Browsing by Subject "Breast cancer"

Controlled breathing techniques are widely used to help people manage pain, and there is growing interest in using these approaches during painful outpatient medical procedures. The outpatient MRI-guided breast biopsy is one setting where patients may particularly benefit from breathing interventions for pain. To date, however, no studies have examined interventions for pain reduction in this setting. This randomized controlled pilot study assessed the feasibility, acceptability, and efficacy of a novel audio-recorded controlled breathing intervention for reducing breast and body pain in women undergoing MRI-guided breast biopsy. Fifty-eight women undergoing MRI-guided breast biopsy were randomized to a 1) controlled breathing intervention or 2) usual care condition. Assessments of pain, anxiety, distraction from pain, relaxation, blood pressure, heart rate, pain catastrophizing, and self-efficacy for managing pain and anxiety were administered. Participants were assessed at baseline, during biopsy, immediately post-biopsy, and 24 hours post-biopsy. Results demonstrated that the intervention was feasible and acceptable. However, when compared to usual care, controlled breathing did not significantly reduce pain, increase distraction from pain or relaxation during biopsy, decrease physiological reactivity, reduce pain catastrophizing, or increase self-efficacy for pain and anxiety from pre- to post-biopsy. These findings could be used to revise the controlled breathing intervention.

A growing number of studies have investigated the role of exercise both during and after a breast cancer diagnosis. Observational data suggests that regular endurance exercise is associated with a 20-50% reduction in cancer-specific mortality in women diagnosed with early stage breast cancer, compared to inactive women; however it is unclear whether there is a differential association across breast cancer subtypes. As a pre-requisite to guide future large phase II/III clinical trials, there is a critical need to confirm the biological plausibility of the exercise association in breast cancer patients as well as elucidate the underlying mechanisms of action via utilization of preclinical models.

In the present study we investigated the systemic effects of prescribed aerobic training in cancer patients and the direct impact on breast cancer cell subtype phenotypes. In order to test the in vivo significance, we interrogated aerobic training effects on breast cancer progression and tumor biology using syngeneic breast cancer mouse models.

Our results suggest that aerobic training may alter the host availability of pro-inflammatory and growth factor cytokines in patients with solid tumors. Modulation of systemic effectors in breast cancer patients compared to controls causes a differential phenotypic response on breast cancer cell subtypes. In vivo, aerobic training has a differential response on breast tumor progression compared to controls that is mediated by Hif1-α and metabolic reprogramming of breast cancer cells.

Cancer is a major threat to human health and results in 1 in 6 deaths globally. Despite an extraordinary amount of effort and money spent, eradication or control of advanced disease has not yet been achieved. Understanding cancer from an evolutionary point of view may provide new insight to more effective control and treatment of the disease. Cancer as a disease of dynamic, stochastic somatic genomic evolution was first described by Nowell in 1976, and since then researchers have identified clonal expansions and genetic heterogeneity within many different types of neoplasms. The advancement in sequencing technology, especially single-cell sequencing, has open up new frontier by bringing the study of genomes to the cellular level. Phylogenetic analysis, which is a powerful tool inferring evolutionary relationships among various biological species or other entities based upon similarities and differences in their physical or genetic characteristics, has recently been applied to cancer studies and start to show promises in deciphering cancer evolution. However, new challenges have also arisen in experimental design, methodology and interpretation regarding to phylogeny of cancer cells. The overarching theme of this dissertation is to bring phylogenetic analysis to the context of cancer evolution. By using in silico simulations, I show the advantages and disadvantages of different sampling designs for phylogenetic analysis. Although bulk sequencing can hardly recover the topology of phylogenetic trees, I then developed a new method to infer sub-clone spatial distribution utilizing phased haplotypes from bulk sequencing. And lastly, I demonstrate the usage of phylogenetic analysis in breast cancer with multi-regional bulk sequencing and lung cancer with single cell sequencing.

The steroid hormone progesterone has complex physiologic effects. In typical development and function, cells respond to progesterone in a dose- and tissue-specific manner. Despite the wide range of physiologic concentrations, canonical effects of progesterone have been characterized in the context of a high physiologic dose (10nM+), relevant during uterine cycling. This narrow focus has produced a gap in knowledge, particularly as it relates to the effects of post-menopausal low concentration progestins (0.1-0.3nM). Given that healthy tissues possess regulatory mechanisms to sense and respond to progesterone in a non-linear dose-specific manner, we hypothesized that breast malignancies would also display discontinuous dose-specific dynamic responses. Our results show that treatment with low dose progestins (0.1-0.3nM) drives proliferation in T47D human breast cancer cells, while high dose progestins (10nM+) inhibit proliferation. Using both unbiased and targeted approaches, we found that low dose progestins facilitate cell cycle entry by enhanced expression of CCND1 (cyclin D1) and SGK1 (serum and glucocorticoid related kinase 1), which are required for initiation of the downstream molecular cascade including phosphorylation of retinoblastoma protein (Rb) and expression E2F1. Expression of CCND1 and SGK1 mRNA are proximal responses to low dose progestin treatment, but transcriptional activation is not mediated by canonical progesterone receptor (PR) activity. Future work is needed to identify previously unexplored mechanisms of PR action in the context of low dose progestin treatments. In summary, these results challenge the assumption of dose response linearity to progestins and show unique functional and molecular effects of low dose progestin treatment. Of potential concern, our findings suggest that certain breast cancers, especially those expressing high levels of PR, may be accelerated by normal post-menopausal circulating concentrations of progestins (0.1-0.3nM). However, these findings also offer a sound rationale for the clinical therapeutic use of high dose progestins for patients with PR+ breast cancer.

