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Cancer Epidemiology, Biomarkers & Prevention
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Research Articles

Downregulation of microRNAs 145-3p and 145-5p Is a Long-term Predictor of Postmenopausal Breast Cancer Risk: The ORDET Prospective Study

Paola Muti, Andrea Sacconi, Ahmed Hossain, Sara Donzelli, Noa Bossel Ben Moshe, Federica Ganci, Sabina Sieri, Vittorio Krogh, Franco Berrino, Francesca Biagioni, Sabrina Strano, Joseph Beyene, Yosef Yarden and Giovanni Blandino
Paola Muti
1Department of Oncology, Faculty of Health Science, McMaster University, Hamilton, Ontario, Canada.
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  • For correspondence: muti@mcmaster.ca
Andrea Sacconi
2Translational Oncogenomics Unit, Regina Elena Italian National Cancer Institute, Rome, Italy.
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Ahmed Hossain
3The Statistics for Integrative Genomics and Methods Advancement Laboratory, Population Genomics Program, Department of Clinical Epidemiology and Biostatistics, Faculty of Health Sciences, McMaster University, Hamilton, Ontario, Canada.
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Sara Donzelli
2Translational Oncogenomics Unit, Regina Elena Italian National Cancer Institute, Rome, Italy.
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Noa Bossel Ben Moshe
4Department of Physics of Complex Systems, Weizmann Institute of Science, Rehovot, Israel.
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Federica Ganci
2Translational Oncogenomics Unit, Regina Elena Italian National Cancer Institute, Rome, Italy.
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Sabina Sieri
5Department of Preventive and Predictive Medicine, Fondazione Istituto Nazionale Tumori, Milano, Italy.
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Vittorio Krogh
5Department of Preventive and Predictive Medicine, Fondazione Istituto Nazionale Tumori, Milano, Italy.
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Franco Berrino
5Department of Preventive and Predictive Medicine, Fondazione Istituto Nazionale Tumori, Milano, Italy.
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Francesca Biagioni
2Translational Oncogenomics Unit, Regina Elena Italian National Cancer Institute, Rome, Italy.
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Sabrina Strano
1Department of Oncology, Faculty of Health Science, McMaster University, Hamilton, Ontario, Canada.
6Molecular Chemoprevention Group, Molecular Medicine Area, Regina Elena Italian National Cancer Institute, Rome, Italy.
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Joseph Beyene
3The Statistics for Integrative Genomics and Methods Advancement Laboratory, Population Genomics Program, Department of Clinical Epidemiology and Biostatistics, Faculty of Health Sciences, McMaster University, Hamilton, Ontario, Canada.
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Yosef Yarden
7Department of Biological Regulation, Weizmann Institute of Science, Rehovot, Israel.
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Giovanni Blandino
1Department of Oncology, Faculty of Health Science, McMaster University, Hamilton, Ontario, Canada.
2Translational Oncogenomics Unit, Regina Elena Italian National Cancer Institute, Rome, Italy.
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DOI: 10.1158/1055-9965.EPI-14-0398 Published November 2014
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  • Figure 1.
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    Figure 1.

    Heatmap of top-ranked 20 miRNAs from postmenopausal samples. The heatmap provided insight into the data structure for each miRNA and sample. We used red and green colors for defining low and high expression values. Blue, cases; yellow, controls. The clustering methods partitioned the dataset into three clusters, identified on the left of the figure. Each miRNA is listed on the right.

  • Figure 2.
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    Figure 2.

    Breast cancer disease-specific survival by miRNA expression. Kaplan–Meier analysis for the association between (A) miR145-3p and (B) miR145-5p expression levels with survival of patients with breast cancer (based on the METABRIC dataset). For each miRNA, we compared the third of patients with the highest expression levels of the corresponded miRNA (red) to the third of patients with the lowest expression (blue). The miRNA name and P value are indicated in the title.

  • Figure 3.
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    Figure 3.

