Effect of donor KIR Genotype On the Outcome of Bone Marrow Transplantation

Transcription

1 Effect of donor KIR Genotype On the Outcome of Bone Marrow Transplantation By: Lee Jia-Hui Jane Bachelor of Science in Biomedical Science and Molecular Biology This thesis is presented for the Honours degree in Biomedical Science at Murdoch University, Western Australia. May 2013 i

2 DECLARATION I declare this thesis is my own account of research and contains as its main content, work that has not been previously submitted for a degree at any tertiary educational institution. Lee Jia-Hui Jane (Student). A Prof. Campbell S. Witt (RPH Supervisor). Dr. Dianne De Santis (RPH Supervisor). A Prof. Wayne Greene (Murdoch Supervisor). ii

3 LIST OF ABBREVIATIONS A/A Haplotype ADCC akir ALL AML APC ATG B/B Haplotype BCR BMT Bp Bu B/x Haplotype CAMP CML CMV Cy DNA Flu GvHD GvL HLA HSCT IFNγ Ig ikir ITIM KIR KLR LILR Mel MHC NK NCR PBSC TBI TCR TNFα WBC Homozygous A Haplotype Antibody Dependent Cell-mediate Cytotoxicity Activating Killer Immunoglobulin-Like Receptor Acute Lymphoid Leukaemia Acute Myeloid Leukaemia Antigen Presenting Cell Anti-Thymocyte Globulin Homozygous B Haplotype B-cell Receptor Bone Marrow Transplant Basepair Busulphan Heterozygous B/x Haplotype Campath Chronic Myeloid Leukaemia Cytomegalovirus Cyclophosphamide Deoxyribonucleic Acid Fludarabine Graft-versus-Host Disease Graft-versus Leukaemia Human Leukocyte Antigen Haematopoietic Stem Cell Transplant Inferon Gamma Immunoglobulin Inhibitory Killer Immunoglobulin-Like Receptor Immunoreceptor Tyrosine-base Inhibitory Motif Killer Immunoglobulin-Like Receptor Killer cell Lectin-like Receptor Leukocyte Immunoglobulin-Like Receptor Melphalan Major Histocompatibility Complex Natural Killer Natural Cytotoxicity Receptor Peripheral Blood Stem Cell Total Body Irradiation T-cell Receptor Tumour Necrosis Factor Alpha White Blood Cell iii

4 ACKNOWLEDGEMENTS First and foremost I wish to express my sincere gratitude to my two Royal Perth Hospital supervisors, A.Prof Campbell Witt and Dr. Dianne De Santis for the opportunity to work under them for my honours project. They have supported and guided me through it, patiently teaching me and not to mention correcting my grammar on countless occasions. As I am writing this I know that they are mentally re-formatting and editing my flowery non-scientific writing. It has been a truly enjoyable journey with both of you! Not forgetting, A.Prof Wayne Greene who was always there to offer his advice and guidance through the fundamentals of the Murdoch Honours degree. Secondly, I would like to thank the RPH Clinical Immunology routine staff and Conexio staff for lending me a hand on multiple occasions and teaching me how to use the various equipments in the lab. I have met some genuinely awesome people who are just a pleasure to work along side; they make long tedious experiment-filled days a little less tedious and a little more enjoyable! Thirdly, I would like to thank my parents, without whom I d have no meals, no clothes, no roof over my head and no paid school fees. Thanks Mum and Dad for your unconditional love and encouraging words of support! You are the best parents any child could ask for; you have supported my ambition to study abroad and never stopped believing in me, which means more than my vocabulary can do justice for. To my two beloved elder brothers who never stopped poking fun at me and my dyslexia, this is for you! Your baby sister finished her honours! Fourthly, I would like to give a shout out to my best friend, Tricia. Who has been in my corner with encouraging from day 1 and she never stopped believing. And to my tight bunch old close friends in Perth and Singapore who I have neglected but still stood by me, you made my journey less lonely. Lastly, I would like to thank the honours committee for giving me a chance and my examiners who will be taking time out of their busy schedules to read this thesis. Thank you, everyone. This is for you. iv

5 ABSTRACT Haematopoietic stem cell transplantation is the only curative treatment for some forms of haematologcial malignancies and bone marrow failure. The role of donor Natural Killer (NK) cells that accompany the donor stem cells is under investigation. In particular, there is interest in the role of the killer immunoglobulin-like receptors (KIR) family of receptors expressed on the surface receptors of NK cells. In this study, we focused on the donor KIR genes and the possibility that the KIR receptors interact with other transplant variables to influence survival. We analyzed a cohort of 140 unrelated donors from bone marrow transplants carried out at Royal Perth Hospital and Princess Margaret Hospital. The variables that were analyzed for interactions with KIR were: cytomegalovirus (CMV) status, transplant graft source, conditioning agents. A number of significant interactions between KIR and transplant variables were identified, the strongest being the interaction between KIR2DS2 and the use of cyclophosphamide as a conditioning agent. Kaplan-Meier analyses showed that the presence of KIR2DS2 in a cyclophosphamide positive transplant resulted in a significantly improved survival (p=0.002) whereas the presence of KIR2DS2 in a cyclophosphamide negative transplant resulted in a poorer survival (p=0.032). Hence the presence of KIR2DS2 could be beneficial or deleterious depending on the presence or absence of cyclophosphamide. As this was an exploratory study, observations of the interactions discovered need to be confirmed in additional studies. v

6 TABLE OF CONTENTS TITLE PAGE Chapter 1 Literature Review 1.1 Immune System Adaptive Immunity Innate Immunity 1.2 Natural Killer Cells 1.3 Missing self Hypothesis in NK cell Recognition 1.4 Natural Killer Cell Functions and Pathways 1.5 Natural Killer Cell Receptors 1.5.1C-type Lectin Receptors CD94/NKG Ly Immunoglobulin Super-family Receptors Killer Cell Immunoglobulin-like Receptors (KIR) KIR Receptor Structure and Nomenclature KIR Genomics and Diversity Allelic Polymorphism of KIR Genes KIR Haplotypes KIR Haplotype Frequencies Ligands for KIR Receptors KIR Expression 1.6 Haematopoietic Stem Cell Transplantation (HSCT) 1.7 Factors Affecting the Outcome of Allogeneic HSCT NK Cell Alloreactivity due to Ligand-Ligand Incompatibility KIR Repertoire on the Outcome of HSCT Preparative Regimen Variables Total Body Irradiation Cytomegalovirus (CMV) Prophylaxis 1.8 Cytomegalovirus (CMV) KIR Repertoire With Associationg to CMV Protection Chapter 2. Materials and Methods 2.1 DNA Samples and Preparation DNA Source Calculations for the Preparation of DNA Samples 2.2 Polymerase Chain Reaction Sequence Specific Priming (PCR-SSP) Assay for KIR Genotyping Oligoneucleotide Primers vi

7 2.2.2 Preparation of PCR Reagents (Reaction mix components) x TDMH PCR Buffer (100ml) mM dntp Other PCR Reagents 2.2.3Preparation of Gel Electrophoresis Reagents x TBE Buffer (2 litre batch) x TBE Buffer (20litre batch) % and 3.5% Agarose Gel Gel Electrophoresis Loading Buffer Gel Electrophoresis Kb Plus DNA Lambda Ladder 2.3 KIR Multiplex PCR-SSP Genotyping Assay Optimization Polymerase Chain Reaction (PCR) Runs Reaction Mix (Mastermix) Volumes KIR PCR-SSP Gene Groupings Optimized Recipes Thermocycler Run Conditions Gel Electrophoresis 2.4 Statistical Analysis Survival Analyses Pearson Chi-Square Analysis of Acute Graft-versus-Host Disease (agvhd) Multivariate Analysis on Survival Chapter 3. Results 3.1 Multiplex PCR-SSP KIR Genotyping Assay Optimizations Optimization of PCR-SSP Group Optimization of PCR-SSP Group Optimization of PCR-SSP Group Optimization of PCR-SSP Group KIR Genotyping of the 146 Donors 3.3 Transplant Characteristics and Statistics Year of Bone Marrow Transplants Transplant Centre and Number of Transplants Transplant Source of Graft Donors Ages and Genders Patient Diagnosis Cytomegalovirus (CMV) Status Conditioning Regimens Acute Graft-versus-Host Disease (GvHD) KIR Gene Frequencies of the Entire Cohort 3.4 Analysis of Acute Graft-versus-Host Disease (agvhd) and KIR genes Effect of KIR Genotype on Prevalence of Acute GVHD Effect of interactions between KIR Genotype and other Transplant Variables on the Prevalence of Acute GVHD 3.5 Analysis of KIR Genes on Survival vii

8 3.5.1 Univariate Kaplan-Meier Analysis of KIR genes on Survival Univariate Kaplan-Meier Analysis of KIR Genes on Survival in patients with Myelogenous leukaemias 3.6 Effect of Interactions between KIR Genes and other Transplant Variables on Survival 3.7 Multivariate Cox Regression Analysis Chapter 4. Discussion 4.1 Optimization of the Multiplex PCR-SSP KIR Genotyping Assay Unexpected PCR bands Migration Validation of the PCR-SSP KIR Genotyping Assay 4.2 Overview of the Data Analyzed in this Study Interactions between KIR2DS2 and Conditioning Agents Interactions between KIR2DS1, KIR2DS5, KIR3DS1, KIR2DL5 and CMV and Graft Source 4.3 KIR Repertoire and Acute Graft-versus-Host Disease (agvhd) 4.4 The Effect of KIR Repertoire on Survival Mechanism of KIR Interaction Effect on Survival Effect of KIR Genotype in Myeloid and Lymphocytic Leukaemia 4.5 Statistical Analysis Errors 4.6 Conclusions REFERENCES APPENDIX A APPENDIX B viii

