MicroRNA-205 directly targets Krüppel-like factor 12 and is involved in invasion and apoptosis in basal-like breast carcinoma

  • Authors:
    • Bing Guan
    • Qing Li
    • Li Shen
    • Qiu Rao
    • Yan Wang
    • Yun Zhu
    • Xiao-Jun Zhou
    • Xiao-Hong Li
  • View Affiliations

  • Published online on: June 8, 2016     https://doi.org/10.3892/ijo.2016.3573
  • Pages: 720-734
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Abstract

We investigated microRNAs (miRs) specific to its target gene and exerting distinct biological functions for basal-like breast carcinoma (BLBC). Total RNA was extracted and subjected to miR microarray and bioinformatics analysis. Based on the comprehensive analysis, expression of miRs including its target was analyzed by quantitative reverse transcription-polymerase chain reaction (qRT-PCR), western blot analysis and immunohistochemistry (IHC). Further functional analyses were conducted including proliferation, invasion and apoptosis. miR-205 was identified as downregulated (less than 0.5-fold) in BLBC relatively to normal control (NC). Gene ontology (GO) analysis suggested miR-205 may directly targeted Krüppel-like factor 12 (KLF12; degree=4). Luciferase assay revealed miR-205 directly targeted KLF12 through binding its 3'-untranslated region (3'-UTR; p=0.0016). qRT-PCR and western blot analysis showed miR-205 expression was low in cells (p=0.007) and tumor tissues (n=6; p=0.0074), and KLF12 RNA/protein was observed at high levels in cells (p=0.0026; p=0.0079) and tumor tissues (n=9; p=0.0083); knock-up of miR-205 increased its expression (p=0.0021) but reduced KLF12 RNA/protein levels (p=0.0038; p=0.009) in cells. Modulation of miR-205 expression by transfecting its mimics in cells, was involved in invasion (p=0.00175) and apoptosis (p=0.006). In conclusion, our results supported that miR-205 was a miR specific to BLBC which functioned as tumor suppressor gene through directly targeting and negatively regulating proto-oncogene KLF12. miR-205 dysregulation was involved in invasion and apoptosis. miR-205 and KLF12 provided a potential diagnosis biomarker and therapeutic approach for BLBC.

Introduction

Breast cancer is the most frequently diagnosed cancer and the leading cause of cancer death worldwide (1). It alone accounts for 25% of all cancer cases and 15% of all cancer deaths among females (1). However, breast cancer presents as a heterogeneous disease, not only from clinical and histological perspectives but also from the view of genetic expression (2). Gene microarray profiling have led to the re-categorization of invasive breast carcinomas into 5 distinct subtypes; luminal A, luminal B, normal breast like, human epithelial growth factor receptor-2 (Her-2) overexpressing, and basal-like (2,3). Basal-like and Her-2 groups, however, have more aggressive clinical behavior than the others (4). The basal-like subtype is the least prevalent and the most aggressive one, but it lacks a target based therapy since its triple-negative characteristic (5). miRs are small, non-coding RNAs that negatively regulate gene expression by their interaction with 3′-untranslated region (3′-UTR) of specific target miRs (6), each of which is capable of regulating hundreds of protein-coding genes (7). miRs are involved in biological and pathologic processes, including cell differentiation, proliferation, apoptosis and metabolism (8). Accumulating evidence indicates that the dysregulation of miRs has been identified in human cancer, but only a few of these miRs have been functionally documented in breast cancer (6,9). Some previous studies showed distinct differences in miR expression patterns and function between breast cancer cells and NC (1012).

miR-205 dysregulationg was identified with a series of tumors in recent studies (13). miR-205 was downregulated and functioned as a tumor suppressor gene in breast cancer (14) and prostate cancer (15), miR-205 was an esophageal squamous cell carcinoma-specific miR that exerts tumor-suppressive activities with epithelial mesenchymal transition inhibition by targeting zinc finger E-box binding homeobox (ZEB)2 (16), miR-205 was a glioma-specific tumor suppressor by targeting vascular endothelial growth factor-A(17), miR-205 was a candidate tumor suppressor that targets ZEB2 in renal clear cell carcinoma (18). miR-205 acts either as a tumor suppressor through inhibiting proliferation and invasion, or as an oncogene through facilitating tumor initiation and proliferation, depending on the specific tumor context and target genes (19). Krüppel-like factor (KLF) and share a three-C2H2 zinc finger DNA binding domain which are involved in cell proliferation and differentiation in both normal and pathological situations (20). KLF family members play an important role in the growth and metastasis and cell cycle of different tumor types (20). KLF12, members of KLF family, binds to the CAGTGGG sequence within target gene promoter regions and represses target gene expression through an N-terminal Pro-Xaa-Asp-Leu-Ser sequence that promotes a physical interaction with the co-repressor C-terminal binding protein 1 (CtBP1) (21). Several studies revealed the differentially expressed KLF12 in human tissues. Nakamura et al introduced KLF12 cDNA into NIH3T3 and AZ-521 cell lines and found that overexpression significantly enhanced their invasive potential (22). Shen et al reported that KLF12, suppressed by 8-Br-cyclic adenosine monophosphate and medroxyprogesterone acetate, negatively regulated human endometrial stromal cells decidualization by inhibiting decidual prolactin and insulin-like growth factor binding protein-1 expression (23).

miR-205 dysregulation was identified with a series of tumour. However, there was little information on the functional roles of miRs specific and its target gene for basal-like breast carcinoma (BLBC). In our previously miRs microarray assay, differentially expression miRs were identified in BLBC. Further bioinformatic analysis revealed KLF12 may be directly targeted by miR-205. Therefore, the study was designed to identify specifically expression miRs and its target gene and distinct biological actions in BLBC.

