Open Access

MicroRNA analysis of breast ductal fluid in breast cancer patients

  • Authors:
    • Luisa Matos Do Canto
    • Catalin Marian
    • Shawna Willey
    • Mary Sidawy
    • Patricia A. Da Cunha
    • Janice D. Rone
    • Xin Li
    • Yuriy Gusev
    • Bassem R. Haddad
  • View Affiliations

  • Published online on: March 10, 2016     https://doi.org/10.3892/ijo.2016.3435
  • Pages: 2071-2078
  • Copyright: © Do Canto et al. This is an open access article distributed under the terms of Creative Commons Attribution License.

Metrics: Total Views: 0 (Spandidos Publications: | PMC Statistics: )
Total PDF Downloads: 0 (Spandidos Publications: | PMC Statistics: )


Abstract

Recent studies suggest that microRNAs show promise as excellent biomarkers for breast cancer; however there is still a high degree of variability between studies making the findings difficult to interpret. In addition to blood, ductal lavage (DL) and nipple aspirate fluids represent an excellent opportunity for biomarker detection because they can be obtained in a less invasive manner than biopsies and circumvent the limitations of evaluating blood biomarkers with regards to tissue of origin specificity. In this study, we have investigated for the first time, through a real-time PCR array, the expression of 742 miRNAs in the ductal lavage fluid collected from 22 women with unilateral breast tumors. We identified 17 differentially expressed miRNAs between tumor and paired normal samples from patients with ductal breast carcinoma. Most of these miRNAs have various roles in breast cancer tumorigenesis, invasion and metastasis, therapeutic response, or are associated with several clinical and pathological characteristics of breast tumors. Moreover, some miRNAs were also detected in other biological fluids of breast cancer patients such as serum (miR-23b, -133b, -181a, 338-3p, -625), plasma (miR-200a), and breast milk (miR-181a). A systems biology analysis of these differentially expressed miRNAs points out possible pathways and cellular processes previously described as having an important role in breast cancer such as Wnt, ErbB, MAPK, TGF-β, mTOR, PI3K-Akt, p53 signaling pathways. We also observed a difference in the miRNA expression with respect to the histological type of the tumors. In conclusion, our findings suggest that miRNA analysis of breast ductal fluid is feasible and potentially very useful for the detection of breast cancer.

Introduction

Breast cancer is the most commonly diagnosed cancer in women and the second most common cause of cancer mortality. Despite major investments to improve early detection and understanding of its biology, the incidence and mortality of the disease remain surprisingly high (1). Current screening methods rely primarily on imaging techniques, including mammography and ultrasonography. Although these methods have become more sensitive and specific for detecting smaller subtle lesions, early detection remains a challenge in many patients. For this reason, identification of biomarkers that can complement the current imaging methods for early detection of breast cancer continues to be desperately needed.

miRNAs are small (18–24 nucleotides in length) non-coding RNA molecules that regulate the activity of specific mRNA targets, and are involved in a variety of physiological and pathological processes, including carcinogenesis (2). Despite the fact that the research regarding miRNA discovery and characterization in human cancers is still evolving, and despite the discrepancies among different studies, there is a general consensus that miRNAs are excellent candidate biomarkers for human cancers, including breast cancer (3). In addition, it has been shown that miRNAs are stable in archived formalin-fixed and paraffin-embedded (FFPE) tissue samples, and reliably detectable in serum, plasma and other biological fluids (4). These characteristics of miRNAs constitute the basis for using them as new biomarkers with clinical relevance, and such efforts are close to fruition in certain cancers such as pancreatic, lung, and kidney cancers, and cancers with unknown primary origin (4).

The first breast cancer specific miRNA expression signature was reported in 2005, and consisted of 29 differentially expressed miRNAs that were able to differentiate normal from cancer tissue with 100% accuracy (5). miRNA profiling in breast cancer revealed subsets of miRNAs capable of accurately reproducing the molecular classification of breast carcinomas; other miRNA subsets were associated with clinical and pathological characteristics of breast cancers (6). A recent detailed review of miRNA biomarkers in breast cancer has revealed that, despite the real progress made through numerous studies on the subject, there is still a lack of consensus among studies (4). This is mainly due to the high degree of variability between studies regarding patient characteristics, experimental design, sample preparation, detection methodology and data analysis, thus making cross-studies comparison of the findings difficult to conduct and interpret.