9 FIGURES LIST OF ILLUSTRATIONS TITLE PAGE Figure 1. NK cell s response (receptor-ligand models) with association to a healthy cell and a tumor cell. Figure 2. KIR protein domains and region lengths. Figure 3. Map of the Leukocyte Receptor Complex (LRC). Figure 4. Centromeric and telomeric region separation of KIR genes which includes a few different A/B haplotypes. Figure 5. Various KIR receptors and their HLA class I ligands. Figure 6. shows the 10mM and 40mM dntp concentrations for selected cell lines with Group 1 primers. Figure 7. Shows the gels of the optimized PCR-SSP Group 1 primers on 20-cell line panel. Figure 8. Gel picture of the two different dntp concentrations from Group 2. Figure 9. Optimized PCR-SSP Group 2 on the 20-cell line panel. Figure 10. Gel picture of the PCR products produced using 10mM and 40mM dntp concentrations from Group 3. Figure 11. The initial Group 3 (before the swapping of KIR primers). Figure 12. The new group 3 (after the swapping of KIR genes). Figure 13. The preliminary test for the new group 3 after the removal of KIR2DS1 sequencing primer tags. Figure 14. The optimized new group 3 primers on the validated panel. Figure 15. PCR products produced using 10mM and 40mM dntp concentrations for group 4 primers. Figure 16. The preliminary PCR run test on the new group 4 primers on selected cell lines from the validated panel. Figure 17. The optimized PCR-SSP Group 4 on selected cell lines. Figure 18. The frequency of haematopoietic stem cell transplants performed in each year. Figure 19a. (Left) The presence of KIR3DS1 in peripheral blood transplant was associated with a poorer survival while there was no observable difference in bone marrow transplants Figure 19b. (Right) There was no difference in the presence or absence of KIR3DS1 in bone marrow transplants. Figure 20a. (Left) Donors without KIR2DS5 in CMV negative transplants were associated with an improved survival while donors with KIR2DS5 were associated with a worse survival. Figure 20b. (Left) There was no difference in survival for CMV positive transplants, in the presence or absence of KIR2DS5. Figure 21a. (Left) KIR2DS1 was associated with a poorer survival in CMV negative transplants. Figure 21b. (Right) There was no difference in the presence or absence of KIR2DS1 in CMV positive transplants. Figure 22a. (Left) KIR3DS1 in CMV negative transplants was associated with a poorer survival. Figure 22b. (Left) There was no difference in the presence or absence ix

10 of KIR3DS1 in CMV positive transplants. Figure 23a. (Left) KIR2DL5 in CMV negative transplants was associated with a poorer survival. Figure 23b. (Left) There was no difference in the presence or absence of KIR2DL5 in CMV positive transplants Figure 24a. (Left) Donors with high number of KIR genes were associated with a poorer survival in CMV negative. Figure 24b. (Right) No significant difference in survival was observed in transplants with donor with a high number of KIR genes. Figure 25a. (Top left) Donors with KIR2DS2 had poorer survival in TBI negative transplants. Figure 25b. (Top right) Donors with KIR2DS2 had better survival in TBI+ transplants. Figure 25c. (Bottom left) Donors with KIR2DL2 had poorer survival in TBI negative transplants. Figure 25d. (Bottom right) Donors with KIR2DL2 had better survival in TBI+ transplants. Figure 26a. (Top left) KIR2DS2 was associated with a poorer survival in cyclophosphamide negative transplants. Figure 26b. (Top right) KIR2DS2 was associated with an improved survival in cyclophosphamide positive transplants. Figure 26c. (Bottom left) KIR2DL2 was associated with a poorer survival in cyclophosphamide negative transplants. Figure 26d. (Bottom right) KIR2DL2 was associated with an improved survival in cyclophosphamide positive transplants. Figure 27. KIR2DS2 was associated with an improved survival in cyclophosphamide positive transplants in the ALL cohort. Figure 28a. (Left) Presence of KIR2DS2 in cyclophosphamide negative transplants was associated with a worse survival in the MYO cohort. Figure 28b. (Right) KIR2DS2 was associated with an improved survival in cyclophosphamide positive transplants in the MYO cohort. Figure 29a. (Left) The absence of KIR2DS2 in melphalan negative transplant was associated with a poorer survival. Figure 29b. (Right) The absence of KIR2DS2 in melphalan positive transplants was associated with better survival. Figure 30a. (Left) The absence of KIR2DS2 in fludarabine negative transplant was associated with poorer survival. Figure 30b. (Right) The absence of KIR2DS2 in fludarabine positive transplants was associated with better survival TABLES Table 1. PCR reaction mix volumes for different amounts of sample. Table 2. Transplant numbers performed at the two transplant centres. Table 3. Frequency of the different transplant graft source. Table 4. Age range of the donors amongst the different transplants. Table 5. Gender of patients and donors of the transplants analyzed in this study. Table 6. Frequency of the different diagnoses in the entire cohort of patients x

11 Table 7. Frequency of patient, donor CMV status and Transplant CMV Status. Table 8. Frequency of the different conditioning regimens used. Table 9. Prevalence of different grades of agvhd. Table 10. Frequency of the individual KIR genes. Table 11. Frequency of donors with different numbers of activating, inhibitory and total number of KIR genes. Table 12. P values for Pearson chi-square analysis of contingency tables relating KIR genotype, or KIR genotype in different transplant subgroups, to grade of acute GVHD. Table 13. Kaplan-Meier p-values for the association of individual donor KIR genes on survival. Table 14. P. values of individual KIR genes on the survival rate of the myelogenous and non-mylogenous cohort Table 15. P-values of all the conditioning variables with individual KIR genes on survival rate. Table 16. Variables initially entered into the multivariate Cox Regression model Table 17. Variables left in the final equation in the multivariate Cox Regression model. Table 18. The genotypes of the validated 20-cell line panel Table 19. Conditioning agents used in the different diagnoses cohorts xi

12 1. Literature Review 1.1 Immune System The human immune system can be divided into two broad branches, the adaptive immune system and the innate immune system. These two branches work hand in hand to combat invading infections and foreign pathogens that causes harm the human body (Janeway et al. 2001) Adaptive Immunity Adaptive immunity is a part of the immune system, which learns and adapts to the pathogen. The cells involved in the adaptive immune system are T and B cells. These cells require a sensitizing event to a pathogen and the response is improved with subsequent exposure to the same pathogen. A key feature of the adaptive immune system is therefore memory. There are three types of T cells: CD4+ T helper cells which aid in the signaling of B cell activation and growth, CD8+ T cytotoxic cells which recognize and destroy virally infected cells when they are presented to by the T helper cells, and T regulatory cells which maintain balance by modulating tolerance to self-antigens, thus preventing autoimmune diseases (Haribhai et al and Holaday et al. 1993). T cell receptors (TCR) are molecules on the surface of T cells, which recognize antigens on the major hiscompatibility (MHC) class I molecules. B cells differentiate into plasma cells and large volumes of antibodies are secreted to combat the foreign pathogens. Both T and B cells have highly specific antigen receptors on their surface. The B cell antigen receptors (BCR) are membrane bound immunoglobulins, which activate the cell when a specific antigen binds to the receptor. Antigen presentation is a process in the immune system, employed by macrophages, dendritic cells and other cells to 1

13 activate T cytotoxic cells. T cell receptors are restricted to the recognition of antigenic peptides when they are bound to major histocompatibility complex (MHC), which is also known as human leukocyte antigen (HLA). The foreign antigen is taken up by the antigen presenting cell (APC) and processed, after which a peptide fragment is bound to an MHC class II molecule which is necessary for the T helper cells to recognize it (Rolland and O Hehir, 1999). Peptide fragments bound to MHC molecules - MHC class I molecules interact with immature CD8+ T cells to stimulate maturation into mature CD8+ T cytotoxic cells, while peptide fragments bound to MHC class II molecules interact with immature CD4+ T cells to become mature CD4+ T helper cells (Milstein et al. 2011) Innate Immunity The innate immune system is described as the first line of defense in response to foreign infections until the adaptive immunity takes over. The innate immune system does not discriminate between pathogens and has no immunological memory (Janeway et al. 2001). The innate immune system provides protection in the form of proteins and white blood cells (WBC) in the blood. The innate immune system consists of particular subsets of WBC in the bloods, which come into play when the physical barriers fail to stop the pathogens from entering the body. The cells of the innate immune system include natural killer cells, neutrophils, macrophages, monocytes, dendritic cells and mast cells (Robinson and Babcock, 1998). These cells are present in the blood and are fully functional without the need for prior sensitization as 2

