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Gene expression patterns associated with p53 status in breast cancer.

Troester MA, Herschkowitz JI, Oh DS, He X, Hoadley KA, Barbier CS, Perou CM - BMC Cancer (2006)

Bottom Line: The cell line signatures were compared with p53-mutation associated genes in breast tumors.Further, a common gene expression signature associated with p53 loss across all four cell lines was identified.Our biologically-based refinements excluded genes that were associated with subtype but not downstream of p53 signaling, and identified a signature for p53 loss that is shared across breast cancer subtypes.

View Article: PubMed Central - HTML - PubMed

Affiliation: Division of Biostatistics and Epidemiology, School of Public Health and Health Sciences, University of Massachusetts Amherst, Amherst, MA, USA. troester@schoolph.umass.edu

ABSTRACT

Background: Breast cancer subtypes identified in genomic studies have different underlying genetic defects. Mutations in the tumor suppressor p53 occur more frequently in estrogen receptor (ER) negative, basal-like and HER2-amplified tumors than in luminal, ER positive tumors. Thus, because p53 mutation status is tightly linked to other characteristics of prognostic importance, it is difficult to identify p53's independent prognostic effects. The relation between p53 status and subtype can be better studied by combining data from primary tumors with data from isogenic cell line pairs (with and without p53 function).

Methods: The p53-dependent gene expression signatures of four cell lines (MCF-7, ZR-75-1, and two immortalized human mammary epithelial cell lines) were identified by comparing p53-RNAi transduced cell lines to their parent cell lines. Cell lines were treated with vehicle only or doxorubicin to identify p53 responses in both non-induced and induced states. The cell line signatures were compared with p53-mutation associated genes in breast tumors.

Results: Each cell line displayed distinct patterns of p53-dependent gene expression, but cell type specific (basal vs. luminal) commonalities were evident. Further, a common gene expression signature associated with p53 loss across all four cell lines was identified. This signature showed overlap with the signature of p53 loss/mutation status in primary breast tumors. Moreover, the common cell-line tumor signature excluded genes that were breast cancer subtype-associated, but not downstream of p53. To validate the biological relevance of the common signature, we demonstrated that this gene set predicted relapse-free, disease-specific, and overall survival in independent test data.

Conclusion: In the presence of breast cancer heterogeneity, experimental and biologically-based methods for assessing gene expression in relation to p53 status provide prognostic and biologically-relevant gene lists. Our biologically-based refinements excluded genes that were associated with subtype but not downstream of p53 signaling, and identified a signature for p53 loss that is shared across breast cancer subtypes.

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Chemosensitivity is altered in the MCF-7 cell line following transduction with p53-RNAi. ME16C, HME-CC, and ZR-75-1 cell lines had similar chemosensitivity curves for wildtype (x), p53-targeted RNAi expressing cells (solid square) and p53 mismatch RNAi expressing cells (open square). Only the p53-RNAi MCF-7 cells showed significant chemoresistance.
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Figure 2: Chemosensitivity is altered in the MCF-7 cell line following transduction with p53-RNAi. ME16C, HME-CC, and ZR-75-1 cell lines had similar chemosensitivity curves for wildtype (x), p53-targeted RNAi expressing cells (solid square) and p53 mismatch RNAi expressing cells (open square). Only the p53-RNAi MCF-7 cells showed significant chemoresistance.

Mentions: The phenotypic effects of p53 knock-down varied by cell line (Figure 2). MCF-7 cells became more resistant to DOX, while ZR-75-1, ME16C and HME-CC cells displayed no change in DOX sensitivity. Consistent with the different responses in the DOX sensitivity assay, gene expression signatures significantly associated with p53 loss (in 2-class SAM analyses) were different for each cell line and cell type (gene lists are given in Additional File 1). As shown in Figure 3, MCF-7 and ZR-75-1 cells showed a stronger p53-dependent signature following treatment with DOX. The immortalized HMECs, conversely, showed stronger p53-dependent signatures in the absence of DOX (i.e. parents vs. RNAi, both untreated). Analysis of SAM-derived gene lists using gene ontology software (EASE) showed enrichment for categories of genes with known relevance to p53 function. For example, among the DOX-treated samples (DOX-treated parent vs. DOX-treated RNAi-expressing), three cell lines (HME-CC, MCF-7 and ZR-75-1) increased genes involved in mitosis after transduction with p53-RNAi. ME16C did not induce categories of mitosis genes, but did suppress negative regulators of cell proliferation. Significant down-regulation of apoptotic genes was only seen in ZR-75-1 cells.


Gene expression patterns associated with p53 status in breast cancer.