Significant recent efforts focusing on the use of circulating miRNAs as breast cancer biomarkers have yielded some candidate markers. However, none were found to be highly specific or could be validated in independent studies, mainly due to the reasons mentioned above. Another conceptual challenge regarding circulating miRNAs as biomarkers is the uncertainty of the diseased tissue of origin for these miRNAs, suggesting that other biofluids should be investigated such as nipple aspirate fluid and ductal lavage fluid in the case of breast cancer (7). Although these biofluids are obtained through more invasive techniques compared to phlebotomy, they are still less invasive than biopsies and could circumvent the limitations of blood based markers regarding specificity and tissue of origin. Historically, these fluids have been used for cytological evaluation, including immunohistochemistry of breast cancer related markers such as Her2. More recently, reports of several biomarker profiling studies in nipple aspirate or ductal lavage fluids have emerged using proteomic, metabolomic, hormones, and nucleic acid analyses (814).

There is a lack of data in the literature regarding miRNA markers in ductal lavage or nipple aspirate fluids. However, there is evidence that these fluids contain sufficient RNA for gene expression screening by microarray studies (13,15), as well as individual gene expression measurement (16). A recent study reported on the analysis of three individual miRNA markers in ductal lavage fluid, as well as gene expression of a candidate gene and array comparative genomic hybridization screening (17).

We investigated for the first time through a real time PCR screening array the expression of 742 miRNAs in the ductal lavage fluid collected from women with unilateral breast cancer. We demonstrated the feasibility of this analysis and its potential for detection of breast cancer.

Materials and methods

Patient population

We enrolled 22 patients with unilateral, biopsy-confirmed, breast tumors [invasive breast cancer (IBC) and/or ductal carcinoma in situ (DCIS)], who were scheduled for surgery (mastectomy/lumpectomy) at MedStar Georgetown University Hospital. Patients were identified by the surgeon and offered the opportunity to participate in the study. If they agreed, they were asked to sign an IRB-approved informed consent. Ductal lavage fluid samples were obtained from 22 eligible patients with DCIS or IBC. The DL samples were collected in the operating room from patients with confirmed diagnosis, prior to their surgery. For each patient, two DL samples were obtained: one from the affected breast and the other from the contralateral normal breast (control). Each patient served as her own control.

Ductal lavage

Prior to starting the operative procedure, for each subject, the surgeon obtained breast ductal fluid from the affected breast and the non-affected contralateral breast, using ductal lavage. The ductal lavage procedure was performed as previously described (18), except that the collected fluid was placed in a sterile tube with no preservative solution, and was transferred immediately to the lab, and divided into different aliquots which were frozen at −80°C for future studies.

One fresh aliquot was used for cytopathology evaluation and to investigate the presence of benign, atypical, or malignant cells, by a certified breast pathologist, using the established criteria for DL cytologic analysis (7).

RNA extraction

Total RNA was extracted from 250 μl of ductal lavage samples using the Qiagen miRNeasy kit and the Ambion RecoverALL Total Nucleic Acid Isolation kit for FFPE, respectively, and the quantity of RNA was assessed using a Thermo Scientific NanoDrop™ Spectrophotometer.

miRNA expression profiling

miRNA profiling was done according to the manufacturer's recommendations using the TaqMan(R) Human microRNA Array Set v3.0 (Thermo Fisher Scientific), a quantitative real time PCR based array containing 742 human miRNAs, 3 endogenous controls to aid in data normalization and one assay not related to humans as a negative control.

Bioinformatics and statistical analysis

A specialized software package DataAssist 3.0 (Thermo Fisher Scientific) was used to process the qRT-PCR data including removal of replicate outliers, normalization using global median method and delta-delta-Ct method for calculating miRNA relative expression level. Further analysis of processed data was performed using MeV 4.8 software package from Dana-Farber Cancer Institute (Harvard University) including filtering, unsupervised hierarchical clustering and statistical group comparison (t-test) as well as principal component analysis (PCA) (19). Groups compared were: DL from affected breasts (lavage tumor, LT) vs. DL from normal contralateral breast (control) lavage control, LC). Statistical group comparison resulted in a list of differentially expressed miRNAs. Differentially expressed miRNAs were analyzed by mapping predicted target genes to the KEGG pathways (20).

Results

Clinical and demographic characteristics of the subjects included in this study are presented in Table I. Most subjects were Caucasians, postmenopausal, with no family history of breast cancer. Most DL samples had insufficient cells for cytopathology evaluation.

Table I

Characteristics of the subjects.

Table I

Characteristics of the subjects.

