Sibyll Hein

Volkmar Müller

Nadine Köhler

Harriet Wikman

Sylke Krenkel

Thomas Streichert

Michaela Schweizer

Sabine Riethdorf

Volker Assmann

Maike Ihnen

Katrin Beck

Rana Issa

Fritz Jänicke

Klaus Pantel

Karin Milde-Langosch

Biologic role of activated leukocyte cell adhesion molecule overexpression in breast cancer cell lines and clinical tumor tissue

Keywords: Breast cancer, ALCAM, immunohistochemistry, function, invasion, apoptosis

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Introduction

Adhesion molecules enable cancer-related biological processes like survival, migration, extravasation, homing and metastasis and thus play a crucial role in cancer progression. Many adhesion molecules are characteristically dysregulated in human cancer, and the development of therapeutic anti-adhesion strategies is ongoing. Therefore, better insights into the function of proteins involved in cell adhesion are necessary.

The activated leukocyte cell adhesion molecule (ALCAM) is a member of the immunoglobulin superfamily, consisting of five extracellular IgG domains (2 V-type and 3 C 2 -type), a transmembrane anchoring region and a short cytoplasmic tail. By homophilic (ALCAM-ALCAM) or heterophilic (ALCAM-CD6) ligand binding mediated by the distal domain (D1) and by lateral oligomerization mediated by the proximal C2-type domains (D3-D5), a clustering of ALCAM molecules and formation of an ALCAM network is achieved [START_REF] Swart | Activated leukocyte cell adhesion molecule (CD166/ALCAM): developmental and mechanistic aspects of cell clustering and cell migration[END_REF]. In normal tissues, ALCAM is expressed on activated lymphocytes, neuronal cells, hepatocytes, pancreatic cells, selected epithelia (i.e. in mammary ducts and acini) as well as in embryonic cells, i.e. bone marrow, endothelial and yolk sac cells [START_REF] Swart | Activated leukocyte cell adhesion molecule (CD166/ALCAM): developmental and mechanistic aspects of cell clustering and cell migration[END_REF][START_REF] Uchida | The characterization, molecular cloning, and expression of a novel hematopoietic cell antigen from CD34+ human bone marrow cells[END_REF][START_REF] Ohneda | ALCAM (CD166): its role in hematopoietic and endothelial development[END_REF]. Moreover, it is localized at the lateral membranes of endothelial cells where it facilitates transmigration of ALCAM-positive monocytes [START_REF] Masedunskas | Activated leukocyte cell adhesion molecule is a component of the endothelial junction involved in transendothelial monocyte migration[END_REF].

Similar to other adhesion molecules, ALCAM binding can activate signalling pathways regulating various biological functions. Thus, ALCAM expression has been implicated in apoptosis [START_REF] Jezierska | ALCAM/CD166 protects breast cancer cells against apoptosis and autophagy[END_REF], angiogenesis [6], migration and invasion [START_REF] Van Kilsdonk | Attenuation of melanoma invasion by a secreted variant of activated leukocyte cell adhesion molecule[END_REF] of various cell types. Concerning the role of ALCAM in human cancer, the results are partly controversial: In many tumours, ALCAM expression is associated with high invasive and metastatic potential and poor prognosis, i.e. in melanoma [START_REF] Degen | MEMD, a new cell adhesion molecule in metastasizing human melanoma cell lines, is identical to ALCAM (activated leukocyte cell adhesion molecule)[END_REF][START_REF] Van Kempen | Activated leukocyte cell adhesion molecule/CD166, a marker of tumor progression in primary malignant melanoma of the skin[END_REF], colorectal cancer [START_REF] Weichert | ALCAM/CD166 is overexpressed in colorectal carcinoma and correlates with shortened patient survival[END_REF], oral cancer [START_REF] Sawhney | Cytoplasmic accumulation of activated leukocyte cell adhesion molecule is a predictor of disease progression and reduced survival in oral cancer patients[END_REF], pancreatic carcinoma [START_REF] Kahlert | Increased expression of ALCAM/CD166 in pancreatic cancer is an independent prognostic marker for poor survival and early tumour relapse[END_REF] and esophageal carcinoma [START_REF] Verma | MEMD/ALCAM: a potential marker for tumor invasion and nodal metastasis in esophageal squamous cell carcinoma[END_REF]. In addition, metastatic clones of a mouse fibrosarcoma cell line are characterized by overexpression of ALCAM [START_REF] Choi | Activated leukocyte cell adhesion molecule (ALCAM) and annexin II are involved in the metastatic progression of tumor cells after chemotherapy with Adriamycin[END_REF]. In contrast, tumour progression in prostate cancer is associated with ALCAM down-regulation [START_REF] Kristiansen | ALCAM/CD166 is up-regulated in low-grade prostate cancer and progressively lost in high-grade lesions[END_REF], and in an immunohistochemical study, loss of membrane staining was associated with an unfavourable prognosis in ovarian cancer [START_REF] Mezzanzanica | Subcellular localization of activated leukocyte cell adhesion molecule is a molecular predictor of survival in ovarian carcinoma patients[END_REF].

Investigations on breast cancer samples revealed contradictory results: ALCAM mRNA overexpression was associated with better prognosis in one study [START_REF] King | Activated leukocyte cell adhesion molecule in breast cancer: prognostic indicator[END_REF], whereas ALCAM protein immunostaining (mainly cytoplasmic) was associated with poor survival in another cohort [START_REF] Burkhardt | Cytoplasmic overexpression of ALCAM is prognostic of disease progression in breast cancer[END_REF]. The lowest transcript levels were found in patients who developed bone metastasis [START_REF] Davies | Expression of the cell to cell adhesion molecule, ALCAM, in breast cancer patients and the potential link with skeletal metastasis[END_REF]. Our own analyses suggested that ALCAM might also have a predictive value in patients treated with conventional chemotherapy [START_REF] Ihnen | Predictive impact of activated leukocyte cell adhesion molecule (ALCAM/CD166) in breast cancer[END_REF].

In the light of these controversial results, we evaluated the role of ALCAM retrospectively in a larger cohort on a tissue microarray including 347 patients with analysis of disseminated tumour cells (DTC) in bone marrow and a median follow-up of 54.3 months, and by experimental studies using two breast cancer cell lines. Therefore, we generated stable clones with enhanced (MCF7) or reduced (MDA-MB231) ALCAM expression, which were compared to control cells in functional assays and by microarray analysis.

Materials and Methods

Cell lines and generation of stable transfectants

MDA-MB231 and MCF7 breast cancer cell lines were cultivated in DMEM/F-12 medium (Gibco/Invitrogen, Darmstadt, Germany) supplemented with 10% FCS, antibiotics and, for MCF7 cells, 10 g/ml insulin. The authenticity of our cells was validated by DSMZ GmbH (Braunschweig, Germany) before the beginning of the experiments. For generation of stable MCF7 cell clones with increased ALCAM expression, the OmicsLink ORF Expression Clone EX-H0002-M02 (GeneCopoeia, Germantown, Maryland) which contains the full-length ALCAM ORF was transfected into the cells, and stable transfectants were selected by addition of G418. For generation of MDA-MB231 cells with diminished ALCAM expression, the following sequences were synthesized and cloned into the pSilencer TM 3.1-H1 puro vector (Applied Biosystems / Ambion, Austin, TX, USA): 5'-GATCCAGTGTTCCCTGATAGACAATTCAAGAGATTGTCTATCAGGGAACACTGGTTTTTTG -GAAA-3' (top strand) and 5'-AGCTTTTCCAAAAAACCAGTGTTCCCTGATAGACAAT-CTCTTGAATTGTCTATCAGGGACACTG-3' (bottom strand). After transfection and selection of puromycin-resistant clones with reduced ALCAM expression as shown in western blots, the sequences of the constructs were verified by direct sequencing. As controls, stable transfections with the appropriate control vectors EX-EGFP-MO2 (GeneCopoeia; for MCF7) or the pSilencer 3.1-H1 puro negative control vector containing a hairpin siRNA with limited homology to any known human sequences (Ambion; for MDA-MB231) were performed, and the resultant, antibiotic-resistant cells were used as negative controls for our experiments (MCF7-NC and MDA-shNC).

Immunocytochemistry

For immunocytochemistry, cells were grown on chamber slides for two days, fixed at -20 o C in methanol for 10 min, then in acetone for 1 min. After rinsing in PBS, the sections were incubated with 10% horse serum (HS) containing 0.2% bovine serum albumin (BSA) for 15 min to block nonspecific binding sites, and incubated with the CD166/ALCAM specific antibody (1:300; Mab NCL-CD166, Novocastra Laboratories Ltd, Newcastle upon Tyne, UK) in PBS containing 1% HS and 0.2 % BSA for 1 h at room temperature. After washing, bound antibodies were visualized using the Vectastain Elite ABC kit (Vector Laboratories, Burlingame, CA, USA) and counterstained with hematoxylin.

Alternatively, the secondary antibody Alex488 (1:1000; Invitrogen-Molecular Probes, Karlsruhe, Germany) was applied for 60 min. Specimens were viewed and photographed either with a confocal microscope (Olympus Fluoview 1000, Olympus Deutschland GmbH Hamburg) or on a Zeiss Axioscope 40. Sections were coverslipped in ProLong Gold antifade reagent with DAPI (Invitrogen).

Functional assays

The invasive potential of the cells was tested with Matrigel TM Invasion Chambers (24-well plates; BD Biosciences, Heidelberg, Germany) according to the manufacturer's instructions with 25,000 cells per insert as described previously [START_REF] Schröder | The transcription factor Fra-2 promotes mammary tumour progression by changing the adhesive properties of breast cancer cells[END_REF]. After 48 h incubation, the cells which had passed the 8 m pores of the membranes were counted under a microscope in 7 identical square fields which together included most of the membrane area without the periphery. As controls, inserts without matrigel provided by the same manufacturer were used.

Motility was measured using a wound healing assay. After grown to confluence in 6-well plates, a band of cells was removed using a sterile pipet tip. Gap closure was monitored and the percentage of gap closure was estimated regarding the photographs made in regular intervals.

Apoptosis was shown by enrichment of nucleosomes in the cytoplasm of cells after addition of different concentrations of camptothecin (Cell Death Detection ELISA PLUS , Roche Diagnostics GmbH, Mannheim, Germany) according to the manufacturer's instructions, and by M30 CytoDeath immunostaining. For the latter assay, cells were incubated with or without 0.4 g/ml camptothecin for 16 hours. After trypsinization, cytospins with 200,000 cells per slide were prepared and fixed in solution B (Epimet, Micromet, Munich, Germany) for 10 min, washed in TBST and blocked with Protein Block (Serum-free, Dako, Glostrup, Denmark) for 20 min, before the monoclonal anti-M30 antibody (Cyto DEATH, Fluorescein; 1:200, Roche, Mannheim, Germany) was applied at RT for 60 min. After washing with PBS, slides were again incubated with Protein Block (Serum-free, Dako) for 20 min. Subsequently, the monoclonal antibody A45-B/B3 labelled with Cy3 (1:300, Micromet) was applied at RT for 45 min followed by washing with PBS. Finally slides were mounted with DAPI mounting medium. M30 staining was evaluated using a Zeiss Axioplan 2 fluorescence microscope and a 40x objective as number of apoptotic cells in at least 12 visual fields. All functional assays were performed at least 3 times.

