Skip to main content

Advertisement

Log in

Relative and Absolute Expression Analysis of MicroRNAs Associated with Luminal A Breast Cancer– A Comparison

  • Original Article
  • Published:
Pathology & Oncology Research

Abstract

MicroRNAs, as small non-coding regulatory RNAs, play crucial roles in various aspects of breast cancer biology. They have prognostic and diagnostic value, which makes them very interesting molecules to investigate. Reverse transcriptase quantitative polymerase chain reaction (RT-qPCR) is the gold standard method to analyse miRNA expression in breast cancer patients. This study investigated two RT-qPCR methods (absolute and relative) to determine the expression of ten miRNAs in whole blood samples obtained from luminal A breast cancer patients compared to healthy controls. Whole blood samples were collected from 38 luminal A breast cancer patients and 20 healthy controls in Paxgene blood RNA tubes. Total RNA was extracted and analysed by relative and absolute RT-qPCR. For relative RT-qPCR, miR-16 was used as an endogenous control. For absolute RT-qPCR, standard curves were generated using synthetic miRNA oligonucleotides to determine the absolute copy number of each miRNA. Of the ten miRNAs that were analysed, the absolute RT-qPCR method identified six miRNAs (miR-16, miR-145, miR-155, miR-451a, miR-21 and miR-486) that were upregulated and one miRNA (miR-195) that was downregulated. ROC curve and AUC analysis of the data found that the combination of three miRNAs (miR-145, miR-195 and miR-486) had the best diagnostic value for luminal A breast cancer with an AUC of 0.875, with 76% sensitivity and 81% specificity. On the other hand, the relative RT-qPCR method identified two miRNAs (miR-155 and miR-486) that were upregulated and miR-195, which was downregulated. Using this approach, the combination of three miRNAs (miR-155, miR-195 and miR-486) was showed to have an AUC of 0.657 with 65% sensitivity and 69% specificity. We conclude that miR-16 is not a suitable normalizer for the relative expression profiling of miRNAs in luminal A breast cancer patients. Compared to relative quantification, absolute quantification assay is a better method to determine the expression level of circulating miRNAs in Luminal A breast cancer.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

References

  1. WHO. World Health Organization (2015) Global health observatory data repository. 2015. Number of deaths (World) by cause. http://wwww.hoint/mediacentre/factsheets/fs310/en/

  2. Ferlay J, Soerjomataram I, Dikshit R, Eser S, Mathers C, Rebelo M, et al. Cancer incidence and mortality worldwide: sources, methods and major patterns in GLOBOCAN 2012. Int J Cancer Journal international du cancer. 2015;136(5):E359–E386. https://doi.org/10.1002/ijc.29210

    Article  PubMed  Google Scholar 

  3. Ferlay J, Steliarova-Foucher E, Lortet-Tieulent J, Rosso S, Coebergh JW, Comber H et al (2013) Cancer incidence and mortality patterns in Europe: estimates for 40 countries in 2012. Eur J Cancer 49(6):1374–1403. https://doi.org/10.1016/j.ejca.2012.12.027

    Article  CAS  PubMed  Google Scholar 

  4. Perou CM, Sorlie T, Eisen MB, van de Rijn M, Jeffrey SS, Rees CA et al (2000) Molecular portraits of human breast tumours. Nature. 406(6797):747–752. https://doi.org/10.1038/35021093

    Article  CAS  PubMed  Google Scholar 

  5. Sorlie T, Wang Y, Xiao C, Johnsen H, Naume B, Samaha RR et al (2006) Distinct molecular mechanisms underlying clinically relevant subtypes of breast cancer: gene expression analyses across three different platforms. BMC Genomics 7:127. https://doi.org/10.1186/1471-2164-7-127

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Goldhirsch A, Wood WC, Coates AS, Gelber RD, Thurlimann B, Senn HJ (2011) 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 22(8):1736–1747. https://doi.org/10.1093/annonc/mdr304

