In women, breast cancer (BC) represents the most commonly diagnosed cancer, which is also the second leading cause of cancer-related death after lung cancer . During the last few decades, progress has been made in its prognosis due to efficient and exact early diagnosis, as well as successful radical surgery and adjuvant therapy [2-3]. However, the current determination of prognosis of BC still remains unsatisfactory, and the 5-year survival rate upon the occurrence of metastasis declines to less than 25% [4-6]. Actually, the mechanism underlying the development and progression of BC is far from clearly understood. Hence, gathering more and precise knowledge about its progression would facilitate the generation of novel diagnostic and therapeutic targets. Now there is a large body of evidence showing that a class of small non-coding RNAs, microRNAs (miRNAs), play important parts in BC progression [7-10].
The microRNA-29 (miR-29) family, which is composed of miR-29a, -b and -c, has been shown to be dysregulated and crucially involved in various types of human cancers [11-14], incuding BC [15,16]. Specifically, Wu et al. showed that miR-29a was significantly decreased in different types of BC, and overexpression of miR-29a resulted in cell growth defects. They speculated that the growth inhibitory role of miR-29a might be mediated by its direct targeting B-Myb transcription factor, which is closely associated with tumorigenesis . However, whether other molecular explanations exist, which could further characterize the function of miR-29a in BC cells, has not been well addressed.
Cell division cycle 42 (CDC42) is a well-known member of the Ras homolog (Rho) family. It regulates crucial cellular processes, including cell cycle, and cell cytoskeleton organization [18,19]. The negative regulation of CDC42 by miR-133 has been reported in gastric cancer cells, which correlates with cell proliferation and migration defects . In the current study, we have endeavored to evaluate the role of miR-29a in breast cancer cells and have constructed the relationship of miR-29a with CDC42. Our findings might highlight miR-29a as a novel therapeutic target for BC treatment.
2 Materials and methods
2.1 Cell culture
MCF-10A, MDA-MB-453, MDA-MB-231, T47D and MCF-7 cells were obtained from American Type Culture Collection. Cells were maintained in their proper media and placed in a humidified incubator with 5% CO2 at 37°C.
Control microRNA and miR-29a mimics were purchased from Genepharma. Fetal bovine serum was from GIBCO. The SuperSignal Substrate Western blotting detection system was from Pierce. B-actin antibody and CDC42 antibody were purchased from Santa Cruz. Luciferase Assay Kit was purchased from Promega. Lipofectamine2000 reagent was purchased from Invitrogen.
2.3 Cell transfection
MDA-MB-453 cells were transfected with control or miR-29a mimics by using lipofectamine2000. After 24 hours, cells were used in different experiments. Transfection of MDAMB-453 cells for luciferase assay is described in detail below.
2.4 Quantitative RT-PCR
Total RNA was extracted using Invitrogen Trizol Reagent. The total level of miR-29s or CDC42 was quantified by qRT-PCR by TaKaRa SYBR Green Real-time PCR Master Mix Kit. Fold changes of miRNA and/or mRNA levels were calculated with the 2−ΔΔCt method using the levels of U6B (for miRNA) or gapdh (for mRNA) as the internal controls.
2.5 Cell counting
MDA-MB-453 cells were transfected with control or miR-29a mimics for 48 hours. After that, cells were trypsinzed and seeded into 24-well plates at a density of 6000 cells. Then cells were counted by a blood-cell-counting chamber for the next 4 days. Experiments were repeated at least three times independently.
2.6 Cell cycle assay
The transfected MDA-MB-453 cells were harvested, fixed with cold 70% ethanol overnight at –20°C, and incubated in the dark with RNase (100mg/ml) and propidium iodide (50 mg/ml) for 1 hour at 37°C. A total of 30000 nuclei were examined by flow cytometry.
2.7 Western blotting
Breast cancer cells were lysed with RIPA lysis buffer with a protease inhibitor mixture. After quantification, equal amounts of protein were separated by 10% SDS-PAGE, transferred to Millipore polyvinylidene difluoride membranes, immunoblotted with primary antibodies, and visualized with horseradish-peroxidase-coupled secondary antibodies.
2.8 Dual-luciferase reporter assays
The 3’-untranslated region (3’-UTR) of CDC42 containing the predicted binding site for miR-29 was amplified and cloned into pGL3 vector. Forty-eight hours after transfection, luciferase activity was detected using a dual-luciferase reporter assay system and normalized to Renilla activity.
2.9 miR-29 target prediction
2.10 Statistical analysis
Statistical analysis was performed using SPSS18.0. Values were expressed as mean ± standard deviation (s.d.). Differences between groups were calculated using the Student’s t-test. P value < 0.05 was considered as statistically significant.
