Ras/Raf-1/MAPK Pathway Mediates Response to Tamoxifen but not Chemotherapy in Breast Cancer Patients

Mutations in the Ras-Raf Axis underlie the prognostic value of CD133 in colorectal cancer

PURPOSE

High expression of cancer stem cell (CSC) marker CD133 has been used as a predictor for prognosis in colorectal cancer (CRC), suggesting that enumeration of CSCs, using CD133, is predictive for disease progression. However, we showed recently that both CD133 mRNA and protein are not downregulated during differentiation of colon CSCs, pointing to an alternative reason for the prognostic value of CD133. We therefore set out to delineate the relation between CD133 expression and prognosis.

EXPERIMENTAL DESIGN

A CRC patient series was studied for expression of CD133 and other CSC markers by microarray and quantitative PCR analysis. In addition, several common mutations were analyzed to determine the relation with CD133 expression.

RESULTS

CD133 mRNA expression predicted relapse-free survival in our patient series, whereas several other CSC markers could not. Moreover, no correlation was found between expression of other CSC markers and CD133. Interestingly, high CD133 expression was related to mutations in K-Ras and B-Raf, and inhibition of mutant K-Ras or downstream mitogen-activated protein kinase kinase (MEK) signaling decreases CD133 expression. In addition, an activated K-Ras gene expression signature could predict CD133 expression in our patient set as well as data sets of other tumor types.

CONCLUSION

CD133 expression is upregulated in CRC tumors that have a hyperactivated Ras-Raf-MEK-ERK pathway and is therefore related to mutations in K-Ras or B-Raf. As mutations in either gene have been related to poor prognosis, we conclude that CD133 expression is not indicative for CSC numbers but rather related to the mutation or activity status of the Ras-Raf pathway.

A MEK-independent role for CRAF in mitosis and tumor progression

RAF kinases regulate cell proliferation and survival and can be dysregulated in tumors. The role of RAF in cell proliferation has been linked to its ability to activate mitogen-activated protein kinase kinase 1 (MEK) and mitogen-activated protein kinase 1 (ERK). Here we identify a MEK-independent role for RAF in tumor growth. Specifically, in mitotic cells, CRAF becomes phosphorylated on Ser338 and localizes to the mitotic spindle of proliferating tumor cells in vitro as well as in murine tumor models and in biopsies from individuals with cancer. Treatment of tumors with allosteric inhibitors, but not ATP-competitive RAF inhibitors, prevents CRAF phosphorylation on Ser338 and localization to the mitotic spindle and causes cell-cycle arrest at prometaphase. Furthermore, we identify phospho-Ser338 CRAF as a potential biomarker for tumor progression and a surrogate marker for allosteric RAF blockade. Mechanistically, CRAF, but not BRAF, associates with Aurora kinase A (Aurora-A) and Polo-like kinase 1 (Plk1) at the centrosomes and spindle poles during G2/M. Indeed, allosteric or genetic inhibition of phospho-Ser338 CRAF impairs Plk1 activation and accumulation at the kinetochores, causing prometaphase arrest, whereas a phospho-mimetic Ser338D CRAF mutant potentiates Plk1 activation, mitosis and tumor progression in mice. These findings show a previously undefined role for RAF in tumor progression beyond the RAF-MEK-ERK paradigm, opening new avenues for targeting RAF in cancer.

Identifying cancer biomarkers by network-constrained support vector machines

BACKGROUND

One of the major goals in gene and protein expression profiling of cancer is to identify biomarkers and build classification models for prediction of disease prognosis or treatment response. Many traditional statistical methods, based on microarray gene expression data alone and individual genes' discriminatory power, often fail to identify biologically meaningful biomarkers thus resulting in poor prediction performance across data sets. Nonetheless, the variables in multivariable classifiers should synergistically interact to produce more effective classifiers than individual biomarkers.