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Rouzier R, Perou CM, Symmans WF, Ibrahim N, Cristofanilli M, Anderson K et al (2005) Breast cancer molecular subtypes respond differently to preoperative chemotherapy. Clin Cancer Res 11(16):5678–5685. https://doi.org/10.1158/1078-0432.ccr-04-2421

    Article  CAS  PubMed  Google Scholar 

  8. Kumar MS, Lu J, Mercer KL, Golub TR, Jacks T (2007) Impaired microRNA processing enhances cellular transformation and tumorigenesis. Nat Genet 39(5):673–677. https://doi.org/10.1038/ng2003

    Article  CAS  PubMed  Google Scholar 

  9. Lu J, Getz G, Miska EA, Alvarez-Saavedra E, Lamb J, Peck D, Sweet-Cordero A, Ebert BL, Mak RH, Ferrando AA, Downing JR, Jacks T, Horvitz HR, Golub TR (2005) MicroRNA expression profiles classify human cancers. Nature. 435(7043):834–838. https://doi.org/10.1038/nature03702

    Article  CAS  PubMed  Google Scholar 

  10. Zen K, Zhang C-Y (2012) Circulating MicroRNAs: a novel class of biomarkers to diagnose and monitor human cancers. Med Res Rev 32(2):326–348. https://doi.org/10.1002/med.20215

    Article  CAS  PubMed  Google Scholar 

  11. Iorio MV, Ferracin M, Liu CG, Veronese A, Spizzo R, Sabbioni S, Magri E, Pedriali M, Fabbri M, Campiglio M, Ménard S, Palazzo JP, Rosenberg A, Musiani P, Volinia S, Nenci I, Calin GA, Querzoli P, Negrini M, Croce CM (2005) MicroRNA gene expression deregulation in human breast cancer. Cancer Res 65(16):7065–7070. https://doi.org/10.1158/0008-5472.CAN-05-1783

    Article  CAS  PubMed  Google Scholar 

  12. Heneghan HM, Miller N, Lowery AJ, Sweeney KJ, Kerin MJ (2009, 2009) MicroRNAs as Novel Biomarkers for Breast Cancer. J Oncol:950201. https://doi.org/10.1155/2010/950201

    Article  Google Scholar 

  13. Tahiri A, Leivonen SK, Luders T, Steinfeld I, Ragle Aure M, Geisler J et al (2014) Deregulation of cancer-related miRNAs is a common event in both benign and malignant human breast tumors. Carcinogenesis. 35(1):76–85. https://doi.org/10.1093/carcin/bgt333

    Article  CAS  PubMed  Google Scholar 

  14. McDermott AM, Miller N, Wall D, Martyn LM, Ball G, Sweeney KJ et al (2014) Identification and validation of oncologic miRNA biomarkers for luminal A-like breast cancer. PLoS One 9(1):e87032. https://doi.org/10.1371/journal.pone.0087032

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Chan M, Liaw CS, Ji SM, Tan HH, Wong CY, Thike AA et al (2013) Identification of circulating microRNA signatures for breast cancer detection. Clin Cancer Res 19(16):4477–4487. https://doi.org/10.1158/1078-0432.CCR-12-3401

    Article  CAS  PubMed  Google Scholar 

  16. Pfaffl MW, Horgan GW, Dempfle L (2002) Relative expression software tool (REST) for group-wise comparison and statistical analysis of relative expression results in real-time PCR. Nucleic Acids Res 30(9):e36

    Article  PubMed  PubMed Central  Google Scholar 

  17. Pfaffl MW (2001) A new mathematical model for relative quantification in real-time RT-PCR. Nucleic Acids Res 29(9):e45

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Agarwal V, Bell GW, Nam JW, Bartel DP (2015) Predicting effective microRNA target sites in mammalian mRNAs. Elife 4. https://doi.org/10.7554/eLife.05005

  19. Klein D (2002) Quantification using real-time PCR technology: applications and limitations. Trends Mol Med 8(6):257–260