RNA isolation and microarray analysis from cell lines

Isolation of total RNA, cDNA synthesis, labeling and hybridization to Affymetrix Human Genome GeneChip U133 Plus 2.0 were carried out as described [START_REF] Milde-Langosch | Role of Fra-2 in breast cancer: influence on tumor cell invasion and motility[END_REF]. To compare samples and experiments, the trimmed mean signal of each array was scaled to a target intensity of 200. Absolute and comparison analyses were performed with Affymetrix GCOS (version 1.4, Affymetrix) software using default parameters. For comparison analysis the implemented Wilcoxon's Signed Rank Test was used. From Wilcoxon's Signed Rank test one-sided p-values were computed for each probe set (cut off p-value: 0.003). To assist in the identification of genes that were positively or negatively regulated in the experiment, we selected genes that were increased or decreased at least 1.74 fold (SLR =/>0.8) compared to the control.

Western blot analysis and ELISA tests

General western blot conditions have been described [START_REF] Milde-Langosch | Role of Fra-2 in breast cancer: influence on tumor cell invasion and motility[END_REF]. For ALCAM detection and validation of differentially expressed genes, the following antibodies were used: ALCAM Mab NCL-CD166 (1:200; Novocastra), rabbit anti-Ets-2 antibody C20 (1:100; Santa Cruz Biotechnology, Heidelberg, Germany), mouse anti-NCAM-L1 (1:200, Santa Cruz), mouse anti-cathepsin D (1:500; Santa Cruz), mouse anti-CK7

(1:30000, Dako, ), and mouse anti-gelsolin antibody (1:30000; DAKO). As secondary antibodies, peroxidase-conjugated anti-mouse-IgG (1:2000) or anti-rabbit-IgG (1:4000; all from Santa Cruz) were used, which were visualized by chemiluminescence reagents (Super Signal West Pico kit, Pierce, Rockfort, Ill.) with Hyperfilm ECL films (Amersham, Braunschweig, Germany). VEGF-165 in cell lysates and supernatants was quantified by commercially available ELISA (Siemens Healthcare Diagnostics, Tarrytown, USA) according to the manufacturer's instructions.

Patients and Immunohistochemistry

In a retrospective study, immunohistochemistry was performed on a Tissue Microarray (TMA) containing samples of 411 breast cancer patients who were treated at the Hamburg University Medical School between 1999 and 2006. Included were all patients from this time period, from whom bone marrow had been taken and analysed for the presence of disseminated tumour cells (DTCs) as described [START_REF] Pantel | Methodological analysis of immunocytochemical screening for disseminated epithelial tumor cells in bone marrow[END_REF], based on availability of tumour material. The diagnosis including evaluation of histological type and grading had been performed by pathologists on whole formalin-fixed paraffinembedded tissue sections, and routine immunohistochemical determination of ER and PR status had been performed as described [START_REF] Bamberger | Expression pattern of the AP-1 family in breast cancer: association of fosB expression with a well-differentiated, receptor-positive phenotype[END_REF]. For TMA generation, 0.6mm cores were taken from invasive parts of the tumours which had been selected by a pathologist. After exclusion of all cases without remaining tissue on TMA sections after IHC or without tumour cells in the 0.6mm-core, 347 cases could be evaluated.

Patient data and tumour characteristics are described in table 3. The median age of the patients was prior to operation. Before surgery, informed consent for the scientific use of tissue materials had been obtained from the patients in coordination with the local ethics committee according to the principles of the declaration of Helsinki. REMARK criteria were used through this report [START_REF] Mcshane | REporting recommendations for tumor MARKer prognostic studies (REMARK)[END_REF].

Serial section of 8 µm were cut from the TMA blocks using an adhesive coated tape system (Tape-Transfer System, Instrumedics, Hackensack, New Jersey, USA), dewaxed with xylene and gradually hydrated. Heat-mediated antigen retrieval was achieved in hot 10mM citrate buffer (pH 6.0) for thirty minutes, washed and incubated in 0.5% H 2 O 2 -methanol solution for 30 min. For immunohistochemistry, the Vectastain Elite ABC mouse Kit (Vector Laboratories, Burlingame, CA, USA) was used according to the manufacturer's instructions with the monoclonal antibody to CD166

(ALCAM) clone MOG/07 (1:400; Vector Lab.) incubated overnight at 4°C. As negative control, the primary antibody was omitted in parallel sections, resulting in negative ALCAM results (not shown).

The ALCAM immunostaining was evaluated independently in a blinded fashion by two people using the immunoreactive score (IRS) as product of staining intensity (graded between 0 and 3) and percentage of positive cells (graded between 0 and 4; 1: 1-20%, 2: 21-50%; 3: 51-80%, 4:>80%) resulting in a score of 0-12. No differentiation between membraneous and cytoplasmic ALCAM staining was done. In case of differences between results, the samples were re-viewed and a consensus was achieved.

Statistical analysis

Correlations between ALCAM protein expression and histological or clinical tumour characteristics were calculated by Chi-square tests using the SPSS 15.0 software using groups described in Table 4.

For Kaplan-Meier analysis, overall survival (OAS) was computed from the date of diagnosis to the date of death due to distant metastasis. Kaplan-Meier survival curves were compared with the logrank test. Cox regression analysis was used to estimate Hazard ratios (HR) in uni-and multivariate analysis.

Results of functional assays were compared by T-tests. All tests were performed at a significance level of p=0.05, and all p values are two-sided.

Results

ALCAM expression inhibits migration, but enhances invasion of breast cancer cells

In order to evaluate the impact of high ALCAM expression on the biological properties of mammary cancer cells, experimental studies with two breast cancer cell lines were performed. In contrast to the highly invasive MDA-MB231 cells which are characterized by strong ALCAM expression as shown in Western blots, ALCAM amounts in untransfected, weakly invasive MCF7 cells are relatively low.

Therefore, MCF7 transfectants with ALCAM overexpression (clone # 1.3) as shown in western blots and two MDA-MB231 clones with strongly reduced ALCAM expression (# 14 and 9) were analyzed and compared to their respective controls. The localization of ALCAM proteins was demonstrated by immunocytochemistry. In MCF7-ALCAM cells, the adhesion molecule was localized in the cytoplasmic membranes in zones of cell-cell contacts, but not in membranes at the outer margins of cell clusters (Fig. 1a-b). In untransfected MDA-MB231 cells, ALCAM expression was also mainly found in regions of cell-cell contacts. Only little cytoplasmic staining was observed in both cell lines (Fig. 1a-b).

For all functional tests, at least 3 experiments were performed. With respect of proliferation, the transfected clones did not differ from their parental cells (not shown). In wound healing assays, migration of MDA-MB231 cells was enhanced 2-3 fold after ALCAM silencing by shRNA transfection (Fig. 1c). Accordingly, motility of MCF7 cells was diminished by 20-30% after ALCAM overexpression (Fig. 1d). In contrast, the invasive potential of MDA-MB231 cells as shown in matrigel invasion assays was strongly reduced in cells with ALCAM downregulation leading to a 80-90% reduction of invasive tumour cells, whereas there was no significant impact of ALCAM expression on cell invasion in MCF7 cells (Fig. 1e-f). In control inserts without matrigel, no significant influence of ALCAM expression on the number of cells passing the pores was found (not shown).

ALCAM expression correlates with apoptosis in breast cancer cells

Apoptosis was monitored by enrichment of nucleosomes after addition of different concentrations of camptothecin and by M30 CytoDeath immunoreactivity. The With both methods, the basal rate of apoptotic MCF7 cells was reproducibly higher in ALCAM transfectants compared to the control, although this difference did not reach statistical significance (Fig. 2a,c). The difference in the number of nucleosomes diminished after addition of higher concentration of camtothecin (>/= 0.4 g/ml) (Fig. 2a) whereas the number of M30-positive cells in the presence of camptothecin was significantly higher in ALCAM transfectants (Fig. 2c). In MDA-MB231, ALCAM downregulation was associated with a reduced percentage of apoptotic cells as shown by both methods. This difference persisted after addition of different concentrations of camptothecin (Fig. 2 b,d).

ALCAM influences expression of genes involved in cell invasion, adhesion and angiogenesis

For evaluation of gene expression data, a threshold expression value of 50 and a signal log ratio (SLR) of >/=0.8 or </=-0.8 was used. Using these parameters, 233 probesets (182 genes) with known function were up-regulated, and 65 genes (85 probesets) were down-regulated in MCF7-ALCAM cells. In MDA-MB231 cells, only genes that were regulated in both clones with diminished ALCAM expression were included, resulting in 156 genes (203 probesets) with decreased expression and 18 genes (20 probesets) with increased expression. Fifteen genes were both significantly up-regulated in Interestingly, overexpression of ALCAM results in up-regulation of additional adhesion molecules, namely NRCAM and CEACAM6 in MCF7 and L1-CAM and integrin ß5 in MDA-MB231 cells (table 2). In addition, ALCAM expression correlates with higher levels of some components of the extracellular matrix (ECM), i.e. fibronectin and different collagen isoforms. In MDA-MB231 cells, proteins involved in angiogenesis were down-regulated by ALCAM silencing (i.e. VEGF-A), and in both cell lines, regulators of apoptosis were affected by ALCAM expression. A list of the most important deregulated genes is shown in table 2.

The regulation of some ALCAM target genes was validated on protein level. By western blot analysis, the down-regulation of cytokeratin 7, cathepsin D, gelsolin, Ets2 and L1-CAM could be shown in MDA-MB231 cells, whereas only gelsolin and cytokeratin 7 up-regulation was validated in MCF7 cells (Fig. 3a). In MDA-MB231 clones with reduced ALCAM expression, both intracellular and secreted VEGF protein levels were diminished as shown by ELISA experiments (Fig. 3b). Similar to our RNA results, this could not be shown in MCF7 cells (Fig. 3c).

ALCAM overexpression is associated with poor prognosis in breast cancer patients

Since prior results concerning the prognostic impact of ALCAM expression were partly controversial, we decided to analyze ALCAM protein expression in a larger, independent cohort. The clinical and histological characteristics of the cohort (n=347) are shown in table 3. Since the subcellular localization of the immunoreactivity was not always clearly definable, we did not differentiate between membraneous and cytoplasmic staining. In 74 cases (21%), no ALCAM staining was observed in tumour cells. Weak staining (immunoreactive score 1-3) was shown in 136 tumours (39%), moderate staining (IRS 4-6) in 95 cases (27%) and in 42 patients (12%), strong staining (IRS 8-12) was observed (Fig. 3a-c).

For statistical analysis, three groups of ALCAM-negative cases, tumours with weak/moderate immunoreactivity (IRS 1-6) and cases with strong staining (IRS 8-12), respectively, were generated, since tumours with weak and moderate expression behaved similar (no significant differences). Using these groups, correlations with clinical and histological parameters were evaluated. There were highly significant positive associations with estrogen and progesterone receptor status (table 4). In contrast, the correlation with histological grading showed a bimodal distribution, with an over-representation of negative or strong ALCAM staining in poorly differentiated tumours. No significant associations with tumour stage, age, or histological type were found (not shown).