Materials and methods

Breast tumor samples

Human breast cancer tissues and paired non-cancerous tissues were collected at Shanghai 6th People's Hospital Jinshan Branch. The samples were immediately snap-frozen in liquid nitrogen and stored at −80°C for DNA/RNA extraction. Hematoxylin and eosin (H&E) sections were reviewed by two pathologists. Assessment of histological grade were using Bloom (25) and Richardson methods modified by Elston and Ellis (24). The study was approved by Shanghai 6th People's Hospital Jinshan Branch Medical Ethics Committee and an informed consent was obtained for the use of tissue samples from each patient.

Cell lines and culture

The human mammary epithelial cell lines MCF-10A and the basal-like breast cancer cell lines MDA-MB-468 (basal-like) (26) were obtained from the Chinese Academy of Sciences Cell Bank (Shanghai, China). MCF-10A cells were maintained in DMEM/F12 (1:1) supplemented with 5% horse serum (both from Invitrogen), EGF (20 ng/ml; Peprotech), hydrocortisone (0.5 μg/ml), cholera toxin (100 ng/ml), insulin (10 μg/ml) (all from Sigma) cultured in 5% CO2 at 37°C. MDA-MB-468 cells were maintained in L-15 supplemented with 10% fetal bovine serum (FBS), cultured in 100% air at 37°C.

Transfection

Cells were plated in 12-well plates and transfected at 80–90% confluence with GenePharma (Shanghai, China) miR mimics (miR-205 mimics, miR-205 mimics NC) and inhibitors (miR-205 inhibitor, miR-205 inhibitor NC) at a final concentration of 100 nM in OPTI-MEM using Lipofectamine 2000 (Invitrogen) according to manufacturer's instruction. L-15 containing 10% FBS was added 6 h after transfection. The transfected cells were used for functional studies or harvested for RNA and protein analyses as described after 48 h culture.

Immunohistochemistry (IHC) and fluorescence in situ hybridization (FISH)

Breast tissue samples were fixed in 4% formalin/phosphate-buffered saline. Tissues were dehydrated, embedded in paraffin and cut. Consecutive 4 μm thick sections were analyzed by IHC using a panel of antibodies against estrogen receptor (ER; 1:100), progesterone receptor (PR; 1:100) (both from Neomarkers), cytokeratin (CK) 5/6 (1:100; Dako), CK14 (Dako), p63 (1:500; Neomarkers), epidermal growth factor receptor (EGFR; 1:50), p53 (1:100), and Ki-67 (1:75) (all from Dako) in order to identify BLBC molecular subtypes (2,3,27). KLF12 (1:100; Santa Cruz Biotechnology, Inc., Santa Cruz, CA, USA) expression pattern was also analyzed using IHC. IHC staining was performed according to manufacturer's instructions. 3,3N-Diaminobenzidine Tertrahydrochloride (Dako) systems were used for detection. Her-2 was stained with a HercepTest kit (Dako). For each stain, the percentage of positive cells was recorded. Marker expression over 10% within tumor cells was considered positive. Marker expression under 10% within tumor cells was considered negative. For Her-2, only cases with a membranous staining score of 3 were considered positive.

FISH was performed for the detection of Her-2 amplification. The probe mix consisted of a mixture of Texas-Red-labeled DNA probes covering a 218-kb region including the Her-2 gene on chromosome-17 (CEN-17) and a mixture of fluorescence-labeled DNA probes targeted at the centromere region of CEN-17. Section preparation and hybridization were performed according to manufacturer's instructions (Dako). Wherever possible, we calculated 30 nuclei per tissue specimen. Specimens with Her-2/CEN-17 ratios over 2.2 were considered to have undergone Her-2. For specimens with borderline ratios (1.8–2.2), an additional 30 nuclei were counted and the ratio was recalculated with 60 nuclei. Specimens with Her-2/CEN-17 ratios under 1.8 were considered to be free of Her-2 amplification.

RNA extraction

Total RNA was isolated including tissue samples and cultured cells using TRIzol reagent (Invitrogen) and then treated with RNase-free DNaseI (Promega). Quality of total RNA was determined on an RNA Nano kit (Bioanalyzer), and the RNA was quantified using a spectrophotometer (Nanodrop-1000; NanoDrop). Extracted RNA samples were stored at −80°C until used.

LNA-based miR microarray and bioinformatics analysis

To identify miRs specific for BLBC, total RNA was extracted from BLBC tissues and paired non-cancerous tissues. The isolated RNA samples were subjected to comprehensive analysis of miRs expression patterns with the microarray-based technology. Purified RNA was labeled with a miRCURY Hy3/Hy5 labeling kit (Exiqon). The Hy3™-labeled samples and Hy5™-labeled reference pool RNA samples were then mixed pair-wise and hybridized to the miRCURY LNA array version 11.0 (Exiqon). The hybridization was performed according to the manufacturer's instructions. To identify miRs that were differentially expressed between the BLBC tissues and NC, supervised analysis was performed using hierarchical clustering analysis (Cluster 3.0).