    Article  CAS  PubMed  Google Scholar 

  20. Livak KJ, Schmittgen TD (2001) Analysis of relative gene expression data using real-time quantitative PCR and the 2(−Delta Delta C(T)) Method. Methods 25(4):402–408. https://doi.org/10.1006/meth.2001.1262

    Article  CAS  PubMed  Google Scholar 

  21. Mannhalter C, Koizar D, Mitterbauer G (2000) Evaluation of RNA isolation methods and reference genes for RT-PCR analyses of rare target RNA. Clin Chem Lab Med 38(2):171–177. https://doi.org/10.1515/cclm.2000.026

    Article  CAS  PubMed  Google Scholar 

  22. Karge WH 3rd, Schaefer EJ, Ordovas JM (1998) Quantification of mRNA by polymerase chain reaction (PCR) using an internal standard and a nonradioactive detection method. Methods Mol Biol 110:43–61. https://doi.org/10.1385/1-59259-582-0:43

    Article  CAS  PubMed  Google Scholar 

  23. Bustin SA (2000) Absolute quantification of mRNA using real-time reverse transcription polymerase chain reaction assays. J Mol Endocrinol 25(2):169–193

    Article  CAS  PubMed  Google Scholar 

  24. Pfaffl MW, Hageleit M (2001) Validities of mRNA quantification using recombinant RNA and recombinant DNA external calibration curves in real-time RT-PCR. Biotechnol Lett 23(4):275–282. https://doi.org/10.1023/a:1005658330108

    Article  CAS  Google Scholar 

  25. Hindson CM, Chevillet JR, Briggs HA, Gallichotte EN, Ruf IK, Hindson BJ, Vessella RL, Tewari M (2013) Absolute quantification by droplet digital PCR versus analog real-time PCR. Nat Methods 10(10):1003–1005. https://doi.org/10.1038/nmeth.2633

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Pohl G, Shih IM (2004) Principle and applications of digital PCR. Expert Rev Mol Diagn 4(1):41–47

    Article  CAS  PubMed  Google Scholar 

  27. Mar-Aguilar F, Mendoza-Ramirez JA, Malagon-Santiago I, Espino-Silva PK, Santuario-Facio SK, Ruiz-Flores P et al (2013) Serum circulating microRNA profiling for identification of potential breast cancer biomarkers. Dis Markers 34(3):163–169

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Kodahl AR, Lyng MB, Binder H, Cold S, Gravgaard K, Knoop AS, Ditzel HJ (2014) 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 8(5):874–883. https://doi.org/10.1016/j.molonc.2014.03.002

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Ng EK, Li R, Shin VY, Jin HC, Leung CP, Ma ES et al (2013) Circulating microRNAs as specific biomarkers for breast cancer detection. PLoS One 8(1):e53141. https://doi.org/10.1371/journal.pone.0053141

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Rask L, Balslev E, Sokilde R, Hogdall E, Flyger H, Eriksen J et al (2014) Differential expression of miR-139, miR-486 and miR-21 in breast cancer patients sub-classified according to lymph node status. Cell Oncol (Dordr) 37(3):215–227. https://doi.org/10.1007/s13402-014-0176-6

    Article  CAS  Google Scholar 

  31. Sochor M, Basova P, Pesta M, Dusilkova N, Bartos J, Burda P, Pospisil V, Stopka T (2014) Oncogenic microRNAs: miR-155, miR-19a, miR-181b, and miR-24 enable monitoring of early breast cancer in serum. BMC Cancer 14:448. https://doi.org/10.1186/1471-2407-14-448

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Madhavan D, Zucknick M, Wallwiener M, Cuk K, Modugno C, Scharpff M et al (2012) Circulating miRNAs as surrogate markers for circulating tumor cells and prognostic markers in metastatic breast cancer. Clin Cancer Res 18(21):5972–5982. https://doi.org/10.1158/1078-0432.ccr-12-1407

