Chapter 1 

Macrophages, Extracellular Matrix, Estrogens and Breast Cancer Risk

Citation: David H. Nguyen. “Macrophages, Extracellular Matrix, Estrogens and Breast Cancer Risk.” Systems Biology of Tumor Physiology, Springer Science+Business Media (New York). Estimated Publication Date 2015. [Draft 12/21/14]

Outline of Chapter 1

Introduction

Section 1. The Estrus Cycle Regulates Macrophages in the Mammary Gland

Section 2. The Estrus Cycle Regulates Macrophages in the Ovaries

Section 3. The Effects of Estrogens on Macrophages
Section 4. Macrophages as Targets of Endocrine Disrupting Agents

Section 5. Estrogen Effects on Macrophage ROS Production
Section 6. Complex Interplay Between Macrophages and the Extracellular Matrix

Section 7. Testing the Estrus-Regulated Macrophage-Dependent Hypothesis of Breast Cancer Risk
 

Introduction

The primary purpose of this chapter is to succinctly present evidence that macrophages are one of the important components within the complex mechanism underlying why lifelong exposure to estrogen is a risk factor for breast cancer. In line with the systems biology theme of this book, this chapter underscores the integrated way in which multiple organs are regulated by macrophages and systemic hormones. This systems biology view reveals that breast cancer risk due to life-long estrogen exposure needs to be understood as having multiple biological mechanisms that are distinct, yet deeply intertwined. This chapter develops what will be referred to as the estrus-regulated, macrophage-dependent theory of breast cancer risk due to life-long exposure to estrogen.

The secondary purpose of this chapter is to present an example of how a systems biology perspective provides an integrated understanding of the ways in which mammalian physiology is intricately tied to tumor development. The advantage of an integrated perspective is that it reveals more mechanisms that can become candidates for therapeutic intervention, since rarely, if ever, is there just one biological mechanism that is responsible for a complex disease phenotype. The systems biology perspective also guides the scope and strategy of how the research literature can be approached. This will be helpful to investigators who are just starting to study physiological mechanisms that pervade the entire organism. It is also helpful to those who study minute molecular/subcellular mechanisms but who seek to have a global understanding of how physiological mechanisms interact to affect their research question.

Epidemiological studies show a correlation between the following: early onset of puberty and breast cancer risk; late onset of menopause and breast cancer risk; exposure to endocrine disrupting chemicals and the early onset of puberty (Collaborative Group on Hormonal Factors in Breast, 2012). The question of interest now becomes about how we can mitigate breast cancer risk by modulating the biological mechanisms behind these risk factors. This chapter attempts to provide the reader with an overview of why macrophages may be a good candidate as targets of prevention and therapeutic modulation. The last section of the chapter has several goals: (1) propose ways of directly testing the theory that is outlined in this chapter via experiments; (2) propose ways of indirectly testing the theory by presenting verifiable predictions of breast biology in different populations of people; (3) discuss the epidemiology studies relating age, breast density, and the theory outlined in this chapter.

Section 7. Testing the Estrus-Regulated Macrophage-Dependent Hypothesis of Breast Cancer Risk
 

Directly and Indirectly Testing the Hypothesis

Up to this point, the content of this chapter was meant to lay the foundation for why macrophages should be considered crucial preventive and therapeutic targets in the biological mechanisms underlying the risk of breast cancer from life-long exposure to estrogen. This last section will briefly outline methods for and challenges to testing the hypothesis that estrus and estrogen-mimicking compounds increase breast cancer risk by inducing macrophages to stiffen the extracellular matrix, which then feeds back to alter macrophage behavior. There are two ways of testing this hypothesis. First is the direct way of experimentally mimicking the effect of estrus-regulated, macrophage-dependent stiffening of the mammary gland microenvironment. The second and indirect way is to make verifiable predictions of altered breast biology in human populations that is consistent with the theoretical framework outlined by the hypothesis.