CharacteristicsN%a
Age (mean ± SD)53.81 (±12.17)
Menopause
 Pre731.81
 Post1568.19
Race/Ethnicity
 A14.54
 AA522.73
 CA1568.19
 H14.54
Family history of breast cancer
 Yes940.90
 No1359.09
Tumor site
 Right940.90
 Left1359.09
Neoadjuvant chemotherapy
 Yes29.09
 No2090.91
Histological type
 DCIS627.28
 IDC and IDC/DCIS1463.64
 ILC14.54
 Mixed14.54
Stage
 0522.73
 I940.90
 II836.37
Grade
 Low14.54
 Intermediate1045.45
 High1150.00
ER
 Pos1986.36
 Neg313.64
PR
 Pos1672.72
 Neg627.28
HER2
 Pos29.09
 Neg1568.18
Affected breast cytology
 Atypical cells29.09
 Benign cells29.09
 Insufficient cells1881.82

a May not add to 100% due to missing values, A-Asian, AA-African American, CA-Caucasian, H-hispanic, DCIS-ductal carcinoma in situ, IDC-invasive ductal carcinoma, ILC-invasive lobular carcinoma.

Evaluation of miRNA expression was completed on all 44 specimens from the 22 study subjects. All DL samples yielded successful results, showing the ability to analyze miRNA expression in DL fluid. We detected 35 miRNAs expressed in at least 20% of the samples. In order to identify differentially expressed miRNAs which will discriminate between DL from a breast with tumor vs. a normal breast we performed statistical analysis using t-test. However, expression of microRNA was highly heterogeneous among groups of tumors with different histologies. Preliminary analysis showed that microRNA expression profiles detected in DL fluid were different for tumors of different histological types. When groups were compared based on histology, a statistical comparison identified 20 differentially expressed miRNAs (Fig. 1). Cluster analysis showed that using expression information of only these 20 differentially expressed miRNAs, the histological type of tumors could be accurately identified as samples of the same histological type clustered together (Fig. 1). Principal component analysis (PCA) results also showed that samples of the same histological type were located in clusters that were well separated on a scatter plots (Fig. 2).

To minimize the heterogeneity of observations, the samples were analyzed separately for each histological type. The DCIS, lobular and mixed types (n=8) were excluded from further analysis due to low sample size. Using this approach we were able to discriminate tumor samples from normal paired controls for all invasive ductal carcinoma samples (n=14). This included samples with only IDC, as well as samples with concomitant IDC and DCIS (Fig. 3). This analysis was conducted in two steps. First, we removed all other samples except for the IDC histological types, which were then subjected to a t-test with p<0.05. Seventeen miRNAs were differentially expressed between tumor and paired normal samples from the same patients (Table II). Based on the expression profiles of these 17 miRNAs, we found that most of the DL fluid samples from the affected breasts clustered together and most of the normal control DL fluid samples clustered together except for one tumor and 3 normal samples (Fig. 3).

Table II

Differentially expressed miRNAs in DL fluid of subjects with IDC.

Table II

Differentially expressed miRNAs in DL fluid of subjects with IDC.

miRNALog ratiop-value
miR-126−2.4320.024
miR-133b−2.034<0.001
miR-181a2.0650.029
miR-23b2.785<0.001
miR-338-3p−1.408<0.001
miR-362-3p−4.310<0.001
miR-363−8.805<0.001
miR-450b-5p−5.056<0.001
miR-500−3.917<0.001
miR-548b-5p−5.509<0.001
miR-625−2.816<0.001
miR-1180−3.610<0.001
miR-200a-5p−3.8090.039
miR-596−6.0840.038
miR-638−3.0430.046
miR-645−2.5620.020
miR-663b−3.8400.045

In order to test if further stratification could improve the clustering of samples, we compared tumor and normal control DL fluid for subjects with IDC and DCIS in their tumors (n=9). Fourteen miRNAs were differentially expressed between tumor and paired normal samples from these patients at p<0.05 (Table III). Based on the expression profiles of these 14 miRNAs we found that all samples from tumor DL were clustered together and all of the normal control DLs were clustered together (Fig. 4).

Table III

Differentially expressed miRNAs in DL fluid of subjects with IDC and DCIS (in the same tumor).

Table III

Differentially expressed miRNAs in DL fluid of subjects with IDC and DCIS (in the same tumor).

miRNALog ratiop-value
let-7a4.990<0.001
miR-181a2.6330.028
miR-301a1.282<0.001
miR-4841.9160.028
miR-520f−4.176<0.001
miR-548b-5p−4.630<0.001
miR-576-3p−5.458<0.001
miR-625−2.615<0.001
miR-6420.697<0.001
miR-99a3.2240.047
miR-1298−3.284<0.001
miR-144-5p−4.765<0.001
miR-4322.5600.027
miR-645−3.6320.003

Discussion

Breast ductal lavage fluid is a valuable biological sample obtained using minimally invasive techniques that is mostly used for cytopathological assessment and is still less commonly evaluated for molecular biomarkers of breast cancer. We have shown herein that miRNA screening is feasible in breast ductal lavage fluid obtained from both breasts of 22 women with unilateral breast cancer. miRNA expression was detected in all 44 DL samples. Initial statistical analysis revealed that in order to determine miRNAs that are differentially expressed in the fluid from breasts with tumors vs. normal control breasts, the samples have to be stratified by histological type to minimize heterogeneity of measurements (Figs. 1 and 2). Therefore, because of sample size constraints we focused on invasive ductal carcinoma (IDC) cases, limiting our further analysis to 14 subjects. These included 5 subjects with IDC only and 9 subjects with DCIS and IDC in their tumors.

