The Mirna-200 Family and Mirna-9 Exhibit Differential Expression in Primary Versus
Gravgaard et al.
The miRNA-200 family and miRNA-9 exhibit differential expression in primary versus corresponding metastatic tissue in breast cancer.
Karina H. Gravgaard1, Maria B. Lyng1, Anne-Vibeke Laenkholm2, Rolf Søkilde3, Boye Schnack Nielsen3#, Thomas Litman3, Henrik J Ditzel1,4.
1 Department of Cancer and Inflammation Research, Institute of Molecular Medicine, University of Southern Denmark, Odense, Denmark; 2Department of Pathology, Hospital South, Slagelse, Denmark; 3Department of Biomarker Discovery, Exiqon A/S, Vedbaek, Denmark; and 4Department of Oncology, Odense University Hospital, Odense, Denmark.
#Present address: Bioneer A/S, Horsholm, Denmark
Corresponding author: Henrik Ditzel, Department of Cancer and Inflammation Research, J.B. Winsloewsvej 25, 5000 Odense C, Denmark. Phone: +45-6550 3781. Fax: +45-6550 3922, Email: .
Supplementary Materials and methods
Patients and tissues
The pathology database FPAS (Funen Patient Administrative System) at Odense University Hospital was used to identify breast cancer patients from whom both the primary and metastatic tumors in either the brain or liver were available as formalin-fixed, paraffin-embedded (FFPE) tissue blocks in the tissue bank. When lymph node metastases were available, these tissues were also retrieved from the tissue bank and analyzed. When lymph node metastases were available, these tissues were also retrieved from the tissue bank and analyzed. The pathology records for all the extracted patients (n=299) were reviewed to confine the study group to those with metastasis originating from breast cancer. A total of 19 patients were applicable, but five were subsequently excluded due to the lack of available tumor tissue (patients 1, 2, 8, 9 and 19) and a skin metastasis rather than a liver metastasis case was included for patient 17. For patient characteristics, see Table 1. The following search criteria were used: 1) For brain metastasis, the period 01.01.96-31.12.06 was searched for women having metastases located in cerebrum, cerebellum, occipital lobe or parietal lobe originating from an adenocarcinoma. 2) For liver metastasis, the period 01.01.03-30.09.07 was searched for women having metastases located in the liver originating from an adenocarcinoma. The 14 selected breast cancer patients were all treated surgically for their distant metastasis at Odense University Hospital, while five (patients 10,12,13,15 and 18) had undergone primary breast cancer surgery at other hospitals. It should be noted that patient 6 had bilateral breast cancer and it is not known from which of the two breast cancers the brain metastasis had arisen, therefore both breast tumors were included. However, in the unsupervised hierarchical clustering analysis, these primary breast cancer tissues were very similar, and it was therefore decided to combine the data for the two samples for the subsequent comparison to the metastasis. The fact that the two samples were very similar suggests that the pooled sample would not create a significant bias.
Global miRNA Array Analysis
Total RNA was isolated from 5x10 µm FFPE tissue using the High Pure miRNA Isolation kit (Roche Applied Science, Indianapolis, IN) according to the manufacturer’s instructions and used for miRNA expression profiling using the miRCURY LNA microRNA Arrays version 11.0 Extended Version (Exiqon, Vedbæk, DK). This array contains 3364 target probes and covers all human, mouse and rat miRNA sequences annotated in miRBase 11.0 [1, 2], as well as all viral miRNAs related to these species. The array also contains 428 novel human miRNA sequences (hsa-miRPlus) not yet annotated in miRBase. All RNA samples were labeled with Hy3™ and compared on the array to a Hy5™-labeled common reference sample (Exiqon). Approximately 1 µg Hy5™- and 1 µg Hy3™-labelled total RNA was co-hybridised on the array for 16 hours at 56⁰C in a Tecan HS 4800 Pro hybridisation station (Tecan, Männedorf, Switzerland). The array was washed and then dried according to the protocol before scanning [3]. The arrays were scanned in an Agilent G2565BA Microarray Scanner System (Agilent Technologies, Santa Clara, CA, USA) and the images were quantified using Imagene v. 8.0 (BioDiscovery, CA). The log2 transformed intensities were normalized as single channel data using quantile normalization in the statistical programming language R with the Bioconductor [4] software package LIMMA (Linear Models for Microarray Data) [5]. Poor quality spots were removed and spots were background-corrected using the Normexp method (with an offset of 50) in R with the Bioconductor [4] software package LIMMA [6].
Statistical analysis
miRNA microarray results were analyzed using an ANOVA statistical test as implemented in the Rosetta Resolver Software. Following the ANOVA, a post hoc analysis was used to identify significant differences between tumor sites and between patients (p<0.1). Differences between primary tumors and metastases were analyzed using a Wilcoxon paired sample test with Benjamini-Hochberg False Discovery Rate (BH-FDR) correction (p<0.01). The real time PCR results were analyzed using Student’s t-test (p<0.05).