Experimental Approaches to Directly Testing the Hypothesis

A direct way of testing this hypothesis is to implant a gel substrate or actual human breast fragment into a mouse for an extended period of time, allowing many estrus cycles to occur, and then measuring the physical properties of the implant, the structural arrangement of the implant’s matrix, and the degree of ROS production of macrophages associated with the implant. A number of materials are commonly used as gels that carry cells or molecules for implanting into mice (reviewed in (Frantz et al., 2010)), but since macrophages are known to promote the formation of and to digest collagen I, a major component of the mammary gland ECM, a collagen I gel would a good candidate substrate. It should be considered, however, that the type of collagen I used should be those that are extracted in a way that preserves their terminal ends, which contain the moieties required for crosslinking individual molecules into a fibril (Sabeh et al., 2009). Since reconstituted collagen gels do not fully replicate the in vivo ECM (Sabeh et al., 2009), intact explanted fragments from human reduction mammoplasties would be closer to the ideal model system. It is important to keep in mind that the human mammary gland has major structural differences compared to the mouse mammary gland. In humans, the ductal epithelia is surrounded by two thick layers of fibrous stroma, whereas the epithelia of mice only have a thin layer of fibroblasts that separate the ductal compartment from the adipose compartment. The scarring that results from the transplantation procedure may confound measures of stiffness in a xenografted tissue, so considerations should be taken to minimize this effect. But regardless of impeded physical measures, histological and immunohistological features can still be measured via the physical properties of fibrillar collagen and the use of antibodies that are specific to human collagen. Immunohistochemistry would be particularly useful in studying the arrangement of human collagen in human explants that were placed into the mouse mammary gland, since it is known that the prevalence of fibrillar collagen is associated with increased tissue stiffness. Xenografted human explants should be placed into the intact mammary glands of adult female mice, as opposed to mouse mammary glands in which the epithelial compartment has been previously removed. This is because the circuitry that recruits macrophages to the mammary gland during each estrus cycle involves complex feedback between multiple compartments (epithelial cells, fibroblasts, adipocytes, etc.). Human mammary fragments would have to be implanted into the mammary glands of immunocompromised mice (Sheffield and Welsch, 1988), which have intact mammary glands (Militzer and Schwalenstocker, 1996). The length of time and window of time for implantation should also be considered. As female mice mature and then age, their menstrual cycles begin to slow down (Nelson et al., 1982). The varied aspects of the estrus cycle are likely dependent on the genetic background of the strain. 

Another method of testing this hypothesis is to measure physical forces, ECM structure, and macrophage phenotype in intact mammary glands of groups of mice that have different estrus rates. Mice that have a shorter cycle length would naturally have more cycles within their lifetime than those that have longer cycles. A genetically engineered BRCA1 mutant mouse model has been reported to exhibit shortened estrus cycles (Hong et al., 2010). Other BRCA1 mutant models may exhibit the same ovarian effect. It is possible to remove the endogenous ovaries of a mouse and then replace them with the over-active ovaries of a syngeneic donor. This approach would allow the endogenous mammary glands to be controlled by a highly active donor ovary.

Indirectly Testing the Hypothesis by Making Verifiable Predictions

The Effect of Aging

The hypothesis and theory – depending on how one uses the idea – developed in this chapter can be indirectly tested by making predictions in human populations. Regarding this estrus-regulated, macrophage-dependent ECM stiffening theory of risk from lifelong estrogen exposure, one of the most straightforward questions to ask is whether the breasts of older women are denser with ECM compared to those in younger women.  Women with denser breasts have four to six times the risk of breast cancer than those with less dense breasts (Bertrand et al., 2013; Boyd et al., 2007; Byng et al., 1998; Pinsky and Helvie, 2010). A study by Checka and colleagues (Checka et al., 2012) analyzed the mammograms of 7,007 women and showed that in general breast density decreases as women age, and that density was highest in women who were pre-menopausal (the average age of menopause is generally considered to be 50). 81% of women less than 40 years-old had dense breasts, while 74% of women between 40 and 49 years had dense breasts. The percentage drops to 57% for those between 50 and 59, then to 44% for those between 60 and 69, then to 36% for those between 70 and 79, and finally rising to 41% for those above 80 years. These data are consistent with the hypothesis that the more menstrual cycles a women undergoes, the more dense her breast tissue will be.