X-ray imaging technology has been used for a multitude of medical applications over the years. The typically measured X-ray transmission data, which records shape and density information by measuring the differences in X-ray attenuation throughout a material, have been used in the imaging modalities of radiography and computed tomography (CT), but there are cases where this information alone is not enough for diagnosis. In contrast, X-ray diffraction (XRD) is another X-ray measurement modality, one that typically does not produce spatially resolved 2D/3D images, but instead investigates small spatial spots for assessing material properties/molecular structures based on scattered X-rays. While XRD measurements of human breast tissue have previously suggested differences between signatures of cancerous and benign tissues, the typical diffraction system architectures do not support fast, large field of view imaging that is necessary for medical applications.In this work, an XRD imaging system was developed that can scan a 15x15 cm2 field of view in minutes with an XRD spatial resolution of 1.4 mm2 and momentum transfer (q) resolution of 0.02 Å-1. An X-ray fan beam was used to collect a 15 cm line of XRD measurements in a single snapshot, while a coded aperture is placed between imaged objects and detector, enabling XRD spectra for individual pixels along the fan beam extent to be recovered from the multiplexed measurement. Simulations were used to identify a suitable geometry for the system, while newly designed phantoms and test objects were used to evaluate the resolution/measurement quality. Upon finishing the design, construction, and characterization of the imaging system, studies on cancerous and benign tissue simulant phantoms were conducted to develop and identify top performing machine learning classification algorithms in a well-controlled study. With a shallow neural network (SNN) developed that achieved ≈99% accuracy on XRD image data, studies progressed to real human tissues. With these developments achieved, the final study was conducted where 22 human breast lumpectomy specimens were scanned and the SNN algorithm was modified for identification of human breast cancer. For 15 primary lumpectomy cases used for training and testing, an accuracy of 99.7% was achieved, with an ROC curve AUC of 0.953 and precision-recall curve AUC of 0.771. On the remaining 7 corner/rare cases present that were held out from initial training/testing (as an external dataset), an accuracy of 99.3% was achieved by the SNN, suggesting high performance along with a need for further representation of rare tissue cases in the training process to improve classifier generalization to new lumpectomy cases. This work demonstrates that fast, large field of view XRD imaging of thin samples on a millimeter spatial scale can be achieved using coded apertures. Further, the work shows that machine learning algorithms can complement this imaging modality by making great use of the multitude of input features available when each image pixel contains a full spectrum of XRD intensity vs angle values, allowing for algorithms to differentiate between cancerous and healthy tissue with higher accuracy (99.7%) compared to simple classification approaches (97.3%). Due to this promising potential, future work should seek to further the technology, by improving the spatial/spectral resolution, scan speed, and adding depth resolution, while applying the technology to useful medical tasks including (but not limited to) intraoperative surgical margin assessment, in-vivo imaging for biopsy vetting, and improved radiation therapy tumor localization.

The transforming growth factor beta (TGF-beta) signaling pathway is a critical regulator of multiple biological processes that are involved in cancer progression, such as proliferation, migration, invasion and metastasis. TGF-beta ligands bind to multiple high-affinity receptors (TbetaRI, TbetaRII, TbetaRIII), whose expression on the cell surface, and subsequent ability to transduce signaling, can be modulated by ectodomain shedding.

TbetaRIII, also known as betaglycan, is the most abundantly expressed TGF-beta receptor. TbetaRIII suppresses breast cancer progression through inhibiting migration, invasion, metastasis, and angiogenesis. TbetaRIII binds TGF-beta ligands, with membrane-bound TbetaRIII presenting ligand to enhance TGF-beta signaling. However, TbetaRIII can also undergo ectodomain shedding, releasing soluble TbetaRIII, which binds and sequesters ligand to inhibit downstream signaling. To investigate the relative contributions of soluble and membrane-bound TbetaRIII on TGF-beta signaling and breast cancer biology, here I describe TbetaRIII mutants with impaired (Delta-Shed-TbetaRIII) or enhanced ectodomain shedding (SS-TbetaRIII). Relative to wild-type (WT)-TbetaRIII, Delta-Shed-TbetaRIII increased TGF-beta signaling and blocked TbetaRIII's ability to inhibit breast cancer cell migration and invasion. Conversely, SS-TbetaRIII, which increased soluble TbetaRIII production, decreased TGF-beta signaling and increased TbetaRIII-mediated inhibition of breast cancer cell migration and invasion.

TbetaRI is released from the cell surface by a common sheddase of the A disintegrin and metalloproteinase (ADAM) family, ADAM17. This shedding event results in a downregulation of TGF-beta signaling. Here, I present evidence that a closely related protease, ADAM10, may be a novel sheddase for TbetaRI. A specific ADAM10 inhibitor was able to increase cell surface expression of TbetaRI, and decrease levels of circulating soluble TbetaRI in vivo. Interestingly, inhibition of ADAM10 concurrently increased shedding of TbetaRIII, and was able to alter TGF-beta signaling in a TbetaRIII-dependent manner.

Together, these studies suggest that ectodomain shedding of TGF-beta receptors is an important determinant for regulation of TGF-beta-mediated signaling and biology.

Lysine specific demethylase 1 (LSD1) is a FAD-dependent amine oxidase enzyme responsible for removing methyl groups from the side chain nitrogen of lysine within histones in order to regulate gene transcription. By its interaction with various transcriptional complexes, including those containing estrogen receptor α (ERα), LSD1 mediates expression of many genes important in cancer proliferation and progression. Herein, we report our efforts towards understanding the function of LSD1 in breast cancer. We have developed a straightforward method for the syntheses of 2-arylcyclopropylamines as irreversible mechanism-based inactivators of LSD1. We employed these small molecules as probes of LSD1 activity, and together with experiments involving the knockout of LSD1 by small interfering RNA (siRNA), we have shown that LSD1 activity is essential for both ERα-postive and ERα-negative breast cancer proliferation. LSD1 inhibitors induce a dramatic cell cycle arrest without causing apoptosis.

Furthermore, we observe that LSD1 and ERα work cooperatively to express certain estrogen-target genes through simultaneous recruitment to promoters; LSD1 inhibition diminishes ERα recruitment. Similarly, knockdown of CoREST, a binding partner of LSD1, results in comparable changes in gene expression. Although, we have not observed a direct interaction between LSD1 and ERα, we believe that CoREST may be facilitating this interaction. We have made efforts to inhibit the interaction between LSD1 and CoREST in vitro in hopes of targeting this interface in breast cancer cells in order to disrupt the necessary functional complex and prevent LSD1 activity.

Whole-genome duplication (WGD) generates polyploid cells possessing more than two copies of the genome. These events commonly occur during the evolution of human tumors across tissue types and mutational drivers, affecting an estimated 30-37% of all tumors. The frequency of WGD increases in advanced and metastatic tumors, and WGD is associated with poor prognosis in diverse tumor types, suggesting a functional role for polyploidy in tumor progression. Experimental evidence suggests that polyploidy has both tumor-promoting and suppressing effects. The polyploidization of a normally diploid cells often compromises genomic stability. In this way, WGD may be capable of promoting tumor formation, growth and progression, by facilitating the evolution of genetic heterogeneity on which selection can act. However, while some features of polyploidy can promote tumor growth, these features can also be countered by associated tumor suppressive qualities of polyploidization and associated cellular stresses. Chromosomal instability and resulting aneuploidy often have negative effects on cellular fitness; this can occur through the induction of proteotoxic stress, replication stress and delayed proliferation. Polyploidization can also be opposed by cell intrinsic and extrinsic pathways, including p53, the Hippo pathway and immunosurveillance. How these diverse and multifaceted features of polyploid cells work together to regulate tumor progression remains unclear.

Using a genetically engineered mouse model of HER2-driven breast cancer, we explored the prevalence and consequences of whole-genome duplication during tumor growth and recurrence. While primary tumors in this model are invariably diploid, nearly 40% of recurrent tumors undergo WGD. WGD in recurrent tumors was associated with increased chromosomal instability, decreased rates of proliferation and increased survival in stress conditions. The effects of WGD on tumor growth were dependent on tumor stage. Surprisingly, in recurrent tumor cells, WGD slowed tumor formation, tumor growth rate and opposed the process of recurrence, while WGD promoted the growth of primary tumors. Our findings highlight the importance of identifying conditions that promote the growth of polyploid tumors, including the cooperating genetic mutations that allow cells to overcome the barriers to WGD tumor cell growth and proliferation.

