, Huang S, Yuan C, Zeng Z, Zhang L et al (2018) Breast cancer development and progression: risk factors, cancer stem cells, signaling pathways, genomics, and molecular pathogenesis. Genes Dis. https://doi.org/10.1016/j.gendis.2018.05.001

    Article  PubMed  PubMed Central  Google Scholar 

  5. Goldhirsch A, Winer EP, Coates AS, Gelber RD, Piccart-Gebhart M, Thürlimann B et al (2013) Personalizing the treatment of women with early breast cancer: highlights of the St Gallen international expert consensus on the primary therapy of early breast cancer 2013. Ann Oncol. https://doi.org/10.1093/annonc/mdt303

    Article  PubMed  PubMed Central  Google Scholar 

  6. Burstein HJ, Curigliano G, Loibl S, Dubsky P, Gnant M, Poortmans P et al (2019) Estimating the benefits of therapy for early-stage breast cancer: the St. Gallen International Consensus Guidelines for the primary therapy of early breast cancer 2019. Ann Oncol. https://doi.org/10.1093/annonc/mdz235

    Article  PubMed  PubMed Central  Google Scholar 

  7. Mei J, Hao L, Wang H, Xu R, Liu Y, Zhu YC, Liu CY (2020) Systematic characterization of non-coding RNAs in triple-negative breast cancer. Cell Prolif. https://doi.org/10.1111/cpr.12801

    Article  PubMed  PubMed Central  Google Scholar 

  8. Iorio MV, Croce CM (2012) MicroRNA dysregulation in cancer: diagnostics, monitoring and therapeutics. A comprehensive review. EMBO Mol Med. https://doi.org/10.1002/emmm.201100209

    Article  PubMed  PubMed Central  Google Scholar 

  9. Bahrami A, Aledavood A, Anvari K, Hassanian SM, Maftouh M, Yaghobzade A et al (2018) The prognostic and therapeutic application of microRNAs in breast cancer: tissue and circulating microRNAs. J Cell Physiol. https://doi.org/10.1002/jcp.25813

    Article  PubMed  Google Scholar 

  10. Dvorska D, Brany D, Nachajova M et al (2021) Breast cancer and the other non-coding RNAs. Int J Mol Sci 22(6):3280. https://doi.org/10.3390/ijms22063280

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  11. Erbes T, Hirschfeld M, Rucker G, Jaeger M, Boas J, Iborra S et al (2015) Feasibility of urinary microRNA detection in breast cancer patients and its potential as an innovative non-invasive biomarker. BMC Cancer. https://doi.org/10.1186/s12885-015-1190-4

    Article  PubMed  PubMed Central  Google Scholar 

  12. Kashyap D, Kaur H (2020) Cell-free miRNAs as non-invasive biomarkers in breast cancer: significance in early diagnosis and metastasis prediction. Life Sci. https://doi.org/10.1016/j.lfs.2020.117417

    Article  PubMed  Google Scholar 

  13. Hellemans J, Mortier G, De Paepe A, Speleman F, Vandesompele J (2007) qBase relative quantification framework and software for management and automated analysis of real-time quantitative PCR data. Genome Biol. https://doi.org/10.1186/gb-2007-8-2-r19

    Article  PubMed  PubMed Central  Google Scholar 

  14. Vandesompele J, De Preter K, Pattyn F, Poppe B, Van Roy N, De Paepe A, Speleman F (2002) Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes. Genome Biol. https://doi.org/10.1186/gb-2002-3-7-research0034

    Article  PubMed  PubMed Central  Google Scholar 

  15. DeLong ER, DeLong DM, Clarke-Pearson DL (1988) Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach. Biometrics. https://doi.org/10.2307/2531595

    Article  PubMed  Google Scholar 

  16. Zweig MH, Campbell G (1993) Receiver-operating characteristic (ROC) plots: a fundamental evaluation tool in clinical medicine. Clin Chem 39:561–577

    CAS  Article  PubMed  Google Scholar 

  17. Sheskin DJ (2011) Handbook of parametric and nonparametric statistical procedures, 5th edn. Chapman & Hall/CRC, Boca Raton

    Google Scholar 

  18. Hill DA, Barry M, Wiggins C, Nibbe A, Royce M et al (2017) Estrogen receptor quantitative measures and breast cancer survival. Breast Cancer Res Treat. https://doi.org/10.1007/s10549-017-4439-6

    Article  PubMed  PubMed Central  Google Scholar 

  19. Purdie CA, Quinlan P, Jordan LB, Ashfield A, Ogston S (2014) Progesterone receptor expression is an independent prognostic variable in early breast cancer: a population-based study. Br J Cancer 110(3):565–572. https://doi.org/10.1038/bjc.2013.756