We identified 17 differentially expressed miRNAs in the DL samples collected from the affected breast compared to the unaffected breast. A list of the differentially expressed miRNAs including several miRNAs that were previously reported as associated with breast cancer is presented in Table II. Most of these miRNAs have been previously identified in breast tumor tissues and cell lines, having various roles in breast cancer tumorigenesis, invasion and metastasis, and therapeutic response, or were associated with several clinical and pathological characteristics of breast tumors. For example, miR-23b and miR-200a were identified as having oncogenic roles in breast cancer, and miR-126, -548b-5p, and -362-3p have been shown to be tumor suppressors (2125). Other miRNAs that we identified are involved in breast cancer invasiveness and metastasis (miR-23b, -126, -181a, -200a) (2629). miR-23b and miR-126 were associated with breast cancer prognosis (21,30), and miR-126, -363, -638, -663 were shown to have a role in the response to therapy in breast cancer patients (3134). In line with these findings, in our samples, miR-23b and miR-181a were significantly expressed at higher levels in the DL fluid of the affected breast compared to the breast without cancer; all other miRNAs were downregulated in the fluid from the breasts with cancer. Moreover, some of these miRNAs were also found to be differentially expressed between breast cancer patients and normal controls in other biological fluids such as serum (miR-23b, -133b, -181a, 338-3p, -625) (3540), and plasma (miR-200a) (41). Noteworthy, miR-181a was also identified in breast milk (42).

A systems biology analysis of these differentially expressed miRNAs points to possible pathways and cellular processes that have been described as having an important role in breast cancer. Among these, several pathways are hallmarks of cancer molecular signaling including for breast cancer, Wnt, ErbB, MAPK, TGF-β, mTOR, PI3K-Akt, and p53 signaling pathways (data not shown). The most significant top two pathways were Wnt and ErbB (p<0.0001).

When restricting the analysis to subjects having both DCIS and IDC in their tumors, we identified 14 differentially expressed miRNAs in the DL samples collected from the affected breast compared to the unaffected breast. A list of the differentially expressed miRNAs including several miRNAs that were previously reported as associated with breast cancer is presented in Table III. Some of these miRNAs are the same as for the entire set of subjects reported in the previous analysis above (miR-181a, -625, -548b-5p, -645), and other miRNAs are specific for this subgroup of subjects (i.e. those with IDC and DCIS), suggesting that there may be a different miRNA molecular signature released from cancer cells in various stages of carcinogenesis as they progress from DCIS to IDC. However, our small sample size of subgroups did not allow for this hypothesis to be specifically tested.

Some of these miRNAs were found to be associated with breast cancer features as well. miR-301a was found to promote breast tumor metastasis (43), miR-520f and miR-99a have tumor suppressor characteristics (44,45), miR-484 and miR-301a were associated with prognosis (46,47), and miR-484, -576-3p, -144 and let-7a were associated with response to therapy in breast cancer patients (4851). Furthermore, some of these miRs were also found differentially expressed in various biological fluids of breast cancer patients compared to normal controls, such as miR-484 and miR-301a in serum (52,53), miR-144 and miR-301a in blood (54,55), and let-7a in breast milk (56,57).

In the analysis of possible pathways and cellular processes involving these miRNAs, several cancer signaling pathways stand out, some of which have been well-documented in breast cancer based on previous reports, such as ErbB, Wnt, mTOR, MAPK, TGF-β, and PI3K-Akt (data not shown).

This is the first study to investigate miRNA profiling in DL samples, and our study design limits variability compared to classical case-control studies. However, there are certain limitations to consider when interpreting our findings, most important of which is the limited sample size in various strata. This would need to be addressed by future larger studies.

In conclusion, we have shown the feasibility of analyzing miRNAs successfully in the breast ductal fluid obtained by ductal lavage. Our findings suggest that miRNA analysis is potentially useful for the detection of breast cancer using ductal fluid analysis and allows discrimination of tumor histological subtypes as well as detection of cancer vs. normal breast samples. To validate our initial findings a larger study is warranted in order to confirm these preliminary results.