It should be noted that the Checka study examined the percentage of women characterized as having dense breasts across continuous age groups, but does not examine the increase in breast density within individual women across their lifetimes. This study did not address whether certain groups of women develop dense breasts early in life and then maintain that level of density up to and beyond menopause, or gradually develop density up through menopause after which the density level is maintained or lost. As with many aspects of physiology, there are likely subgroups of women with regard to this phenotype.  Radiographic breast density, as measured by the Checka study and others, is defined as the ratio of the area represented by epithelial and stromal cells, which appears white, compared to fatty tissue, which appears radiolucent (varying shades of gray). The Checka study involved patients that were mostly Caucasian and who had medical insurance. It is well known that racial disparities significantly affect breast density, along with the age of onset of breast cancer and the type of breast cancer that develops. African-American women have higher rates of triple-negative breast cancers (Kurian et al., 2010), the most aggressive type of breast cancer. Thus, race is likely another important factor in the rate of density gain and loss.

Breast tissue from reduction mammoplasty or other surgical procedures from women of varying ages would be great for examining the structural arrangement of collagen in the extracellular matrix. An increase of fibrillar collagen and stiffness with increasing age would support the theory outlined in this chapter.

The Effect of Premature Ovarian Failure

A second question for indirectly testing the theory is to ask whether women with premature ovarian failure have less dense breast tissue than normal women, since those who live beyond the ovarian failure would have had fewer menstrual cycles than normal women of the same age. Benetti-Pinto and colleagues (Benetti-Pinto et al., 2014) examined the mammographic density of 56 women who experienced premature ovarian failure (POF) at an average age of 32.35 years. Each subject had two mammograms that were taken an average of 5.25 years apart. Consistent with the theory outlined in this chapter, the authors found that the breast density of women with POF decreased across five years, regardless of whether they used estrogen-progestin therapy. The same research group conducted a similar study six years prior to this one in which they did a one-time-point comparison of mammographic density between POF patients who were on hormone therapy and normal women (Benetti-Pinto et al., 2008). In that study they did not find a difference in breast density between the POF group and the normal controls, suggesting that POF does not decrease breast density. However, the findings from the 2014 study nullify the results of the 2008 study, because the 2014 study revealed that parity significantly reduces the degree of breast density in POF patients. In the later 2014 study 32% (18/56) of POF patients were nulliparous (never having had a full-term pregnancy) while those who were multiparous (having had more than one full-term pregnancy) were shown to have a lesser degree of breast density. In other words, having had children decreases women’s degrees of breast density. This is significant for the comparison of the two studies because the earlier 2008 study reported 54.8% of the POF patients as “breastfeeding,” meaning that they had at least one full-term pregnancy. The fact that half of the POF group in the 2008 study was parous means that the POF cohorts between the two studies are not comparable. Further evidence for this can be found in the two papers. In the 2008 study, the POF group had an average age of 36.9 years and an average digitized breast density of 25.1%. In the 2014 study, the nulliparous POF group at the second mammography screening had an average age of 40.33 years and an average digitized breast density of 25.4%. It is known that mammographic density decreases with age (Checka et al., 2012), so even though the POF group in the 2008 study was several years younger, it had a comparable degree of breast density as the POF group in the 2014 study; likely due to the fact that half of the 2008-POF group was parous, which correlates with decreased breast density. The effect of parous POF patients also applies to the third study from this research group, which was published in 2010 (Soares et al., 2010). Soares and colleagues compared the mammographic density of POF patients who were on hormone therapy to normal post-menopausal women who were on hormone therapy, finding no difference. However, as in their 2008 study, half of the POF cohort had breastfed and were thus parous. Additionally, in the Soares study the patients in the POF group had already been diagnosed for an average of 85.9 months (7.16 years) at the time of the study. 7.16 years may have been a time during which significant reduction in breast density in the POF cohort had already occurred, since the 2014 study showed this effect. In summary, further studies with larger sample sizes and comparable experimental design are warranted to clarify the effect of POF on mammographic density.         