In addition to lymph node involvement, the presence of disseminated tumour cells in bone marrow is a potential risk factor for metastatic relapse in breast cancer [START_REF] Braun | A pooled analysis of bone marrow micrometastasis in breast cancer[END_REF]. In our cohort, ALCAM overexpression correlated significantly with nodal involvement (p=0.006), and there was a tendency pointing to a higher rate of tumour cells in bone marrow in these patients (p=0.084; table 4).

By Kaplan-Meier analysis (median follow-up time 54.3 months), high ALCAM staining (IRS 8-12)

was associated with shorter overall survival compared to patients with low/moderate ALCAM scores (p=0.021, Fig. 4). ALCAM-negative tumours had an intermediate position. In terms of recurrence-free survival, tumours with negative or weak/moderate results (ALCAM score 0-6) had a better prognosis compared to those with ALCAM overexpression, but this difference was statistically not significant (p= 0.279).

By stratification according to histological tumour type, we could show that the prognostic impact of ALCAM overexpression was more clear-cut in ductal carcinomas (OAS: p=0.003; RFS: p=0.048; Fig. 4), whereas in other types, no significant prognostic value was found (not shown). After further stratification according to endocrine or chemotherapy, no significant differences in RFS or OAS according to ALCAM levels in the respective subgroups were found (not shown).

For univariate Cox regression analysis, patients with negative and weak/moderate ALCAM staining were combined and compared to cases with ALCAM overexpression. Thus, a significant prognostic effect of overexpression on RFS (HR = 2.47, 95% CI: 1.17 -5.22, p=0.018) and OAS (HR = 4.32, 95% CI: 1.61 -11.56, p=0.004) was seen in ductal carcinomas. In the total cohort, the prognostic effect was not (RFS) or only marginally significant (OAS: HR = 2.34, 95% CI: 1.01 -5.39, p=0.047).

By multivariate analysis including stage, nodal involvement, grading, ER status and the presence of DTCs, the prognostic effect of ALCAM on RFS in ductal carcinomas curtly missed significance (p=0.050; table 5).

Since in most studies, the median expression level was used as cut-off value, we performed the same analysis with two groups of similar size (IRS 0-2: n=174; IRS 3-12: n=173). By this approach, no significant correlations with clinical or histological parameters and disease outcome were found except an association of high ALCAM expression with nodal involvement (p=0.006; not shown).

Discussion

Although ALCAM expression has been shown in various tumour types, there is only limited knowledge about the biological role of this adhesion molecule in cancer cells. In order to evaluate the effects of ALCAM expression in breast cancer cells in more detail, we performed functional assays with two cell lines. In both MDA-MB231 and MCF7 cells, high ALCAM levels were associated with a reduced motility in wound healing assays, which corresponds to results obtained with other experimental systems: In endothelial-like yolk sac cells and human microvascular endothelial cells, ALCAM inhibited migration, but enhanced tube formation on matrigel [6]. Inhibition of ligand binding and of network formation by overexpression of a short secreted (s)ALCAM variant reverted this effect. Thus, escape of tumour cells from the tumour mass might be facilitated by loss of ALCAM-mediated cell-cell contacts.

Interestingly, ALCAM enhanced the invasive potential of the hormone-receptor-negative MDA-MB231 cells. This corresponds to the aggressive nature of tumours with strong ALCAM immunostaining in our cohort of 347 patients, shown by lymph node involvement and shorter RFS and OAS. A role of ALCAM in cell invasion has been reported in melanoma cells where inhibition of ALCAM clustering by (s)ALCAM overexpression reduced invasion in a reconstituted skin model.

Moreover, cells with (s)ALCAM expression were attenuated in metastasis frequency in a xenograft mouse model [START_REF] Van Kilsdonk | Attenuation of melanoma invasion by a secreted variant of activated leukocyte cell adhesion molecule[END_REF]. Similar to melanomas [START_REF] Swart | Activated leukocyte cell adhesion molecule (ALCAM/CD166): signaling at the divide of melanoma cell clustering and cell migration?[END_REF], ALCAM might function as a cell surface sensor in breast cancer cells which regulates dynamic responses at high cell densities leading to enhanced invasion into the surrounding tissue.

Apoptosis was positively influenced by ALCAM in both cell lines. This might result in an increased chemoresistance in these cells and corresponds well with our observations on clinical tumour tissues where high ALCAM levels are associated with better prognosis in chemotherapy-treated patients [START_REF] Ihnen | Predictive impact of activated leukocyte cell adhesion molecule (ALCAM/CD166) in breast cancer[END_REF] .

In order to identify changes in gene expression which are induced by high ALCAM levels, cDNA microarrays were performed. Among the genes which are deregulated in both MDA-MB231 and MCF7 cells, there was an overlap of 15 genes. Among those, cathepsin D might be involved in enhanced invasiveness of ALCAM-expressing MDA-MB231 cells. This aspartic protease is an independent predictor of early metastasis and shorter survival in mammary carcinomas [START_REF] Liaudet-Coopman | Cathepsin D: newly discovered functions of a longstanding aspartic protease in cancer and apoptosis[END_REF][START_REF] Ohri | The propeptide of cathepsin D increases proliferation, invasion and metastasis of breast cancer cells[END_REF]. Most other genes which were deregulated in both cell lines have also been shown to be associated with tumourigenesis and tumour progression, e.g. PLAC1 [START_REF] Koslowski | A placentaspecific gene ectopically activated in many human cancers is essentially involved in malignant cell processes[END_REF], amphiregulin (AREG) [START_REF] Willmarth | Altered EGFR localization and degradation in human breast cancer cells with an amphiregulin/EGFR autocrine loop[END_REF], cytokeratin 7 [START_REF] Tot | Cytokeratins 20 and 7 as biomarkers: usefulness in discriminating primary from metastatic adenocarcinoma[END_REF], RUNX2 [START_REF] Pratap | The Runx2 osteogenic transcription factor regulates matrix metalloproteinase 9 in bone metastatic cancer cells and controls cell invasion[END_REF][START_REF] Shore | A role for Runx2 in normal mammary gland and breast cancer bone metastasis[END_REF][START_REF] Akech | Runx2 association with progression of prostate cancer in patients: mechanisms mediating bone osteolysis and osteoblastic metastatic lesions[END_REF], STMN3 [START_REF] Singer | Coordinated expression of stathmin family members by far upstream sequence element-binding protein-1 increases motility in non-small cell lung cancer[END_REF], gelsolin [START_REF] Bartkowiak | Two-dimensional differential gel electrophoresis of a cell line derived from a breast cancer micrometastasis revealed a stem/ progenitor cell protein profile[END_REF] and fibronectin [START_REF] Ioachim | Immunohistochemical expression of extracellular matrix components tenascin, fibronectin, collagen type IV and laminin in breast cancer: their prognostic value and role in tumour invasion and progression[END_REF][START_REF] Helleman | Association of an extracellular matrix gene cluster with breast cancer prognosis and endocrine therapy response[END_REF]. Another target gene, the transcription factor Ets2, is frequently up-regulated in breast cancer [40] [41],. The enhanced apoptotic potential of cells with high ALCAM expression is in accordance with the increased expression of some pro-apoptotic genes in both cell lines (table 2). In contrast to others [START_REF] Jezierska | ALCAM/CD166 protects breast cancer cells against apoptosis and autophagy[END_REF], we did not observe an influence of ALCAM on BCL2 expression. Thus, the influence of ALCAM on apoptosis and chemoresistance should be further analyzed.

A high number of genes was deregulated in only one cell line. In MDA-MB231 cells, ALCAM silencing leads to reduced VEGF expression. A positive influence of ALCAM on angiogenesis has been shown in studies on endothelial cells [6] and in other experimental systems [START_REF] Chen | The gene expression profile induced by Wnt 3a in NIH 3T3 fibroblasts[END_REF]. Moreover, comparison of gene expression profiles of ALCAM-positive, metastatic melanoma cell lines versus ALCAM-negative cell lines showed overexpression of VEGF [START_REF] Swart | Activated leukocyte cell adhesion molecule (ALCAM/CD166): signaling at the divide of melanoma cell clustering and cell migration?[END_REF]. The influence of ALCAM on cell invasion in MDA-MB231 cells also corresponds to its effect on expression of the adhesion molecule L1-CAM, which has been shown to enhance invasiveness of other cells [START_REF] Gavert | L1, a novel target of beta-catenin signaling, transforms cells and is expressed at the invasive front of colon cancers[END_REF][START_REF] Meier | The adhesion molecule L1 (CD171) promotes melanoma progression[END_REF] and is a negative prognostic parameter in mammary carcinomas [START_REF] Schroder | Expression and prognostic value of L1-CAM in breast cancer[END_REF].

The signalling pathways which lead to changes in expression of these genes are still unclear, and further studies are required to elucidate these mechanisms. In other investigations, most of the biological functions of ALCAM could be blocked by inhibition of ALCAM network formation which implies the presence and importance of membraneous ALCAM protein [START_REF] Van Kilsdonk | Attenuation of melanoma invasion by a secreted variant of activated leukocyte cell adhesion molecule[END_REF]. Whether similar pathways can also be activated by intracellular ALCAM which is observed in many tumours [START_REF] Burkhardt | Cytoplasmic overexpression of ALCAM is prognostic of disease progression in breast cancer[END_REF], should be further analysed.

In prior studies on the role of ALCAM in breast cancer, contradictory results indicating associations with good prognosis [START_REF] King | Activated leukocyte cell adhesion molecule in breast cancer: prognostic indicator[END_REF][START_REF] Jezierska | Activated Leukocyte Cell Adhesion Molecule (ALCAM) is associated with suppression of breast cancer cells invasion[END_REF] or poor outcome [START_REF] Burkhardt | Cytoplasmic overexpression of ALCAM is prognostic of disease progression in breast cancer[END_REF][START_REF] Ihnen | Predictive impact of activated leukocyte cell adhesion molecule (ALCAM/CD166) in breast cancer[END_REF] have been reported. This might be partially due to different technical or statistical approaches. In our immunohistochemical study, we differentiated between negative, weak/moderate and strong ALCAM expression, and found the worst outcome in cases with strong ALCAM staining (Fig. 3). If only two groups were analysed with the median ALCAM expression as cut-off value, no significant differences were found indicating that the results of ALCAM studies might be influenced strongly by the selected cut-off for statistical analysis.

By our approach, we could show the previously reported correlation of ALCAM expression with an ER-/PR-positive phenotype which suggests an association with a more differentiated phenotype. On the other hand, strong ALCAM expression was associated with nodal involvement and shorter recurrence-free and overall survival, especially in ductal carcinomas. The presence of disseminated tumour cells (DTC) is a surrogate parameter of hematogenous tumour cell spread [START_REF] Pantel | Cancer micrometastases[END_REF]. We observed an association of the presence of DTC with ALCAM expression which was not significant, probably due to the low incidence of DTC in patients with primary breast cancer applying restrictive evaluation criteria.