    CAS  Article  PubMed  Google Scholar 

  20. Lombardi A, Lazzeroni R, Bersigotti L, Vitale V, Amanti C (2021) The proper Ki-67 cut-off in hormone responsive breast cancer: a monoinstitutional analysis with long-term follow-up. Breast Cancer 13:213–217. https://doi.org/10.2147/BCTT.S305440

    Article  PubMed  PubMed Central  Google Scholar 

  21. Nielsen TO, Leung SCY, Rimm DL, Dodson A, Badve S et al (2021) Assessment of Ki67 in breast cancer: updated recommendations from the international Ki67 in Breast Cancer Working Group. JNCI J Natl Cancer Inst. https://doi.org/10.1093/jnci/djaa201

    Article  PubMed  Google Scholar 

  22. Kanyilmaz G, Yavuz BB, Aktan M, Karaagac M, Uyar M, Findik S (2019) Prognostic importance of Ki-67 in Breast Cancer and its relationship with other prognostic factors. Eur J Breast Health. https://doi.org/10.5152/ejbh.2019.4778

    Article  PubMed  PubMed Central  Google Scholar 

  23. Hennigs A, Riedel F, Gondos A, Sinn P, Schirmacher P, Marmé F et al (2016) Prognosis of breast cancer molecular subtypes in routine clinical care: a large prospective cohort study. BMC Cancer. https://doi.org/10.1186/s12885-016-2766-3

    Article  PubMed  PubMed Central  Google Scholar 

  24. Soliman NA, Yussif SM (2016) Ki-67 as a prognostic marker according to breast cancer molecular subtype. Cancer Biol Med 13(4):496–504. https://doi.org/10.20892/j.issn.2095-3941.2016.0066

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  25. Zhu W, Liu M, Fan Y, Ma F, Xu N, Xu B (2018) Dynamics of circulating microRNAs as a novel indicator of clinical response to neoadjuvant chemotherapy in breast cancer. Cancer Med 7(9):4420–4433. https://doi.org/10.1002/cam4.1723

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  26. De Mattos-Arruda L, Bottai G, Nuciforo PG, Di Tommaso L, Giovannetti E et al (2015) MicroRNA-21 links epithelial-to-mesenchymal transition and inflammatory signals to confer resistance to neoadjuvant trastuzumab and chemotherapy in HER2-positive breast cancer patients. Oncotarget. https://doi.org/10.18632/oncotarget.5495

    Article  PubMed  PubMed Central  Google Scholar 

  27. Ilhan-Mutlu A, Tezcan G, Schoppmann SF, Preusser M, Spyridoula K et al (2015) microRNA-21 expression is elevated in esophageal adenocarcinoma after neoadjuvant chemotherapy. Cancer Investig 33(6):246–250. https://doi.org/10.3109/07357907.2015.1024319

    CAS  Article  Google Scholar 

  28. McGuire A, Casey MC, Waldron RM, Heneghan H, Kalinina O et al (2020) Prospective assessment of systemic microRNAs as markers of response to neoadjuvant chemotherapy in breast cancer. Cancers 12(7):1820. https://doi.org/10.3390/cancers12071820

  29. Di Cosimo S, Appierto V, Pizzamiglio S, Silvestri M, Baselga J et al (2020) Early modulation of circulating microRNAs levels in HER2-positive breast cancer patients treated with trastuzumab-based neoadjuvant therapy. Int J Mol Sci. https://doi.org/10.3390/ijms21041386

  30. Gezer U, Keskin S, Iğci A, Tükenmez M, Tiryakioğlu D et al (2014) Abundant circulating microRNAs in breast cancer patients fluctuate considerably during neoadjuvant chemotherapy. Oncol Lett. https://doi.org/10.3892/ol.2014.2188

  31. Lindholm EM, Aure MR, Haugen MH, Sahlberg KK, Kristensen VN et al (2019) miRNA expression changes during the course of neoadjuvant bevacizumab and chemotherapy treatment in breast cancer. Mol Oncol. https://doi.org/10.1002/1878-0261.12561

  32. Gulyaeva LF, Kushlinskiy NE (2016) Regulatory mechanisms of microRNA expression. J Transl Med. https://doi.org/10.1186/s12967-016-0893-x