RESULTS

We developed an integrated approach, namely network-constrained support vector machine (netSVM), for cancer biomarker identification with an improved prediction performance. The netSVM approach is specifically designed for network biomarker identification by integrating gene expression data and protein-protein interaction data. We first evaluated the effectiveness of netSVM using simulation studies, demonstrating its improved performance over state-of-the-art network-based methods and gene-based methods for network biomarker identification. We then applied the netSVM approach to two breast cancer data sets to identify prognostic signatures for prediction of breast cancer metastasis. The experimental results show that: (1) network biomarkers identified by netSVM are highly enriched in biological pathways associated with cancer progression; (2) prediction performance is much improved when tested across different data sets. Specifically, many genes related to apoptosis, cell cycle, and cell proliferation, which are hallmark signatures of breast cancer metastasis, were identified by the netSVM approach. More importantly, several novel hub genes, biologically important with many interactions in PPI network but often showing little change in expression as compared with their downstream genes, were also identified as network biomarkers; the genes were enriched in signaling pathways such as TGF-beta signaling pathway, MAPK signaling pathway, and JAK-STAT signaling pathway. These signaling pathways may provide new insight to the underlying mechanism of breast cancer metastasis.

CONCLUSIONS

We have developed a network-based approach for cancer biomarker identification, netSVM, resulting in an improved prediction performance with network biomarkers. We have applied the netSVM approach to breast cancer gene expression data to predict metastasis in patients. Network biomarkers identified by netSVM reveal potential signaling pathways associated with breast cancer metastasis, and help improve the prediction performance across independent data sets.

Genomic collaboration of estrogen receptor alpha and extracellular signal-regulated kinase 2 in regulating gene and proliferation programs

The nuclear hormone receptor, estrogen receptor α (ERα), and mitogen-activated protein kinases (MAPKs) play key roles in hormone-dependent cancers, and yet their interplay and the integration of their signaling inputs remain poorly understood. In these studies, we document that estrogen-occupied ERα activates and interacts with extracellular signal-regulated kinase 2 (ERK2), a downstream effector in the MAPK pathway, resulting in ERK2 and ERα colocalization at chromatin binding sites across the genome of breast cancer cells. This genomic colocalization, predominantly at conserved distal enhancer sites, requires the activation of both ERα and ERK2 and enables ERK2 modulation of estrogen-dependent gene expression and proliferation programs. The ERK2 substrate CREB1 was also activated and recruited to ERK2-bound chromatin following estrogen treatment and found to cooperate with ERα/ERK2 in regulating gene transcription and cell cycle progression. Our study reveals a novel paradigm with convergence of ERK2 and ERα at the chromatin level that positions this kinase to support nuclear receptor activities in crucial and direct ways, a mode of collaboration likely to underlie MAPK regulation of gene expression by other nuclear receptors as well.

High expression of sphingosine 1-phosphate receptors, S1P1 and S1P3, sphingosine kinase 1, and extracellular signal-regulated kinase-1/2 is associated with development of tamoxifen resistance in estrogen receptor-positive breast cancer patients

Various studies in cell lines have previously demonstrated that sphingosine kinase 1 (SK1) and extracellular signal-regulated kinase 1/2 (ERK-1/2) interact in an estrogen receptor (ER)-dependent manner to influence both breast cancer cell growth and migration. A cohort of 304 ER-positive breast cancer patients was used to investigate the prognostic significance of sphingosine 1-phosphate (S1P) receptors 1, 2, and 3 (ie, S1P1, S1P2, and S1P3), SK1, and ERK-1/2 expression levels. Expression levels of both SK1 and ERK-1/2 were already available for the cohort, and S1P1, S1P2, and S1P3 levels were established by immunohistochemical analysis. High membrane S1P1 expression was associated with shorter time to recurrence (P=0.008). High cytoplasmic S1P1 and S1P3 expression levels were also associated with shorter disease-specific survival times (P=0.036 and P=0.019, respectively). Those patients with tumors that expressed high levels of both cytoplasmic SK1 and ERK-1/2 had significantly shorter recurrence times than those that expressed low levels of cytoplasmic SK1 and cytoplasmic ERK-1/2 (P=0.00008), with a difference in recurrence time of 10.5 years. Similarly, high cytoplasmic S1P1 and cytoplasmic ERK-1/2 expression levels (P=0.004) and high cytoplasmic S1P3 expression and cytoplasmic ERK-1/2 expression levels (P=0.004) were associated with shorter recurrence times. These results support a model in which the interaction between SK1, S1P1, and/or S1P3 and ERK-1/2 might drive breast cancer progression, and these findings, therefore, warrant further investigation.