    Article  CAS  PubMed  Google Scholar 

  33. Godfrey AC, Xu Z, Weinberg CR, Getts RC, Wade PA, LA DR et al (2013) Serum microRNA expression as an early marker for breast cancer risk in prospectively collected samples from the Sister Study cohort. Breast Cancer Res 15(3):R42. https://doi.org/10.1186/bcr3428

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Heneghan HM, Miller N, Lowery AJ, Sweeney KJ, Newell J, Kerin MJ (2010) Circulating microRNAs as novel minimally invasive biomarkers for breast cancer. Ann Surg 251(3):499–505. https://doi.org/10.1097/SLA.0b013e3181cc939f

    Article  PubMed  Google Scholar 

  35. Park IH, Kang JH, Lee KS, Nam S, Ro J, Kim JH (2014) Identification and clinical implications of circulating microRNAs for estrogen receptor-positive breast cancer. Tumour Biol 35:12173–12180. https://doi.org/10.1007/s13277-014-2525-5

    Article  CAS  PubMed  Google Scholar 

  36. Schrauder MG, Strick R, Schulz-Wendtland R, Strissel PL, Kahmann L, Loehberg CR, Lux MP, Jud SM, Hartmann A, Hein A, Bayer CM, Bani MR, Richter S, Adamietz BR, Wenkel E, Rauh C, Beckmann MW, Fasching PA (2012) Circulating micro-RNAs as potential blood-based markers for early stage breast cancer detection. PLoS One 7(1):e29770. https://doi.org/10.1371/journal.pone.0029770

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Heneghan HM, Miller N, Kelly R, Newell J, Kerin MJ (2010) Systemic miRNA-195 differentiates breast cancer from other malignancies and is a potential biomarker for detecting noninvasive and early stage disease. Oncologist 15(7):673–682. https://doi.org/10.1634/theoncologist.2010-0103

    Article  PubMed  PubMed Central  Google Scholar 

  38. 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 9(5):e96228. https://doi.org/10.1371/journal.pone.0096228

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Ng EK, Chong WW, Jin H, Lam EK, Shin VY, Yu J et al (2009) Differential expression of microRNAs in plasma of patients with colorectal cancer: a potential marker for colorectal cancer screening. Gut. 58(10):1375–1381. https://doi.org/10.1136/gut.2008.167817

    Article  CAS  PubMed  Google Scholar 

  40. Mitchell PS, Parkin RK, Kroh EM, Fritz BR, Wyman SK, Pogosova-Agadjanyan EL, Peterson A, Noteboom J, O'Briant KC, Allen A, Lin DW, Urban N, Drescher CW, Knudsen BS, Stirewalt DL, Gentleman R, Vessella RL, Nelson PS, Martin DB, Tewari M (2008) Circulating microRNAs as stable blood-based markers for cancer detection. Proc Natl Acad Sci 105(30):10513–10518. https://doi.org/10.1073/pnas.0804549105

    Article  PubMed  PubMed Central  Google Scholar 

  41. Liu J, Mao Q, Liu Y, Hao X, Zhang S, Zhang J (2013) Analysis of miR-205 and miR-155 expression in the blood of breast cancer patients. Chin J Cancer Res 25(1):46–54. https://doi.org/10.3978/j.issn.1000-9604.2012.11.04

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Calvano Filho CM, Calvano-Mendes DC, Carvalho KC, Maciel GA, Ricci MD, Torres AP et al (2014) Triple-negative and luminal A breast tumors: differential expression of miR-18a-5p, miR-17-5p, and miR-20a-5p. Tumour Biol 35(8):7733–7741. https://doi.org/10.1007/s13277-014-2025-7

    Article  CAS  PubMed  Google Scholar 

  43. Anfossi S, Giordano A, Gao H, Cohen EN, Tin S, Wu Q, Garza RJ, Debeb BG, Alvarez RH, Valero V, Hortobagyi GN, Calin GA, Ueno NT, Woodward WA, Reuben JM (2014) 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 9(1):e83113. https://doi.org/10.1371/journal.pone.0083113