Real-time PCR
Verification of miRNAs exhibiting altered expression in the miRNA array analysis was conducted using the miRCURY LNA™ PCR system (Exiqon, Vedbæk, Denmark) according to the manufacturer’s instructions on an Applied Biosystems 7500 Real-Time PCR System (Applied Biosystems, Foster City, CA, USA). Triplicate cDNA syntheses were performed for all real time reactions and included no-template controls and no-reverse transcription controls. The threshold for fluorescence was manually set in the exponential phase. The inclusion criteria of Ct values were as follows: The Ct value between replicates should be below 0.5 with amplification of at least two replicates. Furthermore, the quality of the PCR run was analyzed by examination of the amplification plot and the melting temperature curve. The difference in Ct (∆Ct) of matched primary tumors and metastases were analyzed.
Immunohistochemistry:
Tissue sections (3 µm) were cut from FFPE blocks and mounted on SuperFrost+ slides, deparaffinized and hydrated. Endogenous peroxidase activity was blocked with 1.5% hydrogen peroxide in TBS buffer, pH 7.4, for 10 minutes. Antigen retrieval for ZEB1 staining was obtained through heat-induced epitope retrieval by microwave boiling for 15 min in TE (Tris/EDTA) buffer (Dako, S2367). The slides were then incubated with polyclonal rabbit anti-ZEB1 antibody (Sigma-Aldrich, #HPA027524 diluted 1:250 in antibody diluent S2022, Dako) for 1 hour at room temperature. The slides were subsequently washed with EnVisionTM FLEX Wash buffer (K8007) and immunostained using the Dako EnVision+ HRP detection system (K4003, Dako) on a DakoAutostainer. Antigen retrieval of the slides for E-cad staining was performed by incubating slides in T-EG buffer (10 mM Tris, 0.5 mM EGTA, pH 9.0) overnight at 60⁰C. The slides were incubated with mouse monoclonal anti-E-cadherin (HECD-1, ab1416, Abcam diluted 1:50 in EnVisionTM FLEX Antibody Diluent, K8006, Dako) for 1 hour at room temperature, washed with EnVisionTM FLEX Wash buffer (K8007) and immunostained with the EnVisionTM FLEX/HRP detection system (SM802, Dako) on a Dako AutoStainerPlusLink. 3,3-Diaminobenzidine was used as the substrate chromogen system (K3467, Dako) for both ZEB1 and E-cad stained slides. Nuclear counterstaining was performed in Mayer’s hematoxylin (ZEB1) or EnVisionTM FLEX Hematoxylin (K8008) (E-Cad) and coverslips were mounted with AquaTex. Sections were analyzed blinded by a trained pathologist on an Olympus BX51 BF (bright field) microscope (Olympus Denmark, Ballerup, Denmark) and images were obtained with a Leica DMLB microscope equipped with a Leica DFC300 FX camera (Leica, Herlev, Denmark).
In situ hybridization
In situ hybridization was performed on FFPE tissue of primary tumors and metastases as described by Nielsen et al [7]. Expression of miR-200b and miR-9 was detected with double-digoxigenin (double-DIG)-labeled miRCURY LNATM microRNA detection probes (Exiqon, Vedbæk, Denmark). In brief, six µm-thick FFPE sections were deparaffinated and placed in a Tecan Freedom Evo automated hybridization instrument (Tecan, Männedorf, Switzerland). The sections were treated with Proteinase K, followed by pre-hybridization and hybridization using the miR-9 or miR-200b probes at 40-80 nM digoxigenin-labeled LNA probe. Following stringent washing and blocking for unspecific binding, bound probes were detected using alkaline phosphatase- (AP) conjugated anti-DIG (#11 093 274 910, Roche) and visualized using 4-nitro-blue tetrazolium (NBT) and 5-bromo-4-chloro-3-indolyl phosphate (BCIP) substrate (Roche), forming a dark blue precipitate. Slides were counterstained with Nuclear Fast Red (Vector Laboratories, Burlingame, CA) and mounted with Eukitt mounting medium (VWR, Herlev, Denmark). The experiments also included a negative control (double-DIG-labeled scrambled miRNA) and a positive control probe (double-DIG-labeled miR-126, endothelial). Tissue samples from morphological normal colon and cerebellum were used as positive control tissue for miR-200b and miR-9, respectively. Sections were analyzed blinded by a trained pathologist using an Olympus BX51 BF microscope and images were obtained on a Leica DM 6000B microscope (Leica) equipped with an Olympus DP72 CCD camera (Olympus).
Color image segmentation was performed to enhance the contrast between the in situ hybridization signal and the tissue structures using Visiopharm's integrated microscope and software module (Visiopharm, Hørsholm, Denmark). A supervised Bayesian pixel classifier was obtained for color segmentation using the Visiomorph software tool, considering the following colors: blue stain (in situ hybridization signal), red stain (nuclear red counterstain), purple stain (in situ hybridization signal located over nuclear red stain) and unstained connective tissue and other background structures. No post-processing was added. In situ hybridization signal was translated into white, nuclear red stain into red, and background structures into black pixels in the classified image. Individual pixel classifiers were applied for each of the three panels in Fig. 3 a, b and c.
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