14 required by the adaptive immune system (Alberts et al. 2002). Macrophages and monocytes have different methods of combating pathogens; they vary from engulfing the pathogen to secreting anti-microbial substances and lysozymes. Natural killer (NK) cells detect mismatches between self and non-self and proceed to signal the target cell for apoptosis (programmed cell death). In addition to the white blood cells of the innate immune system, the blood also contains a variety of proteins some of which serve to recruit the white cells of the adaptive immune response (Janeway et al. 2001). 1.2 Natural Killer Cells (NK Cells) NK cells are derived from bone marrow and appear morphologically as large granular lymphocytes (Roitt et al. 2001). NK cells do not require prior sensitization to the foreign antigen in order to carry out their effector function. This is the intrinsic difference between the innate and adaptive immune system. NK cells recognize and lyse target cells either by (i) natural cytotoxicity, (ii) cytolytic granule mediated cell apoptosis or (iii) antibodydependent cell mediated cytotoxicity (ADCC) (Rajalingam, 2012). NK cytotoxicity does not require antibodies but is controlled by a balance of inhibitory and activating signals resulting from the interaction of receptors on a NK cell s surface with specific corresponding ligands on a target cell. NK cells possess multiple surface receptors that help distinguish self from non-self. Natural killer cell receptors include: killer cell lectin-like receptors (KLR), killer immunoglobulin-like receptors (KIR), leukocyte immunoglubin-like receptor (LILR) and natural cytotoxicity receptors (NCR). In this study, the KIR receptors are of interest and their interactions with transplant variables. 3

15 1.3 Missing Self Hypothesis in NK Cell Recognition NK cells possess activating and inhibitory receptors which produce cytoplasmic signals corresponding their function and the balance of these signals determine the NK cell s response to the target cell. The missing self hypothesis is based on the foundational understanding that if a target cell lacks the human lymphocyte antigen (HLA) class I ligand to the inhibitory receptor on the NK cell, it leads to the activation of NK cell cytotoxicity and lysis of target cell (Kroger et al. 2006). The missing self theory was introduced by Ljunggren and Kärre (1990) in a series of experiments, which used lymphoma cells and transplantation into mice. The study demonstrated the importance of the expression of MHC class I molecules, by analyzing murine MHC class I (H-2) molecule expression in malignant tumours and linking it to NK cell reactivity (Ljunggren & Karre, 1985). It was observed that lymphoma cells with the loss of H-2 expressions were less malignant than the wild types, which resulted in decreased tumourigenicity. The down regulation of MHC class I molecules, as seen in tumour cells and virus infected cells, results in NK cell mediated lysis of a target cell (Rajalingam, 2012). It was suggested that tumour cells could be killed at low or reduced expression levels of MHC class I molecules, due to NK cell interactions with MHC class I molecules (Karre et al. 1986). So it was hypothesized that NK cells were able to recognize and lyse target cells that lack the expression of MHC class I molecules (Ljunggren & Karre, 1990). 4

16 1.4 Natural Killer (NK) Cell Functions and Pathways NK cells play an important role in tumour surveillance, eradication of pathogens and pregnancy. NK cells mediate the recognition function though natural cytotoxicity receptors and antibody-dependent cell-mediated cytotoxicity (ADCC), while mediating killing functions through cytolytic granule mediated cell apoptosis, cytokine production and natural cytotoxicity (Smyth et al and Smyth et al. 2005). Antibody-dependent cell-mediated cytotoxicity (ADCC) involves the activating receptor CD16. The infected cell is opsonized (binding of antibodies to enhance effector molecules) with antibodies that are recognized by CD16 receptors on the NK cell. This triggers activation and the release of cytolytic granules and cell apoptosis (Tschopp et al. 1986). Cytolytic granule mediated cell apoptosis is the utilization of perforin, a poreforming protein and proteases known as granzymes. Upon degranulation of the target cell s membrane, perforins are inserted into the membrane creating a pore (Tschopp et al. 1986). The synergistic effect of perforins and granzymes trigger an endogenous pathway of programmed cell death through the activation of apoptotic cysteine proteases (caspases). However it is said that apoptosis can occur even in the absence of these activated caspases (Trapani, 1995). Tumour cell surveillance in NK cells has many modes of effector pathways, but most of the NK cell responses lead to apoptosis. Activated NK cells can release cytokines such as: tumor necrosis factor α (TNFα) and interfon gamma (IFNγ) both are pro-inflammatory, while 5

17 interleukin (IL-10) is immuno-suppressive. NK cells are able to mediate tumour cell recognition through various receptors: NKG2D, KNp44, NKp46, NKp30 and DNAM (Terunuma et al. 2008). For instance, irradiation was reported to up-regulate ligands for the activating NK cell receptor NKG2D, which in turn increased NK cell cytotoxicity towards tumour cells (Kim et al, 2006). Adapted from Elsevier Science, 2002 (USA). Figure 1. NK cell s response (receptor-ligand models) to a healthy cell and a tumor cell. Cancers have been shown to down-regulate MHC class I molecules, thereby preventing presentation of tumour antigens to T cells. However, such cells are susceptible to NK cell mediated lysis. 6

18 1.5 Natural Killer Cell Receptors NK receptors can be divided two families; the C-type lectin-like family and the immunoglobulin superfamily, which include the killer immunoglobulin-like receptors (KIR), leukocyte immunoglubin-like receptor (LILR) and the natural cytotoxicity receptors (NCR). The C-type lectin-like family includes the homodimer NKG2D and CD94/NKG2-A,B,C,F heterodimers in humans and in the mouse, the Ly49 family (equivalent to human KIR receptors). Both families of receptors include inhibitory receptors and activating receptors. The NCR group consists of three receptors, NKp46, NKp44 and NKp30. All three receptors share the same crystal structure and are important activating receptors, however, their ligands are still poorly defined (Rajalingam, 2012) C-type Lectin Receptors CD94/NKG2 The CD94/NKG2 heterodimers are found in rodents and primates, but also in humans. CD94/NKG2 interact with non-classical MHC class I molecules like HLA-E. HLA-E has a very specific role in NK cell recognition. The peptide binding groove of HLA-E binds signal peptides of classical MHC class I molecules such as; HLA-A, -B, -C and G. HLA-E expression on a cell s surface is not stable unless it is bound to the signal peptides. Hence the CD94/NKG2 receptors recognition of HLA-E is dependent on the production of the other MHC class I molecules. Though it is an indirect method of surveillance, it is able to monitor the average expression level of MHC class I molecules (Braud et al. 1997). 7

19 Ly49 The Ly49 receptor family is a family of activating and inhibitory receptors found only in mice that interact with H-2 (murine MHC class I) molecules as their ligands. They are part of the C-type lectin family, which is found on murine chromosome 6 (Yokoyama and Seaman, 1993). It is thought that humans probably evolved from an ancestral species containing Ly49 genes because a single Ly49 pseudogene was found in the human natural killer complex (NKC) (Hsu et al. 2002). The Ly49 homodimers are found in mice and despite being members of the C type lectin family, are the functional equivalent of the human KIR receptors that are found in primates including man (Moretta et al. 2002). In relation to murine recognition of MHC class I ligands on target cells, there are inhibitory Ly49 receptors that trigger an inhibitory signal, thus preventing NK cell mediated cytotoxicity. However, like killer cell immunoglobulin-like receptors (KIR), some members of the Ly49 receptor family also are activating receptors (Yokoyama et al. 1989) Immunoglobulin super-family Receptors The other major sub-family of NK cell receptors are the immunoglobulin superfamily which includes the KIR receptors encoded on the human chromosome 19 in the leukocyte receptor complex (LRC) (Vilches and Parham, 2002). Besides KIR, the other set of receptors is the natural cytotoxicity receptors (NCR) comprising: NKp46, NKp44 and NKp30. Upon stimulation, these receptors mediate NK cytotoxicity through the release of IFNγ (Terunuma et al. 2008). 8

20 Killer Cell Immunoglobulin-like Receptor (KIR) KIR receptors are a large family of receptors that are expressed by NK cells and a small subset of T cells. KIR receptors are considered to be important receptors in the development and function of human NK cells. KIR receptors are encoded in a highly polymorphic gene family that results in a vast diversity, in that different individuals have different sets of KIR genes. Genes encoding KIR receptors and HLA class I ligands are located on different chromosomes. This allows for different KIR-HLA interactions in different individuals and thus genetic diversity of the immune response. Consequently, certain KIR-HLA combinations are associated with various autoimmune diseases, viral infections and cancers (Khakoo & Carrington and Bashirova et al. 2006) KIR Receptor Structure and Nomenclature KIR receptors are type I transmembrane proteins and have two or three Ig-like domains. The Ig-like domains in their extracellular regions, enable recognition of classical MHC class I molecules, which are the ligands for the KIR receptors. Ligand binding results in either activating or inhibitory signals in the cytoplasm of the NK cell, depending on the KIR receptor it is bound to (Garcia et al. 2003). KIR receptor nomenclature can be broken down into three parts. The first is the number of Ig-like domains that are present in the receptor protein; 2D represents two Ig-like domains while 3D represents three Ig-like domains. 9

21 The second part of the nomenclature specifies the length of the cytoplasmic tail; an S represents a short tail while an L represents a long tail. The long cytoplasmic tails contains immune-receptor tyrosine-based inhibitory motifs (ITIMs) that are responsible for triggering inhibitory signals. The short cytoplasmic tails lack ITIMs but they possess positively charged lysine residue in their transmembrane region. This is association with the DAP12 signaling molecule that is capable of generating activation signals (Lanier. 2009). The third and final part is the number that comes at the end, which differentiates members having the same structure but different amino acid sequence. An example would be KIR2DS1 and KIR2DS2. Adapted from KIR Proteins by Ebi.ac.uk Figure 2. KIR protein domains and region lengths. KIR receptors can be divided into three groups based on the configuration of their Ig-like domains. Type I KIR receptors are KIR2D proteins (KIR2DL1, - 2DL2, -2DL3, -2DS1, -2DS2, -2DS3, -2DS4 and -2DS5) with the exception of KIR2DL4 and 2DL5 which have a membrane-distal Ig-like domain similar in structure to KIR3D receptors (Garcia et al. 2003). Type II receptors are the 10