A potential limitation of our immunohistochemical study is that the patients were not uniformly treated and that we have no untreated cohort. Therefore, we are not able to differentiate between prognostic and predictive effects of ALCAM expression in this cohort. In addition, the analysis of additional breast cancer cell lines would be interesting since the role of ALCAM is probably dependent on the tumour cell type.

In the present study, the first functional analysis of the role of ALCAM in breast cancer cells is presented and correlated with data from human tumour tissues. In conclusion, our results indicate that the biological role of ALCAM in breast cancer cells is complex and partially dependent on the tumour cell type. The effects of strong ALCAM overexpression on the biology of breast cancer cells might include decreased motility, enhanced invasive potential, and increased apoptosis. This might partly explain the contradictory results obtained with breast cancer samples where ALCAM was associated either with a positive or a negative prognosis [START_REF] King | Activated leukocyte cell adhesion molecule in breast cancer: prognostic indicator[END_REF][START_REF] Burkhardt | Cytoplasmic overexpression of ALCAM is prognostic of disease progression in breast cancer[END_REF][START_REF] Ihnen | Predictive impact of activated leukocyte cell adhesion molecule (ALCAM/CD166) in breast cancer[END_REF][START_REF] Jezierska | Activated Leukocyte Cell Adhesion Molecule (ALCAM) is associated with suppression of breast cancer cells invasion[END_REF]. In a recent study, a human antibody phage library was screened for cancer-specific antibodies, resulting in an ALCAM-binding scFV antibody which inhibited invasiveness of MDA-MB231 cells and showed anti-tumour activity in an in-vivo mouse colorectal carcinoma model [START_REF] Wiiger | A novel human recombinant single-chain antibody targeting CD166/ALCAM inhibits cancer cell invasion in vitro and in vivo tumour growth[END_REF]. In the light of the possible importance of ALCAM as target for cancer therapies, our results allow further insights into the biology of ALCAM in breast cancer.

58. 1

 1 years (range 27.5 -85.0 years), and the median follow-up time was 54.3 months (range 0.1 -103.5 months). Patients received endocrine treatment and/or taxane-free chemotherapy according to national guidelines. No therapy like radiotherapy or neoadjuvant chemotherapy had been performed

MCF7-

  ALCAM and down-regulated in MDA-shALCAM cells. The encoded proteins include factors involved in proteolysis (cathepsin D, PRSS23), signal transduction and transcriptional regulation (amphiregulin, Runx2, Ets2, Stmn3), components of the cytoskeleton (filamin A, cytokeratin 7, gelsolin) and extracellular matrix (fibronectin), and others (Plac1, SH3BGRL, IDS, PRICKLE2, SLC16A4; tables 1-2).

Fig. 1

 1 Fig. 1 Characterization of stably transfected MCF7 and MDA-MB231 cells with enhanced or down-

Fig. 2 Fig. 3

 23 Fig. 2 Influence of ALCAM expression on apoptosis in MCF7 and MDA-MB231 cells with enhanced

  . Differentially regulated genes which were validated by western blot analysis or ELISA are shown in bold.

Table 1 . Genes deregulated by ALCAM overexpression in MCF7 and/or ALCAM silencing in MDA-MB231 cells: subdivision into functional groups

 1

	Function of gene products	MCF7-ALCAM	MDA-shALCAM
		Increase Decrease Increase	Decrease
	adhesion	5	1	0	11
	angiogenesis	1	0	0	7
	apoptosis	7	3	1	8
	cell cycle	4	5	3	3
	cytoskeleton	9	0	1	8
	development	6	0	0	4
	ECM	7	4	0	3
	immune response	4	3	1	7
	kinase/phosphatase	2	0	0	6
	metabolism	21	11	0	20
	proteolysis	9	0	0	3
	signal transduction	31	6	1	14
	transcriptional regulation	18	15	3	13
	transport	17	9	4	16
	others	41	8	4	33
	total	182	65	18	156

Table 2 .

 2 Differentially regulated genes in MCF7-ALCAM and MDA-MB231-shALCAM clones.

					SLR	SLR
		Gene			MCF7-	MDA-
	Probe Set ID	Symbol	Gene Title	function	ALCAM	shALCAM
	Genes deregulated in both cell lines
	202458_at	PRSS23	protease, serine, 23	proteolysis	2.9	a	-0.9
	219702_at	PLAC1	placenta-specific 1	development	1.8	-1.3
	200766_at	CTSD	cathepsin D	proteolysis	1.4	-0.8
	205234_at	SLC16A4	solute carrier family 16, member 4	transport	1.4	-1.1
				transcriptional
	232231_at	RUNX2	runt-related transcription factor 2	reg.	1.3	-0.8
				signal
	205239_at	AREG	amphiregulin /// amphiregulin B	transduction	1.3	-1.1
	211719_x_at	FN1	fibronectin 1	ECM	1.3	-1.5	d
				signal
	222557_at	STMN3	stathmin-like 3	transduction	1.1	-1
	225968_at	PRICKLE2	prickle homolog 2 (Drosophila)	ion binding	1.0	-0.9
	201312_s_at	SH3BGRL	SH3 domain binding glutamic acid-rich protein like	others	1.0	a	-1.5
	201328_at	ETS2	v-ets erythroblastosis virus E26 oncogene homolog 2	transcriptional reg.	0.9	a	-0.8
	202439_s_at	IDS	iduronate 2-sulfatase	metabolism	0.9	a	-1.0	a
	214752_x_at	FLNA	filamin A, alpha	cytoskeleton	0.8	a	-0.8
	209016_s_at	KRT7	keratin 7	cytoskeleton	0.8	-0.8
	200696_s_at	GSN	gelsolin	cytoskeleton	0.8	-0.9
	Genes involved in proteolysis
	208683_at	CAPN2	calpain 2, (m/II) large subunit	proteolysis	1.7
	201666_at	TIMP1	TIMP metallopeptidase inhibitor 1	proteolysis	1.4
	201117_s_at	CPE	carboxypeptidase E	proteolysis	1.2	a
	Genes involved in angiogenesis
			tumour necrosis factor, alpha-induced protein
	202510_s_at	TNFAIP2	2	angiogenesis				-1.0
	210512_s_at	VEGFA	vascular endothelial growth factor A	angiogenesis				-1.1	a
	231183_s_at	JAG1	Jagged 1 (Alagille syndrome)	angiogenesis				-1.3	c
	200878_at	EPAS1	endothelial PAS domain protein 1	angiogenesis				-1.3
	Genes involved in adhesion
	204105_s_at	NRCAM	neuronal cell adhesion molecule	adhesion	1.9
			carcinoembryonic antigen-related cell
	211657_at	CEACAM6	adhesion molecule 6	adhesion	1.7
	203953_s_at	CLDN3	claudin 3	adhesion	-1.0	a
	203323_at	CAV2	caveolin 2	adhesion				-0.9
	212070_at	GPR56	G protein-coupled receptor 56	adhesion				-0.9
	204584_at	L1CAM	L1 cell adhesion molecule	adhesion				-0.9
	201124_at	ITGB5	integrin, beta 5	adhesion				-1.1
			transforming growth factor, beta-induced,
	201506_at	TGFBI	68kDa	adhesion				-1.4
	227566_at	HNT	neurotrimin	adhesion				-3.6
	Genes involved in apoptosis
			caspase 8, apoptosis-related cysteine
	213373_s_at	CASP8	peptidase	apoptosis	1.4
	209406_at	BAG2	BCL2-associated athanogene 2	apoptosis	1.3
	215719_x_at	FAS	Fas (TNF receptor superfamily, member 6)	apoptosis	0.9
	204595_s_at	STC1	stanniocalcin 1	apoptosis				-1.0	b
	201849_at	BNIP3	BCL2/adenovirus E1B 19kDa interacting protein 3	apoptosis				-1.1	a
	221666_s_at	PYCARD	PYD and CARD domain containing	apoptosis				-1.3
	202887_s_at	DDIT4	DNA-damage-inducible transcript 4	apoptosis				-1.3
	205207_at	IL6	interleukin 6 (interferon, beta 2)	apoptosis				-1.7

Table 4 . ALCAM protein expression in breast cancer patients: correlations with clinical and histological tumour characteristics

 4

			ALCAM	ALCAM	ALCAM	p=
	n	a	IRS 0	IRS 1-6	IRS 8-12

a

, missing patients to n=347: no data. Tumours with missing values were excluded from the single analysis.

Table 5 : Cox regression analysis including conventional prognostic markers, presence of DTC in bone marrow and ALCAM overexpression in ductal breast cancer

 5

	Overall survival
		HR	95% CI	p value
	ALCAM 1	2.98	0.94-9.53	0.065
	grading	1.72	0.59-5.07	0.322
	stage	0.79	0.35-1.75	0.556
	ER status	0.45	0.15-1.33	0.149
	Lymph node status	2.62	0.88-7.81	0.084
	Bone marrow status	3.68	1.40-9.67	0.008
	Recurrence-free survival
	ALCAM 1	2.30	1.00-5.27	0.050
	grading	1.77	0.87-3.59	0.115
	stage	1.12	0.67-1.87	0.673
	ER status	1.57	0.68-3.66	0.294
	Lymph node status	1.99	0.98-4.03	0.057
	Bone marrow status	2.94	1.50-5.77	0.002

1

, two groups corresponding to IRS 0-6 and 8-12 were compared. Other groups used for analysis: see table

3

.

Acknowledgements

This work was kindly supported by the Wilhelm-Sander-Stiftung, Munich, and by the Burkhard Meyer foundation, Hamburg (Grants to K. Milde-Langosch and V. Müller). We thank Kristin Klätschke for excellent technical assistance with the microarray analysis.

Conflict of interest

The authors declare that there are no conflicting interests.


Prof. Dr Andreas Ziegler
email: ziegler@imbs.uni-luebeck.de

Kristel Van Steen

Stefan Wellek

Investigating Hardy-Weinberg equilibrium in case-control or cohort studies or meta-analysis

Keywords: Disequilibrium coefficient, Meta-analysis, Quality control, Relative excess heterozygosity

Purpose: Yu et al. [2009 Breast Cancer Res Treat 117:675-677] recently stated that testing for deviation from Hardy-Weinberg equilibrium (HWE) is necessary to identify systematic genotyping errors in case-control studies. They criticized a meta-analytic study for the deviation from HWE in the case group of one study. The aim of this paper is two-fold. First, we derive recommendations on how to test for deviations from HWE in different study designs. Second, we develop a meta-analytic framework for assessing compatibility with HWE or measuring deviation from HWE.

Methods: We sketch possible reasons behind deviation from HWE and provide guidelines for proper investigation of HWE deviations in different study designs. We argue that the standard HWE χ 2 lack of fit test is logically flawed and provide a logically unflawed approach for measuring deviation from HWE using confidence intervals. Our method is applicable to the meta-analysis of both case-control or cohort association studies. We illustrate our approach using the meta-analysis criticized by Yu et al.

Results:

In case-control studies, deviation from HWE should only be investigated in controls.

In population-based cohort studies, deviation from HWE should be investigated using the entire sample. A simple meta-analytic framework based on confidence intervals is available for investigating deviation from HWE and establishing compatibility with HWE.