Sphingosine 1-phosphate receptor 4 uses HER2 (ERBB2) to regulate extracellular signal regulated kinase-1/2 in MDA-MB-453 breast cancer cells

We demonstrate here that the bioactive lipid sphingosine 1-phosphate (S1P) uses sphingosine 1-phosphate receptor 4 (S1P(4)) and human epidermal growth factor receptor 2 (HER2) to stimulate the extracellular signal regulated protein kinase 1/2 (ERK-1/2) pathway in MDA-MB-453 cells. This was based on several lines of evidence. First, the S1P stimulation of ERK-1/2 was abolished by JTE013, which we show here is an S1P(2/4) antagonist and reduced by siRNA knockdown of S1P(4). Second, the S1P-stimulated activation of ERK-1/2 was almost completely abolished by a HER2 inhibitor (ErbB2 inhibitor II) and reduced by siRNA knockdown of HER2 expression. Third, phyto-S1P, which is an S1P(4) agonist, stimulated ERK-1/2 activation in an S1P(4)- and HER2-dependent manner. Fourth, FTY720 phosphate, which is an agonist at S1P(1,3,4,5) but not S1P(2) stimulated activation of ERK-1/2. Fifth, S1P stimulated the tyrosine phosphorylation of HER2, which was reduced by JTE013. HER2 which is an orphan receptor tyrosine kinase is the preferred dimerization partner of the EGF receptor. However, EGF-stimulated activation of ERK-1/2 was not affected by siRNA knockdown of HER2 or by ErbB2 (epidermal growth factor receptor 2 (or HER2)) inhibitor II in MDA-MB-453 cells. Moreover, S1P-stimulated activation of ERK-1/2 does not require an EGF receptor. Thus, S1P and EGF function in a mutually exclusive manner. In conclusion, the magnitude of the signaling gain on the ERK-1/2 pathway produced in response to S1P can be increased by HER2 in MDA-MB-453 cells. The linkage of S1P with an oncogene suggests that S1P and specifically S1P(4) may have an important role in breast cancer progression.

Molecular alterations in key-regulator genes among patients with T4 breast carcinoma

Background

Prognostic factors in patients who are diagnosed with T4 breast carcinomas are widely awaited. We here evaluated the clinical role of some molecular alterations involved in tumorigenesis in a well-characterized cohort of T4 breast cancer patients with a long follow-up period.

Methods

A consecutive series of 53 patients with T4 breast carcinoma was enrolled between 1992 and 2001 in Sardinia, and observed up for a median of 125 months. Archival paraffin-embedded tissue sections were used for immunohistochemistry (IHC) and fluorescence in situ hybridization (FISH) analyses, in order to assess alterations in expression levels of survivin, p53, and pERK_1-2 proteins as well as in amplification of CyclinD1 and h-prune genes. The Kaplan-Meier and Cox regression methods were used for survival assessment and statistical analysis.

Results

Overall, patients carrying increased expression of pERK_1-2 (p = 0.027) and survivin (p = 0.008) proteins as well as amplification of h-prune gene (p = 0.045) presented a statistically-significant poorer overall survival in comparison with cases found negative for such alterations. After multivariate analysis, the pathological response to primary chemotherapy and the survivin overexpression in primary carcinoma represented the main parameters with a role as independent prognostic factors in our series.

Conclusions

Although retrospective, our study identified some molecular parameters with a significant impact on prediction of the response to therapy or prognosis among T4 breast cancer patients. Further large prospective studies are needed in order to validate the use of such markers for the management of these patients.

Sphingosine kinase 1 induces tolerance to human epidermal growth factor receptor 2 and prevents formation of a migratory phenotype in response to sphingosine 1-phosphate in estrogen receptor-positive breast cancer cells

We demonstrate here a new concept termed "oncogene tolerance" whereby human EGF receptor 2 (HER2) increases sphingosine kinase 1 (SK1) expression in estrogen receptor-positive (ER(+)) MCF-7 HER2 cells and SK1, in turn, limits HER2 expression in a negative-feedback manner. The HER2-dependent increase in SK1 expression also limits p21-activated protein kinase 1 (p65 PAK1) and extracellular signal regulated kinase 1/2 (ERK-1/2) signaling. Sphingosine 1-phosphate signaling via S1P(3) is also altered in MCF-7 HER2 cells. In this regard, S1P binding to S1P(3) induces a migratory phenotype via an SK1-dependent mechanism in ER(+) MCF-7 Neo cells, which lack HER2. This involves the S1P stimulated accumulation of phosphorylated ERK-1/2 and actin into membrane ruffles/lamellipodia and migration. In contrast, S1P failed to promote redistribution of phosphorylated ERK-1/2 and actin into membrane ruffles/lamellipodia or migration of MCF-7 HER2 cells. However, a migratory phenotype in these cells could be induced in response to S1P when SK1 expression had been knocked down with a specific siRNA or when recombinant PAK1 was ectopically overexpressed. Thus, the HER2-dependent increase in SK1 expression functions to desensitize the S1P-induced formation of a migratory phenotype. This is correlated with improved prognosis in patients who have a low HER1-3/SK1 expression ratio in their ER(+) breast cancer tumors compared to patients that have a high HER1-3/SK1 expression ratio.