Acknowledgements

This study was supported by a grant from the Avon Foundation for Women.

References

1 

American Cancer Society. Global Cancer Facts & Figures. 2nd edition. American Cancer Society; Atlanta, GA: 2011

2 

Negrini M, Nicoloso MS and Calin GA: MicroRNAs and cancer - new paradigms in molecular oncology. Curr Opin Cell Biol. 21:470–479. 2009. View Article : Google Scholar : PubMed/NCBI

3 

Bertoli G, Cava C and Castiglioni I: MicroRNAs: New biomarkers for diagnosis, prognosis, therapy prediction and therapeutic tools for breast cancer. Theranostics. 5:1122–1143. 2015. View Article : Google Scholar : PubMed/NCBI

4 

Graveel CR, Calderone HM, Westerhuis JJ, Winn ME and Sempere LF: Critical analysis of the potential for microRNA biomarkers in breast cancer management. Breast Cancer (Dove Med Press). 7:59–79. 2015.

5 

Iorio MV, Ferracin M, Liu CG, 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. 65:7065–7070. 2005. View Article : Google Scholar : PubMed/NCBI

6 

Ferracin M, Querzoli P, Calin GA and Negrini M: MicroRNAs: Toward the clinic for breast cancer patients. Semin Oncol. 38:764–775. 2011. View Article : Google Scholar : PubMed/NCBI

7 

Masood S: Development of a novel approach for breast cancer prediction and early detection using minimally invasive procedures and molecular analysis: How cytomorphology became a breast cancer risk predictor. Breast J. 21:82–96. 2015. View Article : Google Scholar : PubMed/NCBI

8 

Brunoro GV, Carvalho PC, Ferreira AT, Perales J, Valente RH, de Moura Gallo CV, Pagnoncelli D and Neves-Ferreira AG: Proteomic profiling of nipple aspirate fluid (NAF): Exploring the complementarity of different peptide fractionation strategies. J Proteomics. 117:86–94. 2015. View Article : Google Scholar : PubMed/NCBI

9 

Nizzoli R, Bozzetti C, Crafa P, Naldi N, Guazzi A, Di Blasio B, Camisa R and Cascinu S: Immunocytochemical evaluation of HER-2/neu on fine-needle aspirates from primary breast carcinomas. Diagn Cytopathol. 28:142–146. 2003. View Article : Google Scholar : PubMed/NCBI

10 

Hornberger J, Chen SC, Li Q, Kakad P and Quay SC: Proliferative epithelial disease identified in nipple aspirate fluid and risk of developing breast cancer: A systematic review. Curr Med Res Opin. 31:253–262. 2015. View Article : Google Scholar

11 

Tredwell GD, Miller JA, Chow HH, Thompson PA and Keun HC: Metabolomic characterization of nipple aspirate fluid by (1)H NMR spectroscopy and GC-MS. J Proteome Res. 13:883–889. 2014. View Article : Google Scholar

12 

Chatterton RT, Muzzio M, Heinz R, Gann PH and Khan SA: Methodological considerations in estrogen assays of breast fluid and breast tissue. Steroids. 99:103–107. 2015. View Article : Google Scholar

13 

Dunmire V, Wu C, Symmans WF and Zhang W: Increased yield of total RNA from fine-needle aspirates for use in expression microarray analysis. Biotechniques. 33:890–896. 2002.PubMed/NCBI

14 

Evron E, Dooley WC, Umbricht CB, Rosenthal D, Sacchi N, Gabrielson E, Soito AB, Hung DT, Ljung B, Davidson NE, et al: Detection of breast cancer cells in ductal lavage fluid by methylation-specific PCR. Lancet. 357:1335–1336. 2001. View Article : Google Scholar : PubMed/NCBI

15 

Assersohn L, Gangi L, Zhao Y, Dowsett M, Simon R, Powles TJ and Liu ET: The feasibility of using fine needle aspiration from primary breast cancers for cDNA microarray analyses. Clin Cancer Res. 8:794–801. 2002.PubMed/NCBI

16 

Phillips TA, Fabian CJ, Kimler BF and Petroff BK: Assessment of RNA in human breast tissue sampled by random periareolar fine needle aspiration and ductal lavage and processed as fixed or frozen specimens. Reprod Biol. 13:75–81. 2013. View Article : Google Scholar : PubMed/NCBI

17 

Danforth DN, Warner AC, Wangsa D, Ried T, Duelli D, Filie AC and Prindiville SA: An improved breast epithelial sampling method for molecular profiling and biomarker analysis in women at risk for breast cancer. Breast Cancer (Auckl). 9:31–40. 2015.

