Chapter 10 Breast Cancer Liver Metastasis
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1 Chapter 10 Breast Cancer Liver Metastasis Sébastien Tabariès and Peter M. Siegel Abstract The emergence of metastatic breast cancer is the most deadly aspect of this disease and once it has spread from the primary site, it is largely incurable. Upon dissemination from the primary tumor, breast cancer cells display preferences for specific metastatic sites. The liver represents the third most frequent site for breast cancer metastasis, following the bone and lung. Despite the evidence that hepatic metastases are associated with poor clinical outcome in breast cancer patients, little is known about the molecular mechanisms governing the spread and growth of breast cancer cells in the liver. In recent years, researchers have utilized animal model systems to isolate breast cancer cells that weakly or aggressively metastasize to the liver and have utilized gene expression profiling to compare these populations. In this manner, genes whose expression is elevated or diminished in highly metastatic breast cancer cells have been identified. We highlight both tumor intrinsic factors as well as aspects of the metastatic microenvironment that contribute to the establishment and growth of breast cancer liver metastases. Keywords Breast cancer Liver metastasis Tight junctions Cell-cell adhesion Abbreviations ASC adipocyte stem cell BCLivM: breast cancer liver metastasis BMDC: bone marrow derived cell BMSC: bone marrow stem cell CRC colorectal cancer DCIS ductal carcinoma in situ DOX doxycycline ECM extracellular matrix ER estrogen receptor P.M. Siegel (B) Goodman Cancer Research Centre, McGill University, Montréal, QC, Canada H3A 1A3; Departments of Medicine and Biochemistry, McGill University, 1160 Pine Avenue West, Room 513, Montréal, QC, Canada H3A 1A3 P. Brodt (ed.), Liver Metastasis: Biology and Clinical Management, Cancer Metastasis Biology and Treatment 16, DOI / _10, C Springer Science+Business Media B.V
2 274 S. Tabariès and P.M. Siegel HPC IDC ILC LCIS MMP MSC PR SAGE SDPP SIRT TACE TEM TMN haematopoietic progenitor cell invasive ductal carcinoma invasive lobular carcinoma lobular carcinoma in situ matrix metalloproteinase mesenchymal stem cell progesterone receptor serial analysis of gene expression stroma-derived prognostic predictor selective internal radiotherapy transcatheter arterial chemoembolization tetraspanin-enriched membrane microdomains tumor-node-metastasis system Contents 10.1 Introduction Classification of Breast Cancer Towards a Molecular Classification of Breast Cancer The Clinical Promise of Molecular Profiling in Breast Cancer Breast Cancer Metastasis Breast Cancer Metastasis to the Liver Treatment of Breast Cancer Liver Metastases The Liver as a Metastatic Site Architectural Features of the Liver Mediators of Breast Cancer Liver Metastasis Studies Using Xenograft Models Studies Using Syngeneic Models A Role for Tight Junctional Proteins in Breast Cancer Liver Metastasis Emerging Areas of Interest The Pre-metastatic Niche Recruitment of Myeloid Cells Factors that Mobilize Bone Marrow Cells Conclusion References Introduction Breast cancer represents the most commonly diagnosed cancer affecting Canadian women and is the second leading cause of cancer deaths in women [1]. It is estimated that 1 in 9 women will develop breast cancer in their lifetime and that 1 in 27 will die from this disease (Canadian Cancer Statistics). While breast cancer is a disease that predominantly affects women, about 1% of breast cancer cases are detected in men [1].
3 10 Breast Cancer Liver Metastasis 275 Breast cancer is a heterogeneous disease that is characterized by diverse histopathologies and molecular features that are associated with distinct clinical outcomes. This disease is driven by the accumulation of genetic abnormalities and can be broadly divided into inherited or sporadic breast cancer. Hereditary breast cancer accounts for approximately 5 10% of all breast cancers, the majority of which are linked to mutations in breast cancer gene 1 (BRCA1) or breast cancer gene 2 (BRCA2). Patients harboring BRCA1 or BRCA2 alterations have a much greater risk of developing both breast and ovarian cancer [2]. The remaining cases of breast cancer cannot be associated with an inherited genetic predisposition, and are termed sporadic breast cancers Classification of Breast Cancer Breast cancer staging is used to predict patient prognosis, guide treatment decisions and is based on the tumor-node-metastasis (TNM) system [3]. Based on the size of the primary tumor (T), the presence and degree of involvement of the regional lymph nodes (N) and the presence of distant metastases (M), breast cancers can be sub-divided into stage 0-IV disease. Stage 0 describes up to 20% of breast cancers, represents non invasive lesions that have not spread distally and includes both lobular carcinoma in situ (LCIS) and ductal carcinoma in situ (DCIS). Stage I refers to tumors that have not spread from the primary site and are smaller than 2 cm in diameter. Stage II breast cancer tumors range from 2 to 5 cm in diameter and have spread to 1 3 lymph nodes. Breast tumors that are larger than 5 cm in diameter and have spread to more than 3 axillary lymph nodes are categorized as Stage III breast cancer. By stage IV, cancer cells have spread through the bloodstream or lymphatic system to colonize other parts of the body. The 5 year survival rates diminish with increasing grade and stage III/IV breast cancers are characterized by a significantly poorer prognosis compared to stage I/II cancers [4]. It is the development of distal metastases that accounts for the majority of cancer-related deaths in patients with this disease Towards a Molecular Classification of Breast Cancer Microarray-based profiling has led to the classification of primary human breast cancers based on distinct gene expression signatures [5 7]. The first major study utilized breast specimens obtained from 42 individuals, which included 36 invasive ductal carcinomas, two invasive lobular carcinomas, one ductal carcinoma in situ, one fibroadenoma and three normal breast tissue samples [5]. Genes that displayed little variance within repeat samples from the same tumor and a high variance across tumors formed an intrinsic gene set that was used to identify five subtypes of breast cancers. These subtypes include luminal A, luminal B, basal-like, HER2-positive and normal-like breast cancers and they have been subsequently identified in independent datasets [6 8]. In general, breast tumors belonging to the