22 KIR2D proteins: KIR2DL4 and KIR2DL5 which have D0 and D2 domains but not the D1 (middle) domain. Type III receptors the KIR3DL and KIR3DS and they use all three Ig-like domains (Vilches et al. 2000) KIR Genomics and Diversity The human KIR gene complex is located on chromosome 19q13.4 in the Leukocyte Receptor Complex (LRC) and is approximately 150kb long (Wilson et al and Trowsdale, 2001). The region itself is highly variable in terms of gene content and up to 14 KIR genes are packed closely. Each KIR gene is separated from the next KIR gene by a 2.4kb intergenic region. The only exception to this pattern is KIR3DP1 (a pseudogene) and KIR2DL4 because it is the center of KIR complex where multiple reciprocal recombination events happen in that region (Yawata et al. 2010). 11

23 Adapted from The KIR Gene Cluster by Carrington M and Norma P. (2003) Figure 3. Map of the Leukocyte Receptor Complex (LRC) Genomic diversity of KIR genes can be achieved on several levels. There are four framework genes that are present in all haplotypes. They are: KIR3DL3, KIR2DL4, KIR3DL2 and the pseudogene KIR3DP1. Apart from these framework genes, diversity arises from a combination of gene content and allelic polymorphism, which together results in genetically diverse human KIR genotypes. That is, the KIR gene receptor repertoire differs between different individuals. Individuals genotypes differ but there are distinct sets of genes that form common haplotypes. KIR haplotypes are divided into two groups: 12

24 KIR-A and KIR-B haplotypes. Each haplotype consists of between 8 KIR to 14 KIR genes (Hsu et al. 2002) Allelic Polymorphism of KIR Genes Allelic polymorphism exists in all the KIR genes and allelic polymorphism is a significant contributor to the diversity of KIR genes. Allelic polymorphism arises mainly from point mutation and homologous recombination. (Rajalingam, 2012) There is a similarity between allelic polymorphism in KIR genes and HLA class I genes in that they follow a shared pattern of homologous recombination KIR Haplotypes Studies show that there are about 30 distinct KIR haplotypes differing in gene content. This was established by sequencing genomic clones and haplotype segregation analysis (Uhrberg et al. 2002, Yawata et al and Pyo et al. 2010). The concept of KIR haplotypes was first introduced by Uhrberg et al (1997), who documented gene repertoire variation among individuals. This was later confirmed by studies showing that the number of genes in a haplotype varies. The 30 haplotypes can be divided into two groups: KIR-A haplotypes and KIR-B haplotypes. 13

25 Figure 4. Centromeric and telomeric region separation of KIR genes which includes a few different A/B haplotypes. The most commonly occurring haplotype is termed the A haplotype, which consist of a fixed set of KIR genes: KIR3DL3 (framework gene (FWG)), - KIR2DL3, KIR2DP1, KIR2DL1, KIR3DP1, KIR2DL4 (FWG), KIR3DL1, KIR2DS4 and KIR3DL2 (FWG). The remaining haplotypes are collectively termed group-b haplotypes. Unlike the A haplotype, the genetic content of the group-b haplotype differs amongst different individuals, and includes genes that are not present in the A haplotype. KIR2DS1, KIR2DS2, KIR2DS3, KIR2DS5, KIR2DL2, KIR2DL5 and KIR3DS1, are KIR genes that are only encoded on group-b haplotypes. The group-b haplotypes have more activating receptors than the A haplotype, which has only one activating receptor, KIR2DS4 (Wilson et al. 2000, Middleton et al and Pyo et al. 2010). An individual derives his/her haplotypes from paternal and maternal inheritance. This results in diversity of KIR gene repertoire, even amongst siblings. Individuals may be homozygous for the A-haplotype (A/A), 14

26 homozygous for the B-haplotype (B/B) or heterozygous (A/B). Homozygous A/A individual have a maximum of 7 functional KIR genes whilst a heterozygous A/B individual could have all 14 functional KIR genes (Yawata et al and Shiling et al. 2002). KIR haplotypes have centromeric and telomeric halves. The halves are divided by a 14kb region enriched with L1 repeats upstream of KIR2DL4. (Pyo et al. 2010) The centromeric half encodes KIR3DL3, KIR2DS2, KIR2DL2 or KIR2DL3, KIR2DL5B, KIR2DS3, KIR2DP1, KIR2DL1 and KIR3DP1, while the telomeric half encodes KIR2DL4, KIR3DL1, KIR2DL5A, KIR2DS3 or KIR2DS5, KIR2DS1, KIR2DS4 and KIR3DL2. The framework genes sit on the ends of each half, with KIR3DL3 situated at the 5 end and KIR3DP1 at the 3 end of the centromeric half. At the telomeric half, KIR2DL4 is situated at the 5 end and KIR3DL2 at the 3 end. The centromeric half of the KIR haplotypes encode the inhibitory receptors KIR2DL2 on B-haplotypes and KIR2DL3 on A-haplotypes. Although originally given distinct gene names, they segregate as different alleles of the same locus. Hence a single centromeric region has either a KIR2DL2 or KIR2DL3 gene. Similarly in the telomeric half, the same phenomenon occurs between KIR3DL1 and KIR3DS1. Nearly all haplotypes contain these two loci, so it is expected that nearly everyone has either KIR2DL2 or KIR2DL3 and KIR3DL1 or KIR3DS1 within their genome. In addition, there are three KIR genes 2DL5, 2DS3 and 2DS5, which can be encoded in either the centromeric or telomeric region (Middleton et al and Shiling et al. 2002). 15

27 There is a phenomenon in KIR genomics known as linkage disequilibrium (LD) whereby some genes are almost always found together. These genes are located close together on the chromosome. Hence if one is present, the other is almost always present. A study of LD by Hsu et al. (2002) found that KIR2DS2 and KIR2DL2 are in strong linkage disequilibrium with each other: also KIR3DL1 and KIR3DS1 shared the same linkage (even though they were in different haplotypes). Another pair is KIR2DL1 and KIR2DL3, which often occur together and are in linkage disequilibrium with KIR3DL1, which are strongly linked to KIR2DS4 (as both KIR3DL1 and KIR2DS4 are A haplotype genes) KIR Haplotype Frequencies Within the human population, haplotype frequencies differ among the races. Individuals with A and B haplotype are commonly found in all races (Uhrberg et al and Yawata et al. 2002). Individuals who are homozygous for the A haplotype are more frequent in northeastern Asians Chinese, Japanese and Koreans but also represent 25% of Caucasians (Yawata et al. 2002). On the other hand, individuals with at least one B haplotype are common in Native Americans (Ewerton et al. 2007), Australian Aborigines (Toneva et al. 2001) and Indians (Rajalingam et al. 2002). NK cells from homozygous A/A individuals can express a maximum of four inhibitory KIR receptors (KIR2DL1, -2DL3, -3DL1 and -3DL2) and one activating KIR gene (KIR2DS4). In contrast, heterozygous A/B or B/B individuals can express a maximum of six inhibitory KIR genes (KIR2DL1-3, 16

28 KIR2DL5, KIR3DL1 and KIR3DL2) and two to six activating KIR genes (KIR3DS1, KIR2DS1-5). Hence, NK cells of A/B and B/B genotype have more activating KIR receptors compared to A/A genotypes. This suggests that they might respond more vigorously to foreign pathogens although at this time, there is very little information concerning the ligands for the activating KIR receptors (Rajalingam et al. 2008) Ligands for KIR Receptors KIR receptors recognize allelic motifs on HLA class I molecules that are encoded on chromosome 6. KIR recognition is not only locus-specific but also specific for certain allotypes that share a common epitope. KIR receptors recognize and bind to the orthogonal orientation across the α1 and α2 helices of the HLA class I molecule (Rajalingam, 2012). Inhibitory KIR receptors interact with the classical HLA class I molecules (HLA-A, -B and C) resulting in the inhibition of NK cell mediated lysis. HLA-C alleles are ligands for several KIR receptors. HLA-C alleles have one of two possible amino acid residues at position 80 that determine KIR binding specificity. All HLA-C allotypes at position 80 have a dimorphism of either asparigine (N) or lysine (K) (Colonna et al. 1993, Wagtmann et al and Winter et al. 1995). 17

29 Adapted from KIR genes By Saikiran Sedimbi. Figure 5. Various KIR receptors and their HLA class I ligands. The KIR2DL1 inhibitory receptor binds to HLA-C alleles (Cw2, Cw4, Cw5, Cw6, Cw15, Cw17 and Cw18) that carry a lysine residue at position 80. They are said to have the C2 epitope. KIR2DL2 and KIR2DL3 inhibitory receptors bind to the remaining HLA-C allelles (Cw1, Cw3, Cw7, Cw8, Cw13 and Cw14), which have an asparagine residue at position 80. These allotypes are said to have the C1 epitope. In addition to C1 epitope binding, KIR2DL2/3 also interacts weakly with C2 epitopes. However the KIR2DL2/3-C2 interactions are comparatively weaker to KIR2DL1-C2 interactions, thus the inhibitory signals triggered are weaker (Colonna et al and Winter et al. 1995). HLA-B alleles can be divided into two groups based on the presence of either a Bw4 or Bw6 motif in the α1 domain at residues of the molecule. KIR3DL1 inhibitory receptor binds to a subset of HLA-A (HLA-A23, A24, A25 and A32) and HLA-B alleles that have the Bw4 epitope on their a-helix 18