As with the data linking aging to breast density, mammography does not reveal the structural characteristics of the extracellular matrix nor the physical properties of the tissue. Measuring these factors in breast tissue from women several years after they underwent POF compared to age-matched normal women would be a way of confirming the predictions of the theory outlined in this chapter.

The Effect of Hormone Replacement Therapy in Post-Menopausal Women

A third question for indirectly testing the theory outlined in this chapter is to ask if hormone replacement therapy in post-menopausal women increases breast density. Exogenously treating a patient with estrogens and progestins is akin to an “over-expression” experiment in which the hypothesized effect is induced by artificially adding or promoting a factor. In this case, the theory outlined in this chapter would predict that treatment with exogenous hormones would increase breast density in post-menopausal women. Indeed, multiple studies have shown this to be true, have reported that varying doses of hormone treatment correlate with varying degrees of increased density, and that not all women who receive treatment exhibit the same degree of increased density (Christodoulakos et al., 2006; Laya et al., 1995; Marugg et al., 1997). Though the post-menopausal patients in these studies exhibit increased mammographic density due to hormone therapy, it is unknown if macrophages are recruited to their mammary tissue as part of why the density increased. An increase in the amount of epithelial cells, stromal cells, and extracellular matrix would all result in increased mammographic density. However, it is unknown whether the new extracellular matrix in these post-menopausal women is arranged in ways that are similar to the effect of macrophages on the matrix during normal menstruation.      

The Effect of Wiskott-Aldrich Syndrome on Breast Density

A fourth question for indirectly testing the theory is to ask if women with mutated macrophages have less dense breasts than women with normal macrophages. The Wiskott-Aldrich Syndrome (WAS) is an X-linked disorder that results in people who have a mutated form of the Wiskott-Aldrich Syndrome protein (WASP). The WASP protein is involved in actin polymerization, which is critical for cell movement. Since the WASP gene is primarily expressed in hematopoietic cells, WAS patients exhibit recurring infections, easy bruising, prolonged bleeding, and a low number of small platelets (reviewed in (Thrasher and Burns, 2010)). Since macrophages are derived from the hematopoietic system, WAS patients should exhibit deficits or impairments regarding physiological features that are governed my macrophages. Macrophages from patients with WASP mutations exhibit impaired filopodia, lamellapodia, and cell migration (reviewed in (Thrasher and Burns, 2010)). Given the role of macrophage in remodeling the ECM of the mammary gland, the theory outlined in this chapter would predict that WAS patients would have breast tissue that is less dense and that has altered extracellular matrix, compared to normal women, because of impaired macrophage function. The advent of modern medical treatments such as bone marrow transplants and antibiotics has allowed WAS patients to survive for multiple decades, which is enough time for their breast tissue to have undergone many menstrual cycles (Blaese et al., 2013). Since WAS patients may have little concern for developing breast cancer, which is a disease significantly influenced by age, there would be shortage of mammography data with which to examine breast density. However, due to the types of cancers that WAS patients experience and die from (Salavoura et al., 2008), they may commonly undergo thoracic computed tomography (CT) scans for diagnostic purposes. The CT data would allow investigators to determine the density of their breast tissue as a function of age. CT scans are relatively comparable to mammography for determining breast density (Salvatore et al., 2014). Retrospective analysis of breast density via CT data should consider and extrapolate the menstrual phase of the patient at the time of the scan. WAS patients who undergo bone marrow transplantations may have most of their myeloid-derived cells, which includes macrophages, replaced, which may be a confounding factor in determining whether the WAS affects breast density based on dysfunctional macrophages. However, differing WAS patients will have received bone marrow transplants at different times and thus may still have had significant years of adult life with dysfunctional macrophages affecting the mammary glands. Furthermore, not all bone marrow graft procedures yield a completely recovered immune system after the same amount of time, which may still leave a graft recipient with a number of years with dysfunctional mammary macrophages.