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. 2019 Nov 25;9(1):17496.
doi: 10.1038/s41598-019-53695-0.

Expression of the BAD pathway is a marker of triple-negative status and poor outcome

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Expression of the BAD pathway is a marker of triple-negative status and poor outcome

Bernadette M Boac et al. Sci Rep. .

Abstract

Triple-negative breast cancer (TNBC) has few therapeutic targets, making nonspecific chemotherapy the main treatment. Therapies enhancing cancer cell sensitivity to cytotoxic agents could significantly improve patient outcomes. A BCL2-associated agonist of cell death (BAD) pathway gene expression signature (BPGES) was derived using principal component analysis (PCA) and evaluated for associations with the TNBC phenotype and clinical outcomes. Immunohistochemistry was used to determine the relative expression levels of phospho-BAD isoforms in tumour samples. Cell survival assays evaluated the effects of BAD pathway inhibition on chemo-sensitivity. BPGES score was associated with TNBC status and overall survival (OS) in breast cancer samples of the Moffitt Total Cancer Care dataset and The Cancer Genome Atlas (TCGA). TNBC tumours were enriched for the expression of phospho-BAD isoforms. Further, the BPGES was associated with TNBC status in breast cancer cell lines of the Cancer Cell Line Encyclopedia (CCLE). Targeted inhibition of kinases known to phosphorylate BAD protein resulted in increased sensitivity to platinum agents in TNBC cell lines compared to non-TNBC cell lines. The BAD pathway is associated with triple-negative status and OS. TNBC tumours were enriched for the expression of phosphorylated BAD protein compared to non-TNBC tumours. These findings suggest that the BAD pathway it is an important determinant of TNBC clinical outcomes.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Figure 1
Figure 1
The BAD pathway gene expression signature (BPGES) was associated with triple-negative status and breast cancer survival. (a) Waterfall plot showing differential expression of the BPGES in non-TNBC samples (green, n = 53, mean BPGES = −1.7 ± 0.24) and TNBC samples (red, n = 53, mean BPGES = −1.7 ± 0.19) in the TCC breast cancer dataset (p = 4.8 × 10−19). (b) Scatter plot showing clustering of non-TNBC samples (green, n = 324) separate from TNBC samples (red, n = 84), when the first principal component (PC1) of the PCA model is graphed against the second principal component (PC2) in TCGA breast cancer samples. (c) Boxplots showing the differential expression of individual genes of the BPGES between non-TNBC (solid circles) and TNBC cases (open squares) from the TCC dataset. Unpaired T-test indicates significance of ***p < 0.001, ** p < 0.01, *p < 0.05, no symbol: p > 0.05. Kaplan-Meier curves showing the association between high BPGES (median threshold) and reduced OS for non-TNBC and TNBC patients in the (d) TCC dataset (n = 105, log-rank test, hazard ratio (HR) = 2.67, p = 0.0072), (e) TCGA dataset (n = 757, log rank test, HR = 2.045, p = 0.0009) and only TNBC patients of the (f) TCC dataset (n = 53, log rant test, HR = 1.07, p = 0.873) and (g) TCGA dataset (n = 82, log rant test, HR = 1.827, p = 0.35).
Figure 2
Figure 2
phospho-BAD-Ser136 expression is enriched in TNBC and correlates with the BPGES. (a) Replicate representative cores of a TMA showing higher levels of phospho-BAD (pBAD) isoforms in TNBC samples when compared to non-TNBC samples. (b) Box plots comparing histological expression scores derived from pathologist assessment (top panel) and Definiens software analysis (bottom panel) of phospho-BAD-Ser112, phospho-BAD-Ser136, and phospho-BAD-Ser155 immunohistochemistry stains. Unpaired T-test p-values indicate significance. (c) Scatter plots showing the correlations between Definien’s Histo-scores for the phospho-BAD isoforms and the BPGES. Kaplan-Meier, 5-year survival curves showing the association between phospho-BAD isoform expression and decreased survival probability in (d) n = 54 breast cancer cases (non-TNBC; n = 18, and TNBC; n = 36) and (e) n = 36 TNBC cases. Significance was determined using log rank tests. Hazard ratios (HR) show risk. All graphs were generated using GraphPad Prism 7.
Figure 3
Figure 3
The BPGES was associated with triple-negative status in breast cancer cell lines of the CCLE. (a) Waterfall plot showing the BPGES in 42 breast cancer cell lines from the CCLE database (www.broadinstitute.org). The mean BPGES score was −1.81 ± 0.33 in non-TNBC cells (n = 14) versus .90 ± 0.25 in TNBC cells (n = 28) (p = 4.22 × 10−7). The graph was generated using GraphPad Prism 7. (b) Box plots showing differences in the median BPGES score between non-TNBC cell (n = 14) and TNBC cells (n = 28) from the CCLE database. The graph was generated using GraphPad Prism 7. (c) Boxplots showing the differential expression of individual genes of the BPGES between non-TNBC (solid circles) and TNBC cell lines (open squares). Unpaired T-test indicates significance of ***p < 0.001, **p < 0.01, *p < 0.05, no symbol: p > 0.05. (d) Western blot showing the expression of active (phosphorylated) and total isoforms of the BAD protein kinases, AKT and PKA in a panel of non-TNBC and TNBC cell lines. Bar graphs show the percent expression of phosphorylated (active) protein in relation to total protein for AKT and PKA after densitometry analysis of at least 3 replicate experiments. All proteins were first normalized to the expression of GAPDH. Error bars indicate standard error of the mean.
Figure 4
Figure 4
Targeted inhibition of BAD protein kinases increases platinum sensitivity in TNBC cells. CellTiter96, MTS cell survival assays showing the effect of a fixed dose of (a) perifosine (AKT inhibitor) and (b) H89 dihydrochloride hydrate (H89) on the sensitivity of breast cancer cell lines to cisplatin. Error bars indicate standard error of the mean from 3 replicate experiments.
Figure 5
Figure 5
The potentiation of cisplatin by perifosine and H89 was mediated by the functional inhibition of BAD protein. CellTiter96, MTS cell survival assays showing siRNA depletion of BAD protein did not affect the sensitivity of TNBC cells to cisplatin but reduced the sensitivity of (a) BT549 and (b) MDA468 to the AKT inhibitor, perifosine as well as the sensitivity of (c) BT549, and (d) MDA436 to the PKA inhibitor, H89. Western blots show depletion of BAD protein by siRNA. Histone H3 and GAPDH were used as loading controls.

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