30 (approximately 40% of B allotypes have the Bw4 epitope). The KIR3DL2 inhibitory receptor binds to only HLA-A3 and A11 allotypes. The strength of the interaction is highly sensitive to the sequence of the peptide bound in the HLA-A peptide-binding groove (Cook et al. 2006). The ligands specificities of KIR2DS2, KIR2DS5, KIR3DS1 and KIR2DL5 have remained elusive KIR Expression The expression of KIR genes in NK cells influence the behavior and interactions of these cells. However the mechanisms controlling expression are barely understood (McErlean et al. 2010). KIR expression in NK cells of siblings shows that the expression repertoire is mostly dependent on the KIR genotype (Davies et al. 2002). There is also evidence that allelic variation in the KIR gene may have a profound effect on expression (Buckland, 2004) and transcription control (Johnson et al. 2005). Each NK cell expresses only one or a few KIR receptors. Selection of KIR receptor expression occurs during NK cell development resulting in NK cells that are only cytotoxic when they have inhibitory receptors to self-hla class I ligands. This prevents auto-agression/auto-immunity (Uhrberg et al. 1997). 1.6 Haematopoietic Stem Cell Transplantation (HSCT) HLA-matched allogeneic haematopoietic stem cell transplantation (HSCT) is used to treat individuals suffering from haematological malignancies (eg. 19

31 leukaemia, lymphomas), bone marrow failure syndromes and inborn biochemical deficiencies (Appelbaum, 2003). The donor maybe a HLAidentical sibling (patient and donor have the same HLA type) or a HLA matched unrelated donor (MUD). MUD donors may have a small number of HLA mismatches with the patient. Often there is a mismatch at HLA-C. The mismatch of HLA-C in the donor s genotype can result in NK alloreactivity due to incompatibility of KIR ligands (Witt, 2009). This will be explained in detail in the next chapter. Patients are prepared for HSCT by high dose chemotherapy and/or irradiation which is intended to destroy the malignant cells but also destroys the patient s bone marrow to make room for the transplanted donor s stem cells. The donor s stem cells can be collected from the bone marrow or peripheral blood. After preparation of the patient, the stem cells are infused and usually engraft but rejection occurs in a few percent of transplants. (Proquest, 2011). Successfully eliminating leukaemia by HSCT is not only attributed to pre-transplant chemoradiotherapy but also due to an anti-tumour effect provided by the infused donor lymphocytes that accompany the stem cells. This effect is termed graft-versus-leukaemia effect (Barnes et al. 1957). Despite advances in medical science, HSCTs are still plagued with immunological complications due to: graft rejection, graft-versus-host disease (GvHD), CMV and other infections, and leukaemia relapse. 20

32 1.7 Factors Affecting the Outcome of Allogeneic HSCT NK Alloreactivity due to Ligand-Ligand Incompatibility HLA antigens are transplantation antigens that are involved in the interactions between patient and donor lymphocytes. Hence to get a successful transplant it s best to use an HLA identical donor. Unlike B and T cells allorecognition that involves recognition of foreign HLA antigens. NK cells allorecognition mostly involves the recognition of missing self-hla antigens. KIR ligand incompatibilities refer to presence or absence of specific HLA ligands (in the patient) for specific inhibitory KIR receptors (in the donor). As mentioned in the previous chapter, an NK cell engages a potential target cell with activating and inhibitory receptors. If the target cell does not have the relevant inhibitory ligands to engage the NK cells inhibitory receptors, the NK cell will proceed to lyse the target (Class, 2010 and Witt & Christiansen. 2006). NK alloreactivity may play a part in the outcome of HSCT. Many studies on the effect of NK alloreactivity on the outcome HSCT have been contradictory. Some studies find a beneficial effect, whilst others find a detrimental effect. The reason for these conflicting reports is unclear. Two studies in particular demonstrate the inconsistency of findings in relation to NK alloreactivity. Davies et al. (2002) studied 175 pediatrics and adult patients with differing malignancies receiving a transplant with at least one HLA allele mismatch. The results showed a poorer survival in transplants with KIR ligand incompatibility and no significant effects on relapse rates. The two biggest factors that affect survival were relapse and GvHD. ATG was used in the preparative regimens for T cell depletion. The results were supported by 21

33 Schaffer et al. (2004) who reported reduced survival rate, no effects on relapse rates and the use of ATG. In contrast to these studies, Giebel et al. (2003) studied 121 pediatric and adult patients with differing malignancies and preparative regimens in which no ATG was used. The results reported improved survival in transplants with KIR ligand incompatibility. Giebel s study supports Ruggeri et al. (2002), findings of an increased survival rate and reduced relapse rates in transplants with ligand incompatibility. It was suggested that the difference between the studies findings of the deleterious and beneficial effects of KIR ligands incompatibility were due to the use of ATG, as a result, more T cells were depleted (Schaffer et al. 2004). KIR ligand incompatibility has also been studied in relation to GvHD. GvHD is thought to be initiated when donor T cells interact with recipient APC. In a mouse model, NK cells have been shown to prevent GvHD by destroying recipient APC and preventing activation of T cells (Ruggeri et al. 2002). Morishima et al (2007) studied 1790 patients receiving T cell repleted grafts and a relatively uniform transplant procedure. KIR ligand incompatibility in acute myloid leukaemia (AML), chronic myeloid leukaemia (CML) and acute lymphoid leukaemia (ALL) patients resulted in an increase in grade III-IV GvHD and mortality. But in similar transplants in which anti-thymocyte globulin (ATG) was used to deplete donor T cells in vivo, KIR ligand incompatibilities protected against GvHD. These two observations suggest that the effect of KIR ligand incompatibility on GvHD may be detrimental or beneficial depending on whether donor T cells are present or not. Other reports have also made similar observations (Franco, 2002). 22

34 When KIR ligand incompatibility was studied in relation to relapse, a beneficial effect on relapse rate was observed. Giebel et al. (2003) studied 130 unrelated patient-donors transplants reporting an association between KIR ligand incompatibilities and decreased relapse rates. When the myeloid leukaemia group was analyzed, the effects were more prominent, leading to a suggestion that myeloid malignancies were more responsive to ligand incompatibility compared to lymphoid leukaemias. However, NK cell-mediated effects have been reported to have an impact on childhood ALL (Pende et al. 2009). Childhood leukaemia blasts express high levels of adhesion molecules, which aid the NK cell-mediated lysis of target cells (Mengarelli et al. 2001). Unfortunately, in Giebel et al. (2003) study, the ALL patients were not categorized into children or adult transplants. Hence, if the studies on childhood ALL are confirmed then not only would patients with myeloid leukaemias benefit from NK cell mediated responses but also childhood ALL patients. In support of Giebel et al. study, a study conducted by Hsu et al. (2006) stated that in the absences of certain KIR ligands, there was a decreased risk of relapse for patients in AML, CML and ALL. There was evidence to support NK cell mediated graft-versus-leukaemia (GvL) effect in ALL patients but it was more prominent in AML patients (Willemze et al. 2009) KIR Repertoire on the Outcome of HSCT There are many contradictory reports in relation to whether particular KIR activating receptors in donors, either increase (Kroger et al, 2006) or 23

35 decrease (Verheyden et al, 2005 and Schellekens J et al, 2008) relapse and GvHD rates. Consequently, the presence of activating KIR genes either improve or decrease survival rate. In this chapter, linking of KIR repertoire (particular set of KIR genes in the individual) to survival rate, GvHD and relapse rate will be focused on. Studies performed by Kroger et al. (2006) and Cooley et al. (2008) showed distinctly different results. Kroger et al. (2006) studied 142 patients with leukaemia who underwent unrelated stem cell transplantation and ATG was used for T cell depletion. The results showed a significantly lower survival rate in transplant with KIR haplotype B/x donors (more activating receptors), while a higher survival rate in transplants with KIR haplotype A/A (less activating receptors) donors. Giebel et al. (2003) found similar observations as Kroger et al. (2006). However, this effect was only seen in AML and less in myeloid leukaemias. In contrast to Kroger et al. s (2006) study, Cooley et al. (2008) studied 448 patients; results showed that donor KIR haplotype A/A (few activating receptors) had a higher treatment related mortality rate (poorer survival) as compared to donors having a B/x haplotype (more activating receptors). Following the aforementioned study, Cooley et al. (2009) continued to study KIR haplotypes in HLA-matched unrelated HSCT outcome, in patients receiving T cell replete grafts. The survival rate was significantly higher with homozygous haplotype B (B/B) donors or at least, heterozygous haplotype B (B/x) donors than with A/A donors. Donors having at least one B haplotype showed a 30% increase in relapse-free survival as compared to a homozygous haplotype A donor (A/A). 24

36 There were contrasting results in the association of the rate of GvHD and KIR repertoire reported by Kroger et al. (2006) and Cooley et al. (2008). Kroger et al. (2006) reported no effect on GvHD rates in association to KIR repertoire. While Cooley et al. (2008) found that increased GvHD rates correlate to increased number of activating receptors. Cooley et al. (2008) showed an increased rate of chronic GVHD but not acute GHVD, in patients transplanted with KIR haplotype B/x or B/B donors. Likewise, contrasting results were observed with relapse rates and KIR repertoire. Kroger et al. (2006) hypothesized an increase in relapse rates in association with activating genes, however they found no effect on relapse rates. These observations by Kroger et al. (2006) were supported by Schaffer et al. (2004). However, Cooley et al. (2009) reported that donor KIR haplotype A/A (few activating receptors) had a higher relapse rate as compared to a B/x haplotype (more activating receptors). The conflicting results reported for KIR genotype and HSCT outcome may be related to the methods used for transplants (preparative regimens) thereby influencing whether matching for donor KIR genotype is beneficial or not. section will look into a few of the more prominent factors that have been previously reported to play a role in a HSCT outcome Preparative Regimens Variables Preparative regimens include many drugs and other treatments such as total body irradiation (TBI) and T cell depletion (use of ATG) that may influence NK 25