While our results revealed fitness disadvantages for recurrent polyploid tumor cells, the paradox remains that WGD is common in cancer cells despite this, suggesting that cells must evolve ways to overcome barriers to tumorigenesis. These findings suggest that a polyploid cancer cell may be delicately balanced, relying on certain pathways or processes to compensate for its cellular deficiencies more than their diploid counterparts. Ploidy-specific lethality describes the phenomenon in which inhibiting the activity or expression of a specific protein results in death of polyploid cells but not their diploid counterparts. To interrogate this idea, we next employed our models of recurrent polyploid cells to explore the impact of polyploidization on gene expression and signaling dependencies. Using RNA sequencing we uncovered that tetraploid cells exhibited decreased expression of genes of the cGAS-STING pathway. We performed two loss-of-function CRISPR screens against the kinome, one in vitro and one in vivo, to identify ploidy-specific lethal genes. The in vivo screen revealed candidates for ploidy-specific lethal genes including Srpk1, Mark4 and Ryk. Together these results demonstrated that polyploid recurrent tumor cells exhibit unique gene expression patterns that may reflect selection pressure of the immune system and may rely on unique survival mechanisms in vivo.

Despite its ubiquitous abundance, Hsp90 inhibitors have shown promise in anti-cancer clinical trials, suggesting that Hsp90 inhibitors selectively target tumor cells while exhibiting minimal effects in normal cells. Extracellular expression of heat shock protein 90 (eHsp90) by tumor cells is strongly correlated with malignancy. Development of small molecule probes that can specifically detect eHsp90 in vivo may therefore have utility in the early detection of malignancy. We synthesized a fluorescent cell impermeable Hsp90 inhibitor, HS-131, to target eHsp90 in vivo. HS-131 was characterized biochemically to ensure specificity for eHsp90, and an inactive analog was also synthesized to be used as an in vivo control.

Through confocal microscopy, eHsp90 can be visualized with cell impermeable, fluorophore-tagged Hsp90 inhibitors. High resolution confocal and real time lattice light sheet microscopy showed that probe-bound eHsp90 accumulates in punctate structures on the plasma membrane of breast tumor cells and is subsequently actively internalized. This internalization occurs in the presence and absence of inhibitors. The extent of internalization correlates with tumor cell aggressiveness, and this process can be induced in benign cells by over-expressing p110HER2, leading to malignant transformation of these cells. Internalization of eHsp90 is also increased after inhibition of Hsp70, suggesting that overcompensation of the heat shock response can also upregulate the eHsp90 trafficking mechanism. Whole body 3D cryo fluorescence imaging and histology of flank and spontaneous tumor-bearing mice strongly suggests that eHsp90 expression is a unique phenomenon in vivo.

Taken together, these results suggest that active and differential internalization of eHsp90 in aggressive cancer cells contributes to the selectivity observed upon Hsp90 inhibitor treatment and may provide a novel metastatic biomarker for solid tumors and may lead to the development of a tumor-specific drug delivery system.

My thesis research has centered on the concept of the peripheral blood cell (PBC) as an indicator of disease and environmental exposure. The PBC is not only easily accessible and constantly replenished, but it provides a snapshot of an individual's health. Doctors have long utilized PBCs as indicators of health based on count, morphology or the expression of particular cell surface markers. Using these methods, PBCs can serve as indicators of infection, inflammation or certain types of hematological malignancies. Now PBCs can be characterized as a function of their gene expression profiles in response to disease and toxicant exposure. Advances in cDNA microarray technology have made it possible to analyze global gene expression in small volumes of whole blood, or even in a sorted population of blood cells. The resulting gene expression data can serve as a molecular phenotype, or signature, of disease or toxicant exposure. These signatures serve a twofold purpose. First, they act as biological markers (biomarkers) that can indicate the presence of disease or aid monitoring the response to treatment. Second, they provide insight into the underlying biological mechanisms that are at work, by revealing genes, networks and pathways that are affected by the disease or toxin. This paradigm has been applied in a number of contexts, including infection, inflammation, leukemia, lymphoma, neurological disorders, cardiovascular disease, environmental exposures and solid tumors.

In the work presented here, we describe signatures of lead (Pb) exposure and breast cancer based on peripheral blood gene expression. Our objective in generating a blood-based signature of lead exposure was to develop a potential predictor of past and present exposure. This is particularly relevant because of continued widespread lead exposure through both environmental and occupational sources. Pb causes significant toxicities in a number of different organ systems including the hematological, endocrine, neurological and renal systems. Pb is considered a potential carcinogen due to evidence that it causes cancer in animal models and contributes to an elevated cancer risk in humans. Pb is thought to contribute to cancer risk indirectly through a variety of mechanisms, such as inhibition of DNA synthesis and repair, oxidative damage, interaction with DNA-binding proteins and tumor suppressor proteins, causing chromosomal aberrations and alterations to gene transcription. In addition, it has been shown to exacerbate the effects of other mutagens. Recent work also indicates that even low-level Pb exposure (defined here as levels below the threshold of detection of many common tests or below the level set by the CDC as an "elevated blood lead level" in children, or 10µg/dL) can impact health, especially in children, who are more susceptible to these negative health consequences.

We hypothesized that we could detect subtle and lasting changes in the PBC transcriptome that correlated to Pb exposure. We used a mouse model of per os Pb exposure to generate signatures corresponding to two different doses of Pb. One dose reflected a high-level exposure and the other a low-level exposure. We also analyzed the gene expression changes following removal of the Pb source. We were able to generate robust, dose-specific signatures of Pb exposure. This supports the growing body of evidence that even low levels of Pb exposure can have biological effects, and that there is likely no safe level of exposure. We also utilized a collection of pathway signatures to identify those pathways that were activated or repressed in response to Pb exposure compared to controls. We observed an increase in interferon-gamma pathway activity in response to low-level Pb exposure and an increase in E2F1 pathway activity in response to high-level Pb exposure. These results support previous findings that low-level Pb exposure can increase interferon-gamma production, whereas high-level Pb has been shown to increase DNA synthesis. The Pb signatures we report here were not predictive of a past lead exposure. These results suggest that the effect of Pb exposure on PBC gene expression is transient, perhaps due to the rapid turnover of blood cells and the absorption of Pb by the bones. We have proposed further studies to identify cells in the bone marrow that may serve as indicators of past Pb exposure based previous reports on the lasting effects of genotoxic stress on this tissue.