Troester MA, Herschkowitz JI, Oh DS, He X, Hoadley KA, Barbier CS, Perou CM - BMC Cancer (2006)

Chemosensitivity is altered in the MCF-7 cell line following transduction with p53-RNAi. ME16C, HME-CC, and ZR-75-1 cell lines had similar chemosensitivity curves for wildtype (x), p53-targeted RNAi expressing cells (solid square) and p53 mismatch RNAi expressing cells (open square). Only the p53-RNAi MCF-7 cells showed significant chemoresistance.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC1764759&req=5

Figure 2: Chemosensitivity is altered in the MCF-7 cell line following transduction with p53-RNAi. ME16C, HME-CC, and ZR-75-1 cell lines had similar chemosensitivity curves for wildtype (x), p53-targeted RNAi expressing cells (solid square) and p53 mismatch RNAi expressing cells (open square). Only the p53-RNAi MCF-7 cells showed significant chemoresistance.
Mentions: The phenotypic effects of p53 knock-down varied by cell line (Figure 2). MCF-7 cells became more resistant to DOX, while ZR-75-1, ME16C and HME-CC cells displayed no change in DOX sensitivity. Consistent with the different responses in the DOX sensitivity assay, gene expression signatures significantly associated with p53 loss (in 2-class SAM analyses) were different for each cell line and cell type (gene lists are given in Additional File 1). As shown in Figure 3, MCF-7 and ZR-75-1 cells showed a stronger p53-dependent signature following treatment with DOX. The immortalized HMECs, conversely, showed stronger p53-dependent signatures in the absence of DOX (i.e. parents vs. RNAi, both untreated). Analysis of SAM-derived gene lists using gene ontology software (EASE) showed enrichment for categories of genes with known relevance to p53 function. For example, among the DOX-treated samples (DOX-treated parent vs. DOX-treated RNAi-expressing), three cell lines (HME-CC, MCF-7 and ZR-75-1) increased genes involved in mitosis after transduction with p53-RNAi. ME16C did not induce categories of mitosis genes, but did suppress negative regulators of cell proliferation. Significant down-regulation of apoptotic genes was only seen in ZR-75-1 cells.

Bottom Line: The cell line signatures were compared with p53-mutation associated genes in breast tumors.Further, a common gene expression signature associated with p53 loss across all four cell lines was identified.Our biologically-based refinements excluded genes that were associated with subtype but not downstream of p53 signaling, and identified a signature for p53 loss that is shared across breast cancer subtypes.

View Article: PubMed Central - HTML - PubMed

Affiliation: Division of Biostatistics and Epidemiology, School of Public Health and Health Sciences, University of Massachusetts Amherst, Amherst, MA, USA. troester@schoolph.umass.edu

ABSTRACT

Background: Breast cancer subtypes identified in genomic studies have different underlying genetic defects. Mutations in the tumor suppressor p53 occur more frequently in estrogen receptor (ER) negative, basal-like and HER2-amplified tumors than in luminal, ER positive tumors. Thus, because p53 mutation status is tightly linked to other characteristics of prognostic importance, it is difficult to identify p53's independent prognostic effects. The relation between p53 status and subtype can be better studied by combining data from primary tumors with data from isogenic cell line pairs (with and without p53 function).

Methods: The p53-dependent gene expression signatures of four cell lines (MCF-7, ZR-75-1, and two immortalized human mammary epithelial cell lines) were identified by comparing p53-RNAi transduced cell lines to their parent cell lines. Cell lines were treated with vehicle only or doxorubicin to identify p53 responses in both non-induced and induced states. The cell line signatures were compared with p53-mutation associated genes in breast tumors.

Results: Each cell line displayed distinct patterns of p53-dependent gene expression, but cell type specific (basal vs. luminal) commonalities were evident. Further, a common gene expression signature associated with p53 loss across all four cell lines was identified. This signature showed overlap with the signature of p53 loss/mutation status in primary breast tumors. Moreover, the common cell-line tumor signature excluded genes that were breast cancer subtype-associated, but not downstream of p53. To validate the biological relevance of the common signature, we demonstrated that this gene set predicted relapse-free, disease-specific, and overall survival in independent test data.

Conclusion: In the presence of breast cancer heterogeneity, experimental and biologically-based methods for assessing gene expression in relation to p53 status provide prognostic and biologically-relevant gene lists. Our biologically-based refinements excluded genes that were associated with subtype but not downstream of p53 signaling, and identified a signature for p53 loss that is shared across breast cancer subtypes.

Show MeSH
Related in: MedlinePlus