Heterogeneity between studies can be assessed. The critique of Yu et al. on the paper of Frank et al. [2008 Breast Cancer Res Treat 111:139-144] can be refuted. Even more, validity of HWE can be proven for the pooled control sample.

Conclusions:

We advocate the use of a confidence interval-based approach to assess HWE.

The latter should only be investigated in control populations. In multicentre studies or metaanalysis, deviation from HWE should be analyzed using a meta-analytic approach.

Introduction

The law of Hardy-Weinberg states that a diallelic marker having allele frequencies and , is in equilibrium if and only if the proportion of subjects with genotypes AA, Aa, and aa will be , , and . Departure from Hardy-Weinberg equilibrium (HWE) can be caused by factors such as inbreeding caused by consanguinity, assortative mating, i.e., non-random mating, selection, or migration [START_REF] Ziegler | A Statistical Approach to Genetic Epidemiology: Concepts and Applications. With an e-learning course by Friedrich Pahlke[END_REF]. In most human populations the effect of these causes on HWE will be small [START_REF] Minelli | How should we use information about HWE in the meta-analyses of genetic association studies?[END_REF] although selection plays an important role in infectious diseases. Other causes which are discussed in the literature to a greater extent are population stratification and copy number variation. Population stratification always leads to a deficit of heterozygotes, while copy number variation can lead to an excess of heterozygosity (homozygote deficit).

Deviation from HWE (Hardy-Weinberg disequilibrium; HWD) in genetic association studies occurs in two different ways. First, population genetic causes leading to a deviation from HWE generally play a minor role in genetic association studies, with the exception of population stratification. However, the latter can be controlled by using appropriate methods, such as genomic control (for a detailed overview, see, e.g, Ref. [START_REF] Ziegler | A Statistical Approach to Genetic Epidemiology: Concepts and Applications. With an e-learning course by Friedrich Pahlke[END_REF]). The first standard source for deviation from HWE therefore is genotyping error.

Second, if the entire population is in perfect HWE, the presence of a genetic association, i.e., a difference in genotype frequencies between cases and controls implies that neither cases nor controls can be in HWE [START_REF] Wittke-Thompson | Rational inferences about departures from Hardy-Weinberg equilibrium[END_REF]. Because the proportion of affected subjects in a population is small, the degree of deviation from HWE is expected to be stronger in cases than in controls.

Even more, Lee [START_REF] Lee | Searching for disease-susceptibility loci by testing for Hardy-Weinberg disequilibrium in a gene bank of affected individuals[END_REF] proposed to scan the genome for disease susceptibility genes by testing for HWD in affected individuals, and several colleagues proposed to incorporate a HWD measure in the genetic association test [START_REF] Hoh | Trimming, weighting, and grouping SNPs in human casecontrol association studies[END_REF][START_REF] Song | A powerful method of combining measures of association and Hardy-Weinberg disequilibrium for fine-mapping in case-control studies[END_REF].

Therefore, as an indicator of genotyping quality, compatibility with HWE should be investigated in control groups only. In cohort studies no deviation from HWE is expected, and therefore the entire sample should be genotyped for assessing HWD.

In a recent publication in this journal, Yu et al. [START_REF] Yu | Test of Hardy-Weinberg equilibrium in breast cancer case-control studies: an issue may influence the conclusions[END_REF] First, they applied the standard procedure to assess HWE, i.e., a χ 2 test of goodness-of-fit. The null hypothesis of this test is that the locus genotype distribution is in HWE. Thus, a significant result indicates incompatibility of the observed data with HWE. However, the aim generally is to statistically show the validity of HWE. In current practice, investigators try to avoid this logical difficulty by increasing the significance bound to the p-value (e.g., from 0.05 to 0.10). Compatibility of the data with HWE is then inferred from a non significant result. Unfortunately, such direct inversion of a statistical testing procedure is not valid for establishing the alternative hypothesis that the data are in sufficiently good agreement with HWE.

Second, Frank et al. tested genetic association by pooling the results of four case-control studies. However, they investigated HWD separately for each control group. These data were not pooled, and the authors did not analyze possible heterogeneity in HWD between study groups.

In this paper we present solutions for these problems. Specifically, we use a logically unflawed solution to the problem of establishing compatibility with HWD which we have developed recently [START_REF] Wellek | A confidence-limit-based approach to the assessment of Hardy-Weinberg equilibrium[END_REF]. We extend this approach to the meta-analytic situation and illustrate it by re-analyzing the data of Frank et al. We demonstrate that the critique of Yu et al. can be refuted. Validity of HWE in the pooled control sample can be demonstrated.

Methods

Measuring the degree of deviation from Hardy-Weinberg equilibrium

To assess HWD by using measures of degree of HWD instead of the p-value approach from classical χ 2 goodness-of-fit test statistics has been proposed recently [START_REF] Wellek | A confidence-limit-based approach to the assessment of Hardy-Weinberg equilibrium[END_REF]. An overview on measures of the degree of HWD is provided, e.g., in Ref. [START_REF] Ziegler | A Statistical Approach to Genetic Epidemiology: Concepts and Applications. With an e-learning course by Friedrich Pahlke[END_REF]. We have argued that the relative excess heterozygosity (REH) estimated by is the most reasonable statistical measure of HWD, and we therefore prefer it over the disequilibrium coefficient

. The REH has a simple genetic interpretation because it reflects the degree of HWD by the extent to which the actual proportion of heterozygotes differs from the proportion of heterozygotes expected in a population which exactly conforms to HWE. The asymptotic confidence interval of the REH was derived using and its variance . In detail, an asymptotic confidence interval for ω is given by , where denotes an upper quantile of the standard normal distribution. To test for deviation from HWE, the 5% testlevel and a two-sided confidence interval are commonly used in candidate gene studies, while a pair of one-sided 95% confidence bounds is calculated for establishing compatibility with HWE. We [START_REF] Wellek | A confidence-limit-based approach to the assessment of Hardy-Weinberg equilibrium[END_REF] have argued that the data are sufficiently good agreement with HWE when the corresponding equal-tails confidence interval of two-sided level 90 % is within the interval 5/7 0.7143 to 7/5 1.400.

Deviation from Hardy-Weinberg equilibrium in meta-analysis

Detecting HWD by pooling over different studies has been discussed extensively in the literature [START_REF] Nam | Testing a genetic equilibrium across strata[END_REF][START_REF] Olson | Testing the Hardy-Weinberg law across strata[END_REF][START_REF] Olson | Testing for homogeneity of Hardy-Weinberg disequilibrium using data sampled from several populations[END_REF][START_REF] Schaid | Exact tests of Hardy-Weinberg equilibrium and homogeneity of disequilibrium across strata[END_REF][START_REF] Troendle | A note on testing the Hardy-Weinberg law across strata[END_REF]. However, only statistical tests were considered; confidence intervals and estimates of heterogeneity which are standard in modern meta-analysis have not been

provided.

An important aspect is the choice of an appropriate measure for assessing HWD in a metaanalysis. Specifically, Olson [START_REF] Olson | Testing the Hardy-Weinberg law across strata[END_REF] noted that the disequilibrium coefficient is not constant across studies when the allele frequency varies over studies. Therefore, she and others [START_REF] Troendle | A note on testing the Hardy-Weinberg law across strata[END_REF] preferred the use of , i.e., the squared REH for statistical tests in meta-analysis. We note that all these authors were not interested in interpreting the degree of deviation the metaanalytic setting. As a result, of study is an appropriate measure of HWD for metaanalysis. Its estimator is . The weighted average in the traditional fixed effect model is calculated as , where . The variance of is estimated by

. The random effects model can be defined similarly [START_REF] Higgins | Quantifying heterogeneity in a meta-analysis[END_REF] using weights, the pooled estimator , and its variance estimated by .

A test of the homogeneity of the can be performed using Cochran's , which is asymptotically distributed with d.f. is obtained using the DerSimonian and Laird approach as .

Heterogeneity between studies can be quantified using or . An asymptotically valid confidence interval for is given by , where is the estimated standard error or . The asymptotic confidence interval for are readily available from the confidence interval for .

Data analysis

Details on the study of Frank et al. are provided in Ref. [START_REF] Frank | The CASP8 -652 6N del promoter polymorphism and breast cancer risk: a multicenter study[END_REF]. We estimated REH and asymptotic two-sided 95% confidence intervals for every control group of the study. A fixed effects meta-analysis was performed over all four control groups. The REH and its asymptotic two-sided 95% confidence interval were calculated. Heterogeneity between studies was assessed using and its two-sided asymptotic 95% confidence interval. To make the calculations for both the fixed effects model and the random effects model traceable, we have created an Excel tool (supplementary material).

Results

Table 1 summarizes the results of both the fixed effects and the random effects meta-analysis for HWE in the control groups. When all control groups were analyzed separately, only a weak deviation of the REH from its expected value 1 was observed. Even more, all two-sided 95% confidence intervals included one which represents the value of perfect agreement with HWE. This means that no deviation from HWE could be detected at the 5% test-level.

Even more, all lower and upper limits of equal-tails 90% confidence intervals are within the interval 5/7 0.7143 to 7/5 1.400 which has been shown to be the appropriate equivalence margin for establishing compatibility with HWE [START_REF] Wellek | A confidence-limit-based approach to the assessment of Hardy-Weinberg equilibrium[END_REF]. As a result, for all four individual studies HWE holds at the 5% test-level.

When the studies were analyzed jointly using the meta-analytic approach proposed above, the first finding was that results from fixed effects and random effects meta-analysis were similar.

The REH of the fixed effects model was 1.0144, and the equal-tails 90% confidence interval ranged from 0.9665 to 1.0629. We calculated the heterogeneity between studies to be = 6.25% (95% confidence interval 0.00%-60.39%). Thus, the heterogeneity between studies was very low according to Ref. [START_REF] Huedo-Medina | Assessing heterogeneity in meta-analysis: Q statistic or I2 index?[END_REF].

Discussion

In genome-wide association (GWA) studies, testing for deviation from HWE is a standard quality control filter [19]. While it should be used for the entire sample in a cohort study, in case-control studies it should only be applied to controls because a deviation from HWE in cases may indicate a genetic association. However, to detect genotyping errors, repeated genotyping of the same probands is preferable over HWE testing. Unfortunately, it is costly, and it only reveals specific genotyping errors that are caused by technical artifacts.

Specifically, it will not identify other errors such as sample swap.

Although testing for HWD in cases is not meaningful for quality control, Yu et al. [START_REF] Yu | Test of Hardy-Weinberg equilibrium in breast cancer case-control studies: an issue may influence the conclusions[END_REF] criticized Frank et al. [START_REF] Frank | The CASP8 -652 6N del promoter polymorphism and breast cancer risk: a multicenter study[END_REF] who explicitly stated in the Methods section that they checked for HWD in controls. These authors performed the χ 2 goodness-of-fit test with 1 d.f. separately for each study. Although this approach is the commonly applied one to show that the data are in sufficiently good agreement with HWD, it is logically flawed. Many tests have been devised to determine whether a finite population follows Hardy-Weinberg proportions.