37 cell alloreactivity. T cell depletion with the use of ATG was mentioned briefly in the previous chapters. The two variables that will be focused on in this section are total body irradiation (TBI) and cytomegalovirus (CMV) prophylaxis, and their potential effects on HSCT outcomes Total Body Irradiation (TBI) TBI is a form of radiotherapy; it is usually part of the preparative regimens in HSCT. The purpose of TBI is to destroy the recipient s body s immune cells, thus preventing any immune responses (from patient lymphocytes against donor graft) that would lead to immunological rejection. In addition to destroying the recipient s immune cells, it also kills off malignant cells, hopefully increasing the success rate of the transplant (Soule et al. 2007). TBI has also been shown to cause an up-regulation of NKG2D ligands and increased sensitivity of NK cell mediated cytotoxicity of tumour cells (Kim et al. 2006). NKG2D is an activating receptor that is found on NK cells and CD8+ T cells (Gasser et al. 2005). Upon stress-induced interaction with tumour cells, NKG2D ligands are up-regulated, which causes the tumour cell to be susceptible to NK cell-mediated lyses (Zafirova et al. 2011). As the use of TBI varies between transplant centres and among the different diagnoses, this might be one factor that influences the role that NK cells play in HSCT, particularly with respect to the GvL effect. 26

38 Cytomegalovirus (CMV) Prophylaxis There are three drugs commonly used to prevent or treat CMV infection; acyclovir, ganciclovir and valacyclovir. Prophylaxis has been shown to reduce CMV activation but it is not 100% effective (Syndman et al. 1993). Acyclovir is known to interfere with viral DNA synthesis and inhibits the herpes simplex virus from replicating (Balfour et al. 1990). Ganciclovir inhibits the viral DNA polymerase (McEvoy, 2003). As a result it interferes with DNA synthesis of the virus. However, problems like poor absorption, resistance of CMV, etc, led to the development of valacyclovir. Valacyclovir is a different form of acyclovir that is administered orally and rapidly converted to ganciclovir in the gastrointestinal tract and liver. The dose given to a particular patient differs depending on CMV risk status. As particular donor KIR gene repertoires have been reported to protect against CMV reactivation (see 1.8 below), the use of CMV prophylaxis might be one factor that influences the effect of donor KIR gene repertoire on the outcome of HSCT. 1.8 Cytomegalovirus (CMV) Cytomegalovirus falls under the broad family of the Herpesviridae, better known as the Herpes virus (Ryan and Ray, 2004). CMV has close relations with another well-known virus, Epstein-Barr virus (associated to cancers like Burkitt s lymphoma, etc) (Maeda et al. 2009). A characteristic that CMV shares with Herpes virus family is the ability to remain latent in the healthy human body. However, the problem arises when the body is immunocompromised from taking immunosuppressuve drugs for organ transplants (kidney, bone marrow, etc) or in a HIV-infected person. The ability 27

39 of CMV to remain latent in the body without alarming the immune system is a result of its genome, which encodes for a few proteins that interferes with viral antigen presentation. They interfere with antigen presentation by degrading MHC class I proteins before it reaches the cell surface as well as blocks translocation of peptides to the endoplasmic reticulum. HSCT in which either the patient or donor is CMV positive tend to have worse outcomes than CMV negative HSCT (Ljungman et al. 2003) KIR Repertoire with Association to CMV Protection Several studies have reported beneficial effects of KIR activating genes in the protection against CMV reactivation. Zaia et al. (2010) and Cook et al. (2009) reported that more donor KIR activating receptors are associated with protection from CMV infection. The former study focused on individual KIR genes, while the latter study focused more on the different (A/A, B/x and B/B) KIR haplotypes as a whole. In a study conducted by Zaia et al. (2010), involving 211 patients-donors who had undergone transplant from 2001 to 2006, data provided showed that there was a prominence of CMV reactivation in recipients, when the donor KIR genotypes contained less than 5 activating KIR genes. 83% of recipients with donors that have 0 activating KIR genes developed CMV reactivation after HSCT, while only 17% were CMV-free. As for recipients of donors with 1-4 activating (akir) KIR genes, 72% developed CMV reactivation while 28% did not. Lastly, last than half (48%) of recipients with donors that have more than 5 activating KIR genes developed CMV reactivation. The data showed 28

40 that if the donor KIR genotype had activating (akir) KIR2DS2 and/or KIR2DS4, this resulted in a lower incidence of CMV reactivation. Interestingly, the KIR2DS4 deletion variant 2DS4d, which does not express the activating KIR2DS4 receptor on the surface, is associated with a higher rate of CMV reactivation. This emphasizes the importance of having activating KIR2DS2 and KIR2DS4 in donor KIR genotypes. Aside from these activating KIR genes, inhibitory (ikir) KIR2DL2 are seen more frequently in groups of patients with no CMV reactivation. But KIR2DS2 and KIR2DL2 are known to be in strong linkage disequilibrium and they are usually expressed together. In conclusion, Zaia et al s data indicated that donor genotypes with KIR2DS2 and KIR2DS4 are associated with reduced CMV activation. In addition to that, the same association of reduced CMV activation can be applied to donor genotypes with at least 5 activating KIR genes, regardless of which activating gene it is. They suggest that the ideal protective donor genotype should be one with both KIR2DS2 and KIR2DS4 or a genotype with at least 5 activating KIR genes. However, this should not be mistaken for a genotype that will result in absolutely no CMV activation. CMV reactivation may occur regardless of these protective KIR genotypes, but it was concluded that the ideal protective genotypes are associated with lower rates of CMV (Gallex- Hawkins et al. 2011). Another study, carried out by Cook et al. (2009) studied 234 patients, 97 with myeloid malignancy, 87 with lymphoid malignancy and 50 with nonmalignant disease. In CMV seropositive recipients, there was a 53% CMV reactivation rate in sibling donor transplants (38 out of 72) and 64% CMV reactivation in 29

41 unrelated or HLA non-identical donor transplants (22 out of 35). In transplants involving siblings, when both donor and recipient were seropositive and the donor KIR haplotype was homozygous A/A, the CMV reactivation rate was 65%. Inversely, donors with a copy of KIR haplotype B, the CMV reactivation rate 28%. However, the KIR haplotype B s protective influence was restricted to myeloablative stem cell transplants. From a multivariate analysis, sibling donor KIR haplotype B was associated to a significantly reduced rate of CMV reactivation. Likewise, in kidney transplants Stern et al. (2008), showed that activating KIR genes played a role in controlling CMV infection. It was observed that the A haplotype (which only has one akir gene) had an infection rate of 36% while a genotype (B haplotype, B/B or B/x) with more than one akir gene had an infection rate of 20%. Using a Cox regression analysis, the risk factor of B haplotype compared to A haplotype was p= This suggests that protection against CMV increases with the number of akir genes. In summary, there are many conflicting reports of beneficial or detrimental effects of KIR repertoire on the outcome of HSCT. This may be due to transplant variables, such as: TBI, CMV status of patients and donors and CMV prophylaxis used, which may have an effect on NK cell activity. The purpose of this thesis is to determine: (a) Whether donor KIR gene repertoires influence the survival rate in HSCT performed at Royal Perth Hospital and Princess Margaret Hospital. 30

42 (b) Whether transplant variables such as TBI, CMV status and prophylaxis interact with activating KIR receptors to influence outcome. 2. Materials and Methods 2.1 DNA Samples and Preparation DNA Source DNA samples were from unrelated donors of all the haematopoietic stem cell transplants performed at RPH since 1990 and PMH. DNA extraction from whole blood was performed by the staff at the Department of Clinical Immunology & Immunogenetics, Royal Perth Hospital using a commercial kit (Qiagen, Valencia, USA). DNA used in the optimization of KIR PCR-SSP genotyping assay was extracted from Epstein-Barr Virus (EBV) transformed cells of the 13th International Histocompatibility Workshop (IHWS) (De Santis et al, 2004). DNA from 20 IHWS cell lines that had been previously typed by other KIR genotyping methods was selected. DNA extraction from cell lines was performed by the staff at the Department of Clinical Immunology & Immunogenetics, Royal Perth Hospital using a commercial kit (Qiagen, Valencia, USA) or a salting out method (Miller et al, 1988). 31

43 2.1.2 Calculations for the Preparation of DNA samples C 1 V 1 = C 2 V 2 (Initial Concentration)(Initial Volume) = (Final Concentration)(Final Volume) This equation was used to dilute both the primers and DNA samples. All DNA samples were diluted to 25ng/uL. The optimal DNA concentration for the KIR PCR-SSP ranged between 25ng/uL to 30ng/uL. 2.2 Polymerase Chain Reaction Sequence Specific Priming (PCR-SSP) Assay for KIR Genotyping Oligonucleotide Primers The primers were purchased from Gene Works (Adelaide, Australia) as freeze-dried material, which were stored in the -20 o C freezer prior to liquid reconstitution. The new primers were reconstituted to 100pmol/uL with TE buffer, ph 8.0 (made by RPH routine staff). An example: Primer KIR3DL1F_4x542 was initially received at 60.0 nmol per tube. After reconstitution the final concentration of KIR3DL1F_4x542 primer was 100pmol/uL per tube. 32

