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Personalized Medicine and Imaging

Comprehensive Transcriptome Profiling Reveals Multigene Signatures in Triple-Negative Breast Cancer

Yi-Rong Liu, Yi-Zhou Jiang, Xiao-En Xu, Xin Hu, Ke-Da Yu and Zhi-Ming Shao
Yi-Rong Liu
1Department of Breast Surgery, Fudan University Shanghai Cancer Center, Shanghai, P.R. China.
2Cancer Institute, Fudan University Shanghai Cancer Center, Shanghai, P.R. China.
3Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, P.R. China.
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Yi-Zhou Jiang
1Department of Breast Surgery, Fudan University Shanghai Cancer Center, Shanghai, P.R. China.
2Cancer Institute, Fudan University Shanghai Cancer Center, Shanghai, P.R. China.
3Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, P.R. China.
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Xiao-En Xu
1Department of Breast Surgery, Fudan University Shanghai Cancer Center, Shanghai, P.R. China.
2Cancer Institute, Fudan University Shanghai Cancer Center, Shanghai, P.R. China.
3Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, P.R. China.
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Xin Hu
1Department of Breast Surgery, Fudan University Shanghai Cancer Center, Shanghai, P.R. China.
2Cancer Institute, Fudan University Shanghai Cancer Center, Shanghai, P.R. China.
3Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, P.R. China.
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Ke-Da Yu
1Department of Breast Surgery, Fudan University Shanghai Cancer Center, Shanghai, P.R. China.
2Cancer Institute, Fudan University Shanghai Cancer Center, Shanghai, P.R. China.
3Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, P.R. China.
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  • For correspondence: zhimingshao@yahoo.com yukeda@163.com
Zhi-Ming Shao
1Department of Breast Surgery, Fudan University Shanghai Cancer Center, Shanghai, P.R. China.
2Cancer Institute, Fudan University Shanghai Cancer Center, Shanghai, P.R. China.
3Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, P.R. China.
4Institutes of Biomedical Sciences, Fudan University, Shanghai, P.R. China.
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  • For correspondence: zhimingshao@yahoo.com yukeda@163.com
DOI: 10.1158/1078-0432.CCR-15-1555 Published April 2016
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  • Figure 1.
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    Figure 1.

    Comparison of the sensitivity and specificity of prognosis by the integrated mRNA–lncRNA signature, the mRNA-only signature, and the traditional clinicopathologic factors in the training (n = 165) and validation (n = 101) sets. Time-dependent ROC curves were plotted to assess the efficacy of the signatures, with AUCs reported. We also calculated the performances of the combined traditional prognostic factors, including tumor size, grade, and number of involved lymph nodes. All factors were coded as categorical variables. Limited by the follow-up time, we could only perform analysis up to two years.

  • Figure 2.
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    Figure 2.

    Estimates of RFS according to the scores calculated by the integrated mRNA–lncRNA signature and the mRNA-only signature in the training (n = 165) and the validation (n = 101) sets. A, Kaplan–Meier analysis of RFS according to the scores calculated by the integrated mRNA–lncRNA signature and the mRNA-only signature. B, patients were stratified according to the receipt of the taxane-based chemotherapy to validate the interaction between each risk group and the taxane-based chemotherapy using multivariate Cox proportional hazards regression analysis adjusted for clinicopathologic factors in Table 2. The low-risk group was used as reference. The bars represent the HRs in different set and the lines represent the 95% CI. If the limit of 95% CI outranges the scale on the x-axis, the data were shown as arrows.

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    Figure 3.

    Biologic function of the lncRNAs HIST2H2BC and SNRPEP4 incorporated in the integrated signature. A, cell proliferation was determined by CCK-8 assay after transfection with siRNAs for 48 hours. The results are shown as the percentage of optical density (OD) with negative control (NC) as reference. B, representative light microscopic images of migrated cells through the Transwell chamber (magnification, 100×). The number of migrated cells was calculated and compared between each siRNA with NC. C, effect of lncRNAs on the resistance to paclitaxel. The results were assessed by CCK-8 assay and the relative cell viability was calculated. All results are represented as the mean ± SD from three independent experiments. Notes: *, P < 0.05; **, P < 0.01; ***, P < 0.001.

Tables

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  • Table 1.

    Clinicopathologic characteristics of TNBC patients according to the integrated RNA signatures in two sets

