A gene expression signature that can predict the recurrence of tamoxifen-treated primary breast cancer.

PURPOSE: The identification of a molecular signature predicting the relapse of tamoxifen-treated primary breast cancers should help the therapeutic management of estrogen receptor-positive cancers. EXPERIMENTAL DESIGN: A series of 132 primary tumors from patients who received adjuvant tamoxifen were analyzed for expression profiles at the whole-genome level by 70-mer oligonucleotide microarrays. A supervised analysis was done to identify an expression signature. RESULTS: We defined a 36-gene signature that correctly classified 78% of patients with relapse and 80% of relapse-free patients (79% accuracy). Using 23 independent tumors, we confirmed the accuracy of the signature (78%) whose relevance was further shown by using published microarray data from 60 tamoxifen-treated patients (63% accuracy). Univariate analysis using the validation set of 83 tumors showed that the 36-gene classifier is more efficient in predicting disease-free survival than the traditional histopathologic prognostic factors and is as effective as the Nottingham Prognostic Index or the "Adjuvant!" software. Multivariate analysis showed that the molecular signature is the only independent prognostic factor. A comparison with several already published signatures demonstrated that the 36-gene signature is among the best to classify tumors from both training and validation sets. Kaplan-Meier analyses emphasized its prognostic power both on the whole cohort of patients and on a subgroup with an intermediate risk of recurrence as defined by the St. Gallen criteria. CONCLUSION: This study identifies a molecular signature specifying a subgroup of patients who do not gain benefits from tamoxifen treatment. These patients may therefore be eligible for alternative endocrine therapies and/or chemotherapy.

A new molecular breast cancer subclass defined from a large scale real-time quantitative RT-PCR study.

BACKGROUND: Current histo-pathological prognostic factors are not very helpful in predicting the clinical outcome of breast cancer due to the disease's heterogeneity. Molecular profiling using a large panel of genes could help to classify breast tumours and to define signatures which are predictive of their clinical behaviour. METHODS: To this aim, quantitative RT-PCR amplification was used to study the RNA expression levels of 47 genes in 199 primary breast tumours and 6 normal breast tissues. Genes were selected on the basis of their potential implication in hormonal sensitivity of breast tumours. Normalized RT-PCR data were analysed in an unsupervised manner by pairwise hierarchical clustering, and the statistical relevance of the defined subclasses was assessed by Chi2 analysis. The robustness of the selected subgroups was evaluated by classifying an external and independent set of tumours using these Chi2-defined molecular signatures. RESULTS: Hierarchical clustering of gene expression data allowed us to define a series of tumour subgroups that were either reminiscent of previously reported classifications, or represented putative new subtypes. The Chi2 analysis of these subgroups allowed us to define specific molecular signatures for some of them whose reliability was further demonstrated by using the validation data set. A new breast cancer subclass, called subgroup 7, that we defined in that way, was particularly interesting as it gathered tumours with specific bioclinical features including a low rate of recurrence during a 5 year follow-up. CONCLUSION: The analysis of the expression of 47 genes in 199 primary breast tumours allowed classifying them into a series of molecular subgroups. The subgroup 7, which has been highlighted by our study, was remarkable as it gathered tumours with specific bioclinical features including a low rate of recurrence. Although this finding should be confirmed by using a larger tumour cohort, it suggests that gene expression profiling using a minimal set of genes may allow the discovery of new subclasses of breast cancer that are characterized by specific molecular signatures and exhibit specific bioclinical features.

The transcriptional coregulator RIP140 represses E2F1 activity and discriminates breast cancer subtypes.