GO analysis was used to organize genes into hierarchical categories and revealed the miR-gene regulatory network on the basis of biological process and molecular functions (2830). In detail, the one-sided Fisher's exact test and χ2-test were used to establish GO categories, and the false discovery rate (FDR) was calculated to correct the p-values (3133). Only GOs that had p-values <0.01 and FDRs <0.05 were chosen. Three datasets of miRs and their predicted targets were also used in this study: TargetScan, PicTar and miRanda (3437). SigTerms software was used to perform GOs analysis simultaneously (38). SigTerms were developed as a set of Excel macros through Excel Visual Basic for Applications using both the selected gene set and the entire set of gene-to-miR associations (38). Affymetrix probe identifiers were mapped to Entrez gene identifiers using version 21 of the U133A annotation. The network of miR-mRNA interactions, representing the critical miRs and their targets, was established according to the miRs degree (38). For interactive viewing of the network, Pajek software was used to process networks of miR-mRNA interaction (39).

qRT-PCR

Expression levels of miRs and KLF12 which showed significant differences based on the microarray and bioinformatic results were analyzed by qRT-PCR using cell lines and tissue samples. cDNA was prepared from total RNA using an All-in-One miRNA qRT-PCR detection kit (GeneCopoeia) following the protocol provided by the manufacturer. All PCR reactions were performed in 20 μl aliquots containing 2 μl first-strand cDNA with 18 μl PCR master mixture (10 μl qPCR mix, 2 μl qPCR primer, 2 μl universal Adaptor PCR Primer and 2 μl RNase-free water), and run in triplicate on the iQ5 real-time PCR detection system (Bio-Rad). Thermal cycling was initiated with a first denaturation step at 95°C for 10 min, followed by 40 cycles of 95°C for 10 sec and 60°C for 20 sec and 72°C for 30 sec. The cycle passing threshold (Ct) was recorded. After normalization to glyceraldehyde 3-phosphate dehydrogenase (GAPDH) mRNA, relative expression levels and fold induction of each target gene were calculated using the comparative CT (ΔΔCT) methods (40).

Western blot analysis

Total protein was extracted using the Total Protein Extraction kit (Thermo Pierce). Tissues and cells were lysed in RIPA buffer supplemented with protease inhibitors according to the manufacturer's instructions. Lysates were separated on a 10% acrylamide gel and subjected to western blot analysis. Immunoblots were incubated overnight at 4°C with the following primary antibodies: anti-KLF12 (1:200) and anti-β-actin (1:2,000) (both from Santa Cruz Biotechnology, Inc.) were used as loading controls. Peroxidase-labeled secondary antibodies (1:2,000; Santa Cruz Biotechnology, Inc.) were used to visualize bands using the enhanced chemiluminescence kit (Amersham) on gel image analysis system (Tanon).

Cell proliferation assay

Cell proliferation was determined by the cell counting kit-8 assay (CCK-8; Obio Technology, Shanghai, China). After transfection and culture for 48 h, MDA-MB-468 cells were plated at a density of 2×104 cells/ml on 96-well plates and cultured in 100% CO2 at 37°C. In each detection point, 10 μl CCK-8 solution reagent was added to each well. Four hours later, the plates were read in a microplate autoreader (infinite M1000; Tecan) at wavelength of 450 nm. The results were expressed as the mean optical density for selected paradigms performed in triplicate.

Transwell invasion assay

Matrigel invasion assay was performed using a 24-well invasion chamber system (BD Biosciences) with polycarbonic membrane (diameter: 6.5 mm, pore size 8 μm). Cells were plated on the top of Matrigel-coated invasion chambers in a serum-free L-15. As a chemo-attractant, L-15 containing 10% of FBS was added to the lower compartment of the chamber. The cells were incubated for 24 h. Invasion of cells to the underside of the Matrigel-coated membrane was detected by staining the cells with Mayer's hematoxylin solution and visualizing the cells under a microscope. After staining, cells were counted under a microscope in four random fields (magnification, ×100) and results were expressed in the form of a bar graph. Assays were done in triplicate for each experiment, and each experiment was repeated three times.

Quantitation of apoptosis

The Annexin V-fluorescein isothiocyanate (FITC) apoptosis detection kit (Beyotime) was used to detect and quantify apoptosis by flow cytometry. In brief, L-15 containing 10% FBS was added 6 h after transfection. Then, cells were cultured 72 h and collected by centrifugation for 5 m at 2,000 rpm. Cells were resuspended at a density of 1–5×106 cells/ml by added 500 μl binding buffer, then 5 μl Annexin V-EGFP and 5 μl propidium iodide were added for 5–10 min, and analyzed by FACSVerse™ Flow Cytometer (Becton-Dickinson) in 1 h. The data obtained were analyzed using CellQuest software.

KLF12 3′-UTR construction and luciferase reporter assay

For the luciferase reporter assays, KLF12 3′-UTR, including the XhoI and NotI restriction sites, was synthesised and then cloned into the psiCHECK-2 Vector (Promega) using the XhoI and NotI (both from NEB) restriction sites. HEK-293T cells were seeded into 48-well plate at a density of 70–80% cells/well. After overnight incubation, the cells were treated with transfection mixture consisting of 25 μl of serum-free medium diluting 100 ng psiCHECK-KLF12 (V1), 25 μl of serum-free medium diluting mir-205 (V2) and 25 μl of serum-free medium diluting Lipofectamine 2000 (V3; Invitrogen). Forty-eight hours post-transfection Renilla and Firefly luciferase activities were measured using the Dual-Luciferase Reporter assay system (Promega). Firefly activity was normalized to Renilla activity to control the transfection efficiency.