However, the most classical way to check HWD is to compare observed to expected genotype frequencies using a formal χ 2 testing procedure. It has been shown by Guo and Thompson [START_REF] Guo | Performing the exact test of Hardy-Weinberg proportion for multiple alleles[END_REF] that asymptotic tests can fail. And even for large samples, as in the presence of multi-allelic markers [START_REF] Guo | Performing the exact test of Hardy-Weinberg proportion for multiple alleles[END_REF], exact testing procedures are advocated. Exact testing is a tedious job and may be computationally intensive, despite several efforts to speed up the exact testing procedure using improved Monte-Carlo algorithms [START_REF] Huber | Monte Carlo algorithms for Hardy-Weinberg proportions[END_REF]. The one-sided confidence interval approach [START_REF] Wellek | A confidence-limit-based approach to the assessment of Hardy-Weinberg equilibrium[END_REF] offers a statistically sound alternative to investigate HWE.

For estimation, we have used the relative excess heterozygosity (REH). Other measures include the inbreeding coefficient which is also termed fixation coefficient, and the disequilibrium coefficient [START_REF] Ziegler | A Statistical Approach to Genetic Epidemiology: Concepts and Applications. With an e-learning course by Friedrich Pahlke[END_REF]. However, both measures depend on the allele frequency of the SNP, and we therefore suggest using the REH as measure of HWD.

In this paper, we have extended the confidence interval method for HWE to the meta-analytic situation of Frank et al. [START_REF] Frank | The CASP8 -652 6N del promoter polymorphism and breast cancer risk: a multicenter study[END_REF]. We were able to show that all their control groups and the overall sample were in sufficiently good agreement with HWE. Furthermore, the I 2 measure of heterogeneity indicated that the relative excess heterozygosity in the control groups was very homogeneous across the different studies.

In conclusion, we have refuted the critique of Yu et al. [START_REF] Yu | Test of Hardy-Weinberg equilibrium in breast cancer case-control studies: an issue may influence the conclusions[END_REF] on the study of Frank et al. [START_REF] Frank | The CASP8 -652 6N del promoter polymorphism and breast cancer risk: a multicenter study[END_REF] by using population genetic arguments. Furthermore, we have derived an approach for investigating deviation from HWE in meta-analyses of small candidate gene studies or even huge consortia of GWA studies. a Relative excess heterozygosity b Asymptotic 95% confidence interval according to [START_REF] Wellek | A confidence-limit-based approach to the assessment of Hardy-Weinberg equilibrium[END_REF] c One-sided or two-sided asymptotic confidence interval. The one-sided confidence interval is used for establishing compatibility with HWE, while the two-sided confidence interval is used for investigating lack of fit d Fixed effects meta-analysis pooled over all four control groups e Random effects meta-analysis pooled over all four control groups f Heterogeneity I 2 between studies was estimated as 6.25% (two-sided 95% confidence interval 0.00%-60.39%)

  criticized the work of Frank et al.[START_REF] Frank | The CASP8 -652 6N del promoter polymorphism and breast cancer risk: a multicenter study[END_REF].

	Specifically, Yu et al. argued that a discussion of the potential influence of HWD in cases in a
	meta-analysis involving four groups was lacking. As outlined above, in the case of genetic
	association, HWD can be expected in cases, while it should not be strong in controls. In fact,
	Frank et al. clearly stated [1, p. 141, column 2] that they investigated deviations of the
	genotype frequencies in the controls from those expected under Hardy-Weinberg equilibrium
	(HWE) using Pearson's goodness-of-fit χ 2 test with 1 d.f. Thus, Frank et al. correctly used the
	available biological reasoning for restricting the analysis to controls. However, two comments
	are required on the approach taken by the authors.

Table 1

 1 Relative excess heterozygosity and asymptotic confidence intervals

	Study f	Genotype	Controls	REH a		95% CI b
			n	%		1-/2-sided c
	GFBCS	ins/ins	270 25.99 0.9494	2	0.8407	1.0722
		ins/del	506 48.70		1	0.8573	1.0515
		del/del	263 25.31
	SBCS	ins/ins	245 20.87 1.0840	2	0.9662	1.2162
		ins/del	608 51.79		1	0.9843	1.1939
		del/del	321 27.34
	GENICA	ins/ins	285 28.33 0.9629	2	0.8506	1.0900
		ins/del	492 48.91		1	0.8678	1.0685
		del/del	229 22.76
	SEARCH	ins/ins	1149 25.68 1.0243	2	0.9660	1.0862
		ins/del	2263 50.58		1	0.9751	1.0760
		del/del	1062 23.74
	Pooled FE d				1.0144	2	0.9700	1.0608
						1	0.9665	1.0629
	Pooled RE e				1.0135	2	0.9770	1.0532
						1	0.9739	1.0548

Acknowledgments

This work was funded by the German Research Foundation (ZI 591/17-1) and the German Ministry of Education and Research (NGFN-Plus, 01GS0831). This work was completed during the sabbatical of AZ at the University of Liège, Belgium.

Conflicts of interest

The authors declare that they have no conflicts of interest.


Nadia Margariti

Stephen B Fox

Alberto Bottini

Nadia Margariti°

Stephen B Fox^

Daniele Generali°

Dr Daniele Generali
email: daniele.generali@gmail.com

"Overcoming breast cancer drug resistance with mTOR inhibitors". Could it be a myth or a real possibility in the short term future?

Keywords: mTOR pathway, temsirolimus, everolimus, breast cancer, drug resistance, aromatase inhibitor

"Overcoming breast cancer drug resistance with mTOR

inhibitors". Could it be a myth or a real possibility in the short-term future?

Introduction

The central component of mTOR pathway, the serine/threonine kinase mTOR (Mammalian Target of Rapamycin), is ubiquitously expressed and highly conserved in eukaryotic cells and functions as the cell gatekeeper. Due to its strategic position, mTOR is a key regulator of multiple cell stimuli, integrating growth factor and cytokine signals with nutrient and energy status. Furthermore, signals emanating from mTOR regulate cell growth, proliferation and survival. Rapamycin (Sirolimus) is the archetypical mTOR-inhibitor: it specifically complexes with FKBP12 (FK506-binding protein 12) which interacts with and inhibits the mTOR protein. The anti-tumour activity of rapamycin has been principally attributed to its ability to modulate the synthesis of critical proteins that are required for ribosome biosynthesis, protein translation, and G1 to S cell cycle phase progression.

Presently there are at least three rapamycin-derived mTOR inhibitors that have been characterized in preclinical models and are in clinical development as anti-cancer agents. These compounds are CCI-779 (Temsirolimus), AP23573 (Deforolimus or Ridaforolimus) and RAD001 (Everolimus). They all have comparable activity against mTOR in biochemical and biological assays but they differ mainly in their bioavailability and formulation. The effect of these drugs on proliferation is cytostatic and not cytotoxic, as they inhibit cell proliferation by causing G1 phase arrest. These agents are thought to have an acceptable safety profile, as generally treatment-related toxicities are mild to moderate in severity and reversible with interruption of therapy or symptom treatment.

Everolimus in particular was developed in an attempt to improve the pharmacokinetic characteristics of Sirolimus, wishing to increase its oral bioavailability [START_REF] Kirchner | Clinical pharmacokinetics of everolimus[END_REF]. Temsirolimus was approved in 2007 by the FDA and EMEA for the treatment of renal cell carcinoma (RCC), while deforolimus is mainly studied for the treatment of sarcoma.

The mTOR signalling pathway, central regulator of cell growth and metabolism

The mammalian target of rapamycin (mTOR) is a serine/threonine protein kinase and it is placed downstream of the phosphatidylinositol-3-kinase (PI3K)/protein-kinase B (Akt) pathway.

The mTOR pathway is mainly involved in the regulation of cell growth and proliferation by controlling these processes at the translational level. In fact, it has two main downstream messengers involved in controlling translation: the ribosomal p70 S6 kinase (S6K1) and the eukaryotic translation initiation factor 4E-binding protein (4E-BP1). The mTOR-driven phosphorylation of S6K1 causes the subsequent phosphorylation of the 40S ribosomal protein S6, enhancing translation of mRNAs that carries a 5'-terminal oligopyrimidine tract (TOP) such as elongation factor-1α and ribosomal proteins. On the other hand, the activation of 4E-BP1 results in its dissociation from the cap-binding protein eIF4E, which is thought to be the rare-limiting component for cap-dependent translation. The increased bioavailability of eIF4E levels thus leads to more efficient cap-dependent protein translation initiation, increasing the synthesis of proteins from that mRNAs with long and highly structured 5'untranslated regions (UTRs), such as cyclin D1 and c-myc. Although mTOR is placed directly downstream of PI3K/Akt in a linear pathway, Akt may also regulate mTOR in a more complex fashion, because the tuberous sclerosis complex (TSC), that is formed by the proteins Tsc1 and Tsc2 and that inhibits mTOR, is also target for Akt. In addition to its effect on protein translation mediated by S6K1 and 4E-BP1, mTOR activation leads to the phosphorylation of several downstream effectors and transcription factors, which in turn influence cell proliferation, survival and angiogenesis (Figure 1).

Involvement of the mTOR pathway in drug resistance

The PI3K/Akt signalling pathway, that is dysregulated in a large number of human cancers, up-regulates the downstream mTOR pathway, resulting in enhanced mRNA translation and increased cellular proliferation, as it was previously described. Genetic alterations in this pathway often occur in breast tumours. In fact, a high frequency of mutations of the PI3KCA gene was reported in breast cancers (18-26%) as for the p-AKT (42%). PTEN mutations are instead rare in sporadic cases of breast cancers, but this is a site of frequent allelic imbalance and the related protein is absent or decreased in a significant number of breast cancers (15%), while germ-line mutations in PTEN are responsible for Cowden's Syndrome, which predisposes to breast cancer.

It is recognised that cancer cells develop resistance to a variety of standard hormone-therapy and chemotherapeutic regimens through the activation of this same pathway. The current hypothesis, supported by pre-clinical and early clinical studies, is that the addition of an mTOR inhibitor to a conventional therapeutic regimen can enhance the efficacy of established chemotherapeutic and anti-hormonal agents and in some instances can even restore the sensitivity of previously resistant tumour cells, thus improving disease treatment and overall survival. In the case of breast cancer, this is true for tamoxifen, letrozole and trastuzumab (Table 1), but further studies are being performed to establish the efficacy of these combination regiments and also to define new drug associations.

Target pathways for mTOR inhibitors

Current evidences indicate that mTOR inhibitors show efficacy in a subgroup of tumours, suggesting that molecular biomarkers predictive of drug sensitivity or resistance will be critical to enable the development of targeted combination regimens. Currently the only known requirements for the appropriate selection of breast cancer patients who can successfully be treated with an mTOR inhibitor are the overexpression of HER-2 and/or the oestrogen receptor positivity. These should be supplemented by direct measures of mTOR activation to appropriately stratify patients for mTOR inhibitors, since mTOR is responsible for the sensitivity (S) or resistance (R) to both conventional drugs (see Table 1) and mTOR-inhibitors. This can be further expanded using the hypothetical patterns of interactions between a generic chemotherapeutic drug or anti-hormonal agent and an mTOR inhibitor, to design treatment strategies to develop target therapies with mTOR inhibitors. Such postulates, together with breast tumour profiling and mTOR pathway genotypic and/or phenotypic features, will help predict the likelihood of tumor response.