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Mangolini A, Ferracin M, Zanzi MV, Saccenti E, Ebnaof SO, Poma VV, Sanz JM, Passaro A, Pedriali M, Frassoldati A, Querzoli P, Sabbioni S, Carcoforo P, Hollingsworth A, Negrini M (2015) Diagnostic and prognostic microRNAs in the serum of breast cancer patients measured by droplet digital PCR. Biomarker Res 3:12. https://doi.org/10.1186/s40364-015-0037-0

    Article  Google Scholar 

  45. Zhang G, Liu Z, Cui G, Wang X, Yang Z (2014) MicroRNA-486-5p targeting PIM-1 suppresses cell proliferation in breast cancer cells. Tumour Biol 35(11):11137–11145. https://doi.org/10.1007/s13277-014-2412-0

    Article  CAS  PubMed  Google Scholar 

  46. Lerebours F, Cizeron-Clairac G, Susini A, Vacher S, Mouret-Fourme E, Belichard C, et al. miRNA expression profiling of inflammatory breast cancer identifies a 5-miRNA signature predictive of breast tumor aggressiveness. Int J Cancer Journal international du cancer. 2013;133(7):1614–1623. https://doi.org/10.1002/ijc.28171

    Article  CAS  PubMed  Google Scholar 

  47. O'Connell RM, Rao DS, Chaudhuri AA, Boldin MP, Taganov KD, Nicoll J, Paquette RL, Baltimore D (2008) Sustained expression of microRNA-155 in hematopoietic stem cells causes a myeloproliferative disorder. J Exp Med 205(3):585–594. https://doi.org/10.1084/jem.20072108

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Kluiver J, Poppema S, de Jong D, Blokzijl T, Harms G, Jacobs S, Kroesen BJ, van den Berg A (2005) BIC and miR-155 are highly expressed in Hodgkin, primary mediastinal and diffuse large B cell lymphomas. J Pathol 207(2):243–249. https://doi.org/10.1002/path.1825

    Article  CAS  PubMed  Google Scholar 

  49. Volinia S, Calin GA, Liu C-G, Ambs S, Cimmino A, Petrocca F et al (2006) A microRNA expression signature of human solid tumors defines cancer gene targets. Proc Natl Acad Sci U S A 103(7):2257–2261

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Wang X, Tang S, Le SY, Lu R, Rader JS, Meyers C et al (2008) Aberrant expression of oncogenic and tumor-suppressive microRNAs in cervical cancer is required for cancer cell growth. PLoS One 3(7):e2557. https://doi.org/10.1371/journal.pone.0002557

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Yanaihara N, Caplen N, Bowman E, Seike M, Kumamoto K, Yi M, Stephens RM, Okamoto A, Yokota J, Tanaka T, Calin GA, Liu CG, Croce CM, Harris CC (2006) Unique microRNA molecular profiles in lung cancer diagnosis and prognosis. Cancer Cell 9(3):189–198. https://doi.org/10.1016/j.ccr.2006.01.025

    Article  CAS  PubMed  Google Scholar 

  52. Kong W, He L, Coppola M, Guo J, Esposito NN, Coppola D et al (2016) MicroRNA-155 regulates cell survival, growth, and chemosensitivity by targeting FOXO3a in breast cancer. J Biol Chem 291(43):22855. https://doi.org/10.1074/jbc.A110.101055

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Zhao FL, Dou YC, Wang XF, Han DC, Lv ZG, Ge SL et al (2014) Serum microRNA-195 is down-regulated in breast cancer: a potential marker for the diagnosis of breast cancer. Mol Biol Rep 41(9):5913–5922. https://doi.org/10.1007/s11033-014-3466-1

    Article  CAS  PubMed  Google Scholar 

  54. Li D, Zhao Y, Liu C, Chen X, Qi Y, Jiang Y et al (2011) Analysis of MiR-195 and MiR-497 expression, regulation and role in breast cancer. Clin Cancer Res 17(7):1722–1730. https://doi.org/10.1158/1078-0432.ccr-10-1800