4 276 S. Tabariès and P.M. Siegel luminal A and B subtypes are estrogen receptor (ER) and/or progesterone receptor (PR) positive. The HER2 subgroup displays elevated HER2 expression, as a result of genomic amplification, and typically possesses low or negative hormone receptor expression, whereas basal breast cancers are characterized as ER-negative, PR-negative and HER2-negative. Signatures within the normal-like breast cancer subtype encompass genes known to be expressed by cell types within the normal breast, including genes associated with adipose tissue. This subtype remains under-studied at present and there is some concern as to whether it simply represents the degree of normal -tissue contamination present within tumor samples [9, 10]. Importantly, it has become clear that these breast cancer subtypes are linked to patient outcomes. The HER2 and basal-like subtypes are associated with the poorest patient prognosis, exhibiting the shortest overall survival and relapse-free survival times. In contrast, the luminal A subtype is associated with the best prognosis whereas patients with luminal B cancers have an intermediate prognosis [6 8, 11, 12]. At present, the identification of molecular subtypes affirms the selection of treatment strategies that are based on more traditional clinico-pathological characteristics of the disease. Luminal cancers, by virtue of their hormone receptor positive status, typically respond well to endocrine therapies such as Tamoxifen. On the other hand, HER2-driven breast tumors, which are usually hormone receptor negative, are resistant to Tamoxifen. However, Trastuzumab, a humanized monoclonal antibody against HER2 specifically inhibits cell growth of HER2-positive cancers. At present, there is a lack of targeted agents that can be effectively used against the basal subtype of breast cancer. However, epidermal growth factor receptor (EGFR) inhibitors are active in basal-like breast cancer with EGFR gene amplification [13]. Furthermore, it has been reported that the basal-like subtype is significantly associated with distant metastasis and displays a greater likelihood of developing visceral metastases [14]. By analyzing the expression data of 344 breast cancers, the preferential sites of relapse have been correlated with each molecular subtype [15]. Recurrence to the bone is most commonly found in patients with breast tumors from the Luminal B and A subtypes (36.6 and 31%, respectively); whereas recurrence to the lung is more frequent in patients with breast cancers belonging to the Luminal B and the HER2 subtypes (36.7 and 40%, respectively). Similarly, the HER2 and basal subtypes of breast cancer preferentially metastasize to the liver (33.3 and 22%, respectively), while brain metastases are mostly found in patients from the Luminal A or the basal subtypes (21.4 and 57.1%, respectively) [15]. The majority of these profiling studies have used RNA extracted from whole tumor samples, which include both the tumor component and elements of the infiltrating stroma. Growing interest in tumor stromal interactions and their importance in breast cancer progression has led investigators to analyze gene expression changes, specifically in the stroma of breast cancers [16 18]. Initial studies relied on the isolation of specific cells types from normal breast tissues, DCIS and invasive breast cancers using cell surface markers and magnetic bead enrichment of epithelial cells, endothelial cells, fibroblasts and leukocytes [19]. SAGE analysis revealed gene expression changes in all cell types during breast cancer progression, with the most dramatic differences observed during the transition from normal breast epithelium to DCIS [19]. Recently, the question of stromal gene expression profiles
5 10 Breast Cancer Liver Metastasis 277 has been examined through the use of laser capture microdissection of fresh frozen breast cancer specimens to selectively harvest the epithelial or stromal components of the tumor without the need for sorting techniques [20]. Using this approach, a 26-gene stromally derived signature was identified, termed the stroma-derived prognostic predictor (SDPP), which could predict outcome in datasets derived using whole tumor material [20]. Together, these studies indicate that gene expression data from both the tumor epithelium and tumor stroma can be informative in identifying breast cancers that are associated with poor patient prognosis and highlight the fact that different and complementary information may be gained from these cellular compartments The Clinical Promise of Molecular Profiling in Breast Cancer Initial concerns regarding the clinical applicability of gene expression signatures included questions regarding quality control of the RNA isolated from samples, the reliability of DNA microarrays for measuring gene expression and the reproducibility of the results generated within a lab and between labs. Many of these issues have been systematically addressed through the microarray quality control project (MQCP consortium, 2006). To date, several molecular predictors for patient prognosis, such as Mammaprint and Oncotype DX, have been described. Mammaprint is a 70-gene signature that was developed by comparing tumors from patients free of metastatic relapse versus those taken from patients with relapse within 5 years [21]. Currently, Mammaprint is being tested in the MINDACT trial to determine whether this gene expression signature is capable of identifying good prognosis patients that could receive less aggressive adjuvant chemotherapy [22]. Another signature, termed Oncotype DX, consists of 21 genes and is being used to identify patients with ER-positive, lymph node negative breast cancer that are at risk for distant recurrence [23, 24]. The gene expression results from these 21 genes are converted into a recurrence score that indicates which patients may require only endocrine therapy versus those that would benefit from adjuvant chemotherapy. The utility of this test in clinical decision-making is being examined in an ongoing TAILORx trial [24]. In addition to these prognosis signatures, expression signatures designed to predict response to current therapies are now being developed and tested. In fact, the role of breast tumor stroma in predicting response to therapy has also been examined and it was found that, in patients with ER-negative breast cancer, an increase in stromal gene expression correlated with resistance to chemotherapy [25]. Thus, there is hope that these initial signatures and second generation predictors will have a great impact on the way breast cancer is managed and treated [26] Breast Cancer Metastasis Most patients that develop metastatic breast cancer will ultimately die of their disease, with a median overall survival of months following diagnosis of metastases [27]. Metastatic tumor cells must overcome numerous barriers in order