Mammalian TOR and the HER-2/neu pathway HER-2/neu (ErbB2) is a member of the EGFR (Epidermal Growth Factor Receptor) family and it is amplified in about 15% of breast cancer. Overall survival and time to progression are shorter in patients whose tumours over-express HER-2. Several studies confirmed in vitro the causal relationship between mTOR activation and HER-2 over-expression, indicating an underlying role of Akt/mTOR pathway activation in ErbB2-mediated breast cancer progression. Indeed, loss of PTEN and the subsequent Akt/mTOR hyperactivation have been reported to mediate resistance to trastuzumab. Thus rapamycin inhibits multiple stages of tumour progression, including established lung metastases. Since in one study it was used a mouse model that develops spontaneous mammary gland tumours, due to aberrant up-regulation of a non-mutated c-Neu/ErbB2 oncogene comparable to that found in human tumours, it was suggested that inhibition of the mTOR pathway might be an effective treatment for early-stage and late-stage HER-2 positive breast cancer. It may be also possible that mTOR dependency occurs early in the c-Neu/ErbB2-induced tumourigenic process, suggesting that treatment of hyperplastic regions with rapamycin could prevent or delay primary tumour formation and may be even used as a pharmacopreventive agent. Although trastuzumab has been shown to be a successful example of a rationally designed therapeutic antibody, only 30% of patients with HER-2 over-expressing breast cancer respond to trastuzumab as a single agent, while the majority of patients initially responding develop resistance to this drug within a year. Based on data from pre-clinical studies on cell cultures and xenograft models, which demonstrated that RAD001 enhances the efficacy of trastuzumab [START_REF] Lu | Preclinical testing of clinically applicable strategies for overcoming trastuzumab resistance caused by PTEN deficiency[END_REF], it was hypothesized that RAD001 could reverse trastuzumab resistance in patients with HER2-overexpressing breast cancer. Surprisingly, early results from two phase I trials in which RAD001 was combined with trastuzumab (Herceptin®) and chemotherapy agents (paclitaxel or vinorelbine), suggest that the addition of RAD001 overcomes resistance to trastuzumab in patients with HER-2 over-expressing metastatic breast cancer with prior resistance to the above mentioned drug. This combination regiment appeared to be highly efficacious, achieving complete responses in a few patients and partial responses or stable disease in a majority of patients. These preliminary results are very important, also given that the women were heavily pre-treated, had documented resistance to trastuzumab and most were even taxane-resistant.

Interaction of growth factors with their receptors activates not only the mTOR pathway, but also multiple downstream kinase pathways that are not less crucial for cell proliferation and survival. Among them, the most important is maybe represented by the MAP kinase cascade, which exerts downstream effects on Elk-1, a transcription factor related to cell proliferation. For this reason, by simultaneously inhibiting multiple pathways or blocking signal transduction at a nodal point where multiple pathways converge, might be needed to provide an effective strategy for treatment of hormone-dependent breast cancer. They should be tested new compounds capable of inhibiting several pathways, as for example the Farnesylthiosalicylic acid (FTS), or strategies that combines different agents to get the same result [START_REF] Yue | Farnesylthiosalicylic acid blocks mammalian target of rapamycin signaling in breast cancer cells[END_REF].

We only have till now information from in vitro models, so the next step is to study this phenomenon in vivo.

Mammalian TOR and the efficacy of anti-hormonal agents

The estrogen receptor (ER) is expressed in about 60% of breast cancers and is an important predictive and prognostic marker in human breast cancer. However up to 50% of patients with ER positive BC who relapses with distant metastasis not respond to endocrine therapy (de novo resistance) and the remainder will eventually relapse despite an initial response (acquired resistance). Efforts to understand the various biologic mechanisms responsible for the development of endocrine resistance are aimed at the development of new strategies to improve anti-ER therapy [START_REF] Ali | Endocrine-responsive breast cancer and strategies for combating resistance[END_REF]. Evidence is emerging to suggest both genomic and non-genomic mechanisms for cross-talk in endocrine resistance despite the present of tamoxifen or aromatase inhibitor: an increase of growth factor expression occur during prolonged endocrine therapy in ER positive breast cancer treatment leading to endocrine resistance. Yue at al demonstrated that different mechanisms are involved when breast cancer cells adapt themselves to escape from the manipulations blocking the estrogen receptor signalling [START_REF] Yue | Mechanisms of acquired resistance to endocrine therapy in hormone-dependent breast cancer cells[END_REF]. This signalling includes EGFR/HER2, Ras/MAPK, ERK1/2 pathway and IGF/PI3K/Akt pathway [START_REF] Arpino | Crosstalk between the estrogen receptor and the HER tyrosine kinase receptor family: molecular mechanism and clinical implications for endocrine therapy resistance[END_REF]. In experimental models of LTED, interrupting signalling pathway with drug targeting EGFR, or HER2, or MAPK or mTOR signal restored endocrine responsiveness providing a strong rationale for the clinical use of their combination with hormone therapy in order to prevent or overcome resistance [START_REF] Musgrove | Biological determinants of endocrine resistance in breast cancer[END_REF]. Using FTS as a tool, we found that the mTOR pathway is a predominant pathway in mediation of proliferation of Long Term Eestrogen Deprivation (LTED) cells. The specific mTOR inhibitor, rapamycin, effectively inhibited growth of LTED cells. Over the last 5 years many studies have established that combining mTOR inhibitors such as CCI-779 or RAD001 with an anti-hormonal agent is synergistic in breast cancer cell in vitro models. For example, both control MCF-7 and MCF-7/Aro (aromatase expressing) cells were found to be sensitive to RAD001 treatment in vitro. Indeed RAD001 almost completely inhibited estradiol induced proliferation in both control MCF-7 cells as well as estradiol and androstenedione induced proliferation in MCF-7/Aro cells. The results showed that a combination treatment with letrozole and RAD001 results in increased inhibition of MCF-7/Aro cell proliferation in an additive manner, even at suboptimal levels of RAD001 [START_REF] Rudloff | The mTOR pathway in estrogen response: a potential for combining the rapamycin derivative RAD001 with the aromatase inhibitor letrozole in breast carcinomas [Abstract[END_REF]. Furthermore, the effect of the combination of letrozole with RAD001 in two models of breast carcinoma (MCF-7 and T47D cells) demonstrated that estrogen-induced proliferation is largely dependent on mTOR signaling and that RAD001 in combination with letrozole has more profound effects on aromatase-mediated estrogen-induced proliferation than either agent alone [START_REF] Boulay | Dual inhibition of mTOR and estrogen receptor signaling in vitro induces cell death in models of breast cancer[END_REF]. Similar findings on growth inhibition have been reported

for MCF-7 cells treated with RAD001 and tamoxifen [START_REF] Treeck | Effects of a combined treatment with mTOR inhibitor RAD001 and tamoxifen in vitro on growth and apoptosis of human cancer cells[END_REF]. Recent clinical findings from a phase II study conducted in 270 postmenopausal women with ER positive breast cancer in the neoadjuvant setting, showed that RAD001 caused tumour shrinkage when given in combination with letrozole.

The combination of letrozole and RAD001 for 4 months before surgery resulted in significantly greater tumour shrinkage, as assessed by ultrasound, and a greater reduction in cell proliferation, as measured by changes in Ki67 after 15 days therapy. Even the overall clinical response rate was significantly greater than letrozole alone treatment in this subset of patients [START_REF] Baselga | Phase II Randomized Study of Neoadjuvant Everolimus Plus Letrozole Compared With Placebo Plus Letrozole in Patients With Estrogen Receptor-Positive Breast Cancer[END_REF].

Can mTOR inhibitors really prevent endocrine resistance?

De novo and acquired resistance to endocrine therapy is a major clinical problem in the treatment of breast cancer. Several studies have shown that the up-regulation of the PI3K/Akt pathway in breast cancers from endocrine-treated patients is responsible for an aggressive clinical phenotype and a short relapse-free and overall survival outcome, by mediating in resistance to antiestrogen therapeutics. Since the PI3K/Akt is frequently deregulated in breast cancer with upregulation of this pathway associated with increased sensitivity to mTOR inhibition, this patient population is especially suitable for the administration of mTOR inhibitor rapamycin-like drugs.

Both mTOR inhibitors and PI3K inhibitors that are still in the early stages of development are being testing in breast cancer in combination with endocrine therapies. Pre-clinical and clinical studies have demonstrated a clear association between PI3Kinase downstream Akt signalling and tamoxifen resistance. Thus, a constitutively active Akt in MCF-7 cells renders these normally hormone-dependent breast cancer cells resistant to the inhibitory effect of tamoxifen. This also applies to other hormone inhibitors, including Letrozole® or Fulvestrant®. However, RAD001 was able to restore endocrine therapy sensitivity to refractory breast cancer cells with high Akt activity and also re-sensitize breast cancer cells not responsive to Letrozole as single agents. Interestingly, these results were independent of estrogen receptor α (ERα) activity, indicating that Akt-induced resistance is mediated, at least in part, by ERα-independent mechanisms. These studies demonstrated that the combination of mTOR inhibition and endocrine agents have excellent anticancer activity in pre-clinical models of Akt-induced resistance and provide a rational basis for the following development of clinical trials with mTOR inhibitors in breast cancer [START_REF] Fbeeram | Aktinduced endocrine therapy resistance is reversed by inhibition of mTOR signaling[END_REF].

The mechanisms by which endocrine resistance occurs remain unclear, but several studies have demonstrated that estrogen-independent growth properties are mediated at least in part through the PI3K/Akt/mTOR pathway and that hyperactivation of this pathway can protect breast cancer cells from tamoxifen-induced apoptosis, suggesting a significant role in hormone-refractory breast cancer. A recent study in research of mechanism involved into endocrine resistance showed that S6K1, a downstream target of mTOR, is responsible for phosphorylating the Ser 167 of ER , regulating its transcriptional activity. By the activation of ER , S6K1 controls the proliferation of ER positive breast cancer cells [START_REF] Yamnik | S6 kinase 1 regulates estrogen receptor alpha in control of breast cancer cell proliferation[END_REF]. Considering the over-expression of S6K1 is related to an higher sensitivity to rapamycin of breast cancer cells, this finding is important as the detection of S6K1 expression in breast cancer could be a representative way to select whose patients need to be treated with the association of endocrine therapy with an mTOR inhibitor. Nevertheless, there are no clinical studies that demonstrate whether mTOR inhibitors are able to overcome endocrine resistance. However, we have tried to address this question in a phase II clinical trial of 113 patients treated with letrozole, administered alone or with cyclophosphamide. We demonstrated that nuclear ERα phosphorylated on serine 118 (pERα) is a strong marker of endocrine treatment response. This is an improving of the currently used IHC assessment for the ER expression, as it predict response to hormone therapy in only 36% to 55% of patients, with a small benefit with the progesterone receptor [START_REF] Ellard | Randomized phase II study comparing two schedules of everolimus in patients with recurrent/metastatic breast cancer: NCIC Clinical Trials Group IND.163[END_REF] marker evaluation. The molecules p44/42 MAPK and HIF-1, instead, was shown to be significantly associated with endocrine resistance [START_REF] Generali | Down-regulation of phosphatidylinositol 3'-kinase/AKT/molecular target of rapamycin metabolic pathway by primary letrozole-based therapy in human breast cancer[END_REF].