44 C 1 V 1 = C 2 V 2 60nmol = 100pmol/ul x V 2 V 2 = 60/100 V 2 = 0.6 ml V 2 = 0.6 ml x 1000 V 2 = 600ul of TE buffer All primers were reconstituted to 100 pmol/ul. The reconstituted primers were vortexed for 1 minute then left on a circular rotator for 20 minutes at room temperature. After rotation, the primers were kept in the -20 o C freezer. The different primers were then diluted to different concentrations based on desired optimal band intensities, during the optimization assay. To avoid freezing and thawing the primers too many times, this would result in the primers gradually degrading and leading to PCR inaccuracies. Working sub-aliquots of 50ul were made in a 1.5ml Eppendorf microcentrifuge tubes. The sub-aliquots were labeled and stored in -20 o C freezer for daily usage. 33

45 Primers Sequence Information KIR Gene: Primer Sequnce: Product Size Group 1: 2DL3F 2DL3Ra 2DL3Rb 2DL1F 2DL1R 3DL1F 3DL1R TCTTCTTTCTCCTTCATCGCTGATGCTG caggaaacagctatgacccctgcaggctcttggtccattacaa caggaaacagctatgaccctgcaggctcttggtccattaccg tgtaaaacgacgccagttgttggtcagatgtcatgtttgaac caggaaacagctatgaccaggtccctgccaggtcttgcg tgtaaaacgacgccatccatyggtcccatgatgct caggaaacagctatgaccccacgatgtccagggga ~500bp 185bp 140bp Group 2: 3DL3F 3DL3R 2DS3Fc 2DS3F T 2DS3R 3DS1F 3DS1R 2DS5F 2DS5R tgtaaaacgacgccagtaatgttggtcagatgtcag caggaaacagctatgaccgcygacaactcatagggta tgtaaaacgacgccaagtcttgtcctgmagctccc tgtaaaacgacgccaagtcttgtcctgmagctcct caggaaacagctatgaccgcatctgtaggttcctcct tgtaaaacgacgccatttctccatcrgttccatgatgcg caggaaacagctatgaccccacgatgtccagggga tgtaaaacgacgccactgcacagagaggggacgtttaacc caggaaacagctatgaccgtcatgcgaccgatggagaagttgc 222bp 191bp 140bp 128bp 34

46 Group 3: 2DL5F 2DL5R 2DL2F 2DL2R 2DS1F No tag 2DS1R C No tag 2DSIR T No Tag 2DL4F 2DL4R tgtaaaacgacgccaatctatccagggaggggag caggaaacagctatgacccgggtctgaccactcatagggt tgtaaaacgacgccagtaaaccttctctctcagccca caggaaacagctatgaccgccctgcagagaacctaca GTTGTTGGTCAGATGTCATGTTTGAAC TAGGTCCCTGCCAGGTCTTGCC TAGGTCCCTGCCAGGTCTTGCT tgtaaaacgacgccagtatcgccagacacctgcatgctg caggaaacagctatgacccaccagcgatgaaggagaaagaaggg 193bp 173bp 140bp 122bp Group 4: 2DS4delF 2DS4delR 3DL2F 3DL2R 2DS2F 2DS2R 2DS4F 2DS4R tgtaaaacgacgccagtcttgtcctgcagctccatctatc caggaaacagctatgaccgagtttgaccactcgtagggagc tgtaaaacgacgccaaggcccatgaacgtaggctccg caggaaacagctatgaccggtcacttgagtttgaccacacgc tgtaaaacgacgccaccttctgcacagagaggggaagta caggaaacagctatgaccaggtccctgcaaggtcttgcttgcatc tgtaaaacgacgccagtttcctggccctcccaggtcac caggaaacagctatgaccaaggaagtgctcaaacatgacatcc 231bp 159bp 165bp 119bp (Note: Framework genes are in bold and universal sequencing primer tags are lower case.) 35

47 The universal sequencing primer tags are: the forward tag was M13F (tgtaaaacgacgcca) and the reverse tag was M13R (caggaaacagctatgacc) Preparation of PCR Reagents (Reaction mix components) x TDMH PCR Buffer (100ml) 8.114g of Trizma base (Sigma, St Louis, USA) was placed in a sterile 200ml bottle and dissolved with 80ml of molecular grade water (Bioscience, St Louis, USA) to make 1 x Tris buffer. The ph was adjusted using a ph meter (EUTECH Instruments, Singapore) and HCL, to ph g of ammonium sulphate (Merck, Victoria, Australia) were then dissolved into the Tris buffer, using a magnetic stirrer. A 0.22um filter (Pall Corporation, Cornwall, UK) was attached to disposable syringe and the mixture was filtered into a new sterile 200ml bottle. 1ml of Tween20 (Promega, Madison, USA) was added to the filtered mixture and shaken then transferred to a sterile measuring cylinder. The mixture was made up to 100ml with molecular grade water and inverted back and forth gently to mix well. The buffer was aliquoted into 15ml tubes and stored at -80 o C. When needed, a 15ml tube was then sub-aliquoted into 1.5ml Eppendorf microcentrifuge tubes and stored in a -20 o C freezer for daily uses mM dntp The routine staff at RPH Clinical Immunology Department prepared the 40mM dntp used in the reaction mix. 36

48 100mM dntp set (Invitrogen, Carlsbad, USA) was thawed and vortexed. 600ul of each datp, dctp, dgtp and dttp was added into 3600ul of sterile deionized water in 15CTS tube. The mixture was vortexed to mix well. Aliquots of 30 x 40ul volumes were prepared into 0.5ml Eppendorf tube and stored at -20 o C Other PCR Reagents Other components of the PCR-SSP reaction mix were commercially acquired: 25mM MgCl 2 (Roche, Indianapolis, USA), molecular grade water (Sigma- Aldrich, St Louis, USA) and GOTaq Polymerase (Promega, Madison, USA) Preparation of Gel Electrophoresis Reagents x TBE Buffer (2 litre batch) The routine staff at RPH Clinical Immunology Department prepared buffer for gel electrophoresis g of Trizma base, 110g of boric acid and 16.4g of EDTA were weighed and placed into a sterile 2L conical flask and dissolved with 1.2L of Milli-Q Ultrapure water using a magnetic stirrer. When dissolved, the mixture was made up to 2L with Milli-Q Ultrapure water then autoclaved x TBE Buffer (20 litre) Gel Electrophoresis Running Buffer 19L of Milli-Q Ultrapure water was added into a 30L dispenser and 1L of 10 x TBE buffer (made by RPH routine staff) was added to the dispenser. The buffer was thoroughly mixed. 37

49 % and 3.5% Agarose Gel 12g (3%) or 14g (3.5%) of UltraPure TM Agarose powder (Invitrogen) was weighed and added to an autoclaved 500ml bottle. 400ml of TBE buffer was measured in a measuring cylinder and transferred to the 500ml bottle. The bottle was placed into a microwave oven, which was set to a 1000w, and microwaved for 2minutes 30 seconds, after which it was taken out, allowed to cool slightly and swirled gently to facilitate even mixing. The bottle was placed back into the microwave oven for 30 seconds then taken out, swirled gently again and labeled 3% -EB. Prior to use, 20uL of ethidium bromide was added to the gel. The bottle was placed into a 70 o C incubator. For this KIR project, all gels were made and used the same day; no molten gels older than 2 days old were used. (Note: before the molten gel was cast, if the gel looked slightly opaque, it was microwaved at 1000w for 1 minute and swirled gently, to make sure there were no small solidified agar lumps.) Gel Electrophoresis Loading Buffer The routine staff at RPH Clinical Immunology Department prepared the loading buffer. 8g of sucrose and 0.05g of bromophenol blue were added to 20ml of Milli-Q Ultrapure water and mixed using a magnetic stirrer. Once dissolved, the mixture was made up with Milli-Q Ultrapure water to 160ml. The mixture was aliquoted into 96-well plates and stored at -20 o C freezer (long term) and 4 o C fridge (daily use). 38

50 Gel Electrophoresis 1Kb Plus DNA Lambda Ladder The routine staff at RPH Clinical Immunology Department prepared the ladder for use. 1ml of 1Kb Plus DNA ladder (Invitrogen, Carlsbad, USA) was added to 4ml of molecular grade water. The mixture was mixed well and aliquoted into 1.5ml Eppendorf centrifuge tubes. The ladder was stored at 4 o C for immediate daily use and at -20 o C freezer for long-term storage. 2.3 KIR Multiplex PCR-SSP Genotyping Assay Optimization The KIR multiplex PCR-SSP genotyping assay included the amplification of 15 KIR genes. Amplification of the 15 KIR genes was divided into 4 groups. Each multiplex PCR group includes the amplification of a framework gene (present in all individuals), which acts as an internal PCR control. Each PCR run included 3 controls 2 positive controls (JBUSH and CB6B), which together include the amplification of all the 15 KIR genes, and 1 negative control (sterile molecular grade water) to check for contamination. Also, as an added precaution, an internal PCR control, a framework KIR gene (present in everyone s DNA) primers were strategically selected for each group based on product sizes of the other primers, so that all PCR product bands will be clear and distinct. For the initial experimental optimization stage, the 3 controls indicated above and another 2 samples from the th IHWS cell line panel were used. Once the PCR was shown to be both specific for the KIR genes as determined by PCR product size on an agarose gel and showed good PCR 39