Statistical analysis

All data were expressed as mean ± SD. The differences between groups were analyzed using the Student's t-test. Statistical difference at p-values <0.05 and significantly statistical difference at p-values <0.01. The statistical software SPSS 16.0 (IBM, Armonk, NY, USA) was used for analysis of Student's t-test.

Results

BLBC identification, miR microarray and GO analysis

Eighteen cases were identified as BLBC (ER, PR and Her-2 negative; CK5/6, CK14, p63, EGFR and p53 positive; Ki-67 high proliferation index; Her-2 no-amplification) (Fig. 1A).

Using the miR microarray, it first evaluated the miR expression profiles in BLBC (n=3) and NC (n=3). The expression profiles of 265 miRs were determined to differ between BLBC and NC which were sufficient to separate samples into biologically interpretable groups. Thus, 11 miRs were identified as upregulated (>2-fold) and 18 miRs were identified as downregulated (<0.5-fold) between BLBC and NC (Fig. 1B and Table I).

Table I

The miR microarray identified between BLBC and NC.

Table I

The miR microarray identified between BLBC and NC.

miRNAGenomic locationNormal control meanBasal-like breast carcinoma meanFold- changeP-valueFunction
Upregulated microRNAs
hsa-miR-19a chr13:92003145–92003226 [+]0.6216.42710.3490.001
hsa-miR-19b chr13:92003446–92003532 [+]1.2014.1733.4750.002
hsa-miR-32* chr9:110848330–110848399 (−)0.7283.6895.0670.007
hsa-miR-106a chrX:133131894–133131974 (−)0.8862.8123.1744.99E-05
hsa-miR-106b chr7:99529552–99529633 (−)1.72112.3677.1860.009Negative regulation of nucleobase, nucleoside, nucleotide and nucleic acid metabolic process
hsa-miR-141 chr12:6943521–6943615 (+)2.69033.96812.6280.006Negative regulation of nucleobase, nucleoside, nucleotide and nucleic acid metabolic process
hsa-miR-200c chr12:6943123–6943190 (+)3.21828.9358.9922.52E-06Negative regulation of nucleobase, nucleoside, nucleotide and nucleic acid metabolic process
hsa-miR-300 chr14:100577453–100577535 (+)0.9902.6092.6350.002
hsa-miR-378 chr5:149092581–149092646 (+)0.8615.8126.7508.33E-06
hsa-miR-550 chr7:30295935–30296031 (+)1.99315.5197.7870.004
hsa-miR-1280 chr3:128081008–128081101 [+]0.7843.5054.4713.98E-05
Downregulated microRNAs
hsa-miR-16 chr13:49521110–49521198 (−)5.7411.4360.2506.92E-06
hsa-miR-21 chr17:55273409–55273480 (+)44.75011.6100.2594.08E-05
hsa-miR-26a chr3:37985899–37985975 (+)8.9992.0590.2293.29E-07
hsa-miR-26b chr2:218975613–218975689 (+)14.6302.8720.1965.05E-07
hsa-miR-125b chr11:121475675–121475762 (−)19.0294.6170.2431.03E-08
hsa-miR-129-5p chr7:127635161–127635232 (+)6.6901.3560.2038.08E-07Positive regulation of nucleobase, nucleoside, nucleotide and nucleic acid metabolic process
hsa-miR-149* chr2:241044091–241044179 (+)10.6632.8090.2633.92E-08
hsa-miR-183* chr7:129201981–129202090 (−)4.8621.3910.2860.001
hsa-miR-205 chr1:207672101–207672210 (+)15.5812.4920.1592.05E-07Positive regulation of nucleobase, nucleoside, nucleotide and nucleic acid metabolic process
hsa-miR-451 chr17:24212513–24212584 (−)20.5321.3100.0640.001Positive regulation of nucleobase, nucleoside, nucleotide and nucleic acid metabolic process
hsa-miR-516a-5p chr19:58951807–58951896 (+)6.4001.4390.2259.62E-06
hsa-miR-557 chr1:166611386–166611483 (+)5.7420.8030.1392.33E-06
hsa-miR-583 chr5:95440598–95440672 (+)12.4644.2600.3423.52E-06
hsa-miR-638 chr19:10690080–10690179 (+)3.5040.8430.2411.53E-05
hsa-miR-665 chr14:100411123–100411194 (+)31.18011.0140.3530.001
hsa-miR-675 chr11:1974565–1974637 (−)21.1071.9050.090.001
hsa-miR-765 chr1:155172547–155172660 (−)18.6034.2820.2306.04E-05
hsa-miR-1275 chr6:33967749–33967828 [−]18.7123.8990.2080.001

GOs analysis displayed up/downregulation of miRs which were significantly involved in the positive/negative regulation of nucleobase, nucleoside, nucleotide and nucleic acid metabolic processes (Tables II and III). miRs were found to interact with the genes relating to those processes, suggesting miRs play an important role in the pathogenesis of BLBC. The miR-mRNA regulatory networks based on positive/negative regulation of nucleobase, nucleoside, nucleotide, and nucleic acid metabolic processes were established (Fig. 1C and D and Tables IV and V), and the assumed targeted mRNAs of up/downregulation miRs were identified. Three upregulation miRs (miR-141/106b/200c) displayed the most targeted mRNAs of three (degree 3). Two downregulation miRs (miR-205/129-5p) showed the most targeted mRNAs of two (degree 2). All three upregulation miRs (miR-141/106b/200c) targeted KLF12 and only one downregulation miR (miR-205) targeted KLF12. So, KLF12 had the highest degree of four (degree 4) in the up/downregulation miR-mRNA regulatory network. GO analysis suggested KLF12 may be targeted by miR-205/141/106b/200c and showed potentially the most important genes affecting positive/negative regulation of nucleobase-, nucleoside-, nucleotide- and nucleic-acid-metabolic-related processes.