    Article  PubMed  PubMed Central  Google Scholar 

  33. Qin XG, Zeng JH, Lin P, Mo WJ, Li Q, Feng ZB, Luo DZ, Yang H, Chen G, Zeng JJ (2019) Prognostic value of small nuclear RNAs (snRNAs) for digestive tract panadenocarcinomas identified by RNA sequencing data. Pathol Res Pract. https://doi.org/10.1016/j.prp.2018.11.004

    Article  PubMed  Google Scholar 

  34. Mroczek S, Dziembowski A (2013) U6 RNA biogenesis and disease association. Wiley Interdiscip Rev RNA. https://doi.org/10.1002/wrna.1181

    Article  PubMed  Google Scholar 

  35. Dvinge H, Guenthoer J, Porter PL, Bradley RK (2019) RNA components of the spliceosome regulate tissue- and cancer-specific alternative splicing. Genome Res. https://doi.org/10.1101/gr.246678.118

    Article  PubMed  PubMed Central  Google Scholar 

  36. Chiam K, Wang T, Watson DI, Mayne GC, Irvine TS, Bright T et al (2015) Circulating serum exosomal miRNAs as potential biomarkers for esophageal adenocarcinoma. J Gastrointest Surg. https://doi.org/10.1007/s11605-015-2829-9

    Article  PubMed  Google Scholar 

  37. Kitamura K, Nimura K (2021) Regulation of RNA splicing: aberrant splicing regulation and therapeutic targets in cancer. Cells 10(4):923. https://doi.org/10.3390/cells10040923

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  38. Appaiah HN, Goswami CP, Mina LA, Badve S, Sledge GW, Liu YL, Nakshatri H (2011) Persistent upregulation of U6:SNORD44 small RNA ratio in the serum of breast cancer patients. Breast Cancer Res. https://doi.org/10.1186/bcr2943

    Article  PubMed  PubMed Central  Google Scholar 

  39. Lou G, Ma N, Xu Y, Jiang L, Yang J, Wang CX et al (2015) Differential distribution of U6 (RNU6-1) expression in human carcinoma tissues demonstrates the requirement for caution in the internal control gene selection for microRNA quantification. Int J Mol Med. https://doi.org/10.3892/ijmm.2015.2338

    Article  PubMed  Google Scholar 

  40. Gee HE, Buffa FM, Camps C, Ramachandran A, Leek R, Taylor M et al (2011) The small-nucleolar RNAs commonly used for microRNA normalisation correlate with tumour pathology and prognosis. Br J Cancer. https://doi.org/10.1038/sj.bjc.6606076

    Article  PubMed  PubMed Central  Google Scholar 

  41. Xiang M, Zeng Y, Yang R, Xu H, Chen Z, Zhong J et al (2014) U6 is not a suitable endogenous control for the quantification of circulating microRNAs. Biochem Biophys Res Commun. https://doi.org/10.1016/j.bbrc.2014.10.064

    Article  PubMed  Google Scholar 

  42. Rehbein G, Schmidt B, Fleischhacker M (2015) Extracellular microRNAs in bronchoalveolar lavage samples from patients with lung diseases as predictors for lung cancer. Clin Chim Acta. https://doi.org/10.1016/j.cca.2015.07.027

    Article  PubMed  Google Scholar 

  43. Yan C, Hu J, Yang Y, Hu H, Zhou DX, Ma M, Xu N (2019) Plasma extracellular vesicle-packaged microRNAs as candidate diagnostic biomarkers for early-stage breast cancer. Mol Med Rep. https://doi.org/10.3892/mmr.2019.10669

    Article  PubMed  PubMed Central  Google Scholar 

  44. Hsieh TH, Hsu CY, Tsai CF, Long CY, Wu CH, Wu DC, Lee JN, Chang WC, Tsai EM (2015) HDAC inhibitors target HDAC5, upregulate MicroRNA-125a-5p, and induce apoptosis in breast cancer cells. Mol Ther. https://doi.org/10.1038/mt.2014.247

    Article  PubMed  PubMed Central  Google Scholar 

  45. Yang C, Wang C, Chen X, Chen SD, Zhang YN, Zhi F, Wang JJ, Li LM, Zhou XJ, Li NY (2013) Identification of seven serum microRNAs from a genome-wide serum microRNA expression profile as potential noninvasive biomarkers for malignant astrocytomas. Int J Cancer. https://doi.org/10.1002/ijc.27657

    Article  PubMed  PubMed Central  Google Scholar 

  46. Moustafa AA, Ziada M, Elshaikh A, Datta A, Kim H, Moroz K, Srivastav S, Thomas R, Silberstein JL, Moparty K (2017) Identification of microRNA signature and potential pathway targets in prostate cancer. Exp Biol Med. https://doi.org/10.1177/1535370216681554