18 

Masood S: Cytomorphology as a risk predictor: experience with fine needle aspiration biopsy, nipple fluid aspiration, and ductal lavage. Clin Lab Med. 25:827–843. viii–ix. 2005. View Article : Google Scholar : PubMed/NCBI

19 

Saeed AI, Sharov V, White J, Li J, Liang W, Bhagabati N, Braisted J, Klapa M, Currier T, Thiagarajan M, et al: TM4: A free, open-source system for microarray data management and analysis. Biotechniques. 34:374–378. 2003.PubMed/NCBI

20 

Vlachos IS, Kostoulas N, Vergoulis T, Georgakilas G, Reczko M, Maragkakis M, Paraskevopoulou MD, Prionidis K, Dalamagas T and Hatzigeorgiou AG: DIANA miRPath v2.0: Investigating the combinatorial effect of microRNAs in pathways. Nucleic Acids Res. 40(W1): W498–W504. 2012. View Article : Google Scholar : PubMed/NCBI

21 

Jin L, Wessely O, Marcusson EG, Ivan C, Calin GA and Alahari SK: Prooncogenic factors miR-23b and miR-27b are regulated by Her2/Neu, EGF, and TNF-α in breast cancer. Cancer Res. 73:2884–2896. 2013. View Article : Google Scholar : PubMed/NCBI

22 

Becker LE, Takwi AA, Lu Z and Li Y: The role of miR-200a in mammalian epithelial cell transformation. Carcinogenesis. 36:2–12. 2015. View Article : Google Scholar :

23 

Ebrahimi F, Gopalan V, Smith RA and Lam AK: miR-126 in human cancers: Clinical roles and current perspectives. Exp Mol Pathol. 96:98–107. 2014. View Article : Google Scholar

24 

Shi Y, Qiu M, Wu Y and Hai L: MiR-548-3p functions as an anti-oncogenic regulator in breast cancer. Biomed Pharmacother. 75:111–116. 2015. View Article : Google Scholar : PubMed/NCBI

25 

Kang H, Kim C, Lee H, Rho JG, Seo JW, Nam JW, Song WK, Nam SW, Kim W and Lee EK: Downregulation of microRNA-362-3p and microRNA-329 promotes tumor progression in human breast cancer. Cell Death Differ. 23:484–495. 2016. View Article : Google Scholar

26 

Ell B, Qiu Q, Wei Y, Mercatali L, Ibrahim T, Amadori D and Kang Y: The microRNA-23b/27b/24 cluster promotes breast cancer lung metastasis by targeting metastasis-suppressive gene prosaposin. J Biol Chem. 289:21888–21895. 2014. View Article : Google Scholar : PubMed/NCBI

27 

Zhang Y, Yang P, Sun T, Li D, Xu X, Rui Y, Li C, Chong M, Ibrahim T, Mercatali L, et al: miR-126 and miR-126* repress recruitment of mesenchymal stem cells and inflammatory monocytes to inhibit breast cancer metastasis. Nat Cell Biol. 15:284–294. 2013. View Article : Google Scholar : PubMed/NCBI

28 

Taylor MA, Sossey-Alaoui K, Thompson CL, Danielpour D and Schiemann WP: TGF-β upregulates miR-181a expression to promote breast cancer metastasis. J Clin Invest. 123:150–163. 2013. View Article : Google Scholar :

29 

Tuomarila M, Luostari K, Soini Y, Kataja V, Kosma VM and Mannermaa A: Overexpression of microRNA-200c predicts poor outcome in patients with PR-negative breast cancer. PLoS One. 9:e1095082014. View Article : Google Scholar : PubMed/NCBI

30 

Liu Y, Cai Q, Bao PP, Su Y, Cai H, Wu J, Ye F, Guo X, Zheng W, Zheng Y, et al: Tumor tissue microRNA expression in association with triple-negative breast cancer outcomes. Breast Cancer Res Treat. 152:183–191. 2015. View Article : Google Scholar : PubMed/NCBI

31 

Hoppe R, Achinger-Kawecka J, Winter S, Fritz P, Lo WY, Schroth W and Brauch H: Increased expression of miR-126 and miR-10a predict prolonged relapse-free time of primary oestrogen receptor-positive breast cancer following tamoxifen treatment. Eur J Cancer. 49:3598–3608. 2013. View Article : Google Scholar : PubMed/NCBI

32 

Zhang R, Li Y, Dong X, Peng L and Nie X: MiR-363 sensitizes cisplatin-induced apoptosis targeting in Mcl-1 in breast cancer. Med Oncol. 31:3472014. View Article : Google Scholar : PubMed/NCBI