Table II

GO analysis significant terms based on upregulated miRs.

Table II

GO analysis significant terms based on upregulated miRs.

CategoryTermCount in selected genesCount in total populationP-value
GORegulation of transcription from RNA polymerase II promoter823791.49E-07
GOPositive regulation of transcription from RNA polymerase II promoter341212.15E-06
GOTranscription factor activity1277157.79E-06
GOPositive regulation of transcription, DNA-dependent451962.07E-05
GOPositive regulation of RNA metabolic process451972.37E-05
GORegulation of gene expression25716682.73E-05
GOTranscription regulator activity16410034.85E-05
GORegulation of transcription24015790.000133
GOPositive regulation of transcription482340.000221
GORegulation of macromolecule biosynthetic process25316890.000222
GORegulation of nucleobase, nucleoside, nucleotide and nucleic acid metabolic process24516300.00023
GORegulation of cellular biosynthetic process25517050.000231
GORegulation of biosynthetic process25517060.00024
GOPositive regulation of gene expression482350.000245
GORegulation of RNA metabolic process22815090.000289
GOPositive regulation of nucleobase, nucleoside, nucleotide and nucleic acid metabolic process492430.000292
GORegulation of transcription, DNA-dependent22514950.000402
GORegulation of macromolecule metabolic process26718310.000827
GORegulation of cellular metabolic process26718340.000914
GOPositive regulation of progression through cell cycle450.001029
GOTranscriptional repressor activity19730.001033
GORhythmic process14470.001134
GONegative regulation of transcription, DNA-dependent351690.00125
GOPositive regulation of macromolecule biosynthetic process502660.001342
GORegulation of metabolic process27018690.001361
GONegative regulation of RNA metabolic process351700.001392
GOActin cytoskeleton21870.00164
GONegative regulation of transcription452360.001697
GOSuckling behavior330.001859
GONegative regulation of gene expression452380.002019
GOPositive regulation of cellular biosynthetic process502730.00237
GOPositive regulation of biosynthetic process502750.002768
GOHistone acetyltransferase binding460.002786
GOProtein serine/threonine kinase activity593390.003442
GOPhosphate metabolic process1036510.003751
GOPhosphorus metabolic process1036510.003751
GOPhosphoprotein phosphatase activity251170.003804
GOProtein amino acid dephosphorylation231050.003889
GOCentrosome13480.004262
GOProtein serine/threonine phosphatase complex9280.004889
GONegative regulation of nucleobase, nucleoside, nucleotide and nucleic acid metabolic process462570.0054
GOPost-translational protein modification1238060.005639
GOProtein kinase cascade261280.006487
GOSynapse organization and biogenesis340.006751
GOSkeletal muscle development340.006751
GOVascular endothelial growth factor receptor activity5110.006817
GOGolgi stack5110.006817
GOMAP kinase kinase kinase activity5110.006817
GONegative regulation of cellular biosynthetic process482750.00739
GONegative regulation of transcription from RNA polymerase II promoter241170.007676
GOSystem development603590.007845
GONegative regulation of biosynthetic process482760.00791
GOProtein serine/threonine phosphatase activity8250.008086
GOProtein kinase activity734520.008364
GOActin cytoskeleton organization and biogenesis17750.008522
GO Dephosphorylation241180.008544
GOSmall conjugating protein ligase activity231120.008812
GOPositive regulation of myeloid cell differentiation6160.009191
GORegulation of myeloid cell differentiation10360.009608

Table III

GO analysis significant terms based on downregulated miRs.

Table III

GO analysis significant terms based on downregulated miRs.

CategoryTermCount in selected genesCount in total populationP-value
GOPositive regulation of nucleobase, nucleoside, nucleotide and nucleic acid metabolic process232430.000412
GOPositive regulation of myeloid cell differentiation5160.000459
GOTranscription factor activity497150.001111
GOTranscriptional repressor activity10730.001221
GORegulation of translation9610.001244
GOPositive regulation of transcription212340.001431
GOPositive regulation of gene expression212350.001509
GOUBC13-MMS2 complex220.00191
GOmRNA binding6320.002334
GOPositive regulation of transcription, DNA-dependent181960.002374
GOTranscriptional activator activity11930.002388
GOPositive regulation of RNA metabolic process181970.00251
GOPositive regulation of macromolecule biosynthetic process222660.003118
GO Post-transcriptional regulation of gene expression10830.003241
GOChromatin modification141410.003473
GOPositive regulation of cellular biosynthetic process222730.004261
GORegulation of myeloid cell differentiation6360.004328
GOPositive regulation of biosynthetic process222750.004646
GONatural killer cell differentiation230.005564
GOUbiquitin conjugating enzyme complex230.005564
GOPositive regulation of macromolecule metabolic process233050.007789
GOPositive regulation of cellular metabolic process233100.009385
GORegulation of gene expression921,6680.009564

Table IV

Datasets of up-go miRs and its targets for interactive viewing of the network using Pajek desktop software.

Table IV

Datasets of up-go miRs and its targets for interactive viewing of the network using Pajek desktop software.