We also describe a predictor of human breast cancer based on peripheral blood gene expression. The objective of this study was to identify and characterize PBC gene expression patterns associated with the presence of a breast tumor. This work has the potential to make a significant impact on breast cancer screening and diagnosis. Despite the success of mammography in reducing mortality from breast cancer, many cancers go undetected due to factors such as breast density, age of the woman, or type of cancer. A blood-based breast tumor predictor would potentially offer an easy and noninvasive means of detecting primary breast cancer as well as monitoring patients for recurrences or metastases. In addition, the concept of using a blood-based biomarker for cancer detection would have positive implications for other types of cancer. For instance, patients with ovarian cancer are typically diagnosed at a late stage because of the absence of definitive symptoms and the lack of effective screenings methods.

We were able to successfully identify robust predictors of both mouse mammary tumors and human breast tumors based on PBC gene expression. The human breast tumor predictor exhibits a high level of sensitivity and specificity in distinguishing breast cancer patients and controls in an independent validation cohort. However, the true novelty in this study is that it integrates a factor modeling approach and a transgenic mouse model of breast cancer to identify biologically meaningful gene expression changes in the mouse PBC transcriptome. These genes were then used as the starting point for developing a human breast cancer predictor. This establishes an experimental system in which we can address questions that are inherently difficult to answer in human studies, such as whether this predictor is useful in detecting breast tumors early or in monitoring patients for recurrence or metastasis. In fact, our work suggests that tumor-associated gene expression changes in the PBCs can be detected in asymptomatic mice. Our results support those of previous studies, which identified blood gene expression profiles that are associated with a variety of solid tumors, including breast cancer. However, the sensitivity and specificity of our predictor are higher than that of the previously reported breast cancer signature. This may suggest that our strategy of using a mouse model to first identify informative genes allowed us to focus on those genes most relevant to the presence of a breast tumor and overcome the influence of the high degree of variation in blood gene expression in our human population. In order to be clinically useful, the predictor we report here would need to be tested in additional, large validation sets to establish its utility in an early detection setting and its specificity in distinguishing breast cancer from other cancer types as well as other potentially confounding conditions such as infection and inflammation. We describe some preliminary experiments in the mouse model intended to address these important questions.

Protein biomarkers can facilitate the diagnosis of many diseases such as cancer and they can be important for the development of effective therapeutic interventions. Current large-scale biomarker discovery and disease state characterization studies have largely focused on the global analysis of gene and protein expression levels, which are not directly tied to function. Moreover, functionally significant proteins with similar expression levels go undetected in the current paradigm of using gene and protein expression level analyses for protein biomarker discovery. Protein-ligand interactions play an important role in biological processes. A number of diseases such as cancer are reported to have altered protein interaction networks. Current understanding of biophysical properties and consequences of altered protein interaction network in disease state is limited due to the lack of reproducible and high-throughput methods to make such measurements. Thermodynamic stability measurements can report on a wide range of biologically significant phenomena (e.g., point mutations, post-translational modifications, and new or altered binding interactions with cellular ligands) associated with proteins in different disease states. Investigated here is the use of thermodynamic stability measurements to probe the altered interaction networks and functions of proteins in disease states. This thesis outlines the development and application of mass spectrometry based methods for making proteome-wide thermodynamic measurements of protein stability in multifactorial complex diseases such as cancer. Initial work involved the development of SILAC-SPROX and SILAC-PP approaches for thermodynamic stability measurements in proof-of-concept studies with two test ligands, CsA and a non-hydrolyzable adenosine triphosphate (ATP) analogue, adenylyl imidodiphosphate (AMP-PNP). In these proof-of-principle studies, known direct binding target of CsA, cyclophilin A, was successfully identified and quantified. Similarly a number of known and previously unknown ATP binding proteins were also detected and quantified using these SILAC-based energetics approaches.

Subsequent studies in this thesis involved thermodynamic stability measurements of proteins in the breast cancer cell line models to differentiate disease states. Using the SILAC-SPROX, ~800 proteins were assayed for changes in their protein folding behavior in three different cell line models of breast cancer including the MCF-10A, MCF-7, and MDA-MB-231 cell lines. Approximately, 10-12% of the assayed proteins in the comparative analyses performed here exhibited differential stability in cell lysates prepared from the different cell lines. Thermodynamic profiling differences of 28 proteins identified with SILAC-SPROX strategy in MCF-10A versus MCF-7 cell line comparison were also confirmed with SILAC-PP technique. The thermodynamic analyses performed here enabled the non-tumorigenic MCF-10A breast cell line to be differentiated from the MCF-7 and MDA-MB-231 breast cancer cell lines. Differentiation of the less invasive MCF-7 breast cancer cell line from the more highly invasive MDA-MB-231 breast cancer cell line was also possible using thermodynamic stability measurements. The differentially stabilized protein hits in these studies encompassed those with a wide range of functions and protein expression levels, and they included a significant fraction (~45%) with similar expression levels in the cell line comparisons. These proteins created novel molecular signatures to differentiate the cancer cell lines studied here. Our results suggest that protein folding and stability measurements complement the current paradigm of expression level analyses for biomarker discovery and help elucidate the molecular basis of disease.

According to the World Health Organization, there were over 2 million new breast cancer cases in 2018. This number is projected to steadily increase year after year. American Cancer Society projections for 2020 list the breast as the leading cancer site for new cancer cases in females, estimating breast cancer to represent 30% of all new cases and 15% of cancer-related deaths.

A leading cause of breast cancer deaths is due to tumor recurrence following therapy. These tumors can recur years, sometimes decades, after treatment from reservoirs of residual cells that persist in a dormant state. Conversely, the absence of residual invasive disease following adjuvant therapy constitutes pathological complete response (pCR) and is positively associated with long-term relapse-free survival. This risk for recurrence is higher for women with human epidermal growth factor receptor 2 (Her2+) breast cancer or triple-negative breast cancer (TNBC). Approximately 50-70% of Her2+ patients and 40-55% of TNBC patients who undergo standard therapy achieve pCR; however, in the remaining patients, only a partial response occurs, leaving residual disease and an increased risk of relapse.

To mitigate the cancer burden, years of research have focused on several common biological capabilities of cancer, deemed the Hallmarks of Cancer, including sustained proliferation, genome mutations, replicative immortality, resistance to cell death, and a deregulated metabolism. Several recent studies have further reported that this last hallmark, metabolism, may be vital to understanding the underlying behavior of dormant and recurrent tumors. Once understood, these changes in metabolic pathways, referred to as metabolic reprogramming, can be leveraged as vulnerabilities and allow for the development of strategies to eliminate residual disease or prevent residual tumor cells’ subsequent reactivation into full recurrence.

