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Metabolic and Microenvironmental Determinants of Breast Cancer

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Metabolic and Microenvironmental Determinants of Breast Cancer Metabolic and Microenvironmental Determinants of Breast Cancer Metastasis: Effects of Glycogen Utilization on Metastatic Phenotypes and a Predictive Brain Metastasis Microfluidic Device by Megan A. Altemus A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy (Cancer Biology) in the University of Michigan 2019 Doctoral Committee: Professor Sofia D. Merajver, Chair Assistant Professor Carlos A. Aguilar Professor Maria G. Castro Professor Eric R. Fearon Assistant Professor Costas A. Lyssiotis Megan A. Altemus [email protected] ORCID ID: 0000-0002-8191-8838 © Megan A. Altemus 2019 DEDICATION For my mother, Barbara Hull, a breast cancer survivor and role model. I’m thankful every day for your never-ending support and love. I began my academic journey wanting to contribute to breast cancer research so other little girls would be able to grow up with their moms just like I got to with you. Everything that I have accomplished has been for and because of you. I love you. ii ACKNOWLEDGEMENTS To Dr. Sofia Merajver, thank you for your support throughout the years and for the opportunity to work and study as a member of your lab. As your student I have grown both as an independent scientist and as a person. You have taught me many things that will aide in my success in my future endeavors and career. Thank you. In addition, thank you to my committee members Eric Fearon, Maria Castro, Costas Lyssiotis, Carlos Aguilar, and past member Shuichi Takayama for all your guidance during the initiation, execution, and completion of this dissertation work. To past and current member of the Merajver lab, especially Ryan Oliver, thank you for sharing your experience and teaching me new things every day. Thank you to Zhi Fen Wu whose dedication to the lab and the success of its members has been invaluable to the completion of this work. Thank you to Koh Meng Aw Yong, Sara Caceres, Laura Goo, and Hannah Cheriyan for always being there when I needed advice or a coffee break. To the Cancer Biology Program faculty, staff, and students, for providing a well- rounded graduate experience and help with completing this degree. Thank you especially to Beth Lawlor and Zarinah Aquil whose dedication to my success and the success of all Cancer Biology students went above and beyond. iii Thank you to my constant companion and friend for the last 14 years, Missy, my cat, whose unconditional love and affection brightened my every day. Whenever things seem bleak, she is always there with a fluffy hug and a purr. And lastly, thank you to my husband, Eric Altemus. You are my one and only. I would not have been able to do this without you. I’m excited to begin this next chapter of my life with you by my side. FINANCIAL ACKNOWLEDGEMENTS I would like to acknowledge all the sources of funding that made this work possible. First, the Cancer Biology Program training grant, an NIH T-32 Training Fellowship (T32CA009676). Also, funds provided by the Rogel Cancer Center and Rogel Cancer Center Nancy Newton Loeb Fund which supported my second year in the Cancer Biology Program. Additional funding for this work and the Merajver lab was provided by National Cancer Institute of the National Institutes of Health under award number P30CA046592, 5T32CA009676-23, CA196018, AI116482, and the METAvivor and Breast Cancer Research Foundation organizations. iv TABLE OF CONTENTS DEDICATION ii ACKNOWLEDGEMENTS iii LIST OF TABLES ix LIST OF FIGURES x ABSTRACT xii CHAPTER 1. Introduction: Aspects of Breast Cancer Metastasis; Effects of Hypoxic Microenvironment on Initiation and Metabolism, and the Brain as the Deadliest Secondary Site 1 Hypoxia and metastasis 2 Metabolic reprogramming under hypoxia 4 Glycogen metabolism 5 Hypoxic regulation of glycogen in cancer 6 Distant site-specific metabolic alterations in cancer 7 Breast cancer brain metastasis 9 Current models of brain metastasis 10 v Blood-brain barrier microfluidic devices 12 CONCLUSION 14 FIGURES 15 REFERENCES 16 2. Breast Cancers Utilize Hypoxic Glycogen Stores via PYGB, the Brain Isoform of Glycogen Phosphorylase, to Promote Metastatic Phenotypes 22 SUMMARY 22 INTRODUCTION 23 MATERIALS AND METHODS 27 Cell culture and media 27 Glycogen assay 28 Periodic acid-Schiff staining 29 RT-qPCR 30 shRNA knockdown 30 Western blotting 30 Proliferation assay 31 Wound-healing assay 31 Transwell invasion assay 32 RESULTS 33 DISCUSSION AND CONCLUSION 38 vi FIGURES 42 TABLES 51 REFERENCES 53 3. A Platform for Artificial Intelligence Based Identification of the Extravasation Potential of Cancer Cells into the Brain Metastatic Niche 56 SUMMARY 56 INTRODUCTION 57 RESULTS AND DISCUSSION 59 Brain seeking breast cancer cell line reveals a distinct μBBN phenotypic pattern 59 PDX-derived brain metastatic and primary tumor cells display differential phenotypic behaviors 62 Brain metastatic cancer cells degrade the endothelial barrier 65 Comprehensive differential cancer cell behavior in vitro leads to an index of brain metastatic potential 66 MATERIALS AND METHODS 69 Study design 69 μm-Blood Brain Niche design and validation 70 Small molecule membrane transfer measurements 71 Cell culture and reagents 72 Patient-derived xenografts 73 vii Live subject statement 73 Seeding microfluidic device 74 Measurement of the cell attributes using confocal tomography 74 Statistical analysis 75 Artificial intelligence machine learning algorithm 75 Breast (cancer) cell lines 76 CONCLUSION 76 FIGURES 77 TABLES 84 REFERNCES 88 4. Conclusions and Future Directions 91 REFERENCES 98 viii LIST OF TABLES TABLE 2.1 Primers for qPCR of glycogen genes. 