3.1 Downregulation of miR-29 in BC cell lines
To examine the relative expression levels of miR-29, including –a, –b and –c, real-time PCR was performed in four human BC cell lines (MDA-MB-453, MD-MB-231, T47D and MCF-7), and in the normal breast epithelium cell line MCF-10A. As shown in Figure 1, all miR-29 showed significantly downregulation in BC cell lines when compared to that of the control MCF-10A cells. Notably, among the miR-29 members, miR-29a represented as the dominant isoform, which showed the most decreased expression in MDA-MB-453 cells. The downregulation of miR-29 in BC cell lines was consistent with the previous findings , and suggested that miR-29 might function in a similar way to suppress BC progression.
3.2 miR-29a negatively modulate MDA-MB-453 cell growth in vitro
To verify the biological roles, especially the growth inhibitory activities of miR-29a in BC cells, cell growth and cell cycle profile were investigated in MDA-MB-453 cells. As shown in Figure 2A, after synthesized mimics of miR-29a was transfected into the MDA-MB-453 cells, the indicated expression level of miR-29a was significantly elevated. Meanwhile, MDA-MB-453 cells overexpressed with miR-29a displayed slower cell growth rate than control cells (Figure 2B). Importantly, compared to the control cells, overexpression of miR-29a led to cell cycle arrested at the G0/G1 phase (Figure 2C). These results indicated that the growth inhibiting activity of miR-29a could be interpreted by the cell cycle progression defects by these miRNAs, among which miR-29a took the major part in the cellular growth process.
3.3 miR-29a targets CDC42
To probe the potential mechanisms of miR-29 in the BC cell growth, we searched the literature and miRNA database, TargetScan (http://www.targetscan.org/) for potential targets of miR-29. We therefore hypothesized that miR-29 might target CDC42 to inhibit BC cell growth. To confirm our hypothesis, we applied the pMIR-REPORT System. A fragment representing the binding sequences within the 3’-UTR of CDC42 DNA was inserted into the luciferase reporter vector. As shown in Figure 3A, in miR-29a over-expressed groups, the activity of luciferase was significantly inhibited, among which miR-29a exhibited the most decreased luciferase expression. Consistently, western blot confirmed that CDC42 mRNA and protein levels were also decreased in the miR-29a overexpressed cells (Figure 3B). The above findings suggest that miR-29a might all regulate BC cell growth by targeting CDC42.
As described previously, miR-29 functions as tumor suppressor in BC progression [15-17]. In other types of human cancers, the roles of miR-29 remain controversial. In clear cell renal cell carcinoma, miR-29 was all downregulated, and restoration of all mature members of miR-29 could inhibit cell proliferation, migration and invasion . However, in a study of pancreatic cancer, miR-29a was found to be increased and could upregulate the expression of pro-inflammatory factors and epithelial-mesenchymal transition (EMT) markers . Hence, the particular roles of miR-29 might be interpreted by its different family members.
In our study, we characterized miR-29a as the dominant isoform of the miR-29 family in our tested BC cells, and we confirmed that miR-29 levels were remarkably decreased in collected BC cell lines. Thereafter, we applied several methods to enrich the functions of miR-29a, and we concluded that miR-29a acted similarly to inhibit cell growth, which might be further explained by the negative modulation of cell cycle progression. A previous study showed that miR-29a could mechanically target tristetraprolin, which is involved in EMT , or P42.3, which was also found to be associated with tumorigenicity . Herein, we showed that miR-29a could also target CDC42, and this targeting might be used to explain the regulation of G0/G1 arrest by miR-29a. Still, direct evidence was lacking to prove whether CDC42 could be responsible for the growth inhibitory activity of miR-29a. Furthermore, how miR-29a/CDC42-mediated signaling works to function in BC cells remains to be explained. In addition, although we showed that miR-29a was the dominant and most deregulated form of miR-29 in the indicated BC cell lines, we are still concerned about the similarity of these miR-29 members in regulating cellular biology. More efforts should be made to understand the common and different roles of these miR-29 members.
Taken together, our current findings support the growth-inhibiting function of miR-29a in BC cells through cell cycle regulation, and miR-29a could target CDC42 in a post-transcriptional manner.