    In vitro effects of miR145-5p and miR145-3p. A, miR145-5p does not affect breast cancer cell proliferation. Proliferation assay was performed in MDA-MB-231 cells upon miR145-5p exogenous expression. Cells were collected and manually counted at the indicated time points. B, miR145-5p inhibits breast cancer cell migration. Transwell migration assay was performed in MDA-MB-231 and MDA-MB-468 cells upon miR145-5p exogenous expression. C, miR145-3p impinges breast cancer cell proliferation. Proliferation assay was performed in MDA-MB-231 cells upon miR145-3p exogenous expression. Cells were collected and manually counted at the indicated time points after transfection. D, miR145-3p impinges breast cancer cell colony formation ability. Clonogenic assay was performed in MDA-MB-231 cells upon miR145-3p exogenous expression. E, miR145-3p does not affect breast cancer cell migration. Transwell migration assay was performed in MDA-MB-231 cells upon miR145-3p exogenous expression. B, C, and E, histogram bars represent mean ± standard deviation of at least three independent replicates.

Tables

  • Figures
  • Additional Files
  • Table 1.

    Descriptive characteristics of the 133 postmenopausal women candidate to become breast cancer and 133 control women: baseline values

    CasesControlsMedian difference (IC 95%)t Student P value
    Age, y; median (SD)57 (5.95)56 (5.89)−0.5:2.50.85
    Age at menarche, y; median (interquartile range)13 (12–14)13 (12–14)−0.36:0.360.93
    IGF1; median (interquartile range)115 (95.5–155)111 (92.2–137.5)−6.2:14.20.16
    TTS; median (interquartile range)0.28 (0.21–0.36)0.26 (0.2–0.32)−0.02:0.060.21
    BMI, kg/m2; median (interquartile range)25.6 (23.3–28.3)25.7 (23.6–28.4)−1.13:0.780.42
    Fasting glucose; median (interquartile range)84 (78–91)85 (78–90)−7.8:5.80.24
    Alcohol intake, g/d; median (interquartile range)4.8 (0–24)3.4 (0–18)−2.3:5.10.75
    Age at first birth; median (SD)26 (4.6)25 (3.6)−0.09:2.10.09
    Full-term pregnancies; median (SD)2 (1)2 (1)−0.28:0.280.92
    Smoking; % of smoker/ex smoker/not smoker19/12/6916/12/72—0.7a

    Abbreviations: IGFI, insulin growth factor 1; TTS, total testosterone.

    • ↵aχ2 P value.

  • Table 2.

    List of the top 20-ranked miRNAs according to FDR values for miRNAs differentially expressed between women candidate to become breast cancer and healthy controls within the ORDET cohort

    miRNALog FCaP valuesbFDRc
    Downregulated miRNAs
     hsa-miR125a-5p−0.6340.00210.400
     hsa-miR141−0.1580.00230.400
     hsa-miR582-5p−0.4960.00280.400
     hsa-miR138−0.1990.00340.400
     hsa-miR199a-5p−0.5810.00390.400
     hsa-miR181c*−0.3210.00410.400
     hsa-miR28-3p−0.6310.00420.400
     hsa-miR224−0.6290.00470.400
     hsa-miR145-3p−0.2610.00530.408
     hsa-miR223−0.4840.00790.503
     hsa-miR145-5p−0.5060.00830.503
     hsa-miR539−0.3640.00980.504
     hsa-miR99b−0.4830.01120.504
     hsa-miR199b-5p−0.3140.01170.504
     hsa-miR920−0.1470.01180.504
    Upregulated miRNAs
     hsa-miR892b0.4600.00010.102
     hsa-miR12880.3040.00450.400
     hsa-miR520a-3p0.4020.00610.430
     hsa-miR542-5p0.3810.01020.504
     hsa-miR122*0.3930.01180.504

    NOTE: Downregulated and upregulated miRNAs in candidates to become breast cancer cases versus controls.

    • ↵aThe Log FC column gives log2 fold change between cases' and controls' expression.

    • ↵bP values for moderated t statistics.

    • ↵cFDR gives the P value adjusted with the Benjamini and Hochberg method to control the FDR.

  • Table 3.