For nearly 100 years, increased aerobic glycolysis has been considered a feature of rapidly proliferating primary tumors. This occurrence, where cells continue to use the metabolic pathway where glucose is converted to lactic acid to release its stored energy and produce adenosine triphosphate (ATP) despite the presence of oxygen, has been termed the Warburg Effect. Because of this, physicians frequently use nuclear medicine directly imaging glucose uptake, fluorodeoxyglucose (FDG) Positron Emission Tomography (PET) imaging, for the diagnosis and staging of cancer. In addition to glycolysis, mitochondrial metabolism through oxidative phosphorylation has grown in recognition as an additional energy source for cancer cells. In mitochondrial metabolism, the tricarboxylic acid (TCA) cycle generates energy carriers to be used in the electron transport chain. Here, the mitochondrial membrane potential provides a gradient to produce large amounts of ATP. Additionally, the TCA cycle can rely on sources of carbon besides glucose alone. A steadily growing consensus points to other energetic sources, such as glutamine, amino acids, and lipids, that are key to survival, especially following environmental stress, treatment, or before migration and metastasis.

Though metabolic reprogramming underpins aspects of tumor dormancy and recurrence, currently, there are no techniques available to provide a systems-level approach to investigate the major axes of metabolism. Several techniques that offer insights into cellular metabolism exist, such as the Seahorse assay, metabolomics, and FDG-PET imaging. They, however, are limited to in vitro model systems, single-time point analyses of in vivo model systems, or single-endpoint analysis of in vivo model systems, respectively. Further, neither the Seahorse assay nor metabolomics can capture information about both the tumor and its native microenvironment. Therefore, there is an unmet need for a method to study metabolism at a spatial resolution that can elucidate the metabolic modulation of residual cell populations longitudinally and across in vitro and in vivo models.

Optical imaging is well-suited to address this gap in technologies owing to its ability to measure multiple metabolic endpoints non-destructively and repeatedly. The Center for Global Women’s Health Technologies has developed protocols for the use of two optical probes 2-[N-(7-nitrobenz-2-oxa-1, 3-diaxol-4-yl) amino]-2-deoxyglucose (2-NBDG) and tetramethylrhodamine, ethyl ester (TMRE), to image glucose uptake and mitochondrial membrane potential, respectively, in preclinical cancer models. These endpoints are superior to imaging of the endogenous fluorescence of NADH and FAD (referred to as the redox ratio) by providing a direct measure of a substrate (glucose uptake) and metabolic output (mitochondrial metabolism). This optical, metabolic imaging approach fills a critical gap that exists between in vitro studies on single cells (Seahorse Extracellular Flux Assay) and whole-body imaging (FDG-PET imaging) and is complementary to metabolomics and immunohistochemistry (IHC) with endpoints measuring the major axes of metabolism.

The work described here details an innovative platform to image changes in the metabolism of primary tumors, residual disease, and recurrent tumors using a Her2+ genetically engineered mouse model. This model exhibits key features of dormancy and mimics sustained use of targeted therapy to facilitate understanding of tumor biology and function, assess recurrence risk, and design therapies to mitigate residual disease and recurrence altogether. Imaging at a cellular level resolution will not only document acute metabolic changes following Her2 downregulation but also allow for metabolic imaging of dormant cell populations that are typically too small to study in human patients, typically referred to as no evidence of disease (NED) in humans. This platform will push metabolic studies of tumor dormancy further.

Three specific aims were proposed towards this ultimate goal to develop a multiparametric platform to characterize the metabolic reprogramming of preclinical cancer models.

Aim 1 establishes the functional flexibility of the fluorescent glucose analog 2-NBDG to measure glycolytic demand and the fluorescent cation TMRE to measure mitochondrial membrane potential to report on the metabolic changes that occur throughout tumor progression, dormancy, and recurrence. Using a genetically engineered mouse-derived three-dimensional in vitro mammosphere model allowed for metabolic endpoints to be captured across key time points. Doxycycline (dox) addition and withdrawal modulates expression of Her2, which is overexpressed in primary and re-activated mammospheres, and downregulated in regressing and dormant mammospheres. The mammospheres were characterized using immunofluorescence to confirm phenotype. Ki67 expression was high in primary and re-activated mammospheres, confirming a proliferative phenotype typical of both primary and recurrent disease presented in the clinic. On the other hand, short-term dox withdrawal resulted in increased cleaved caspase 3 (CC3) expression, confirming apoptosis due to Her2 downregulation. Finally, both Ki67 and CC3 expression were negative in dormant mammospheres, demonstrating a viable, but non-proliferative, steady-state phenotype.

Metabolic imaging revealed unique metabolic phenotypes across the tumor development stages that were consistent with the gold standard assays. While primary mammospheres, overexpressing Her2, maintained increased glucose uptake (“Warburg effect”), after Her2 downregulation, regressing and residual disease mammospheres appeared to switch to oxidative phosphorylation. Interestingly, in mammospheres where Her2 overexpression was turned back on to model recurrence, glucose uptake was lowest, indicating a potential change in substrate preference following the reactivation of Her2, re-eliciting growth. These findings highlight the importance of imaging metabolic adaptations to gain insight into residual and recurrent disease’s fundamental behaviors.

This work paved the way for similar studies in vivo using a mammary window chamber with the ultimate goal of informing the potential impact of metabolically-targeted therapies on tumor dormancy and recurrence.

In Aim 2, 2-NBDG and TMRE imaging was applied to in vivo mammary tumors as they transitioned from primary tumors, through regression and dormancy, to regrowth as recurrent tumors. Two tumor models varying in periods of dormancy (termed slow recurring and fast recurring tumors) were selected to characterize the importance of either axis of metabolism in the context of recurrent disease. When comparing the glucose demand and mitochondrial membrane potential levels between slow and fast recurring tumors, both sets of primary tumors behaved similarly to the primary mammosphere cultures: increased 2-NBDG indicating highly glycolytic tumors with low TMRE indicating little mitochondrial activity. Following acute Her2 downregulation, there was an increase of mitochondrial activity that remained relatively constant through regression, dormancy, and recurrence for both tumor types. However, glucose uptake varied between the two tumor types following Her2 downregulation. The mice bearing slow-recurring tumors showed a resurgence of glucose uptake during recurrence; conversely, the mice bearing fast-recurring tumors maintained decreased glucose levels continually following Her2 downregulation. Because the fast-recurring tumors did not have a meaningful change in glucose uptake during recurrence, it was hypothesized that the fast-recurring tumors might have reprogrammed to use fatty acids as a fuel source. Indeed, inhibiting fatty acid oxidation in these tumors resulted in increased glucose uptake during regression. Additionally, following this acute change in metabolism due to the inhibition of fatty acid oxidation, the tumor’s dormancy period prior to recurrence was prolonged, pointing to lipids as a crucial fuel source for residual disease and recurrence in aggressive breast cancer.

Aim 2 showed the importance of lipid metabolism in residual disease and recurrence. Additionally, other groups have also shown increased reliance on fatty acid oxidation in breast cancer residual disease following oncogene downregulation. Thus, Aim 3 established a method of visualizing long-chain fatty acid uptake in breast cancer murine models. Until now, the ability to monitor such uptake has been limited to in vitro and ex vivo approaches. Here, an imaging strategy that combines a fluorescently labeled palmitate molecule, Bodipy FL c16, and intravital, optical imaging was developed to measure exogenous fatty acid uptake. Because the palmitate’s 16th carbon is fluorescently labeled, immediate degradation of the Bodipy dye during fatty acid oxidation (β-oxidation) is prevented, allowing for fatty acid to be visualized through fluorescence imaging.