Tamoxifen resistance in early breast cancer: statistical modelling of tissue markers to improve risk prediction

BACKGROUND

For over two decades, the Nottingham Prognostic Index (NPI) has been used in the United Kingdom to calculate risk scores and inform management about breast cancer patients. It is derived using just three clinical variables - nodal involvement, tumour size and grade. New scientific methods now make cost-effective measurement of many biological characteristics of tumour tissue from breast cancer biopsy samples possible. However, the number of potential explanatory variables to be considered presents a statistical challenge. The aim of this study was to investigate whether in ER+ tamoxifen-treated breast cancer patients, biological variables can add value to NPI predictors, to provide improved prognostic stratification in terms of overall recurrence-free survival (RFS) and also in terms of remaining recurrence free while on tamoxifen treatment (RFoT). A particular goal was to enable the discrimination of patients with a very low risk of recurrence.

METHODS

Tissue samples of 401 cases were analysed by microarray technology, providing biomarker data for 72 variables in total, from AKT, BAD, HER, MTOR, PgR, MAPK and RAS families. Only biomarkers screened as potentially informative (i.e., exhibiting univariate association with recurrence) were offered to the multivariate model. The multiple imputation method was used to deal with missing values, and bootstrap sampling was used to assess internal validity and refine the model.

RESULTS

Neither the RFS nor RFoT models derived included Grade, but both had better predictive and discrimination ability than NPI. A slight difference was observed between models in terms of biomarkers included, and, in particular, the RFoT model alone included HER2. The estimated 7-year RFS rates in the lowest-risk groups by RFS and RFoT models were 95 and 97%, respectively, whereas the corresponding rate for the lowest-risk group of NPI was 89%.

CONCLUSION

The findings demonstrate considerable potential for improved prognostic modelling by incorporation of biological variables into risk prediction. In particular, the ability to identify a low-risk group with minimal risk of recurrence is likely to have clinical appeal. With larger data sets and longer follow-up, this modelling approach has the potential to enhance an understanding of the interplay of biological characteristics, treatment and cancer recurrence.

Key signalling nodes in mammary gland development and cancer. Mitogen-activated protein kinase signalling in experimental models of breast cancer progression and in mammary gland development

Seven classes of mitogen-activated protein kinase (MAPK) intracellular signalling cascades exist, four of which are implicated in breast disease and function in mammary epithelial cells. These are the extracellular regulated kinase (ERK)1/2 pathway, the ERK5 pathway, the p38 pathway and the c-Jun N-terminal kinase (JNK) pathway. In some forms of human breast cancer and in many experimental models of breast cancer progression, signalling through the ERK1/2 pathway, in particular, has been implicated as being important. We review the influence of ERK1/2 activity on the organised three-dimensional association of mammary epithelial cells, and in models of breast cancer cell invasion. We assess the importance of epidermal growth factor receptor family signalling through ERK1/2 in models of breast cancer progression and the influence of ERK1/2 on its substrate, the oestrogen receptor, in this context. In parallel, we consider the importance of these MAPK-centred signalling cascades during the cycle of mammary gland development. Although less extensively studied, we highlight the instances of signalling through the p38, JNK and ERK5 pathways involved in breast cancer progression and mammary gland development.

Role of senescence and mitotic catastrophe in cancer therapy

Senescence and mitotic catastrophe (MC) are two distinct crucial non-apoptotic mechanisms, often triggered in cancer cells and tissues in response to anti-cancer drugs. Chemotherapeuticals and myriad other factors induce cell eradication via these routes. While senescence drives the cells to a state of quiescence, MC drives the cells towards death during the course of mitosis. The senescent phenotype distinguishes tumor cells that survived drug exposure but lost the ability to form colonies from those that recover and proliferate after treatment. Although senescent cells do not proliferate, they are metabolically active and may secrete proteins with potential tumor-promoting activities. The other anti-proliferative response of tumor cells is MC that is a form of cell death that results from abnormal mitosis and leads to the formation of interphase cells with multiple micronuclei. Different classes of cytotoxic agents induce MC, but the pathways of abnormal mitosis differ depending on the nature of the inducer and the status of cell-cycle checkpoints. In this review, we compare the two pathways and mention that they are activated to curb the growth of tumors. Altogether, we have highlighted the possibilities of the use of senescence targeting drugs, mitotic kinases and anti-mitotic agents in fabricating novel strategies in cancer control.