51 2.2 shRNA oligonucleotides for shPYGL and shPYGB. 51 2.3 Glycogen phosphorylase knockdown decreases doubling time of MCF-7 and MCF-10A cells 52 3.1 Summary of metrics measured for each cell line. 84 3.2 Cell counts and volumes by location. 84 3.3 Summary of metrics measure for each PDX type. 85 3.4 PDX type counts and volumes by location. 85 3.5 Comparison of methods to classify cancer cells by brain met potential. 86 3.6 Confusion matrix for random forest. 86 3.7 Comparison of methods to classify breast PDX cancer cells by brain met potential. 87 3.8 Confusion matrix for random forest using PDX cancer cells. 87 ix LIST OF FIGURES FIGURE 1.1 Graphical depiction of the steps in the metastatic cascade 15 2.1 Glycogen accumulates in breast cancer cells under hypoxic conditions across subtypes. 42 2.2 Glycogen accumulates in additional breast cancer cells under hypoxic conditions. 43 2.3 Glycogen pathway gene expression changes in breast cancer cells exposed to hypoxia. 44 2.4 Additional glycogen pathway gene expression changes in breast cancer cells exposed to hypoxia. 45 2.5 Glycogen phosphorylase brain isoform knockdown inhibits glycogen utilization in breast cancer cells. 46 2.6 shPYGL and shPYGB reduces glycogen phosphorylase mRNA expression. 47 2.7 Glycogen phosphorylase knockdown in SUM-149 cells. 48 2.8 Loss of glycogen phosphorylase inhibits proliferation in MCF-7 and normal-like MCF-10A cells but not MDA-MB-231. 49 2.9 Loss of glycogen phosphorylase brain isoform inhibits wound-closure in MCF-7 and invasion in MDA-MB-231 cells. 50 3.1 Overview of method. 77 3.2 Microfluidic BBNiche device design to study brain metastatic process. 78 3.3 Differences in extravasation and morphology of brain-seeking cells compared to non-brain-seeking cell in the µBBN device analyzed using confocal tomography. 79 3.4 Profiling of patient derived xenografts in µBBN device. 80 3.5 Cancer cell interaction with the μBBN endothelium 81 x 3.6 Accurate identification of brain metastatic potential in μBBN device. 82 3.7 Mask of four-channel device 83 3.8 Optimizing media composition for co-culture 83 xi ABSTRACT Breast cancer has the highest incidence rates of all cancer types among women in the United States, and the second highest mortality. While survival is high for localized disease, breast cancer that has metastasized has a five-year survival rate of roughly 30%. This highlights the need for a better understanding of the breast cancer metastatic process, both at the primary and distant sites such as the brain, in order to develop new treatments and preventative measures. The work presented here focuses on two different avenues for combatting breast cancer metastasis. The first of these is exploiting metabolic vulnerabilities of the cancer cells at the primary site in order to prevent invasion and metastasis. The second fills the pressing need for quick and biologically accurate models of distant sites in order study secondary site-specific metastatic processes of cancer cells and patient samples. Therefore, in this dissertation work we aim to 1) determine the effects hypoxic glycogen utilization has on metastatic phenotypes of breast cancer and 2) develop a microfluidic device that accurately mimics the interactions of cancer cells and the blood-brain niche. We found that many different breast cancer cell lines increased stores of glycogen, the main glucose storage molecule in the body, in response to hypoxia, such as a growing solid tumor might encounter. This extent of glycogen accumulation in response to hypoxia did not seem to correlate with breast cancer receptor status and xii differences in glycogen pathway gene expression under hypoxic exposure were not conserved across cell lines. Additionally, using shRNA knockdowns of both the liver (PYGL) and brain (PYGB) isoforms of the glycogen degradation enzyme glycogen phosphorylase, we were able to determine that the ability to utilize glycogen was mainly controlled by PYGB rather than PYGL in breast cancer cell lines and directly influences the rate of migration and invasion. For the second aim, we created and validated a brain niche mimetic microfluidic device that in conjunction with machine learning algorithms can accurately predict the brain metastatic potential.
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