33 

Tan X, Peng J, Fu Y, An S, Rezaei K, Tabbara S, Teal CB, Man YG, Brem RF and Fu SW: miR-638 mediated regulation of BRCA1 affects DNA repair and sensitivity to UV and cisplatin in triple-negative breast cancer. Breast Cancer Res. 16:4352014. View Article : Google Scholar : PubMed/NCBI

34 

Hu H, Li S, Cui X, Lv X, Jiao Y, Yu F, Yao H, Song E, Chen Y, Wang M, et al: The overexpression of hypomethylated miR-663 induces chemotherapy resistance in human breast cancer cells by targeting heparin sulfate proteoglycan 2 (HSPG2). J Biol Chem. 288:10973–10985. 2013. View Article : Google Scholar : PubMed/NCBI

35 

Wu Q, Wang C, Lu Z, Guo L and Ge Q: Analysis of serum genome-wide microRNAs for breast cancer detection. Clin Chim Acta. 413:1058–1065. 2012. View Article : Google Scholar : PubMed/NCBI

36 

Guo LJ and Zhang QY: Decreased serum miR-181a is a potential new tool for breast cancer screening. Int J Mol Med. 30:680–686. 2012.PubMed/NCBI

37 

Chan M, Liaw CS, Ji SM, Tan HH, Wong CY, Thike AA, Tan PH, Ho GH and Lee AS: Identification of circulating microRNA signatures for breast cancer detection. Clin Cancer Res. 19:4477–4487. 2013. View Article : Google Scholar : PubMed/NCBI

38 

Godfrey AC, Xu Z, Weinberg CR, Getts RC, Wade PA, DeRoo LA, Sandler DP and Taylor JA: Serum microRNA expression as an early marker for breast cancer risk in prospectively collected samples from the Sister Study cohort. Breast Cancer Res. 15:R422013. View Article : Google Scholar : PubMed/NCBI

39 

Si H, Sun X, Chen Y, Cao Y, Chen S, Wang H and Hu C: Circulating microRNA-92a and microRNA-21 as novel minimally invasive biomarkers for primary breast cancer. J Cancer Res Clin Oncol. 139:223–229. 2013. View Article : Google Scholar :

40 

Kodahl AR, Zeuthen P, Binder H, Knoop AS and Ditzel HJ: Alterations in circulating miRNA levels following early-stage estrogen receptor-positive breast cancer resection in post-menopausal women. PLoS One. 9:e1019502014. View Article : Google Scholar : PubMed/NCBI

41 

Madhavan D, Zucknick M, Wallwiener M, Cuk K, Modugno C, Scharpff M, Schott S, Heil J, Turchinovich A, Yang R, et al: Circulating miRNAs as surrogate markers for circulating tumor cells and prognostic markers in metastatic breast cancer. Clin Cancer Res. 18:5972–5982. 2012. View Article : Google Scholar : PubMed/NCBI

42 

Na RS, EGX, Sun W, Sun XW, Qiu XY, Chen LP and Huang YF: Expressional analysis of immune-related miRNAs in breast milk. Genet Mol Res. 14:11371–11376. 2015. View Article : Google Scholar : PubMed/NCBI

43 

Ma F, Zhang J, Zhong L, Wang L, Liu Y, Wang Y, Peng L and Guo B: Upregulated microRNA-301a in breast cancer promotes tumor metastasis by targeting PTEN and activating Wnt/β-catenin signaling. Gene. 535:191–197. 2014. View Article : Google Scholar

44 

Keklikoglou I, Koerner C, Schmidt C, Zhang JD, Heckmann D, Shavinskaya A, Allgayer H, Gückel B, Fehm T, Schneeweiss A, et al: MicroRNA-520/373 family functions as a tumor suppressor in estrogen receptor negative breast cancer by targeting NF-κB and TGF-β signaling pathways. Oncogene. 31:4150–4163. 2012. View Article : Google Scholar

45 

Wang X, Li Y, Qi W, Zhang N, Sun M, Huo Q, Cai C, Lv S and Yang Q: MicroRNA-99a inhibits tumor aggressive phenotypes through regulating HOXA1 in breast cancer cells. Oncotarget. 6:32737–32747. 2015.PubMed/NCBI

46 

Volinia S and Croce CM: Prognostic microRNA/mRNA signature from the integrated analysis of patients with invasive breast cancer. Proc Natl Acad Sci USA. 110:7413–7417. 2013. View Article : Google Scholar : PubMed/NCBI

47 

Yu H, Li H, Qian H, Jiao X, Zhu X, Jiang X, Dai G and Huang J: Upregulation of miR-301a correlates with poor prognosis in triple-negative breast cancer. Med Oncol. 31:2832014. View Article : Google Scholar : PubMed/NCBI