Vertices*49
1miR-106b
2miR-141
3miR-200c
4ZNF238
5NCOA2
6MXD4
7KHDRBS1
8FOXN3
9KLF12
10CTNNB1
11DR1
12E2F1
13EDNRA
14ELK3
15EREG
16BPTF
17ZHX2
18HIC2
19SIRT5
20ZFPM2
21PDCD4
22ID2
23JARID2
24MECP2
25NAB1
26ZBTB7A
27POU4F2
28BCOR
29RB1
30ARID4A
31BCL6
32PRDM1
33SMURF2
34BMI1
35STAT3
36TBX3
37ZEB1
38THRA
39KLF10
40TRPS1
41TSG101
42ZNF148
43NRIP1
44KLF11
45BHLHE40
46DEDD
47KLF4
48HDAC4
49ZEB2

Edges*

14
18
19
112
114
115
117
120
123
124
126
129
130
131
135
136
138
140
141
142
144
146
148
24
28
29
210
211
218
219
221
227
228
245
248
249
35
36
37
39
313
316
318
320
322
325
332
333
334
337
339
340
343
347
348
349

Table V

Datasets of down-go miRs and its targets for interactive viewing of the network using Pajek desktop software.

Table V

Datasets of down-go miRs and its targets for interactive viewing of the network using Pajek desktop software.

Vertices*26
1miR-129-5p
2miR-205
3miR-451
4KLF12
5CREBBP
6DDX5
7DLX2
8ELF1
9EP300
10EREG
11ESRRG
12BPTF
13ILF3
14INHBA
15SMAD1
16NR4A2
17PLAGL2
18MED1
19RNF4
20SP1
21SRF
22STAT5B
23UBE2N
24YWHAH
25ARID1A
26RUNX1T1

Edges*

15
17
19
111
112
113
116
120
121
122
124
126
24
26
28
210
211
212
214
215
217
218
219
223
225
miR-205 directly targeted KLF12 through binding its 3′-UTR

To determine whether KLF12 was directly targeted by miR-205/141/106b (miR-200c context score percentile was too low and was discard), the wild-type 3′-UTR of KLF12 and mutant were constructed and inserted into the luciferase reporter plasmid. The wild-type or mutant vectors were co-transfected with miR-205/141/106b mimics or negative control miRs in MDA-MB-468 cells. Co-transfection of the reporter plasmid along with miR-205 resulted in significantly reducing KLF12-WT-3′-UTR-luciferase expression than its NC miR + KLF12-WT (p=0.0016) or miR-205 + KLF12-Mut (p=0.0011) (Fig. 2A and B) groups; however, no KLF12-Mut-3′-UTR-luciferase expression variation was observed compared to its NC miR + KLF12-Mut (Fig. 2A and B). Co-transfection of the reporter plasmid along with miR-141/106b did not result in the reduction of KLF12-WT/Mut-3′-UTR-luciferase expression compared to its NC miR + KLF12-WT/Mut (Fig. 2–F). This supported miR-205 was likely to target KLF12 directly.

miR-205 downregulates in BLBC cells/tissues and negatively modulates KLF12

Based on the microarray and bioinformation and luciferase assay, qRT-PCR and western blot analysis were used to relatively quantify expression levels of miR-205 and KLF-12. miR-205 had low expression in MDA-MB-468 cells, significantly lower than in MCF10A cells (p=0.007) (Fig. 3A); knock-up of miR-205 by transfection with miR-205 mimics in MDA-MB-468 cells, its expression levels substantially increased, and was significantly higher than in mimics of NC in cell lines (p=0.0021) (Fig. 3A); knockdown of miR-205 by transfection with miR-205 inhibitor in MDA-MB-468 cells, its expression levels substantially reduced, and was lower than in inhibitor NC in cell lines (p=0.034) (Fig. 3A). In BLBC tumor tissues, miR-205 had significantly lower expression levels than in the NC (n=9; p=0.0074) (Fig. 3B). KLF12 had high expression in MDA-MB-468 cells, significantly higher than it in MCF10A cells (p=0.0026) (Fig. 3C); knock-up of miR-205 by transfection with miR-205 mimics in MDA-MB-468 cells, its expression levels substantially reduced, and was significantly lower than in mimics of NC in cell lines (p=0.0038) (Fig. 3C); knockdown of miR-205 by transfection with miR-205 inhibitor in MDA-MB-468 cells, its expression levels substantially increased, and was higher than in inhibitor NC in cell lines (p=0.043) (Fig. 3C). KLF12 protein showed high expression levels in MDA-MB-468 cells, significantly higher than in MCF10A cells (p=0.0079) (Fig. 3D); knock-up of miR-205 by transfection with miR-205 mimics in MDA-MB-468 cells, its expression level substantially reduced, and was significantly lower than in the mimics of NC in cell lines (p=0.009) (Fig. 3D); knockdown of miR-205 by transfection with miR-205 inhibitor in MDA-MB-468 cells, its expression levels substantially increased, and was higher than in inhibitor NC in cell lines (p=0.035) (Fig. 3D). In BLBC tumor tissues, KLF12 protein was higher expressed than in NC (n=9; p=0.0083) (Fig. 3E). IHC results displayed positive rates of KLF12 at 88.9% (16/18) in BLBC and 0% in normal breast non-cancerous tissues, and its expression pattern was nuclear positive in the normal ductal inner epithelium and outer myoepithelial cells (Fig. 3F) but diffuse nuclear positive in BLBC tumor cells (Fig. 3G). It indicated downregulation of miR-205 was specific to BLBC, and negatively regulated KLF12 expression by directly targeted its 3′-UTR.

