ANNOTATION OF THE UNDERSTUDIED KINOME AND PRELIMINARY TESETING OF KINASE INHIBITOR COMBINATIONS Claire Reisig Hall A thesis submitted to the faculty at the University of North Carolina at Chapel Hill in partial fulfillment of the requirements for the degree of Master of Science in the Joint Program of Biomedical Engineering in the School of Medicine. Chapel Hill 2017 Approved by: Shawn Gomez Jeffrey Macdonald Glenn Walker © 2017 Claire Reisig Hall ALL RIGHTS RESERVED ii ABSTRACT Claire Reisig Hall: Annotation of the Understudied Kinome and Preliminary Testing of Kinase Inhibitor Combinations (Under the direction of Shawn Gomez) A technique utilizing multiplexed inhibitor beads and mass spectrometry (MIB/MS) detects functional protein kinases in breast cancer cell lines. Data from this technique was used to shed light on the understudied kinome, a portion of which is captured by the MIB/MS method. Regression analysis was performed to find correlations in kinase activity. The functional linkages were then used to annotate the understudied kinases. Annotations revealed new possible functions and disease relations for many understudied kinases. Kinase inhibitor combinations were suggested by principle components analysis (PCA) results performed on MIB/MS data from treated breast cancer cell lines. The combinations were preliminarily tested for signs of effectiveness. Dose curves and growth assays were performed to compare drug combinations in the SKBR3 cell line. The interpretation of in vitro experiment results was impeded because of poor accuracy and reproducibility. Possible designs for in vitro experiments producing interpretable results are presented. iii TABLE OF CONTENTS LIST OF TABLES ............................................................................................................................................ vi LIST OF FIGURES .......................................................................................................................................... vii INTRODUCTION ............................................................................................................................................ 1 Cancer and treatment ....................................................................................................................1 Protein kinases and inhibitors ........................................................................................................2 Understudied kinases .....................................................................................................................3 Multiplexed inhibitor beads/mass spectrometry ...........................................................................4 Goals ...............................................................................................................................................5 CHAPTER 1: REGRESSION AND ANNOTATION .............................................................................................. 6 Introduction ....................................................................................................................................6 Regression .......................................................................................................................................7 Annotation ......................................................................................................................................9 Results and discussion ..................................................................................................................10 ADCK1 ..............................................................................................................................11 SG196 ...............................................................................................................................12 CSK23 ...............................................................................................................................13 M3KL4 ..............................................................................................................................14 Conclusions ...................................................................................................................................15 CHAPTER 2: KINASE INHIBITOR COMBINATIONS ........................................................................................ 16 Introduction ..................................................................................................................................16 iv Methods ........................................................................................................................................17 Results and discussion ..................................................................................................................18 Conclusions ...................................................................................................................................20 FIGURES AND TABLES .................................................................................................................................. 22 REFERENCES ................................................................................................................................................ 40 v LIST OF TABLES Table 1. Example of raw MIB/MS data ....................................................................................................... 38 Table 2. Gene name, classification and regression features of four Tdark kinases .................................... 39 vi LIST OF FIGURES Figure 1. Overlay of understudied kinases on phylogenetic kinome tree ................................................. 22 Figure 2. Heat map of normalized MIB/MS data ...................................................................................... 23 Figure 3. Flowchart of methods for lasso regression and annotations..................................................... 24 Figure 4. List of annotations occuring most frequently for understudied kinases ................................... 26 Figure 5. Subnetwork for ADCK1 ............................................................................................................... 27 Figure 6. Subnetwork for SG196 ............................................................................................................... 28 Figure 7. Subnetwork for CSK23 ................................................................................................................ 29 Figure 8. Subnetwork for M3KL4 ............................................................................................................... 30 Figure 8. PCA plot of kinome changes in MIB/MS data of treated breast cancer cell lines ...................... 31 Figure 10. Ideal dose curve and ideal growth assay .................................................................................. 32 Figure 11. Dose curves for calculating IC30’s used in initial growth assay ................................................ 33 Figure 12. First growth assay for Lapatinib, Dasatinib, Trametinib, and BEZ235 ...................................... 34 Figure 13. Compilation of dose curves for BEZ235, Dasatinib, and Trametinib ......................................... 35 Figure 14. Second growth assay for Lapatinib, Dasatinib, Trametinib, and BEZ235 .................................. 37 vii INTRODUCTION Cancer and treatment Cancer, a widespread and destructive disease with over 100 different types, is the second highest cause of death in the United States [1]. Breast cancer is the most common type of cancer, and is predicted to occur in over 250,000 new cases throughout the year 2017 [1]. For women, breast cancer has the second highest death rate behind lung cancer, meriting further research for understanding and treating the disease [1]. Breast cancer is separated into subgroups, emphasizing the heterogeneity of this type of cancer. Subsequently, treatment is also heterogeneous, depending on the subtype and progression of the disease. From a clinical standpoint the subtypes are divided into luminal (further subdivided into luminal A and luminal B), HER2-enriched, and triple-negative [2]. These three major subtypes are classified via the presence or absence of three receptors, estrogen (ER), progesterone (PR) and human epidermal growth factor receptor 2 (HER2) [2]. Localized treatments include surgery and radiation therapy. Systemic treatments are composed of drugs which circulate throughout the body via the bloodstream. These treatments include chemotherapy, hormone therapy, or targeted therapy, and are often dependent on subtype. Commonly, a combination of localized treatments and systemic treatments is used for combating breast cancer. Chemotherapy consists of drugs which cause apoptosis by damaging DNA or inhibiting cell division. Chemotherapy drugs generally target quickly dividing cells, a characteristic of cancer cells, thus enhancing the effectiveness of these drugs against cancer. However, as these drugs are not selective to only cancer cells, they also may target quickly dividing non-cancerous cells, causing degenerative and severe side effects associated with current cancer treatment. Drugs that can be targeted specifically to 1 the cancer cells thus minimize the side effects, but the available targets are dependent on the presence of receptors, and consequently, the subtype of breast cancer. The luminal subgroup of cancer has at least one of the ER or PR receptors present and therefore hormone therapy is an effective