    Training setValidation set
    mRNA signaturemRNA–lncRNA signaturemRNA signaturemRNA–lncRNA signature
    CharacteristicsNHigh risk (%)Low risk (%)High risk (%)Low risk (%)NHigh risk (%)Low risk (%)High risk (%)Low risk (%)
    Age, y
     Median555056505653.553.553.55453
     IQR46–6143–5849.8–6243–5949–61.344.8–5945.5–58.344.8–60.346.5–5944–59
     ≤506838 (55.9)30 (44.1)34 (50.0)34 (50.0)3919 (48.7)20 (51.3)20 (51.3)19 (48.7)
     >509731 (32.3)66 (68.8)31 (32.3)66 (68.8)6226 (41.9)36 (58.1)32 (51.6)30 (48.4)
    Menopause
     Yes10137 (36.6)64 (63.4)35 (34.7)66 (65.3)6426 (40.6)38 (59.4)31 (48.4)33 (51.6)
     No6432 (50.0)32 (50.0)30 (46.9)34 (53.1)3214 (43.8)18 (56.3)16 (50.0)16 (50.0)
     Unknown00 (0.0)0 (0.0)0 (0.0)0 (0.0)55 (100.0)0 (0.0)5 (100.0)0 (0.0)
    Tumor size, cm
     ≤25823 (39.7)35 (60.3)19 (32.8)39 (67.2)3617 (47.2)19 (52.8)19 (52.8)17 (47.2)
     >210444 (42.3)60 (57.7)45 (43.3)59 (56.7)6528 (43.1)37 (56.9)33 (50.8)32 (49.2)
     Unknown32 (66.7)1 (33.3)1 (33.3)2 (66.7)00 (0.0)0 (0.0)0 (0.0)0 (0.0)
    Tumor grade
     I–II329 (28.1)23 (71.9)10 (31.3)22 (68.8)3115 (48.4)16 (51.6)18 (58.1)13 (41.9)
     III10448 (46.2)56 (53.8)45 (43.3)59 (56.7)7030 (42.9)40 (57.1)34 (48.6)36 (51.4)
     Unknown2912 (41.4)17 (58.6)10 (34.5)19 (65.5)00 (0.0)0 (0.0)0 (0.0)0 (0.0)
    Positive LNs
     ≤311547 (40.9)68 (59.1)44 (38.3)71 (61.7)8238 (46.3)44 (53.7)44 (53.7)38 (46.3)
     >35022 (44.0)28 (56.0)21 (42.0)29 (58.0)197 (36.8)12 (63.2)8 (42.1)11 (57.9)
    Chemotherapy
     Taxane12452 (41.9)72 (58.1)48 (38.7)76 (61.3)6629 (43.9)37 (56.1)34 (51.5)32 (48.5)
     Non-taxane2712 (44.4)15 (55.6)12 (44.4)15 (55.6)3516 (45.7)19 (54.3)18 (51.4)17 (48.6)
     Unknown145 (35.7)9 (64.3)5 (35.7)9 (64.3)00 (0.0)0 (0.0)0 (0.0)0 (0.0)
    Radiotherapy
     Yes5023 (46.0)27 (54.0)21 (42.0)29 (58.0)3919 (48.7)20 (51.3)21 (53.8)18 (46.2)
     No10341 (39.8)62 (60.2)41 (39.8)62 (60.2)4218 (42.9)24 (57.1)21 (50.0)21 (50.0)
     Unknown125 (41.7)7 (58.3)3 (25.0)9 (75.0)208 (40.0)12 (60.0)10 (50.0)10 (50.0)
    Follow-up time, mo
     Median13.912.614.211.714.318.518.518.31819.2
     IQR8.6–21.18.4–19.39.3–22.28.2–18.49.5–22.615–26.213.6–26.115.1–26.513.7–25.715.2–27.5
    RFS event2217517597281

    Abbreviations: IQR, interquartile range; LN, lymph node; mo, months; RFS, recurrence-free survival; y, year.

    • Table 2.

      Multivariate Cox proportional hazards regression analysis of the derived RNA signatures and traditional characteristics with RFS

      mRNA-only signatureIntegrated mRNA–lncRNA signature
      Training setValidation setTraining setValidation set
      VariableaHR (95% CI)PHR (95% CI)PHR (95% CI)PHR (95% CI)P
      Age (≤50 y as reference)1.06 (0.16–6.95)0.9491.29 (0.10–16.09)0.8451.01 (0.09–11.11)0.9951.18 (0.11–12.90)0.890
      Menopause (no as reference)0.67 (0.12–3.73)0.6460.43 (0.03–5.77)0.5210.63 (0.07–5.38)0.6720.56 (0.05–6.18)0.635
      Tumor grade (≤II as reference)1.61 (0.40–6.45)0.5010.71 (0.10–5.00)0.7291.79 (0.44–7.31)0.4160.91 (0.14–6.09)0.920
      Tumor size (≤2 cm as reference)1.13 (0.34–3.70)0.8464.45 (0.48–41.47)0.1890.78 (0.20–2.99)0.7124.72 (0.51–43.68)0.171
      Positive LNs (≤3 as reference)1.95 (0.53–7.24)0.3192.48 (0.53–11.53)0.2472.37 (0.61–9.16)0.2113.38 (0.70–16.31)0.130
      Radiotherapy (no as reference)4.03 (0.93–17.39)0.0623.87 (0.64–23.49)0.1413.79 (0.83–17.31)0.0863.58 (0.63–20.33)0.151
      Chemotherapy (non-taxane as reference)0.49 (0.15–1.57)0.2281.22 (0.25–5.95)0.8040.69 (0.17–2.74)0.5931.41 (0.27–7.26)0.683
      Signature (low-risk as reference)4.46 (1.34–14.91)0.0156.31 (1.20–33.26)0.03010.00 (2.53–39.47)0.00114.04 (1.56–126.71)0.019

      Abbreviation: LN, lymph node.