    Cancer predicted pathways targeted by the three clusters identified by the cluster analysis

    miRNA clusterMost significant predicted pathways
    Cluster 1Wnt signaling pathway
    miR145-5p miR199a-5p miR542-5p miR892b miR1288Steroid biosynthesis
    Glycosylphosphatidylinositol(GPI)-anchor biosynthesis
    Hedgehog signaling pathway
    Adherens junction
    Transcriptional misregulation in cancer
    Pathways in cancer
    TGFβ signaling pathway
    MAPK signaling pathway
    Cell cycle
    Cluster 2MAPK signaling pathway
    miR28-3p miR122* miR138 miR141 miR145-3p miR181c* miR520-3p miR539 miR920ErbB signaling pathway
    mTOR signaling pathway
    Insulin signaling pathway
    PI3K-Akt signaling pathway
    Transcriptional misregulation in cancer
    Chemokine signaling pathway
    Cluster 3MAPK signaling pathway
    miR99b miR582-5p miR199b-5pTranscriptional misregulation in cancer
    Pathways in cancer
  • Table 4.

    miR145-3p modulation in breast cancer cases and in a variety of breast cancer tissues and peritumoral tissues by different databases

    miR145-3pORDETBiagioni et al. (7)CGANFarazi et al. (33)Enerly et al. (34)
    Tumor133 (cases)63694168101
    Peritumor—5983——
    Normal133 (controls)——11—
    PlatformAgilentAgilentIlluminaSolexaAgilent
    Subsetscase vs. controlT vs. PTLum A-B vs. basal—Basal vs. Lum A
     mut p53 vs. wt p53
     ER-p53 mut vs. ER-p53 wt
     proliferative samples
    ModulationDownDownDown—Down

    Abbreviations: basal, basal breast cancer; DCIS, ductal carcinoma in situ; ER, estrogen receptor; IDC, invasive ductal carcinoma; lum, luminal breast cancer; mut p53, mutated p53; PT, peritumoral tissue; T, tumor tissue; wt, wild-type.

    • Table 5.

      miR145-5p modulation in breast cancer cases and in a variety of breast cancer tissues and peritumoral tissues by different databases

      miR145-5pORDETBiagioni et al. (7)CGANFarazi et al. (33)Enerly et al. (34)
      Tumor133 (cases)63694168101
      Peritumor—5983——
      Normal133 (controls)——11—
      PlatformAgilentAgilentIlluminaSolexaAgilent
      SubsetsCase vs. controlT vs. PTLum. B vs. BasalDCIS vs. normal;Basal vs, Lum A;
       IDC HER2+ ER− vs. normal mut p53 vs. wt p53;
       ER-p53 mut vs. ER-p53 wt
       proliferative samples
      ModulationDownDownDownDownDown

      Abbreviations: basal, basal breast cancer; DCIS, ductal carcinoma in situ; ER, estrogen receptor; IDC, invasive ductal carcinoma; lum, luminal breast cancer; mut p53, mutated p53; PT, peritumoral tissue; T, tumor tissue; wt, wild-type.

      • Table 6.

        miRNAs modulation in breast cancer tissues versus normal tissues in the 1,359 patients with breast cancer from the METABRIC study and in subtypes of breast cancer tissues versus normal tissues derived from the highly characterized subgroup of 81 participants

        P value for all subtyped togetherP value for matched samples by subtype
        Expression in Caldas dataset (METABRIC)Direction of changeN vs. T (81 vs. 1,278)Matched N vs. T (81)Normal-like (15)Her2 (5)Basal-like (15)Lum A (27)Lum B (19)KM P value
        Downregulated miRNAs
         hsa-miR125a-5pExpressedUpregulated in T<0.001<0.0010.8140.1100.724<0.001<0.0010.791
         hsa-miR141ExpressedUpregulated in T<0.001<0.0010.1980.0560.445<0.001<0.0010.0637
         hsa-miR582-5pExpressedUpregulated in T<0.001<0.0010.4210.5030.4830.0040.1300.144
         hsa-miR138Not Expressed—————————
         hsa-miR199a-5pExpressedNo difference0.1090.3040.7430.0790.6150.0940.0180.0043
         hsa-miR181c*ExpressedNo difference0.0630.4890.4700.0080.3530.0180.9870.00857
         hsa-miR28-3pNot Expressed—————————
         hsa-miR224ExpressedDownregulated in T<0.001<0.001<0.0010.5980.511<0.001<0.0010.202
         hsa-miR145-3pExpressedDownregulated in T<0.001<0.001<0.0010.0610.0120.002<0.0010.00121
         hsa-miR145-5pExpressedDownregulated in T<0.001<0.0010.0050.007<0.001<0.001<0.0010.112
         hsa-miR223ExpressedNo difference0.1690.3640.3720.4270.1010.8700.4980.0086
         hsa-miR539ExpressedDownregulated in T<0.0010.0810.2630.5700.9740.7470.0080.0113
         hsa-miR99bExpressedDownregulated in T0.0030.4390.3150.1140.6730.3920.1600.0197
         hsa-miR199b-5pExpressedDownregulated in T<0.0010.0030.0080.1840.1250.4760.012<0.001
         hsa-miR920Not expressed—————————
        Upregulated miRNAs
         hsa-miR892bNot expressed—————————
         hsa-miR1288Not expressed—————————
         hsa-miR520a-3pNot expressed—————————
         hsa-miR542-5pExpressedNo difference0.1220.2490.5650.2560.0600.0950.1030.0188
         hsa-miR122*Not expressed—————————