6 278 S. Tabariès and P.M. Siegel Brain Metastases At diagnosis: 8% At autopsy: 22% Lung Metastases At diagnosis: 30% At autopsy: 65% Liver Metastases At diagnosis: 26% At autopsy: 60% Bone Metastases At diagnosis: 49% At autopsy: 65% Fig Percentage of organ involvement in advanced breast cancer. Text in red: within 3 years of primary breast cancer diagnosis [29]; text in blue: at time of autopsy [30] to disseminate. These include local invasion, migration and intravasation into the lymphatic system or bloodstream, survival in the circulation, immunosuppression, adhesion/extravasation at the metastatic site and tumor outgrowth in a foreign microenvironment [28]. Interestingly, breast cancer cells preferentially metastasize to specific organs and tissues including bone, lung, liver and brain (Fig. 10.1) [29, 30]. Communication between the tumor and host cells is likely to be the most important determinant contributing to the ability of cancer cells to metastasize to specific organs. This notion was first conceptualized over a century ago when Stephen Paget proposed that metastatic tumor cells were like seeds that would only grow in a suitable and compatible soil [31]. The bone represents the most frequent site for breast cancer metastasis. In approximately one quarter of all breast cancers, the bone will be the first site of metastasis and at the time of autopsy, about 65% of patients display bone metastases (Fig. 10.1)[29, 30]. Bone metastases are associated with significant morbidity in breast cancer patients, including complications such as bone pain, hypercalcemia or fractures [32 34]. When the bone is recorded as the first or the most significant metastatic site in patients with bone metastases, the 5-year overall survival rate is 16 % [35]. The lung is the second most common site for breast cancer relapse affecting about 60 % of patients with metastatic breast cancer as assessed at the time of autopsy (Fig. 10.1) [29, 30, 36]. In about 20 % of cases, the lung is the only site of metastasis. The prognosis for patients with breast cancer that has spread to the lungs is worse than for patients with bone metastases since the 5-year overall survival rate decreases to 12 % [35]. The brain is also considered a common site for breast cancer metastasis and is found in about 16 % of all metastatic breast cancers (Fig. 10.1). It is generally detected late in disease progression and the prognosis associated with brain metastasis is poor with a median survival times of less than 6 months [36].
7 10 Breast Cancer Liver Metastasis Breast Cancer Metastasis to the Liver Breast cancer liver metastases (BCLivM) are frequent in the clinical course of breast cancer and the liver represents the third most frequent site for breast cancer metastases [37, 38]. Within 3 years of primary tumor diagnosis, 49% of breast cancer patients have bone metastases, 30% have lung metastases and 26% have liver metastases (Fig. 10.1) [29]. At autopsy 65% of patients have bone or lung metastases while 60% of patients with metastatic breast cancers have liver involvement (Fig. 10.1)[30]. Breast cancer patients with hepatic metastases display a poor prognosis, with median survival times between months and 5 year survival rates that reach only % [39, 40] Treatment of Breast Cancer Liver Metastases It is accepted that most patients with liver metastases also have extra hepatic lesions and the presentation of isolated liver metastases, with no evidence of metastatic disease in other sites, is only found in 1 5% of breast cancer patients [27, 41]. In patients with hormone positive breast cancer, systemic anti-endocrine therapy is warranted and the presence of hepatic breast cancer metastases is not contraindicating. However, since BCLivM are more likely to develop in patients with breast cancer belonging to the basal-like subtype, which are ER/PR-negative, hormonal therapy is rarely successful in these patients [42]. As a result, systemic chemotherapy is usually considered the standard therapeutic strategy [43]. BClivM are responsive to anthracyclines and taxane-based chemotherapy in 50 70% of the cases, with median survival times increasing to up to 24 months compared to less than 6 months in patients that have not received treatment [44]. Thus, chemotherapy in the setting of breast cancer that has spread to the liver serves to delay progression of the disease and prolongs patient survival, but is rarely curative. While most of the blood supply in the liver originates from the hepatic portal vein, hepatic metastases generally derive their blood supply from the liver artery. This fact has been exploited by a procedure known as transcatheter arterial chemoembolization (TACE), in which catheters are inserted into branches of the hepatic artery that are supplying the metastases. Embolic particles in conjunction with chemotherapy, or particles laden with the chemotherapeutic agent, are injected into the catheter. Indeed, some breast cancer patients may benefit from TACE, which can result in a two fold increase in survival rates compared to patients treated with systemic chemotherapy [45]. Two factors contribute to the efficacy of TACE, the first being the focused administration and increased local concentration of the chemotherapeutic agent to the liver metastases and the second results from the embolization of the hepatic artery, which leads to necrosis of the developing liver metastases due to the reduction in blood flow. Similarly to breast cancer patients, the liver is one of the most common sites for the spread of gastro-intestinal cancers and is the most frequent site for colorectal cancer (CRC) metastasis [29]. In CRC patients, surgical resection represents