    Article  Google Scholar 

  47. Bergamaschi A, Katzenellenbogen BS (2012) Tamoxifen downregulation of miR-451 increases 14–3-3 zeta and promotes breast cancer cell survival and endocrine resistance. Oncogene. https://doi.org/10.1038/onc.2011.223

    Article  PubMed  Google Scholar 

  48. Wang W, Zhang L, Wang Y, Ding Y, Chen T, Wang Y (2017) Involvement of miR-451 in resistance to paclitaxel by regulating YWHAZ in breast cancer. Cell Death Dis. https://doi.org/10.1038/cddis.2017.460

    Article  PubMed  PubMed Central  Google Scholar 

  49. Shao B, Wang X, Zhang L, Li D, Liu X, Song G, Cao H, Zhu J, Li H (2019) Plasma microRNAs predict chemoresistance in patients with metastatic breast cancer. Technol Cancer Res Treat. https://doi.org/10.1177/1533033819828709

    Article  PubMed  PubMed Central  Google Scholar 

  50. Xing AY, Wang B, Li YH, Chen X, Wang YW et al (2021) Identification of miRNA signature in breast cancer to predict neoadjuvant chemotherapy response. Pathol Oncol Res 27:1609753. https://doi.org/10.3389/pore.2021.1609753

    Article  PubMed  PubMed Central  Google Scholar 

  51. Gu X, Xue JQ, Han SJ, Qian SY, Zhang WH (2016) Circulating microRNA-451 as a predictor of resistance to neoadjuvant chemotherapy in breast cancer. Cancer Biomark 16(3):395–403. https://doi.org/10.3233/CBM-160578

    CAS  Article  PubMed  Google Scholar 

  52. Zhang H, Chen P, Yang J (2020) miR-451a suppresses the development of breast cancer via targeted inhibition of CCND2. Mol Cell Probes. https://doi.org/10.1016/j.mcp.2020.101651

    Article  PubMed  PubMed Central  Google Scholar 

  53. Fang R, Zhu Y, Hu L, Khadka VS, Ai J, Zou H, Ju D, Jiang B, Deng Y, Hu X (2019) Plasma microRNA pair panels as novel biomarkers for detection of early stage breast cancer. Front Physiol. https://doi.org/10.3389/fphys.2018.01879

    Article  PubMed  PubMed Central  Google Scholar 

  54. Luo J, Zhao Q, Zhang W, Zhang Z, Gao J, Zhang C, Li Y, Tian Y (2014) A novel panel of microRNAs provides a sensitive and specific tool for the diagnosis of breast cancer. Mol Med Rep. https://doi.org/10.3892/mmr.2014.2274

    Article  PubMed  PubMed Central  Google Scholar 

  55. Ouyang M, Li Y, Ye S, Ma J, Lu L, Lv W, Chang G, Li X, Li Q, Wang S, Wang W (2014) MicroRNA profiling implies new markers of chemoresistance of triple-negative breast cancer. PLoS ONE. https://doi.org/10.1371/journal.pone.0096228

    Article  PubMed  PubMed Central  Google Scholar 

  56. Liu B, Su F, Chen M, Li Y, Qi X, Xiao J, Li X, Liu X, Liang W, Zhang Y, Zhang J (2017) Serum miR-21 and miR-125b as markers predicting neoadjuvant chemotherapy response and prognosis in stage II/III breast cancer. Hum Pathol. https://doi.org/10.1016/j.humpath.2017.03.016

    Article  PubMed  PubMed Central  Google Scholar 

  57. Motamedi M, Chaleshtori MH, Ghasemi S, Mokarian F (2019) Plasma level of mir-21 and mir-451 in primary and recurrent breast cancer patients. Breast Cancer Targets Ther. https://doi.org/10.2147/BCTT.S224333

    Article  Google Scholar 

  58. Al-Khanbashi M, Caramuta S, Alajmi AM, Al-Haddabi I, Al-Riyami M, Lui WO, Al-Moundhri MS (2016) Tissue and serum miRNA profile in locally advanced breast cancer (LABC) in response to neo-adjuvant chemotherapy (NAC) treatment. PLoS ONE. https://doi.org/10.1371/journal.pone.0152032

    Article  PubMed  PubMed Central  Google Scholar 

  59. Ng EKO, Li R, Shin VY, Jin HC, Leung CPH, Ma ESK, Pang R, Chua D (2013) Circulating microRNAs as specific biomarkers for breast cancer detection. PLoS ONE. https://doi.org/10.1371/journal.pone.0053141