        NOTE: For each miRNA, it is indicated whether it is expressed in the METABRIC dataset (column 2); for the expressed miRNAs, it is also indicated whether they are over- or underexpressed in the tumor tissue relative to normal samples (column 3), and corresponding P values for all samples together (column 4), only in matched tumor and normal samples from the same patient across all subtypes (column 5), and for each subtype alone (columns 6–10). The number of patients in each comparison is indicated in parentheses in the column heads. The last column contains P values for Kaplan–Meier analysis, comparing the difference in survival between the third of patients with the highest expression of the miRNA to the third of patients with lowest expression.

        Abbreviations: N, normal tissue; T, tumoral tissue.

        Additional Files

        • Figures
        • Tables
        • Supplementary Tables 1-18, Figure 1

          Files in this Data Supplement:

          • Data Supplement - Supplementary Table 1 - miR-125a-5p expression across different databases; Supplementary Table 2 - miR-99b expression across different databases; Supplementary Table 3 - miR-199a-5p expression across different databases; Supplementary Table 4 - miR-199b-5p expression across different databases; Supplementary Table 5 - miR-892b expression across different databases; Supplementary Table 6 - miR-141 expression across different databases; Supplementary Table 7 - miR-582-5p expression across different databases; Supplementary Table 8 - miR-138 expression across different databases; Supplementary Table 9 - miR-181c* expression across different databases; Supplementary Table 10 - miR-28-3p expression across different databases; Supplementary Table 11 - miR-1288 expression across different databases; Supplementary Table 12 - miR-224 expression across different databases; Supplementary Table 13 - miR-520a-3p expression across different databases; Supplementary Table 14 - miR-223 expression across different databases; Supplementary Table 15 - miR-539 expression across different databases; Supplementary Table 16 - miR-542-5p expression across different databases; Supplementary Table 17 - miR-122* expression across different databases; Supplementary Table 18 - miR-920 expression across different databases.
          • Data Supplement - Supplementary Figure 1. qRT-PCR analysis of miR-145-5p expression in MDA-MB-231 cells used for proliferation assay.
          • Data Supplement - Figure Legend Supplementary Material
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        Cancer Epidemiology Biomarkers & Prevention: 23 (11)
        November 2014
        Volume 23, Issue 11
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        Downregulation of microRNAs 145-3p and 145-5p Is a Long-term Predictor of Postmenopausal Breast Cancer Risk: The ORDET Prospective Study
        Paola Muti, Andrea Sacconi, Ahmed Hossain, Sara Donzelli, Noa Bossel Ben Moshe, Federica Ganci, Sabina Sieri, Vittorio Krogh, Franco Berrino, Francesca Biagioni, Sabrina Strano, Joseph Beyene, Yosef Yarden and Giovanni Blandino
        Cancer Epidemiol Biomarkers Prev November 1 2014 (23) (11) 2471-2481; DOI: 10.1158/1055-9965.EPI-14-0398

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        Downregulation of microRNAs 145-3p and 145-5p Is a Long-term Predictor of Postmenopausal Breast Cancer Risk: The ORDET Prospective Study
        Paola Muti, Andrea Sacconi, Ahmed Hossain, Sara Donzelli, Noa Bossel Ben Moshe, Federica Ganci, Sabina Sieri, Vittorio Krogh, Franco Berrino, Francesca Biagioni, Sabrina Strano, Joseph Beyene, Yosef Yarden and Giovanni Blandino
        Cancer Epidemiol Biomarkers Prev November 1 2014 (23) (11) 2471-2481; DOI: 10.1158/1055-9965.EPI-14-0398
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