This technique was validated in two breast cancer models: a MYC-overexpressing transgenic triple-negative breast cancer (TNBC) model, previously reported to dramatically upregulate fatty acid oxidation intermediates, and the murine model of the 4T1 family, a group of sibling tumor lines with a reported wide range of metabolic phenotypes.

Using a genetically engineered mouse-derived xenograft allowed for fatty acid uptake levels to be captured during MYC-overexpression and following oncogene downregulation. Similar to the previously described genetically engineered model, this model used doxycycline addition and withdrawal to modulate MYC expression.

Through in vivo Bodipy FL c16 imaging, fatty acid uptake was found to be increased in MYC-high tumors. This model showcased two critically needed features for clinically relevant study of fatty acid uptake: 1) longitudinal metabolite tracking in a single animal shown through intra-animal decreases in fatty acid uptake following MYC-downregulation; and 2) providing a link between oncogene expression, which can be modulated therapeutically, and metabolic endpoints. This decreased uptake is indicative of a less aggressive state and correlates with a visible reduction in tumor volume. Additionally, this method found an increased fatty acid uptake in tumors with high metastatic potential, as well as the ability of the system to monitor inhibition efficacy, potentially allowing for therapeutic pharmaceutical testing of drug efficacy.

This fast and dynamic approach to image fatty acid uptake in vivo is a tool relevant to study tumor metabolic reprogramming or the effectiveness of drugs targeting lipid metabolism.

Targeting a tumor’s metabolic dependencies is a clinically actionable therapeutic approach, but identifying subtypes of tumors that are likely to respond remains difficult. The work presented here indicates that an optical platform to image 2-NBDG, TMRE, and Bodipy FL c16 longitudinally is well suited to characterize breast cancer residual disease and recurrence’s critical metabolic features and to pinpoint metabolic vulnerabilities for potential treatments. While the primary goal was to develop an imaging strategy for the unprecedented assessment of residual and recurrent disease at high resolution in in vitro and in vivo models, this innovation also fits within the broader framework of existing metabolic assessment techniques and provides a systematic way to connect in vitro studies to whole-body imaging within the context of preclinical pharmacology research.

Future work will focus on establishing a combined imaging strategy for simultaneous imaging of all three endpoints, transitioning imaging to a hand-held microscope for wide-spread adoption and rapid metabolic phenotyping of clinical samples, and integrating optical spectroscopy with this imaging platform to track the long-term effects therapy has on an individual tumor’s metabolism. The third will enable the ability to retrospectively look for changes in primary and regressing phenotypes that might foreshadow dormant behavior or the risk of early recurrence.

Introduction

Materials and methods

Results

Conclusion

Prostate and breast cancers are major health concerns, being amongst the most common forms of cancers in both men and women. The majority of prostate and breast cancers are driven by the hormone receptors androgen receptor (AR) and estrogen receptor (ESR1), respectively, and as such, endocrine therapies targeting the actions of these receptors has been a cornerstone of treatment for these patients. While these endocrine therapies are generally initially efficacious, resistance inevitably emerges. Resistance can emerge through various mechanisms, such as amplification of the receptor, generation of activating point mutations, alternative splicing of the receptor resulting in constitutively active forms of the receptor, and activating cross-talk from growth factor signaling pathways. A salient feature of these diseases is that the nuclear receptor (AR or ER) often remains engaged upon the emergence of resistance, and thus targeting of the receptor still provides therapeutic benefit. Therefore, much work in these fields has been performed to design better forms of endocrine therapy to help patients upon tumor progression. As cells are altering their signaling to deal with these pressures, this thesis work investigated the global genomic changes which arise in prostate and breast cancer cells after endocrine therapy to understand the effects of utilizing different forms of endocrine therapy, and whether these alterations in the cells induce novel vulnerabilities which can be therapeutically exploited. In the first set of studies, the differences between utilizing a competitive antagonist (enzalutamide-Enz) vs an AR degrader (AR-targeting proteolysis targeting chimera-PROTAC) were evaluated in prostate cancer. PROTACs are a new form of therapy for prostate cancer which have encouraging results in early clinical trials, so we wanted to better understand the genomic architecture and gene expression landscape after this new treatment modality compared to the current standard of care with an aim to use this knowledge to understand endocrine therapy resistance and identify therapeutically targetable pathways emerging from treatment. A factor agnostic approach was taken utilizing ATACseq and RNAseq to compare the genomic landscape after Enz or PROTAC treatment. It was found that the different AR inhibitors create distinct genomic landscapes which appear to be driven by unique sets of transcription factors. Further, it was discovered that AR inhibition, especially through degradation creates a novel liability which can be therapeutically exploited. AR was found to mediate these effects through regulating expression of a key transcription factor, and we propose a model in which the two proteins interact to regulate this axis. As AR is expressed in many other malignancies, it is feasible this strategy of degrading AR to induce this therapeutic vulnerability could have efficacy beyond prostate cancer. In the second set of studies, we investigated the genomic changes which are manifest after the emergence of endocrine therapy resistance in breast cancer and identified a novel signaling pathway that, when targeted, impairs tumor progression. Utilizing, DNAse hypersensitivity analysis, ChIP-seq, and RNAseq, it was found that GRHL2 cooperates with FOXA1 to drive a novel cistrome in endocrine therapy resistant breast cancer cells. The protein LYPD3 was found to be a downstream effector of GRHL2 and targeting LYPD3, or its ligand AGR2, with monoclonal antibodies significantly impaired primary tumor growth. Further studies into the functional role of LYPD3 were then undertaken, and it was discovered that LYPD3 knockdown significantly alters metastatic outgrowth of breast cancer cells in the lung. Investigation into the signaling of LYPD3 revealed a novel function of this protein. This work and future mechanistic studies will elucidate the signaling of LYPD3, and as LYPD3 is expressed in numerous subtypes of advanced cancers, understanding its signaling could provide a new biomarker for cancers which would be amenable to the targeted therapies identified in these studies in combination with LYPD3 targeted therapies.