48 

Ye FG, Song CG, Cao ZG, Xia C, Chen DN, Chen L, Li S, Qiao F, Ling H, Yao L, et al: Cytidine deaminase axis modulated by miR-484 differentially regulates cell proliferation and chemoresistance in breast cancer. Cancer Res. 75:1504–1515. 2015. View Article : Google Scholar : PubMed/NCBI

49 

Wu J, Li S, Jia W, Deng H, Chen K, Zhu L, Yu F and Su F: Reduced let-7a is associated with chemoresistance in primary breast cancer. PLoS One. 10:e01336432015. View Article : Google Scholar : PubMed/NCBI

50 

Lv J, Xia K, Xu P, Sun E, Ma J, Gao S, Zhou Q, Zhang M, Wang F, Chen F, et al: miRNA expression patterns in chemoresistant breast cancer tissues. Biomed Pharmacother. 68:935–942. 2014. View Article : Google Scholar : PubMed/NCBI

51 

Yu L, Yang Y, Hou J, Zhai C, Song Y, Zhang Z, Qiu L and Jia X: MicroRNA-144 affects radiotherapy sensitivity by promoting proliferation, migration and invasion of breast cancer cells. Oncol Rep. 34:1845–1852. 2015.PubMed/NCBI

52 

Zearo S, Kim E, Zhu Y, Zhao JT, Sidhu SB, Robinson BG and Soon PS: MicroRNA-484 is more highly expressed in serum of early breast cancer patients compared to healthy volunteers. BMC Cancer. 14:2002014. View Article : Google Scholar : PubMed/NCBI

53 

Hatse S, Brouwers B, Dalmasso B, Laenen A, Kenis C, Schöffski P and Wildiers H: Circulating microRNAs as easyto-measure aging biomarkers in older breast cancer patients: Correlation with chronological age but not with fitness/frailty status. PLoS One. 9:e1106442014. View Article : Google Scholar

54 

McDermott AM, Miller N, Wall D, Martyn LM, Ball G, Sweeney KJ and Kerin MJ: Identification and validation of oncologic miRNA biomarkers for luminal A-like breast cancer. PLoS One. 9:e870322014. View Article : Google Scholar : PubMed/NCBI

55 

Chang CW, Wu HC, Terry MB and Santella RM: microRNA expression in prospectively collected blood as a potential biomarker of breast cancer risk in the BCFR. Anticancer Res. 35:3969–3977. 2015.PubMed/NCBI

56 

Gu YQ, Gong G, Xu ZL, Wang LY, Fang ML, Zhou H, Xing H, Wang KR and Sun L: miRNA profiling reveals a potential role of milk stasis in breast carcinogenesis. Int J Mol Med. 33:1243–1249. 2014.PubMed/NCBI

57 

Xi Y, Jiang X, Li R, Chen M, Song W and Li X: The levels of human milk microRNAs and their association with maternal weight characteristics. Eur J Clin Nutr. Oct 21–2015.(Epub ahead of print). View Article : Google Scholar : PubMed/NCBI

Related Articles

Journal Cover

May-2016
Volume 48 Issue 5

Print ISSN: 1019-6439
Online ISSN:1791-2423

Sign up for eToc alerts

Recommend to Library

Copy and paste a formatted citation
x
Spandidos Publications style
Do Canto LM, Marian C, Willey S, Sidawy M, Da Cunha PA, Rone JD, Li X, Gusev Y and Haddad BR: MicroRNA analysis of breast ductal fluid in breast cancer patients. Int J Oncol 48: 2071-2078, 2016
APA
Do Canto, L.M., Marian, C., Willey, S., Sidawy, M., Da Cunha, P.A., Rone, J.D. ... Haddad, B.R. (2016). MicroRNA analysis of breast ductal fluid in breast cancer patients. International Journal of Oncology, 48, 2071-2078. https://doi.org/10.3892/ijo.2016.3435
MLA
Do Canto, L. M., Marian, C., Willey, S., Sidawy, M., Da Cunha, P. A., Rone, J. D., Li, X., Gusev, Y., Haddad, B. R."MicroRNA analysis of breast ductal fluid in breast cancer patients". International Journal of Oncology 48.5 (2016): 2071-2078.
Chicago
Do Canto, L. M., Marian, C., Willey, S., Sidawy, M., Da Cunha, P. A., Rone, J. D., Li, X., Gusev, Y., Haddad, B. R."MicroRNA analysis of breast ductal fluid in breast cancer patients". International Journal of Oncology 48, no. 5 (2016): 2071-2078. https://doi.org/10.3892/ijo.2016.3435