    Article  PubMed  PubMed Central  Google Scholar 

  60. Pan X, Wang R, Wang ZX (2013) The potential role of miR-451 in cancer diagnosis, prognosis, and therapy. Mol Cancer Ther. https://doi.org/10.1158/1535-7163.MCT-12-0802

    Article  PubMed  PubMed Central  Google Scholar 

  61. Khordadmehr M, Jigari-Asl F, Ezzati H, Shahbazi R, Sadreddini S, Safaei S, Baradaran B (2019) A comprehensive review on miR-451: a promising cancer biomarker with therapeutic potential. J Cell Physiol. https://doi.org/10.1002/jcp.28888

    Article  PubMed  Google Scholar 

  62. Ozawa PMM, Jucoski TS, Vieira E, Carvalho TM, Malheiros D, Ribeiro EMDS (2020) Liquid biopsy for breast cancer using extracellular vesicles and cell-free microRNAs as biomarkers. Transl Res. https://doi.org/10.1016/j.trsl.2020.04.002

    Article  PubMed  Google Scholar 

  63. Aggarwal V, Priyanka K, Tuli HS (2020) Emergence of circulating MicroRNAs in breast cancer as diagnostic and therapeutic efficacy biomarkers. Mol Diagn Ther. https://doi.org/10.1007/s40291-020-00447-w

    Article  PubMed  Google Scholar 

Download references

Acknowledgements

We appreciate the support of this research by Charles University in Prague (Progres Q28/LF1, Progres Q25/LF1), Ministry of Health of the Czech Republic (CZ-DRO FNBr 65269705, RVO-VFN 64165), Avast Foundation (SSD2018\100022) and ČEPS a.s. (1410002640, 1410002385, 1410002088). We would like to thank Libor Viktora, M.D. for clinicopathological data assessment (Center I data).

Funding

LZ received institutional funding from Charles University, Prague (Progres Q28/LF1) and research support from the Avast Foundation (SSD2018\100022) and ČEPS a.s. (1410002640, 1410002385, 1410002088). OS received institutional funding from Charles University, Prague (Progres Q25/LF1). AH received institutional funding from Charles University, Prague (Progres Q25/LF1) and research support from the Ministry of Health of the Czech Republic (Grant Project RVO-VFN 64165). VW and LM received research support from the Ministry of Health of the Czech Republic (CZ-DRO FNBr 65269705). MK received institutional funding from Charles University, Prague (Progres Q28/LF1).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Luděk Záveský.

Ethics declarations

Conflict of interest

There are no conflicts of interest.

Ethical approval

The study was approved by the multi-centric Ethics Committee of the General University Hospital in Prague, Ethics Committee of the Institute of the Care of Mother and Child in Prague and the Ethics Committee of the University Hospital Brno.

Informed consent

All patients provided an informed consent.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (DOCX 887 kb)

Supplementary file2 (DOCX 108 kb)

Supplementary file3 (DOCX 104 kb)

Supplementary file4 (DOCX 103 kb)

Supplementary file5 (DOCX 109 kb)

Supplementary file6 (DOCX 109 kb)

Supplementary file7 (DOCX 92 kb)

Supplementary file8 (DOCX 103 kb)

Supplementary file9 (DOCX 21 kb)

Supplementary file10 (DOCX 19 kb)

Supplementary file11 (DOCX 19 kb)

Supplementary file12 (DOCX 28 kb)

Supplementary file13 (DOCX 18 kb)

Supplementary file14 (DOCX 15 kb)

Supplementary file15 (DOCX 15 kb)

Supplementary file16 (DOCX 15 kb)

Supplementary file17 (DOCX 15 kb)

Supplementary file18 (DOCX 15 kb)

Supplementary file19 (DOCX 15 kb)

Supplementary file20 (DOCX 16 kb)

Supplementary file21 (DOCX 17 kb)

Supplementary file22 (DOCX 19 kb)

Supplementary file23 (DOCX 25 kb)

Supplementary file24 (DOCX 19 kb)

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Záveský, L., Jandáková, E., Weinberger, V. et al. Small non-coding RNA profiling in breast cancer: plasma U6 snRNA, miR-451a and miR-548b-5p as novel diagnostic and prognostic biomarkers. Mol Biol Rep 49, 1955–1971 (2022). https://doi.org/10.1007/s11033-021-07010-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11033-021-07010-8

Keywords

  • Biomarker
  • Breast cancer
  • microRNA
  • miR-451a
  • miR-548b-5p
  • U6 snRNA