Cancer treatment regimens often include surgery, radiation, and chemotherapy. Though the World Health Organization (WHO) Essential Medicines List includes many globally accessible chemotherapies, surgery and radiation are inaccessible to 90% of patients in low- and middle-income countries (LMICs) due to lack of infrastructure, medical specialists, and funds. Novel treatment options, such as immune checkpoint inhibitors (ICIs), are increasing in use in high income countries (HICs), but can be prohibitively expensive for patients, especially in LMICs. Further, even when accessible in HICs, ICI therapies are not always effective. Breast cancers are especially non-responsive to ICIs. There is a compelling need to advance and/or enhance therapies in both HICs and LMICs. We have developed a novel ablation therapy that encases ethanol in a polymer local destruction of tumors. This proposal shows how we can adapt this for both scenarios as described in greater detail below.Ablation, the chemical or thermal destruction of tissue, is an alternative or adjunct to surgery and radiation because it is less expensive, less time intensive and minimally invasive. In HICs ablation is mainly used for local tumor control, but it can also induce immunomodulation that aids systemic response. When used in combination with chemotherapy or ICI therapy, it can target local and systemic responses. However, LMICs, which often lack access to surgery, also lack access to thermal ablation methods such as radiofrequency ablation (RFA), microwave ablation (MWA), and cryoablation due to cost, reliability of electricity. Further, they often lack trained physicians and personnel to maintain equipment. Even in HICs, thermal ablation is not always accessible or possible due to tumor location, exclusion criteria, or cost. Overall, to achieve clinical translation of this therapy it is essential to understand both: 1) the effect of delivery parameters on distribution and necrosis and 2) the potential for combination of novel ablative therapies with chemotherapy and ICI therapy to inform treatment and practice. Ethanol ablation is portable and low-cost, allowing it to overcome treatment barriers in LMICs. However, ethanol ablation has limited treatment efficacy due to poor ethanol localization and off-target leakage. Incorporating ethyl-cellulose (EC), an ethanol-soluble, water-insoluble polymer, to ethanol help mitigate these limitations. EC-ethanol (ECE) transitions from liquid to fibrous gel upon injection into tissue (in-situ gelation). This acts to sequester ethanol, reduces off-target leakage and, overall, can improve ablation efficacy. ECE has the potential to create a more predictable distribution of ablation, therefore I investigated the impact of key components affecting the delivery and therapeutic effect of ECE (Aim 1) and investigate the biological impact of ECE in combination with current clinical treatment paradigms and as a novel drug delivery agent (Aim 2). Pursuit of these aims was intended to elucidate the efficacy, safety, and predictability of ECE ablation for use in cancer treatment and inform eventual clinical translation of this technology. The outcome should demonstrate that ECE is safe for human use and exhibits pharmacological activity, bringing this technology steps closer to investigation in clinical trials. Research in this dissertation pursued a thorough understanding of key factors governing the therapeutic effects of ECE with goal of informing translation of ECE to a clinical setting. I assessed the effect of formulation and delivery parameters on the resultant distribution or leakage and on necrosis. This can lead to algorithms enabling clinicians to select optimal tools and delivery methods to maximize treatment efficacy. Further, adoption of ECE in the clinical setting cannot be achieved without a clear understanding of the healing response to ablation and the safety of the procedure. Thus, time course analysis of the wound healing response and treatment safety compared to traditional ethanol ablation is necessary. To assess these key components, we need a method for assessment that allows for real time visualization of the ablation. For optimization we can us a high resolution more expensive technology, such as computed tomography, with the intent of adapting methods for more accessible technologies like ultrasound in the future. I developed a method for utilizing CT and investigated delivery parameters in both small and large animal models. In addition to investigating larger scale models to inform clinical translation (Aim 1), I also assessed these key determinants of injections success in small animal models to inform the biological mechanisms of injection efficacy (Aim 2). This led to investigating the synergy of ECE with ICI therapy and modification of the ECE formulation as a cytotoxic drug carrier. In particular, ECE ablation has potential for synergy with combination therapeutics, specifically immunotherapies and chemotherapeutic agents. This could have high potential for impact in HICs where implementation of immunotherapies and intensive chemotherapy regimens is more common and accessible. ECE exposes tumor antigens to T cells, evoking an immune-stimulatory response. I hypothesized that ECE can prime “cold” tumors to enhance response to ICI, for which many breast cancers are non-responsive. Previous work demonstrated that low- dose cyclophosphamide enhances the therapeutic effect of ECE. Therefore the combination of ECE ablation and low-dose cyclophosphamide was a logical choice to investigate a neoadjuvant therapy to enhance response to ICIs in non-responsive tumors. I hypothesized that the in-situ gelation of EC can be implemented to improve intra-tumoral drug delivery. Ethanol is know for its cytotoxic effects on cells. vehicle compared to many inert polymer vehicles. Combining ECE with chemotherapy (often, small drug molecules) as a local treatment could synergize apoptotic and necrotic cell death induced by the drugs and ethanol, respectively, a therapeutic process absent in traditional drug carriers. Thus, I focused upon effect of ECE on small molecule transport, drug uptake and distribution throughout the body over time, and also assessed safety and efficacy of this novel combination treatment. The goal of this dissertation research was to improve efficacy, safety, and predictability of ECE ablation. I aimed to optimize delivery of ECE, working to understand the effects of salient injection parameters on distribution and necrosis. I also investigated ECE ablation in combination with chemotherapies or ICIs, helping to lay the groundwork for clinical translation, and informing the foundation for local and systemic treatment responses. To achieve this goal, I completed two parallel aims. Aim 1 focused on delivery of ECE, specifically development of real-time assessment methods, infusion parameter assessment at preclinical and clinical scales, and investigation of resultant necrosis and the wound healing response. Aim 2 focused on investigating the utility, efficacy, and safety of the ECE formulation as a cytotoxic drug carrier, and examined the synergy of ECE with ICIs.

Human epidermal growth factor receptor 2-positive (HER2+) and triple-negative breast cancer patients often present with brain metastasis. HER2-targeted therapies have not been successful to treat brain metastases in part due to poor blood-brain barrier (BBB) penetrance and emergence of resistance. Notably, there is a lack of effective FDA-approved targeted therapies for patients with triple-negative breast cancer brain metastases. Here we explore the transcriptional and translational networks that drive breast cancer brain metastasis.

We report that ABL kinase allosteric inhibitors improve overall survival and impair HER2+ brain metastatic burden in vivo. ABL kinase inhibition leads to a profound decrease in HER2 protein levels in HER2+ brain metastatic cells. Mechanistically, ABL kinases regulate translation of HER2/ERBB2 through the RNA binding protein Y-box-binding protein 1 (YB-1). YB-1 crosslinking immunoprecipitation (CLIP)-sequencing and RNA immunoprecipitation of YB-1 revealed YB-1 binds to ERBB2 and a subset of mRNAs linked to brain metastasis. Loss of YB-1 inhibits brain metastatic outgrowth and impairs expression of a subset of ABL-dependent brain metastatic targets. These data support a previously unknown role for ABL kinases in the translational regulation of brain metastatic targets through YB-1 and offer a new therapeutic target for HER2+ brain metastasis patients. To characterize the transcriptional landscape of human brain metastases, spatial transcriptomics was performed on patient samples. Analysis of the tumor and surrounding brain microenvironment may identify novel vulnerabilities that could translate into therapies for patients with brain metastases.