8 280 S. Tabariès and P.M. Siegel an important treatment modality and this approach is associated with 5 year survival rates ranging from 23 to 45% [41, 46, 47] (For more information on treatment options for CRC liver metastasis, see Chapter 12 in this volume). Based on these observations, liver resection as a treatment option for breast cancer patients with liver metastases is increasingly being explored. Indeed, breast cancer patients with BCLivM that have undergone liver resection have 5-year overall survival rates that range from 21 to 42% [41, 44, 46, 48 50]. This treatment option is only offered to those patients with low surgical risk, who present with an identifiable and low number of liver metastases in a location that permits resection and where the liver is the only site of distant metastases [51]. Unfortunately, only 1 5% of patients with hepatic metastases qualify under these criteria [27, 41]. Local ablation therapies have been developed and are beginning to be used in small case studies to directly kill tumor cells. This can be accomplished by cryotherapy (freezing cancer cells) or burning them through the use of radiofrequency ablation [52] or microwave coagulation therapy [53]. These loco-regional approaches are best applied to a small number of liver lesions, which are less than 5 cm, and are often used when surgical resection is not possible or following chemotherapy that has reduced the tumor burden in the liver [51]. For liver metastases that are too large to be treated with the above-mentioned local ablation therapies, localized radiation therapy such as selective internal radiotherapy (SIRT) and stereotactic body radiotherapy have been shown to be feasible and provide local control in breast cancer patients with liver metastases [54, 55] (for a more extensive discussion, see Chapter 13 in this volume). Despite these systemic and regional therapeutic strategies, a targeted reagent that could be employed in patients with breast cancer liver metastasis has not yet been developed The Liver as a Metastatic Site Due to the numerous steps and barriers that constitute the metastatic cascade, the distal spread of cancer cells is considered to be an inefficient process [28]. The greatest hurdle that metastatic cancer cells must overcome is believed to be their early survival and growth once they have seeded the metastatic site [28] (For additional discussion, see Chapters 3 and 8 in this volume). Indeed, the ability of tumor cells to progress rapidly to macroscopic metastases depends on the compatibility of the tumor cell and the new microenvironment in which they now find themselves. Although any malignancy can spread to the liver, the direct passage of blood from the gastrointestinal tract to the liver via the portal circulation results in a high rate of liver metastasis from gastrointestinal tract tumors. For example, liver metastases occur in 35 78% of patients with colorectal cancer [29, 56 60]. In fact, the liver represents the main target organ of gastrointestinal (GI) cancers such as carcinomas of the colon (35 78%), pancreas (85%), esophagus (52%) and the stomach (39%) [29, 57]. In other cancers such as the lung or the breast, the liver is rarely the only target organ (16 and 30%, respectively) and these cancers typically spread to other sites [29].
9 10 Breast Cancer Liver Metastasis 281 Most research on liver metastasis has been focused on CRC, in which cancer cells are directly delivered to the liver via the portal vein. However, observations made from the study of CRC liver metastasis may not be entirely applicable to BCLivM. While the underlying mechanisms that drive breast cancer liver metastasis may differ from those in CRC liver metastasis, it is likely that the nature of the liver architecture and microenvironment will impose specific constrains that select for unique characteristics within tumor cells that seed this organ, regardless of whether they originated from the breast or colon Architectural Features of the Liver The liver is the largest gland in the body and its architecture is distinct from that of other organs. For example, blood delivery in the liver is provided by both the hepatic artery and the portal vein. Unlike what is observed in other organs, the majority of the liver s blood supply is venous blood. Indeed, the portal vein drains the blood from the GI tract and accounts for 70 % of the liver blood supply [61]. The first point of contact between metastatic cancer cells and cells within the liver microenvironment is with the endothelial cells lining the liver sinusoids. It has been shown that interactions between cancer cells and endothelial cells may be important in facilitating the arrest of tumor cells in the vessels, permitting the initiation of a cascade of events leading to the extravasation and colonization of distant organs by circulating cancer cells [62 64]. Liver sinusoids are lined by flat endothelial cells and also contain resident Kupffer cells. The Kupffer cells, which are liver-specific macrophages, anchor to the vessel walls and may partially obstruct the liver sinusoid, leading to the physical entrapment of tumor emboli [65]. In addition, the endothelial lining of the liver sinusoids possesses numerous fenestrae or small pores and the endothelial cells lack a well formed and substantial sub-endothelial basement membrane, two features which are uncharacteristic of blood vessels found in most other organs. These characteristics are likely to have important consequences for the early seeding and survival of cancer cells that invade the liver and may represent conditions that are conducive to the implantation of tumor cells in this organ (Fig. 10.2) [66] (for more on the unique architecture of the liver and the role of inflammation in liver metastasis, see Chapters 2, 3, 6 and 7 in this volume). Following adhesion to endothelial cells in the liver sinusoids, tumor cells initially interact with underlying extracellular matrix (ECM) proteins rather than an organized, laminin-containing basement membrane such as exists in other organs. The space of Disse separates the sinusoidal endothelial cells from the hepatocytes. It contains extracellular matrix components that are deposited by hepatic stellate cells, which play an important role in cell differentiation and maintenance of cell function within the liver. In the adult liver, the sub-sinusoidal ECM is characterized predominantly by the presence of fibronectin and, to a lesser extent, collagen I [67]. Small quantities of collagen III, IV, V and VI are present, whereas the laminins are exceedingly low [67]. Nevertheless, it has recently been suggested that collagen IV and laminin-1, which are typical constituents of basement membranes, can