miR-205 is not involved in cellular proliferation

Knock-up/down of miR-205 by transfection with miR-205 mimics/inhibitor with sufficient concentrations to increase/decrease miR-205 expression levels, respectively, had no significant impact on the optical densities of CCK-8 assays (Fig. 4A).

miR-205 involved in cellular invasion and apoptosis

The Transwell Matrigel invasion assay was performed to evaluate the impact of miR-205 on invasive ability of MDA-MB-468 cells. Knock-up of miR-205 by transfection with miR-205 mimics significantly inhibited the transmembrane ability when compared with miR-205 mimics NC (p=0.00175) (Fig. 4B) in vitro. Knockdown of miR-205 by transfection with miR-205 inhibitor promoted the transmembrane ability when compared with miR-205 inhibitor NC (p=0.033) (Fig. 4B) in vitro. It supported dysregulation of miR-205 was involved in BLBC cell invasion.

The flow cytometric analyses of propidium iodide-stained cells were performed to detect BLBC cell apoptosis rates. The apoptosis rates were significantly different between MDA-MB-468 and MCF-10A cells (p=0.0075) (Fig. 4C) in vitro. Knock-up of miR-205 by transfection with miR-205 mimics significantly increased apoptosis rates when compared with miR-205 mimics of NC (p=0.006) (Fig. 4C) in vitro. Knockdown of miR-205 by transfection with miR-205 inhibitor inhibited the apoptosis rates when compared with miR-205 inhibitor of NC (p=0.041) (Fig. 4C) in vitro. It indicated dysregulation of miR-205 impaired the BLBC cell apoptosis.

Discussion

BLBC is more common in younger patient and related to high histological grade, aggressive clinical course, distant metastasis, poor prognosis, and relatively high mortality rate (41). Owning to its triple-negative phenotype, patients with BLBC are not likely to benefit from endocrine therapies or trastuzumab, but are likely to benefit from systemic chemotherapy (41). Genetic, morphological and IHC features of BLBC were reported, however, there was no universal definition and specific biomarker which could identify those tumors in routine diagnostics (41). Previously studies revealed miR dysregulation and dysfunction in breast cancer (1012), and miR-205 was significantly under-expressed in breast tumors compared with matched normal breast tissue (42). In breast cancer cell lines, including MCF-7 and MDA-MB-231, miR-205 expressed lower levels than non-malignant MCF-10A cells (42). Only a few studies which associated with triple- negative breast cancer revealed that miR-205 was directly transactivated by oncosuppressor p53 (43). In our studies, miR-205 was significantly downregulated in BLBC tumor tissues and MDA-MB-468 cell lines.

Each miR is capable of regulating hundreds of protein-coding genes. Previous studies revealed that most miR-205 target genes were Her-2/3 and ZEB1/2/3 in breast cancer (42,44). Some others studies also identified that miR-205 directly targeted phosphatase and tensin homolog deleted on chromosome ten and interleukin-24 in A549 cells and human KB oral cancer cells (45). miR-205 in cancer is an angel or a devil depending on the specific tumor context and target genes (19). KLF12 played an important role in poorly differentiated gastric cancer progression and negatively regulated human endometrial stromal cell decidualization (22,23). miR-181a played a functionally important role in human endometrial stromal cell decidualization in vitro by inhibiting KLF12 (46). Ectopic expression of miR-205 significantly inhibits proliferation, growth and invasion as well as impairs apoptosis. These findings established the tumor suppressive role of miR-205, which was probably through directly targeting oncogenes such as Her-2/3 and ZEB1/2/3 (42,44). In our studies, miR-205 directly targeted KLF12 3′-UTR in luciferase assays, KLF12 was negatively regulated by miR-205 in expression analysis, overexpression of miR-205 significantly inhibited invasion and promoted apoptosis in functional investigation. Our finds suggested miR-205/KLF12 functioned as tumor suppressor gene/proto-oncogene in BLBC, respectively.

The mechanism of miR-205-KLF12, apoptosis is an interesting question. From the literature reviews, we found that activating protein-2 (AP-2) factors executed important functions during embryonic development and malignant transformation (21). AP-2α and AP-2γ overexpression in breast cancer cells direct transcriptional activated Her-2 (47) and correlated with regulation of multiple growth factor signaling pathways (21). Specifically, interaction of AP-2 with the c-Myc-Max heterodimer negatively regulated c-Myc target genes and c-Myc-induced apoptotic cell death, it proposed AP-2 genes were involved in programming cell survival (48,49). The adenoviral oncoprotein E1A activated expression of the endogenous AP-2α gene. Furthermore, activation of AP-2α transcription was dependent on the presence of a functional E1A-CtBP1 interaction motif and involves inactivation of the transcriptional silencer AP-2rep (KLF12) by directly interaction with the corepressor CtBP1 (21). Combined with previous studies and our experiments, we speculated that down-regulation of miR-205 negatively regulated KLF12 overexpression, was involved in activation of the transcriptional silencer AP-2rep (KLF12) by direct interaction with the corepressor CtBP1 and inactivation of E1A-CtBP1 interaction motif, led to inactivation of AP-2α transcription, negatively regulating c-Myc-induced apoptotic cell death and repressing transcriptional activation of Her-2 in BLBC. So, we thought miR-205-KLF12-AP-2α axis played an important role in negatively regulated c-Myc-induced apoptotic cell death and repressed transcriptional activation of Her-2 in BLBC. However, further experimental studies are required, and the mechanism of miR-205-KLF12-invasion remains unclear.