    Article  CAS  PubMed  Google Scholar 

  55. Luo Q, Wei C, Li X, Li J, Chen L, Huang Y et al (2014) MicroRNA-195-5p is a potential diagnostic and therapeutic target for breast cancer. Oncol Rep 31(3):1096–1102. https://doi.org/10.3892/or.2014.2971

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Hu Z, Dong J, Wang LE, Ma H, Liu J, Zhao Y, Tang J, Chen X, Dai J, Wei Q, Zhang C, Shen H (2012) Serum microRNA profiling and breast cancer risk: the use of miR-484/191 as endogenous controls. Carcinogenesis. 33(4):828–834. https://doi.org/10.1093/carcin/bgs030

    Article  CAS  PubMed  Google Scholar 

  57. Iorio MV, Visone R, Di Leva G, Donati V, Petrocca F, Casalini P et al (2007) MicroRNA signatures in human ovarian cancer. Cancer Res 67(18):8699–8707. https://doi.org/10.1158/0008-5472.can-07-1936

    Article  CAS  PubMed  Google Scholar 

  58. Asangani IA, Rasheed SA, Nikolova DA, Leupold JH, Colburn NH, Post S et al (2008) MicroRNA-21 (miR-21) post-transcriptionally downregulates tumor suppressor Pdcd4 and stimulates invasion, intravasation and metastasis in colorectal cancer. Oncogene 27(15):2128–2136. https://doi.org/10.1038/sj.onc.1210856

    Article  CAS  PubMed  Google Scholar 

  59. Chan JA, Krichevsky AM, Kosik KS (2005) MicroRNA-21 is an antiapoptotic factor in human glioblastoma cells. Cancer Res 65(14):6029–6033. https://doi.org/10.1158/0008-5472.can-05-0137

    Article  CAS  PubMed  Google Scholar 

  60. Stuckrath I, Rack B, Janni W, Jager B, Pantel K, Schwarzenbach H (2015) 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. 6(15):13387–13401. https://doi.org/10.18632/oncotarget.3874

    Article  PubMed  PubMed Central  Google Scholar 

  61. Shin VY, Siu JM, Cheuk I, Ng EK, Kwong A (2015) Circulating cell-free miRNAs as biomarker for triple-negative breast cancer. Br J Cancer 112(11):1751–1759. https://doi.org/10.1038/bjc.2015.143

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  62. Guo LJ, Zhang QY (2012) Decreased serum miR-181a is a potential new tool for breast cancer screening. Int J Mol Med 30(3):680–686. https://doi.org/10.3892/ijmm.2012.1021

    Article  CAS  PubMed  Google Scholar 

  63. McDermott AM, Kerin MJ, Miller N (2013) Identification and validation of miRNAs as endogenous controls for RQ-PCR in blood specimens for breast cancer studies. PLoS One 8(12):e83718

    Article  PubMed  PubMed Central  Google Scholar 

  64. Lu J, Clark AG (2012) Impact of microRNA regulation on variation in human gene expression. Genome Res 22(7):1243–1254. https://doi.org/10.1101/gr.132514.111

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Contributions

Conceived and designed the experiments: TJS VA. Performed the experiments: VA. Analysed the data: VA EH OK JN. Contributed reagents/materials/analysis tools: TJS RMD MJK. Wrote the paper: VA EC TJS.

Corresponding authors

Correspondence to Vahid Arabkari or Terry J. Smith.

Additional information

Publisher’s Note

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

Electronic supplementary material

ESM 1

(DOCX 1368 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Arabkari, V., Clancy, E., Dwyer, R.M. et al. Relative and Absolute Expression Analysis of MicroRNAs Associated with Luminal A Breast Cancer– A Comparison. Pathol. Oncol. Res. 26, 833–844 (2020). https://doi.org/10.1007/s12253-019-00627-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12253-019-00627-y

Keywords

Navigation