10 282 S. Tabariès and P.M. Siegel Space of Disse Hepatic Sinusoid Hepatocyte Hepatic stellate cell Kupffer cell Endothelial cell Breast cancer cell Collagen (I, II, III) Fibronectin Collagen IV Laminin Fig The liver architecture. Four major cell types reside in the liver: the hepatocytes, the stellate cells, the Kupffer cells and the liver endothelial cells. The main cell types in the liver are the hepatocytes that perform vital and diverse metabolic functions such as the regulation of cholesterol levels, glucose storage and synthesis of albumin and bile. Liver sinusoidal endothelial cells separate the hepatocytes from the blood flowing through the sinusoids. These cells form a single layer with fenestrae that allow the efficient flow of essential materials from the blood to hepatocytes. The Space of Disse that separates sinusoidal endothelial cells from the hepatocytes, contains extracellular matrix (ECM) components that are deposited by hepatic stellate cells. In the adult liver, the sub-sinusoidal ECM is characterized predominantly by the presence of fibronectin and, to a lesser extent; collagen I. Small quantities of collagen III, IV, V and VI are present, whereas the laminins are exceedingly low. The fenestrated sinusoidal endothelium creates a unique situation where tumor cells have direct access to ECM components within the Space of Disse. Finally, Kupffer cells are the resident macrophages of the liver that adhere to the sinusoidal endothelium. These cells are responsible for clearing the blood of ingested bacterial pathogens and removing spent red blood cells from the circulation also be detected in the Space of Disse (Fig. 10.2) [68]. The fenestrated sinusoidal endothelium provides a unique situation where tumor cells have direct access to ECM components within the Space of Disse. Such interactions with the underlying ECM components may provide attachment points for cancer cells and permit their early survival and growth in the liver. Cancer cell attachment to, and subsequent migration and invasion through the ECM requires interactions which are predominantly mediated by integrins. Indeed, metastatic CRC cells are characterized by specific expression patterns of adhesion molecules such as integrins [69]. Inhibition of certain integrins (α2, α6, β1, β4) results in a reduction in tumor cell adhesion within the sinusoid, suggesting that integrin-mediated adhesion to ECM
11 10 Breast Cancer Liver Metastasis 283 plays an extremely important role in the ability of colon cancer cells to establish and grow in this organ [69]. Thus, tumor cells arresting in the liver sinusoids interact directly with the ECM, rather than basement membrane components, to facilitate their extravasation, survival and outgrowth [68, 70 72]. These distinctive features of the liver may require that diverse cancer cell types express similar mediators in order to successfully colonize this organ. It is also conceivable that breast cancer cells may adopt unique strategies to metastasize to this organ that are distinct from other types of liver-metastatic cancers. For example, colorectal metastases to liver display three main types of growth. The desmoplastic growth pattern, where metastases are separated from the liver parenchyma by a layer of desmoplastic stroma is characterized by the prevention of direct interaction between tumor cells and hepatocytes. The second growth pattern is termed pushing type growth, with an absence of desmoplastic stroma and a thin layer of reticulin fibres separating the tumor cells from the hepatocytes. Finally, the minority of colorectal liver metastases exhibit a replacement type growth pattern, where tumor cells replace hepatocytes and co-opt the pre-existing sinusoidal blood vessels and this is characterized by minimal angiogenesis [73](see Chapter 3 in this volume for a more extensive discussion on the different types of liver metastases). In contrast to colorectal liver metastases that are predominantly of the desmoplastic (42%) or the pushing (46 %) growth types, breast cancer liver metastases are mostly of the replacement type (96%) [74]. In addition, it has been demonstrated that breast cancer cells interact directly with hepatocytes [75]. Remarkably, electron microscopy of metastatic breast cancer cells within the liver revealed that they form tight junctions with hepatocytes [76]. Together, these observations suggest that breast cancer cells may also evoke unique molecular mechanisms to facilitate their colonization, survival and growth in the liver Mediators of Breast Cancer Liver Metastasis Organotropism of cancer cells may also be mediated by the expression of cell surface adhesion molecules or receptors that are specific for ligands (and counter receptors) found in the target organ. The expression of common genes may be found in different types of cancers that metastasize to the same organ. For instance, breast cancer cells expressing the chemokine receptor CXCR4 preferentially target organs with high levels of its natural ligand SDF-1 (CXCL12) such as the lung, bone and liver [19, 77]. Interestingly, CXCR4 has also been demonstrated to be involved in CRC liver metastasis [78]. Furthermore, hepatic stellate cells producing SDF-1 may facilitate the formation of liver metastases from CXCR4 + CRC cells [79]. Similarly, elevated expression of PRL-3, a non-receptor protein tyrosine phosphatase, correlates with progression and metastasis of CRC, gastric and breast cancers [80 82]. These observations suggest that different cancers that metastasize to the liver may use common strategies. However, recent studies have highlighted the ability of breast cancer cells to adopt specific strategies to metastasize to the liver compared to other liver-metastatic cancers. Indeed, in vivo selection strategies, using xenograft