      • ↵aAdjusted by Cox proportional hazards models including age, menopausal status, tumor grade, tumor size, positive lymph nodes, radiotherapy, chemotherapy, and integrated RNA signature.

    • Table 3.

      Multivariate Cox proportional hazards regression analysis of RFS, including interaction of signatures with adjuvant chemotherapy

      mRNA signaturemRNA–lncRNA signature
      Training setValidation setTraining setValidation set
      VariableaHR (95% CI)PHR (95% CI)PHR (95% CI)PHR (95% CI)P
      Chemotherapy (non-taxane as reference)0.49 (0.15–1.57)0.2281.22 (0.25–5.95)0.8040.69 (0.17–2.74)0.5931.41 (0.27–7.26)0.683
      Signature (low-risk as reference)4.46 (1.34–14.91)0.0156.31 (1.20–33.26)0.03010.00 (2.53–39.47)0.00114.04 (1.56–126.71)0.019
      Interaction1.82 (0.62–5.37)0.2774.14 (0.93–18.48)0.0635.74 (1.54–21.33)0.0094.46 (1.00–19.88)0.05
      • ↵aAdjusted by Cox proportional hazards models including clinical variables as categorized in Table 2. Here, we present only three items: chemotherapy, signature, and the interaction between them. Other parameters (age, menopausal status, tumor grade, tumor size, positive lymph nodes and radiotherapy) are not shown.

    Additional Files

    • Figures
    • Tables
    • Supplementary Data

      • Supplementary table 1 - Supplementary Table 1. Selected mRNAs and lncRNAs by comparing the expression profiles in 33 paired tumor and adjacent normal tissues of triple-negative breast cancer.
      • Supplementary figures - Supplementary Figure 1. Kaplan-Meier estimates of recurrence-free survival (RFS) according to the expression of every ten mRNA/lncRNA incorporated in the integrated signature in the training set (n=165). RNA expression level was coded as high or low according to the median expression level. Supplementary Figure 2. Validation of the expression of each mRNA/lncRNA incorporated in the integrated signature in the 33 paired tumor and normal breast tissues from the training set using quantitative real-time polymerase chain reaction (qRT-PCR). Supplementary Figure 3. Flowchart of the study design, patient selection and analytical strategy. Supplementary Figure 4. Details of the filtration procedures. For lncRNAs, either lncRNAs with fold change >1.5 and P<0.05 in survival analysis or fold change >2 and P<0.1 were included. Supplementary Figure 5. Down regulations of the HIST2H2BC and SNRPEP4 enhanced apoptosis induced by paclitaxel. Supplementary Figure 6. Flow cytometric analyses of cell cycle distribution in control and siRNA knockdown breast cancer cells.
    • Supplementary Data

      • Supplementary table 1 - Supplementary Table 1. Selected mRNAs and lncRNAs by comparing the expression profiles in 33 paired tumor and adjacent normal tissues of triple-negative breast cancer.
      • Supplementary figures - Supplementary Figure 1. Kaplan-Meier estimates of recurrence-free survival (RFS) according to the expression of every ten mRNA/lncRNA incorporated in the integrated signature in the training set (n=165). RNA expression level was coded as high or low according to the median expression level. Supplementary Figure 2. Validation of the expression of each mRNA/lncRNA incorporated in the integrated signature in the 33 paired tumor and normal breast tissues from the training set using quantitative real-time polymerase chain reaction (qRT-PCR). Supplementary Figure 3. Flowchart of the study design, patient selection and analytical strategy. Supplementary Figure 4. Details of the filtration procedures. For lncRNAs, either lncRNAs with fold change >1.5 and P<0.05 in survival analysis or fold change >2 and P<0.1 were included. Supplementary Figure 5. Down regulations of the HIST2H2BC and SNRPEP4 enhanced apoptosis induced by paclitaxel. Supplementary Figure 6. Flow cytometric analyses of cell cycle distribution in control and siRNA knockdown breast cancer cells.
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    Clinical Cancer Research: 22 (7)
    April 2016
    Volume 22, Issue 7
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    Comprehensive Transcriptome Profiling Reveals Multigene Signatures in Triple-Negative Breast Cancer
    Yi-Rong Liu, Yi-Zhou Jiang, Xiao-En Xu, Xin Hu, Ke-Da Yu and Zhi-Ming Shao
    Clin Cancer Res April 1 2016 (22) (7) 1653-1662; DOI: 10.1158/1078-0432.CCR-15-1555

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    Comprehensive Transcriptome Profiling Reveals Multigene Signatures in Triple-Negative Breast Cancer
    Yi-Rong Liu, Yi-Zhou Jiang, Xiao-En Xu, Xin Hu, Ke-Da Yu and Zhi-Ming Shao
    Clin Cancer Res April 1 2016 (22) (7) 1653-1662; DOI: 10.1158/1078-0432.CCR-15-1555
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