Prognosis of hormone-dependent breast cancers: implications of the presence of dysfunctional transcriptional networks activated by insulin via the immune transcription factor T-bet

Estrogen receptor alpha (ERalpha)-positive breast cancers that co-express transcription factors GATA-3 and FOXA1 have a favorable prognosis. These transcription factors form an autoregulatory hormonal network that influences estrogen responsiveness and sensitivity to hormonal therapy. Disruption of this network may be a mechanism whereby ERalpha-positive breast cancers become resistant to therapy. The transcription factor T-bet is a negative regulator of GATA-3 in the immune system. In this study, we report that insulin increases the expression of T-bet in breast cancer cells, which correlates with reduced expression of GATA-3, FOXA1, and the ERalpha:FOXA1:GATA-3 target gene GREB-1. The effects of insulin on GATA-3 and FOXA1 could be recapitulated through overexpression of T-bet in MCF-7 cells (MCF-7-T-bet). Chromatin immunoprecipitation assays revealed reduced ERalpha binding to GREB-1 enhancer regions in MCF-7-T-bet cells and in insulin-treated MCF-7 cells. MCF-7-T-bet cells were resistant to tamoxifen in the presence of insulin and displayed prolonged extracellular signal-regulated kinase and AKT activation in response to epidermal growth factor treatment. ERalpha-positive cells with intrinsic tamoxifen resistance as well as MCF-7 cells with acquired tamoxifen and fulvestrant resistance expressed elevated levels of T-bet and/or reduced levels of FOXA1 and GATA-3. Analysis of publicly available databases revealed ERalpha-positive/T-bet-positive breast cancers expressing lower levels of FOXA1 (P = 0.0137) and GATA-3 (P = 0.0063) compared with ERalpha-positive/T-bet-negative breast cancers. Thus, T-bet expression in primary tumors and circulating insulin levels may serve as surrogate biomarkers to identify ERalpha-positive breast cancers with a dysfunctional hormonal network, enhanced growth factor signaling, and resistance to hormonal therapy.

Three-dimensional overlay culture models of human breast cancer reveal a critical sensitivity to mitogen-activated protein kinase kinase inhibitors

Tumor cells that are grown in three-dimensional (3D) cell culture exhibit relative resistance to cytotoxic drugs compared with their response in conventional two-dimensional (2D) culture. We studied the effects of targeted agents and doxorubicin on 2D and 3D cultures of human breast cell lines that represent the progression from normal epithelia (modeled by MCF10A cells) through hyperplastic variants to a dysplastic/carcinoma phenotype (MCF10.DCIS cells), variants transformed by expression of activated Ras, and also a basal-subtype breast carcinoma cell line (MDA-MB-231). The results showed the expected relative resistance to the cytotoxic agent doxorubicin in 3D cultures, with greater resistance in normal and hyperplastic cells than in carcinoma models. However, the response to the targeted inhibitors was more complex. Inhibition of mitogen-activated protein kinase kinase (MEK) by either 1,4-diamino-2,3-dicyano-1,4-bis(methylthio)butadiene (U0126) or 2-(2-chloro-4-iodo-phenylamino)-N-cyclopropylmethoxy-3,4-difluoro-benzamide (CI-1040, PD184352) produced a similar inhibition of the growth of all the MCF10 cell lines in 2D. In 3D culture, the normal and hyperplastic models exhibited some resistance, whereas the carcinoma models became far more sensitive to MEK inhibition. Increased sensitivity to MEK inhibition was also seen in MDA-MB-231 cells grown in 3D compared with 2D. In contrast, inhibition of phosphatidylinositol 3'-kinase activity by wortmannin had no significant effect on the growth of any of the cells in either 2D or 3D. Our conclusion is that 3D culture models may not only model the relative resistance of tumor cells to cytotoxic therapy but also that the 3D approach may better identify the driving oncogenic pathways and critical targeted inhibitors that may be effective treatment approaches.