12 284 S. Tabariès and P.M. Siegel or syngeneic breast cancer cell models, have allowed sub-populations of metastatic cells to be isolated from particular organs or tissues. Coupled with gene-expression profiling approaches, we and others have identified distinct genes which are characteristic of breast cancer cells that metastasize to several different organs [83 91]. While these studies have focused on metastatic sites such as the bone, lung and brain; relatively little work has been performed to identify functional mediators of breast cancer metastasis to the liver. The identification of molecular mediators that govern organ-specific breast cancer metastasis has been largely achieved through the use of animal models of the disease. The most desirable models for investigating this process involve the orthotopic implantation of breast cancer cells into the mammary fat pad of syngeneic, immunocompetent mice, which permits spontaneous metastasis following primary tumor growth. The second approach utilizes immunodeficient mice in which human derived breast cancer cells (xenograft models) are introduced orthotopically to examine primary tumor growth and spontaneous metastasis or following injection directly into the bloodstream to study experimental metastasis to the bone, lung or liver [92]. Using these model systems, numerous genes involved in different pathways such as cell adhesion, apoptosis or TGF-β signaling have been identified. The importance of these genes in the liver metastatic phenotype will be described below Studies Using Xenograft Models c-jun: A potential role for c-jun, a transcription factor, in promoting breast cancer liver metastasis has recently been suggested [93]. In this study, MCF-7 breast cancer cells were engineered to overexpress c-jun and shown to possess enhanced proliferation, motility and adhesion in vitro and enhanced tumorigenicity in vivo, when compared to control cells. When c-jun overexpressing cells were injected into the tail vein of mice, 50% of the animals developed macroscopic liver metastases while animals receiving the vector control cells failed to develop liver metastases. Interestingly, mice injected with c-jun expressing MCF-7 cells failed to develop lung metastases suggesting that overexpression of c-jun was sufficient to evoke a liver-specific metastatic phenotype. The same group subsequently demonstrated very similar results when c-jun was expressed in SKBR3 human breast cancer cells. In this study, c-jun overexpression was correlated with increased expression of VEGF, CXCR4 and eif-4e as potential target genes; however, their functional involvement in promoting breast cancer metastasis to the liver was not demonstrated [94]. Galectin-3: Galectin-3 is a member of the lectin family and is involved in various biological processes, including tumorigenesis and metastasis [95, 96]. Galectin-3 overexpression in BT549 breast cancer cells, which do not normally express this protein, promotes their ability to form liver metastases following splenic injection [97]. It has been proposed that Galectin-3 expression can protect breast cancer cells from the toxicity associated with the formation of reactive oxygen species and nitric
13 10 Breast Cancer Liver Metastasis 285 oxide production by hepatocytes or Kupffer cells during the arrest of tumor cells in the hepatic sinusoids. This protective effect is thought to be mediated by inhibition of apoptosis in Galectin-3 expressing cells [97, 98]. CD44: The adhesion molecule CD44, which is expressed at the surface of the cell, binds to hyaluronic acid as well as ECM components such as fibronectin or Collagen [99]. By alternative splicing, nine CD44 isoforms of different sizes are produced including the standard form of CD44 (CD44s), which corresponds to the shorter isoform and the one most frequently expressed in cells. Moreover, CD44 splice isoforms respond differently to post-translational modification and correlative evidence has linked CD44 expression, and specific splice variants, with the invasive and metastatic abilities of breast cancer cells [100]. Indeed, the CD44 variant v5 and v6 are the most frequently expressed in breast cancer tissues and elevated soluble CD44v6 levels in breast cancer patients correlates with the presence of liver or bone metastases [100]. Recently, experimental evidence based on the use of a Tet-Off regulatable system to control expression of CD44s has functionally implicated CD44s in promoting breast cancer liver metastasis. MCF-7 breast cancer cells became more motile and invasive in vitro when CD44 was expressed compared to the same cells in which CD44s expression was suppressed by the addition of doxycycline (DOX). When injected sub-cutaneously, the MCF-7 breast cancer cells formed tumors with the same penetrance and growth characteristics, irrespective of CD44s expression. However, 8/11 animals injected with MCF-7 cells that expressed CD44s (-DOX) developed liver metastases while 0/12 mice developed liver metastases when CD44s expression was suppressed by doxycycline treatment [101]. Interestingly, while MCF-7 cells have previously been reported to metastasize to different organs including the lung, bone and the liver; in this study CD44s expression resulted specifically in liver metastasis. Smad7: Increases in TGF-β expression have been reported in several cancers, particularly breast cancers, and they have been correlated with increased invasiveness [ ]. TGF-β signaling is transmitted through Smad proteins and among these, Smad7 functions as a dominant negative to inhibit TGF-β signaling by interacting with the TGF-β type I receptor [105, 106]. JygMC(A) cells, that were originally derived from a mouse mammary carcinoma and spontaneously metastasize to the lung and liver following subcutaneous injection in nude mice [107], have been used to demonstrate a negative role for Smad7 in breast cancer metastasis to the liver. Mice injected with JygMC(A) cells engineered to overexpress Smad7 displayed longer survival times and these animals displayed a decrease in metastasis to both the lung and the liver. Moreover, using a high-throughput Western blotting approach, protein expression changes were identified between parental or Smad7 expressing cells. In this way, several proteins involved in cell-cell adhesion were found to be upregulated in Smad7 expressing cells, including E-cadherin, α- catenin and β-catenin that are involved in the formation of adherens junctions or Occludin and ZO-2 that participate in the formation of tight junctions. The coordinated upregulation of these cell-cell adhesion proteins resulted in a decrease in the migratory and invasive abilities of the JygMC(A) cells, suggesting that Smad7 may function to inhibit breast cancer metastasis by stabilizing cell-cell adhesion complexes [108].