PURPOSE: Receptor-interacting protein of 140 kDa (RIP140) is a transcriptional cofactor for nuclear receptors involved in reproduction and energy homeostasis. Our aim was to investigate its role in the regulation of E2F1 activity and target genes both in breast cancer cell lines and in tumor biopsies. EXPERIMENTAL DESIGN: Glutathione S-transferase pull-down assays, coimmunoprecipitation experiments, and chromatin immunoprecipitation analysis were used to evidence interaction between RIP140 and E2F1. The effects of RIP140 expression on E2F1 activity were determined using transient transfection and quantification of E2F target mRNAs by quantitative real-time PCR. The effect on cell cycle was assessed by fluorescence-activated cell sorting analysis on cells overexpressing green fluorescent protein-tagged RIP140. A tumor microarray data set was used to investigate the expression of RIP140 and E2F1 target genes in 170 breast cancer patients. RESULTS: We first evidenced the complex interaction between RIP140 and E2F1 and showed that RIP140 represses E2F1 transactivation on various transiently transfected E2F target promoters and inhibits the expression of several E2F1 target genes (such as CCNE1 and CCNB2). In agreement with a role for RIP140 in the control of E2F activity, we show that increasing RIP140 levels results in a reduction in the proportion of cells in S phase in various human cell lines. Finally, analysis of human breast cancers shows that low RIP140 mRNA expression was associated with high E2F1 target gene levels and basal-like tumors. CONCLUSION: This study shows that RIP140 is a regulator of the E2F pathway, which discriminates luminal- and basal-like tumors, emphasizing the importance of these regulations for a clinical cancer phenotype.

CIP2A is associated with human breast cancer aggressivity.

PURPOSE: To investigate the clinical relevance of the recently characterized human oncoprotein cancerous inhibitor of protein phosphatase 2A (CIP2A) in human breast cancer. EXPERIMENTAL DESIGN: CIP2A expression (mRNA and protein) was measured in three different sets of human mammary tumors and compared with clinicopathologic variables. The functional role of CIP2A in breast cancer cells was evaluated by small interfering RNA-mediated depletion of the protein followed by an analysis of cell proliferation, migration, anchorage-independent growth, and xenograft growth. RESULTS: CIP2A mRNA is overexpressed (n = 159) and correlates with higher Scarff-Bloom-Richardson grades (n = 251) in samples from two independent human breast cancer patients. CIP2A protein was found to be overexpressed in 39% of 33 human breast cancer samples. Furthermore, CIP2A mRNA expression positively correlated with lymph node positivity of the patients and with the expression of proliferation markers and p53 mutations in the tumor samples. Moreover, CIP2A protein expression was induced in breast cancer mouse models presenting mammary gland-specific depletion of p53 and either BRCA1 or BRCA2. Functionally, CIP2A depletion was shown to inhibit the expression of its target protein c-Myc. Loss of CIP2A also inhibited anchorage-independent growth in breast cancer cells. Finally, CIP2A was shown to support MDA-MB-231 xenograft growth in nude mice. CONCLUSIONS: Our data show that CIP2A is associated with clinical aggressivity in human breast cancer and promotes the malignant growth of breast cancer cells. Thus, these results validate the role of CIP2A as a clinically relevant human oncoprotein and warrant further investigation of CIP2A as a therapeutic target in breast cancer treatment.

[Gene expression profiling of ER+ breast cancers: to discriminate the poor prognosis tumors or to define the most suitable treatment?]. / Analyse du transcriptome des cancers du sein ER+ : discriminer les tumeurs agressives ou définir le traitement le plus adapté ?

The cDNA microarray technology allows the simultaneous analysis of all genes expressed in a tumor. This approach has already permitted to propose a molecular classification of breast cancers. Gene expression profiling is now expected to define prognosis signatures claiming the disease outcome as well as signatures predicting response to therapy. The over-expression of a cluster of genes that are implicated in cell cycle and mitosis control has been shown to discriminate a subgroup of ER+ breast cancers exhibiting a poor prognosis. This "proliferation cluster" is shown to be also present in signatures predicting relapse of ER+ breast cancers treated by the anti-estrogen tamoxifen, including the 36-gene classifier that we have recently identified. Consequently, it seems legitimate to wonder if this part of such predictive signature is really specific to the insensitivity to tamoxifen or rather indicates a poor disease outcome whatever the therapy applied. On the other hand, low expression of ER+ related genes and high expression of genes associated to ER- status or low ERalpha levels have been shown to sign a poor prognosis. Whether the estrogen-related genes that are present in our 36-gene classifier specify the clinical disease outcome or are really specific to the response to tamoxifen, remains to be determined. In any case, the specificity of our 36-gene classifier as those predicting the recurrence of ER+ breast cancer under one treatment or another should be demonstrated. In the same way, future studies should define molecular signatures that will be really predictive of the response to the treatment in order to define which one is the most suitable to decrease the risk of relapse of ER+ breast cancers. These studies should be based on neoadjuvant clinical trials that permit to evaluate the response to treatment in an objective manner.