We observed that the PI3K/Akt/mTOR pathway is significantly down-regulated following estrogen deprivation. Nevertheless, although the observed changes in p-mTOR levels were not significantly associated with tumour shrinkage nor with reduction in proliferation activity, it was tightly associated with a longer disease free survival [START_REF] Generali | Phosphorylated ERalpha, HIF-1alpha, and MAPK signaling as predictors of primary endocrine treatment response and resistance in patients with breast cancer[END_REF].

It still remains to unfold if the use of mTOR inhibitors in combination with anti-hormonal agents can delay, prevent or overcome the development of endocrine resistance in breast tumors.

Enhancing the anti-tumour activity of mTOR inhibitors

Since AMP-Activated Protein Kinase (AMPK) activity is regulated by the cellular energy level through the balance in ATP:AMP ratio, activated AMPK on its turn can phosphorylate TSC2 at multiple serine and threonine sites, leading to the inactivation of mTOR (Figure 1). Thus, the inhibition of translation through both AMPK activation and mTOR inhibition represents an alternative mechanism to further reduce cancer cell growth. Thus the anti-tumour activity of rapamycin and its derivatives such as metformin, most commonly used for the treatment of type II diabetes, is being explored. Although the molecular mechanism of metformin have been only studied in tissues such as liver, muscle and fat in relation to glucose homeostasis and insulin action, there are occasional reports of anti-neoplastic activity of metformin in various cancer experimental models. A recent work examined the previously uncharacterized direct action of metformin on cancer cells and its potential indirect action due to the overall reduction of insulin levels. Metformin was shown to act as an inhibitor of proliferation in vitro in MCF-7 breast cancer cells and in other kinds of epithelial cells. Intracellular control systems, physiologically activated by nutrient deprivation, were induced after treatment with metformin. They were down-regulated processes that consume energy, such as protein translation and cell division, and they were up-regulated those that generate energy. The growth inhibition was associated with decreased mammalian target of rapamycin and S6 kinase activation and a general decrease in mRNA translation, suggesting potential roles for activators of AMP kinase such as metformin in cancer prevention and treatment [START_REF] Zakikhani | Metformin is an AMP kinase-dependent growth inhibitor for breast cancer cells[END_REF]. A more recent study on MCF-7 cells shows that metformin inhibits the initiation step in translation via mTOR and that metformin requires two major tumour suppressors, LKB1 and TSC2, to mediate its effects on translation. The results demonstrate that metformin-mediated AMPK activation leads to the inhibition of mTOR and to a reduction in translation initiation, thus providing a possible mechanism of action for metformin-driven inhibition of cancer cell growth. Furthermore, translation in MDA-MB-231 cells, which lack the LKB1 kinase (the kinase responsible for phosphorylating AMPK), and in tuberous sclerosis complex 2 null (TSC2-/-) mouse embryonic fibroblasts, was unaffected by metformin. This indicates that both LKB1 and TSC2 are involved in metformin mechanism of action, in accordance with classical experimental observation on rodents in which severe dietary restriction protects from a variety of carcinogenic influences [START_REF] O'reilly | mTOR inhibition induces upstream receptor tyrosine kinase signaling and activates Akt[END_REF]. There is also evidence that this protection is mediated at least in part by the suppressive effect on the circulating level of Insulin-like Growth Factor 1 (IGF-1), which play a role in cancer risk [START_REF] Hankinson | Circulating concentrations of insulin-like growth factor-I and risk of breast cancer[END_REF]. At the cellular level, physiologic or pharmacological activation of AMP kinase would further attenuate signalling in networks downstream of insulin and IGF-1 receptors, particularly at the level of mTOR. Further studies will be needed to determine the relative importance of direct (AMP kinase pathway activation) and indirect (reduction of insulin levels) mechanisms by which metformin acts as an antiproliferative agent for epithelial cells in vivo.

It is now starting a pilot study in vitro and in vivo which combines rapamycin with metformin, to enhance mTOR inhibition in cancer cells. Furthermore, this study will try to understand if this combination can help overcoming resistance to HER-2 target therapies (trastuzumab and lapatinib) in HER-2 positive breast cancer, given than the PI3K/Akt/mTOR pathway is involved.

Resistance to mTOR Inhibitors

New evidences regarding compensatory pathways involved into mTOR inhibitors resistance are emerging. mTOR inhibition blocks the negative feed-back on IGF-1R signalling interfering on Akt/PI3K signalling. The result is an increase in Akt phosphorylation, protein kinase activity and downstream signaling, which could potentially counteract the inhibition of mTOR. Either in vivo or in vitro data showed that treatment with mTOR inhibitors increase significantly the p-Akt expression in tumor biopsy or in breast cancer cell lines [START_REF] O'reilly | mTOR inhibition induces upstream receptor tyrosine kinase signaling and activates Akt[END_REF]. However, their understanding is therefore critical to optimize targeted therapies. Based on preclinical models, dual inhibition of both IGF1Rwith either monoclonal antibodies or tyrosine kinase inhibitorsand mTOR results in a superior anti-proliferative effect over each single strategy [START_REF] Cosimo | Targeted therapies in breast cancer: where are we now?[END_REF], and this combination is now under evaluation in phase I/II trials in patients with breast cancer.

Conclusion

The described findings have brought to light the great potential of the mTOR-inhibitor class of compounds. mTOR inhibitors are ahead in their development providing evidence of anticancer activity in multiple tumor types; rapamycin (sirolimus) derivates such as temserolimus, everolimus and deferolimus are potent inhibitor of mTOR without showed the same pharmacokinetic problems of rapamycin. Phase I safety analysis showed that the mTOR inhibitors are generally well tolerated.

Class-specific adverse events are consistently observed with each of the three agents including stomatatis, skin rush, erythema, hyperglycaemia and hyperlipidemia. Temsirolimus and everolims are currently selected for clinical trials. In the case of everolimus, on breast cancer, the Phase I trial identified the dose of 10 mg/day as optimal for further clinical development [START_REF] Baselga | Phase II Randomized Study of Neoadjuvant Everolimus Plus Letrozole Compared With Placebo Plus Letrozole in Patients With Estrogen Receptor-Positive Breast Cancer[END_REF][START_REF] Ellard | Randomized phase II study comparing two schedules of everolimus in patients with recurrent/metastatic breast cancer: NCIC Clinical Trials Group IND.163[END_REF]. In the phase II, double-blind, randomized study of everolimus in combination with letrozole versus placebo and letrozole in the neoadjuvant setting [START_REF] Frogne | Antiestrogen-resistant human breast cancer cells require activated protein kinase B/Akt for growth[END_REF], the combination arm proved to be superior over letrozole and placebo with a higher significant response rate (68% vs. 59%) [START_REF] Frogne | Antiestrogen-resistant human breast cancer cells require activated protein kinase B/Akt for growth[END_REF]. Based on encouraging preliminary results where everolimus was associated to trastuzumab showing an anticancer activity, an ongoing phase III trial is evaluating the addition of everolimus to HER2 targeted-therapy and paclitaxel in order to overcome/delay trastuzumab resistance in first-line therapy of HER positive breast cancer. Regarding the other mTOR inhibitor, the initial phase II study of letrozole alone or in combination with temsirolimus in metastatic breast cancer patients, after adjustment of treatment schedule, showed benefit from the combination in terms of median progression-free survival (13.2 months vs. 11.6 months); the consequent phase III trial was interrupted due to the lack of efficacy for the combination.

However, it will be necessary not only to further confirm the efficacy of mTOR-inhibitor in reverting trastuzumab resistance and to verify its interactions with the oestrogen receptor pathway, but also to test if mTOR-inhibitor in combination with other drugs, as for example lapatinib (that is a small molecule inhibitor of ErbB1 and ErbB2 tyrosine kinases), will drive the same overcoming effect. Many other questions needs to be solved, as for example the followings: which are the best conditions or the minimal conditions for the treatment of a breast cancer patient with an mTOR inhibitor? Is it possible to predict an on-coming resistance or we can only waiting for it before an mTOR-inhibitor administration? And more again, is metformin really able to amplify the efficacy of mTOR inhibitors? Are there other undiscovered drug associations with mTOR inhibitor? Future experiments based on pre-clinical studies in animal models and/or clinical trials in breast cancer patients would try to define the parameters for the selection of patients. The neoadjuvant model or the basal stratification based on mTOR activity of breast tumours would probably address the clinician in a better selection of whose patients will have benefits from the use of mTOR inhibitor.

New diagnostic markers need to be validated and introduced in the clinical practice, to stratify and carefully select patients on the basis of mTOR activity in tumour tissues, to take advantage the more as possible of this powerful class of drugs. To conclude, the optimization of mTOR inhibitors' drug administration is opening the way for a new era of bio-oncology. Table 1. Molecular events in the mTOR pathway involved in breast cancer drug resistance.

Molecular events Resistance to References

Activation of PI3K and AKT Trastuzumab [START_REF] Generali | Phosphorylated ERalpha, HIF-1alpha, and MAPK signaling as predictors of primary endocrine treatment response and resistance in patients with breast cancer[END_REF] Activation of PI3K and AKT Endocrine therapy [START_REF] Generali | Down-regulation of phosphatidylinositol 3'-kinase/AKT/molecular target of rapamycin metabolic pathway by primary letrozole-based therapy in human breast cancer[END_REF] Constitutive AKT activation Tamoxifen [START_REF] Hankinson | Circulating concentrations of insulin-like growth factor-I and risk of breast cancer[END_REF], [START_REF] Rudloff | The mTOR pathway in estrogen response: a potential for combining the rapamycin derivative RAD001 with the aromatase inhibitor letrozole in breast carcinomas [Abstract[END_REF], [START_REF] Kirchner | Clinical pharmacokinetics of everolimus[END_REF] EGFR, AKT1 and ERK1 activation Cisplatin [START_REF] Lu | Preclinical testing of clinically applicable strategies for overcoming trastuzumab resistance caused by PTEN deficiency[END_REF] Raf activation Doxorubicin and Paclitaxel [START_REF] Mccubrey | Roles of the RAF/MEK/ERK and PI3K/PTEN/AKT pathways in malignant transformation and drug resistance[END_REF] ERK activation Tamoxifen [START_REF] Musgrove | Biological determinants of endocrine resistance in breast cancer[END_REF], [START_REF] O'reilly | mTOR inhibition induces upstream receptor tyrosine kinase signaling and activates Akt[END_REF] JNK activation Tamoxifen [START_REF] Musgrove | Biological determinants of endocrine resistance in breast cancer[END_REF] Table 2. Tumour Sensibility (S) or Resistance (R) to a generic conventional drug and to an mTOR inhibitor and expected efficacy of a combined therapy. An additive effect is the sum of the individual effects while a synergistic effect is greater than the sum of the single parts.

Figure 1 Figure 1 Figure

 11 Figure 1 mTOR pathway and influence on cell proliferation, survival and angiogenesis.