14 286 S. Tabariès and P.M. Siegel DEC1: More recently, the same group has compared the gene expression profiles of parental and Smad7 overexpressing JygMC(A) cells and reported that TGF-β may play a role in promoting breast cancer survival through the induction of DEC1 (Differentially Expressed in Chondrocytes 1) expression in both JygMC(A) and 4T1 cells [109]. Moreover, inhibition of DEC1 function using a dominant-negative mutant resulted in a decrease in lung and liver metastasis through enhanced apoptosis, without affecting primary tumor growth. Finally, the authors showed that DEC1 expression is suppressed by a dominant negative mutant of the TGF-β receptor II or by Smad7 [109]. Taken together, these studies argue that autocrine TGF-β signaling induced in JygMC(A) breast cancer cells supports cell survival. Indeed, increased expression of Smad7 and decreased expression of DEC1, two molecules involved in TGF-β signaling, inhibited lung and liver metastasis [108, 109] Studies Using Syngeneic Models While the use of human-derived cell lines that can be xenografted into athymic mice has provided important insights into breast cancer metastasis in general and breast cancer liver metastasis in particular, there are a few caveats to this experimental system. First, injection of human-derived breast cancer cells requires the use of immuno-compromised mice. As a result, the metastatic process is modeled in the absence of a host anti-tumor adaptive immune response which undoubtedly has a significant impact on the dissemination of cancer cells. Second, the use of human tumor cells in a mouse host may result in the failure to detect important tumor/host cells interactions due to reduced affinities of receptor/ligand or adhesion molecule interactions between species. Third, these metastasis models generally require that tumor cells be injected directly into the bloodstream (cardiac or tail vein injection) to investigate organ-specific metastases to the bone or lung, which obviates the first steps of the metastatic cascade, namely local invasion from the primary site and intravasation into the circulation. Finally, the spectrum of metastatic sites that can be examined using these xenograft models are limited and metastasis to additional organs, such as liver and brain, is rare. From this perspective, the 4T1 mouse mammary carcinoma cell populations have proven to be an excellent model system to study breast cancer metastasis [ ]. The 4T1 mouse mammary carcinoma cell population was derived as one of several sublines from a single spontaneously arising mammary tumor in a Balb/cfC3H mouse [ ]. Sublines with distinct biological properties were established including 67NR cells which are tumorigenic but non-metastatic, 168FAR and 4T07 cells which are tumorigenic and disseminate to distant organs and tissues but fail to establish metastatic lesions, 66cl4 cells that form tumors and metastasize to the lungs and 4T1 cells that are the most aggressive of the series. Indeed, as in human cancer, 4T1 cells form tumors that invade locally to the lymph nodes and metastasize distally to the bone, lung, liver and brain [113]. These cell models have been widely used to decipher mechanisms through which breast cancer cells spread to distant organs. Thus, this series of cell lines has been used to identify candidate genes that are important for the ability of breast cancer
15 10 Breast Cancer Liver Metastasis 287 cells to spontaneously metastasize from the primary site. This approach has implicated numerous candidate genes that are involved in pathways such as apoptosis, inflammation or Wnt signaling as important mediators of breast cancer metastasis. Bnip3: Using the 67NR, 4T07 and 4T1 breast cancer cells, a role for the Bcl2/Adenovirus E1B 19 kda Interacting Protein-3 (Bnip3) as a negative regulator of general breast cancer metastasis has been proposed [114]. Indeed, expression of Bnip3 inversely correlated with the intrinsic metastatic ability of the individual cell populations. Of the three cell populations tested, the 67NR cells expressed the highest level of Bnip3 while the 4T1 cells expressed the lowest levels. Interestingly, the 4T07 breast cancer cells that are known to form primary mammary tumors but fail to establish macroscopic distant metastases expressed intermediate levels of Bnip3 [114]. A sirna-based approach to diminish Bnip3 expression in 4T07 or 67NR cells resulted in enhanced primary tumor growth and the formation of metastases in multiple organs including the sternum, lungs and liver by a mechanism involving the evasion of Bnip3-induced cell death under hypoxic conditions [114]. Thus, Bnip3 appears to function as a negative regulator of generalized breast cancer metastasis. CCL5: CCL5 is a pleiotropic chemokine that is able to recruit T cells, NK cells, dendritic cells, mast cells, eosinophils and basophils to sites of inflammation [115]. Moreover, elevated CCL5 plasma levels correlate with disease progression in breast cancer patients [116, 117]. This observation is further validated by the fact that normal breast epithelial ductal cells express negligible CCL5 levels, but this cytokine is readily detectable in breast tumor cells derived from both DCIS and IDC lesions [118]. Recent evidence also suggests that CCL5 may act directly on tumor cells to increase their migratory and invasive properties [118]. Using antisense approaches, reduced CCL5 levels in 4T1 breast cancer cells was shown to be associated with a diminished ability to form spontaneous lung and liver metastasis and correlated with diminished expression of downstream targets such as cathepsin-l, MMP-2, MMP-3, MMP-10 and MMP-17 [119]. These results suggest that tumor-derived CCL5 expression may contribute to breast cancer cell invasion and metastasis, in part, through its ability to upregulate the expression of numerous proteases [119]. These data also suggest that CCL5 does not function as a liver-specific metastasis mediator but acts as a general regulator of breast cancer metastasis. Wnt-5a: Wnt family signaling proteins are involved in various pathways including cell proliferation and differentiation, embryonic patterning, maintenance and differentiation of stem cells, cell polarity and axon guidance and have also been implicated in carcinogenesis, including the development of breast cancer [ ]. Wnt-5a, a member of the Wnt protein family, activates non-canonical signaling pathways such as the Wnt/Ca 2+ pathway which involves stimulation of intracellular Ca 2+ release via activation of Phospholipase C and Protein Kinase C [127]. Elevated Ca 2+ levels activate the calcium-regulated phosphatase, Calcineurin and this leads to activation and nuclear accumulation of the transcription factor NF-AT1 [128]. Furthermore, NF-AT1 activity has been shown to suppress the canonical Wnt signaling pathway during Xenopus development, whilewnt-5a has been suggested to antagonize canonical Wnt activity in limb development, in part, through promoting β-catenin degradation [123, 129]. Altered expression of Wnt-5a has been reported