Cell adhesion protects c-Raf-1 against ubiquitin-dependent degradation by the proteasome.

MAP kinase activation by growth factors depends on cell adhesion to the extracellular matrix. Disrupting the cell adhesion process in NIH 3T3 fibroblasts induced an almost complete inhibition of MAP kinase, which was impaired by proteasome inhibitors. In the absence of cell anchorage, c-Raf-1 expression was dramatically decreased after 24 h. This down-regulation was suppressed by proteasome inhibitors, suggesting that a proteasome-dependent degradation of Raf occurred in the absence of cell adhesion. Proteasome inhibitors did not affect Raf-1 levels in adherent cells, indicating that this degradation only occurred in the absence of cell adhesion. Finally, ectopic coexpression of Raf-1 and ubiquitin in HEK-293 and NIH 3T3 cells generated ubiquitylated forms of Raf-1, both in adherent and suspended cells, suggesting a possible ubiquitin-dependent degradation of the protein.

MAP kinase-dependent degradation of p27Kip1 by calpains in choroidal melanoma cells. Requirement of p27Kip1 nuclear export.

We investigated the status and the regulation of the cyclin-dependent kinases (CDK) inhibitor p27(Kip1) in a choroidal melanoma tumor-derived cell line (OCM-1). By contrast to normal choroidal melanocytes, the expression level of p27(Kip1) was low in these cells and the mitogen-activated protein (MAP) kinase pathway was constitutively activated. Genetic or chemical inhibition of this pathway induced p27(Kip1) accumulation, whereas MAP kinase reactivation triggered a down-regulation of p27(Kip1) that could be partially reversed by calpain inhibitors. In good accordance, ectopic expression of the cellular calpain inhibitor calpastatin led to an increase of endogenous p27(Kip1) expression. In vitro, p27(Kip1) was degraded by calpains, and OCM-1 cell extracts contained a calcium-dependent p27(Kip1) degradation activity. MAP kinase inhibition partially inhibited both calpain activity and calcium-dependent p27(Kip1) degradation by cellular extracts. Immunofluorescence labeling and subcellular fractionation revealed that p27(Kip1) was in part localized in the cytoplasmic compartment of OCM-1 cells but not of melanocytes, and accumulated into the nucleus upon MAP kinase inhibition. MAP kinase activation triggered a cytoplasmic translocation of the protein, as well as a change in its phosphorylation status. This CRM-1-dependent cytoplasmic translocation was necessary for MAP kinase- and calpain-dependent degradation. Taken together, these data suggest that in tumor-derived cells, p27(Kip1) could be degraded by calpains through a MAP kinase-dependent process, and that abnormal cytoplasmic localization of the protein, probably linked to modifications of its phosphorylation state, could be involved in this alternative mechanism of degradation.

Regulation of Chk2 phosphorylation by interaction with protein phosphatase 2A via its B' regulatory subunit.

Chk2 is a key player of the DNA damage signalling pathway. To identify new regulators of this kinase, we performed a yeast two-hybrid screen and found that Chk2 associated with the B' regulatory subunit of protein phosphatase PP2A. In vitro GST-Chk2 pulldowns demonstrated that B'gamma isoforms bound to Chk2 with the strongest apparent affinity. This was confirmed in cellulo by co-immunoprecipitation after overexpression of the respective partners in HEK293 cells. The A and C subunits of PP2A were present in the complexes, suggesting that Chk2 was associated with a functionnal PP2A. In vitro kinase assays showed that B'gamma3 was a potent Chk2 substrate. This phosphorylation increased the catalytic phosphatase activity of PP2A measured on MAP kinase-phosphorylated myelin basic protein as well as on autophosphorylated Chk2. Finally, we demonstrated that overexpressing B'gamma3 in HEK293 suppressed the phosphorylation of Chk2 induced by a genotoxic treatment, suggesting that PP2A may counteract the action of the checkpoint kinase in living cells.