In previously studies, the mainly used public miRs target prediction databases facilitate gene-by-gene searches PicTar, TargetScan and miRanda algorithms (3437). However, its disadvantage was too many target genes to be predicted and many of them were false positive. On the other hand, integration of miR-mRNA target predictions with gene expression data on a large scale using these databases currently is cumbersome and time-consuming for researchers. So, we employed the bioinformatics tool including GOs analysis (2830) and SigTerms (38) in this study. An analysis of significant differences in GOs, which was based on the reported and predicted target genes of these miRs, was developed to highlight whether particular functions were enriched in BLBC. GO organized genes targeted by differential miRs into hierarchical categories based on biological process and then outlined the effects of miRs on BLBC through significantly differences of GOs (31,38). SigTerms for a given target prediction database, retrieves all miR-mRNA functional pairs represented by an experimentally derived set of genes. Furthermore, for each miR, the software computed an enrichment statistic for over-representation of predicted targets within the gene set, which could help to implicate roles for specific miRs and miR-regulated genes in the system under study. Currently, the software supported searching of results from PicTar, TargetScan and miRanda algorithms. Gunaratne et al (ref.?) discussed the latest methodologies for determining genome-wide miRs and gene expression changes and considered three programs (SigTerms, CORNA and MMIA) to be essential for determining the false positive and negative rates of existing algorithms and refining our knowledge on the rules of miR-mRNA relationships. The advantage of GOs and SigTerms was the accuracy in miR target prediction, but specific training for researchers was needed.

The expression pattern of KLF12 was less known in tumor tissues. In our studies, KLF12 was diffusely nuclear positive in BLBC tumor tissues, but nuclear positive in the normal ductal inner epithelium and outer myoepithelial cells, respectively. Basal markers (CK14, CK5/6 and EGFR) and myoepithelial markers (smooth muscle actin and p63) were positive in myoepithelial cells, and epithelial markers (epithelial membrane antigen, cytokeratin Cam5.2) were positive in luminal epithelial. So, the double staining characteristics of KLF12 were helpful for the differential diagnosis between benign lesion and invasive ductal carcinoma. It also suggested that KLF12 may function as molecular biomarker for BLBC combination with other biomarkers, but this requires further studies in clinical specimens.

In conclusion, miR-205 is miR-specific in BLBC functioning as tumor suppressor gene through directly targeted and negatively regulated proto-oncogene KLF12. miR-205 dysregulation was involved in invasion and apoptosis in MDA-MB-468 cells in vitro. miR-205 and KLF12 provide potential diagnostic biomarkers and therapeutic approach for BLBC.

Acknowledgements

The study reported in this publication was funded by grants from the Medical Guide Program of Science and Technology of Shanghai Municipal Science and Technology Commission, Shanghai, China (134119b2800) and the General Program of Shanghai Jinshan District Health and Family Planning Commission, Shanghai, China (JSKJ-KTMS-2014-14).

Abbreviations:

BLBC

basal-like breast carcinoma

miR

microRNA

qRT-PCR

quantitative reverse transcription-polymerase chain reaction

IHC

immunohistochemistry

NC

normal control

GO

gene ontology

KLF12

Krüppel-like factor 12

UTR

untranslated region

AP-2

activating protein-2

Her-2

human epidermalgrowth factor receptor-2

ZEB

zinc finger E-box binding homeobox

CtBP1

C-terminal-binding protein 1

H&E

hematoxylin and eosin

FBS

fetal bovine serum

FISH

fluorescence in situ hybridization

ER

estrogen receptor

PR

progesterone receptor

CK

cytokeratin

EGFR

epidermal growth factor receptor

FDR

false discovery rate

GAPDH

glyceraldehyde 3-phosphate dehydrogenase

CCK-8

cell counting kit-8 assay

FITC

fluorescein isothiocyanate

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Guan B, Li Q, Shen L, Rao Q, Wang Y, Zhu Y, Zhou X and Li X: MicroRNA-205 directly targets Krüppel-like factor 12 and is involved in invasion and apoptosis in basal-like breast carcinoma. Int J Oncol 49: 720-734, 2016
APA
Guan, B., Li, Q., Shen, L., Rao, Q., Wang, Y., Zhu, Y. ... Li, X. (2016). MicroRNA-205 directly targets Krüppel-like factor 12 and is involved in invasion and apoptosis in basal-like breast carcinoma. International Journal of Oncology, 49, 720-734. https://doi.org/10.3892/ijo.2016.3573
MLA
Guan, B., Li, Q., Shen, L., Rao, Q., Wang, Y., Zhu, Y., Zhou, X., Li, X."MicroRNA-205 directly targets Krüppel-like factor 12 and is involved in invasion and apoptosis in basal-like breast carcinoma". International Journal of Oncology 49.2 (2016): 720-734.
Chicago
Guan, B., Li, Q., Shen, L., Rao, Q., Wang, Y., Zhu, Y., Zhou, X., Li, X."MicroRNA-205 directly targets Krüppel-like factor 12 and is involved in invasion and apoptosis in basal-like breast carcinoma". International Journal of Oncology 49, no. 2 (2016): 720-734. https://doi.org/10.3892/ijo.2016.3573