Breast cancer is the most common type of cancer among women in the United States. Despite more women undergoing treatment and increased survival rates, many women continue to suffer from emotional distress and physical symptoms associated with treatments for breast cancer (e.g., surgery). To date, there has been limited research investigating the efficacy of psychosocial interventions for breast cancer patients during the surgical time frame. This randomized controlled pilot study examined the effect of a lovingkindness meditation intervention on key psychological and physical outcomes surrounding breast surgery. Sixty women undergoing surgery were randomly assigned to one of three treatment conditions at breast biopsy: 1) lovingkindness meditation, 2) music, 3) standard care. Assessments of emotional distress, physical symptoms, and positive psychosocial resources occurred prior to patients' biopsy, following their biopsy, one week after receipt of their biopsy results, and one week following breast surgery. Multilevel model analyses demonstrated that lovingkindness meditation significantly improved anxiety, pain, self-compassion, emotional suppression, mindfulness, social isolation, and heart rate levels over time compared to control conditions. These results support the efficacy of a brief lovingkindness meditation intervention for breast cancer patients during the surgical time frame. The implications of these findings on future research, theory, and policy are discussed.

Cancers are a complex set of related diseases with wide ranging etiologies, and humans are exposed to a milieu of environmental exposures that may contribute to disease development. Breast cancer in particular is a complex and multifactorial disease, yet prior research has largely focused on studying exposures to one factor/contaminant at a time, which does not reflect the real-world environment. In addition, investigating incidence of total breast cancer has the potential to mask the impacts of environmental factors on 1) the development of different subsets of breast cancer, varying in hormone receptor status and 2) progression of these cancers to advanced and more aggressive stages. Patients with distant metastatic breast cancer have poor prognosis despite aggressive, multidisciplinary treatment regimens compared to carcinoma in situ or early-stage breast cancer. This reinforces the unmet need to identify risk factors associated with advanced breast cancers to reduce incidence and improve overall breast cancer outcomes. The objective of these studies was thus to determine environmental risk factor associations with breast cancer by stage, and to utilize a real world environmental exposure chemical mixture to interrogate potential impacts on breast tumor progression by hormone receptor status.

These studies begin by evaluating the associations between breast cancer summary stages and the Environmental Quality Index (EQI), which includes a range of environmental factors across five overarching environmental domains. Our analysis found total and localized breast cancer incidence were increased in counties with poor environmental quality compared to those with good environmental quality. These overall environmental trends were largely driven by land quality, which was associated with incidence of early-stage disease (carcinoma in situ and localized breast cancer), in addition to total breast cancer, especially in urban counties.

Taking advantage of more granular patient data, these studies further evaluated the odds of localized, regional, or distant metastatic breast cancer in categories of environmental quality using women with carcinoma in situ as registry-based controls. Overall environmental quality was not associated with invasive breast cancer; however, poor land environmental quality was associated with increased odds of all invasive breast cancer types, particularly in more rural communities (distant metastatic breast cancer was 5-8% more likely compared to carcinoma in situ). Cumulatively, epidemiologic analyses indicate significant associations between poor overall and land environmental quality and breast cancer incidence as well as odds of invasive breast cancer. Furthermore, associations differed by breast cancer summary stage, rural-urban status, and environmental domain thus identifying a critical need to assess cumulative environmental exposures in the context of cancer stage.

Emerging evidence suggests the role of environmental chemicals, in particular endocrine disrupting chemicals (EDCs), in incidence and progression of breast cancer, which can impact survival outcomes. Polycyclic aromatic hydrocarbons (PAHs) are a toxic and ubiquitous class of environmental chemicals, many of which exhibit endocrine disrupting activity. They are products of fuel combustion from human and natural sources. PAH exposure is widespread, and many PAHs are considered carcinogenic. Urinary metabolite data were collected from 9517 individuals from the U.S. CDC National Health and Nutrition Examination Survey years 2005-2014 for four parental PAHs naphthalene, fluorene, phenanthrene, and pyrene. We utilized these urinary biomarkers to estimate PAH intake, and regression models were fit for multiple demographic and lifestyle variables, to determine variable effects, interactions, odds of high versus low PAH intake. Smoking and secondhand smoke (SHS) exposure accounted for the largest PAH intake rate variability (25.62%), and there were strongest interactions between race and ethnicity and smoking or secondhand smoke exposure, reflected in a much greater contribution of smoking to PAH intake in non-Hispanic Whites as compared to other racial and ethnic groups. Increased risk of high PAH intake was observed in older age groups, obese persons, college graduates, midrange incomes, smokers, and those who were SHS exposed. Among the non-smoking population, effects of other demographic factors lessened, suggesting a highly interactive nature. Results suggest that there are demographic subpopulations with high PAH intake because of different smoking behaviors and other exposures.

The PAH-contaminated Atlantic Wood Industries, Inc. (AWI) Superfund site in Portsmouth, Virginia provides a model for studying a real-world complex PAH mixture, and its extrapolation to cancer risk and PAH exposure in the general population. Cancer risk at the Superfund site due to sediment-derived PAHs was examined and PAH sources in the general population upon PAH mixture exposure were then evaluated. The PAH mixture was assessed for potential carcinogenicity using US EPA’s OncoLogic ranking tool and the US EPA list of priority PAHs. Cancer risk due to PAH exposure was calculated for Superfund site users and compared to the US EPA assessment. Human intake and health endpoints of PAHs within the mixture were extracted from USEtox chemical fate database. Eleven PAH compounds within the mixture were of carcinogenic concern, and seven PAHs conveyed significant excess cancer risk at the Superfund site and in the general population, wherein PAH-contaminated seafood ingestion was a main route of exposure.

Most research tends to focus on tumor etiology and the effect of single chemicals, offering little insight into the effects of realistic complex mixture exposures on tumor progression. To address this issue, the final portion of this work investigated the effect of the previously mentioned AWI Superfund site-derived PAH-enriched EDC mixture in a panel of normal mammary epithelial cells and breast cancer cell models. Cells or organoids in culture were treated with EDC mixture at doses estimated from U.S. adult intake of the top four PAH compounds within the mixture from the National Health and Nutrition Examination Survey database. Physiologic doses of this PAH mixture (6, 30, 300nM) demonstrated increased aryl hydrocarbon receptor (AhR) expression and CYP activity in estrogen receptor (ER) positive, but not normal mammary epithelial cells or ER negative breast cancer cells. In addition, upregulated AhR signaling corresponded with increased cell proliferation and expression of anti-apoptotic and antioxidant proteins XIAP and SOD1. A mathematical model was employed to validate PAH-mediated increases in AhR and XIAP expression in the MCF-7 ER-positive cell line. Furthermore, the PAH mixture caused significant growth increases in ER-negative breast cancer cell derived 3D tumor organoids, providing further evidence for the role of a real world-derived PAH mixture in enhancing a tumor proliferative phenotype.

Results from these studies have implications for cancer control and prevention and targeted PAH exposure reduction initiatives by identifying vulnerable subpopulations, and further identify key consequences of PAH exposure and how it may contribute to breast cancer biology and progression.