Sung H, Rosenberg PS, Chen WQ, Hartman M, Lim WY, Chia KS, Wai-Kong Mang O, Chiang CJ, Kang D, Ngan RK, Tse LA, Anderson WF, Yang XR: Female breast cancer incidence among Asian and Western populations: more similar than expected. J Natl Cancer Inst 2015; 107(7): pii: djv107 Google Scholar
Gerasimova E, Audit B, Roux SG, Khalil A, Gileva O, Argoul F, Naimark O, Arneodo A: Wavelet-based multifractal analysis of dynamic infrared thermograms to assist in early breast cancer diagnosis. Front Physiol 2014; 5:176 Google Scholar
Chan A, Shannon C, de Boer R, Baron-Hay S, Redfern A, Bauwens A, Craft P, Webb S, Townsend A, Kotasek D: Phase II, open-label trial of lapatinib and vinorelbine in women with previously treated HER2-positive metastatic breast cancer. Asia Pac J Clin Oncol 2014; 10(4):368-375 Google Scholar
Siegel R, Naishadham D, Jemal A: Cancer statistics. CA Cancer J Clin 2013; 63(1):11-30 Google Scholar
Jang GB, Kim JY, Cho SD, Park KS, Jung JY, Lee HY, Hong IS, Nam JS: Blockade of Wnt/β-catenin signaling suppresses breast cancer metastasis by inhibiting CSC-like phenotype. Sci Rep 2015; 5:12465Google Scholar
Printz C: Low breast density linked to poor breast cancer prognosis. Cancer 2015; 121(15):2479 Google Scholar
Bertoli G, Cava C, Castiglioni I: MicroRNAs: New Biomarkers for Diagnosis, Prognosis, Therapy Prediction and Therapeutic Tools for Breast Cancer. Theranostics 2015;5(10):1122-1143 Google Scholar
Takahashi RU, Miyazaki H, Ochiya T: The Roles of MicroRNAs in Breast Cancer. Cancers (Basel) 2015; 7(2):598-616Google Scholar
Zhang W, Liu J, Wang G: The role of microRNAs in human breast cancer progression. Tumour Biol 2014; 35(7):6235-6244Google Scholar
Shah NR, Chen H: MicroRNAs in pathogenesis of breast cancer: Implications in diagnosis and treatment. World J Clin Oncol 2014; 5(2):48-60 Google Scholar
Amodio N, Rossi M, Raimondi L, Pitari MR, Botta C, Tagliaferri P, Tassone P: miR-29s: a family of epi-miRNAs with therapeutic implications in hematologic malignancies. Oncotarget 2015; 6(15):12837-12861 Google Scholar
Jiang H, Zhang G, Wu JH, Jiang CP: Diverse roles of miR-29 in cancer (review). Oncol Rep 2014; 31(4):1509-1516Google Scholar
Wang Y, Zhang X, Li H, Yu J, Ren X: The role of miRNA-29 family in cancer. Eur J Cell Biol 2013; 92(3):123-128Google Scholar
Schmitt MJ, Margue C, Behrmann I, Kreis S: MiRNA-29: a microRNA family with tumor-suppressing and immune-modulating properties. Curr Mol Med 2013; 13(4):572-585 Google Scholar
Rostas JW 3rd, Pruitt HC, Metge BJ, Mitra A, Bailey SK, Bae S, Singh KP, Devine DJ, Dyess DL, Richards WO, Tucker JA, Shevde LA, Samant RS: microRNA-29 negatively regulates EMT regulator N-myc interactor in breast cancer. Mol Cancer 2014; 13:200 Google Scholar
Cittelly DM, Finlay-Schultz J, Howe EN, Spoelstra NS, Axlund SD, Hendricks P, Jacobsen BM, Sartorius CA, Richer JK: Progestin suppression of miR-29 potentiates dedifferentiation of breast cancer cells via KLF4. Oncogene 2013; 32(20):2555-2564 Google Scholar
Wu Z, Huang X, Huang X, Zou Q, Guo Y: The inhibitory role of Mir-29 in growth of breast cancer cells. J Exp Clin Cancer Res. 2013 Dec 1;32:98 Google Scholar
Cerione RA: Cdc42: new roads to travel. Trends Cell Biol 2004; Mar;14(3):127-132 Google Scholar
Arias-Romero LE, Chernoff J: Targeting Cdc42 in cancer. Expert Opin Ther Targets 2013; 17(11):1263-1273 Google Scholar
Cheng Z, Liu F, Wang G, Li Y, Zhang H, Li F: miR-133 is a key negative regulator of CDC42-PAK pathway in gastric cancer. Cell Signal 2014; 26(12):2667-2673 Google Scholar
Nishikawa R, Chiyomaru T, Enokida H, Inoguchi S, Ishihara T, Matsushita R, Goto Y, Fukumoto I, Nakagawa M, Seki N: Tumour-suppressive microRNA-29s directly regulate LOXL2 expression and inhibit cancer cell migration and invasion in renal cell carcinoma. FEBS Lett 2015; 589(16):2136-2145 Google Scholar
Sun XJ, Liu BY, Yan S, Jiang TH, Cheng HQ, Jiang HS, Cao Y, Mao AW: MicroRNA-29a Promotes Pancreatic Cancer Growth by Inhibiting Tristetraprolin. Cell Physiol Biochem 2015;37(2):707-718 Google Scholar
Gebeshuber CA, Zatloukal K, Martinez J: miR-29a suppresses tristetraprolin, which is a regulator of epithelial polarity and metastasis. EMBO Rep 2009; 10(4):400-405 Google Scholar
Cui Y, Su WY, Xing J, Wang YC, Wang P, Chen XY, Shen ZY, Cao H, Lu YY, Fang JY: MiR-29a inhibits cell proliferation and induces cell cycle arrest through the downregulation of p42.3 in human gastric cancer. PloS One 2011; 6(10):e25872 Google Scholar
About the article
Published Online: 2016-03-30
Published in Print: 2016-01-01
Conflict of interest statement: Authors state no conflict of interest.