16 288 S. Tabariès and P.M. Siegel in both colon and breast cancers [130, 131]. More specifically, Wnt-5a expression has been reported as a prognostic factor for long-term disease free survival in breast cancer patients [131]. Loss of Wnt-5a protein expression is associated with an aggressive tumor phenotype in IDC, such as higher histology grade and absence of ER and PR. Interestingly, no correlation has been found with ILC [132]. Moreover, the same study reported that Wnt-5a expression was lost in 78% of patients with recurrent cancer while loss of expression was found in only 35% of recurrencefree patients [132]. Finally, Wnt-5a repression has been shown to correlate with increased adhesion to collagen and reduced migration of HB2 ductal breast epithelial cells [124]. Together, these data identify a tumor suppressive role for Wnt-5a and predict that loss of Wnt-5a expression could increase the risk of early relapse, possibly by influencing cell adhesion and migration [124, 132]. The Wnt-5a signaling pathway has recently been identified as a negative regulator of breast cancer metastasis to the lung and the liver [133]. Indeed, intraperitoneal administration of Foxy-5, which mimics Wnt-5a signaling in 4T1 breast cancer cells, resulted in decreased metastasis to the lung and the liver [133]. In vitro studies further suggested that Foxy-5 can also impair breast cancer cell migration and invasion without affecting cell proliferation or apoptosis in 4T1 cells [133]. These results are in accordance with previous data, described above, suggesting that loss of Wnt-5a expression in the primary breast tumors correlates with an increased risk of metastatic spread [132]. While the majority of these studies have identified factors that affect the ability of breast cancer cells to metastasize to the liver and the lung, few appear to describe molecules that specifically regulate liver metastasis A Role for Tight Junctional Proteins in Breast Cancer Liver Metastasis Loss of cell-cell adhesion complexes appears to constitute a hallmark of a more aggressive phenotype in cancer. Based on their intercellular adhesion role, it has been hypothesized that reduced expression of adhesion molecules in metastatic cancers would enhance tumor cell motility and invasion. Tight junctions create a seal between adjacent epithelial cells to regulate the paracellular movement of water, solutes and macromolecules [134]. Claudins are key transmembrane proteins that promote cell-cell adhesion through homo- and heteromeric interactions between adjacent cells. Given this function, Claudin levels are predicted to be reduced in metastatic cancers. Indeed, many Claudins are down-regulated during cancer progression, including Claudin-1 and Claudin-7 in breast cancer [ ]. The importance of modulating cell-cell adhesion complexes in general and a specific role for tight junctional proteins in the process of breast cancer liver metastasis has recently been highlighted (Fig. 10.3). A 4T1-derived cell subpopulation (4THM) that exhibits an elevated ability to metastasize to the liver when compared to the parental 4T1 cells was used to compare the gene expression profiles of liver metastases with those of 4THM-derived primary tumors [138]. This approach revealed that gene expression profiles of primary tumors arising from 4T1 and 4HTM cells
17 10 Breast Cancer Liver Metastasis 289 A Normal Cells Loss of Claudin Expression Invasive Cancer Dissemination B? Claudin-2 Fig Potential effects of differential Claudin expression on breast cancer liver metastasis. (a) Loss of tight junction components facilitates transition to invasive cancer and may enable breast cancer cells to spread to distant organs [139, 141]. (b) Claudin-2 may mediate breast cancer cell/hepatocyte adhesion or help breast cancer cell/ecm interactions that promote cancer cell survival and growth in the liver. ITG; integrin-containing complex were very similar while the breast cancer liver metastasis profile was more divergent. Indeed a 16 gene signature was identified that was specifically reduced in 4THM primary tumors and their liver metastases compared to parental 4T1 tumors. Among these genes, several encode proteins that are normally involved in the formation of cell-cell junctions. Indeed, claudin-3, claudin-4 and ZO-1 participate in the formation of tight junctions while γ-catenin is involved in the formation of adherens junctions and desmosomes [139]. Although these data identify loss of intercellular interactions as an important factor during breast cancer liver metastasis, a causal role for the loss of these junctional proteins in this process has yet to be firmly established. In a similar manner, we have utilized an in vivo selection approach to enrich for breast cancer cells that aggressively grow in the liver and identify novel breast tumor cell intrinsic genes that are important for the development of hepatic metastases. Following two rounds of splenic injection, we have isolated 4T1 breast cancer cells that display either a weak or aggressive growth phenotype in the liver. Gene expression profiling identified several tight junction proteins that are specifically lost in the liver-aggressive breast cancer cells (Fig. 10.3). Interestingly, in the context of diminished expression of several tight junction proteins, we also observed that Claudin-2 levels are specifically elevated in our liver-aggressive 4T1 sub-populations [140]. We observed a coordinated loss of Claudin-3, -4, -7 and Occludin in our liver aggressive breast cancer cells and this is in line with a recent study that has identified
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