51 band intensities, the full 20-cell-line IHWS panel run was tested to further confirm primer specificity. To optimize the KIR gene multiplex assay, the following variables were tested, different: dntp concentrations (10mM or 40mM), primer concentrations (5pmol/ul to 30pmol/ul), primer volumes (0.5ul per sample to 1ul per sample), MgCl 2 concentrations (2.0mM to 3.0mM), batch volumes (10 typings, 25 typings, 100 typings and 200 typings) and Taq Polymerases (AmpliGold Taq and GO Taq) Polymerase Chain Reaction (PCR) Runs Reaction Mix (Mastermix) Volumes Number of Samples Primers Varied Varied Varied Varied Volumes Volumes Volumes Volumes 10x TDMH 2ul 20ul 50ul 200ul 25mM MgCl2 1.6ul 16ul 40ul 160ul 10mM/40mM 1ul 10ul 25ul 100ul dntp Sterile Water Total Volume Other Reagents = Volume of Sterile Water Taq Polymerase 0.2ul 2ul 5ul 20ul Total Volume 18ul 180ul 450ul 1800ul Table 1. PCR reaction mix volumes for different amounts of sample. 40

52 The total volume in each well on the 96-well plate was 20ul, which consisted of 2ul of DNA and 18ul of mastermix. The mastermix was vortexed before mixing with the DNA sample. The PCR plate was placed on ice while the DNA samples and mastermixes were pipetted. To make sure there was no liquid on the walls of the wells, the plate was spun down in the centrifuge then placed into the thermocycler (refer to for thermocycler conditions). 41

53 KIR PCR-SSP Gene groups Optimized Recipes Group 1 Optimized Mastermix Recipe Group 2 Optimized Mastermix Recipe Reaction Mix Concentration Volume Per Reaction Mix Concentration Volume Per Components Sample Components Sample 2DL1F_4x431 5pmol/ul 1ul 3DL3F_4x428 25pmol/ul 0.5ul 2DL1R_4x583 5pmol/ul 1ul 3DL3R_4x623 25pmol/ul 0.5ul 2DL3F_7x782M6 10pmol/ul 1ul 2DS3F_Fy803_C 30pmol/ul 0.5ul 2DL3Ra_8x826 10pmol/ul 1ul 2DS3F_Fy803_T 30pmol/ul 0.5ul 2DL3Rb_8x827 10pmol/ul 1ul 2DS3R_5x576 30pmol/ul 0.5ul 3DL1F_4x542 10pmol/ul 1ul 2DS5F_4x177 10pmol/ul 0.75ul 3DL1R_4x649 10pmol/ul 1ul 2DS5R_4x272 10pmol/ul 0.75ul 3DS1F_4x pmol/ul 0.75ul 3DS1R_4x pmol/ul 0.75ul dntp 40mM 1ul 10x TDMH Buffer - 2ul 25mM MgCl 2-1.6ul Sterile Water GO Taq Polymerase 5ug/ul 0.2ul Total Reaction Mix Volume: 20ul dntp 10mM 1ul 10x TDMH Buffer - 2ul 25mM MgCl 2-1.6ul Sterile Water - 7.7ul GO Taq Polymerase 5ug/ul 0.2ul Total Reaction Mix Volume: 20ul 42

54 Group 3 Optimized Mastermix Recipe Group 4 Optimized Mastermix Recipe Reaction Mix Concentration Volume Per Reaction Mix Concentration Volume Per Components Sample Components Sample 2DL4F_7x707 5pmol/ul 1ul 3DL2F_5x778 5pmol/ul 1ul 2DL4R_7x796 5pmol/ul 1ul 3DL2R_5x904 5pmol/ul 1ul 2DL2F_5x383 20pmol/ul 1ul 2DS4F_4x91 10pmol/ul 1ul 2DL2R_5x523 20pmol/ul 1ul 2DS4R_4x177 10pmol/ul 1ul 2DL1F_4x431 No Tag 15pmol/ul 1ul 2DS4dF_5x437 10pmol/ul 1ul 2DS1R_4x541C No Tag 15pmol/ul 1ul 2DS4dR_5x635 10pmol/ul 1ul 2DS1R_4x541T No Tag 15pmol/ul 1ul 2DS2F_4x168 10pmol/ul 1ul 2DL5F_5x460 5pmol/ul 1ul 2DS2R_4x297 10pmol/ul 1ul 2DL5R_5x621 5pmol/ul 1ul dntp 40mM 1ul 10x TDMH Buffer - 2ul 25mM MgCl 2-1.6ul Sterile Water - 4.2ul GO Taq Polymerase 5ug/ul 0.2ul Total Reaction Mix Volume: 20ul dntp 40mM 1ul 10x TDMH Buffer - 2ul 25mM MgCl 2-1.6ul Sterile Water - 5.2ul GO Taq Polymerase 5ug/ul 0.2ul Total Reaction Mix Volume: 20ul 43

55 Thermocycler Run Conditions Thermocycler PCR Programme Name: KIR62 Temperature and Time Number of Cycles 96 o C for 6minutes 1 96 o C for 30 seconds 62 o C for 30 seconds 72 o C for 2 minutes o C for 10 minutes 1 4 o C HOLD After completion of thermocycling, the 96-well plate was centrifuged (to make sure the condensed liquids on the walls of the wells were not left out) and placed in a 4 o C fridge until loaded onto agarose gels Gel Electrophoresis The percentage of agarose gel used was dependent on the KIR genotyping PCR group; 3% agarose gels were used for Group 1 and Group 2 while 3.5% agarose gels were used for Group 3 and 4. This was because Group 3 and 4 PCR products were slightly harder to separate. The casting of the agarose gel was as follows; the bottle containing the molten agar gel was removed from the 70 o C incubator. 20ul of ethidium bromide was added and gently but thoroughly swirled. A liberal amount was poured into the gel cast, to create a deep well so no PCR products would accidentally float out when pipetting into the well. While still hot, the bubbles at the top and inside the gels were carefully pushed to 44

56 the ends of the gels to prevent impeding the visualization and migration of PCR products through the gel. After which the 16-well comb was inserted at the top of the gel. The gel was left to set for about 30 to 40 minutes depending on the gel size. 5ul of PCR product and 5ul of loading buffer were mixed, pipetted up and down 5 times and added to each gel well. 5ul of 1Kb Plus DNA Lambda ladder (made by RPH staff) was added to the first well. Gels were subjected to electrophoresis at 150 volts (V) for 45minutes. An extra 5 to 15minutes was sometimes required to ensure clear band separation. After electrophoresis, the gel was taken out of the tank and PCR bands were visualized using a Gel Doc TM (BIO-RAD). 2.4 Statistical Analysis All analyses were performed using the Statistical Package for Social Sciences (SPSS) Version 21. Survival analyses were performed on patients who only had haematological malignancies (n = 130), as leukaemia/lymphoma relapse is a major contributor to death in these patients but not in non-malignant cases. Analyses of acute graft versus host disease were performed on the entire cohort (n = 140) of donors Survival Analyses For survival, the univariate analyses were performed by Kaplan-Meier analysis. Kaplan-Meier analyses were also used to look for interactions between KIR and non- KIR variables by coding new variables based on the presence or absence of the KIR gene and non-kir variable. Variables showing significance at the p < 0.05 level were then included in a multivariate Cox-regression model. 45

57 2.4.2 Pearson Chi-Square Analysis of Acute Graft-versus-Host Disease (agvhd) Acute GvHD grades 0-IV were collapsed into variables with only two categories: I. Grades 0-I v II-IV II. Grades 0-II v III-IV Univariate analyses were then conducted using the chi-square test for contingency tables. Those interaction variables found to interact with KIR genes in the survival analysis were also tested for influence on agvhd using contingency tables Multivariate Cox Regression Analysis on Survival Cox regression is used to determine if newly identified variables remained significant after correcting for other variables known to influence survival. The interactions that were newly identified as significant (from the Kaplan-Meier analyses) were entered into the initial model. Through a process of elimination, only the most significant interactions will be retained in the final equation Chapter 3. Results 3.1 Multiplex PCR-SSP KIR Genotyping Assay Optimizations The KIR PCR-SSP genotyping assay was used to genotype all unrelated bone marrow transplant donors. The assay was designed and optimized to produce strong and distinct PCR bands for each of the 15 KIR genes. Group 1 included primers that amplified: KIR2DL3, KIR2DL1 and KIR3DL1. Group 2 included primers that amplified: KIR3DL3, KIR2DS3, KIR2DS5 and KIR3DS1. Group 3 included primers that amplified: KIR2DL5, KIR2DL2, KIR2DS1 and KIR2DL4. Lastly, Group 4 included primers that ampilfed: KIR2DS4d (deleted variant of KIR2DS4), KIR3DL2, KIR2DS2 and KIR2DS4. The PCR-SSP primer groupings were selected so that all PCR products in that one 46

58 group would have different sizes and would therefore produce a distinct band in an electrophoresis gel. The second consideration was that each group was to include an internal positive PCR control, thus the inclusion of primers for the framework genes (present in everyone): 3DL3 (in Group 2), 2DL4 (in Group 3), and 3DL2 (in Group 4) were each included in a group. The KIR gene 2DL1 present in all but one individual out of the entire cohort of donors genotyped (99.3%), was also considered as an internal PCR control in Group 1. The assay was validated on a 20-cell line panel from the 13 th International HLA and Immunogenetics Workshop (IHIWS). The KIR genotype of these cell lines had been established in international exchanges (De Santis et al, 2006). At the start of this honours project, none of the PCR conditions for the 4 PCR- SSP multiplex groups were optimized. However, the scientists in the Department of Clinical Immunology, Royal Perth Hospital, had demonstrated previously that all primers amplified the intended KIR gene Optimization of PCR-SSP Group 1 The first step of the optimization of Group 1 was to test which dntp concentration (10mM or 40mM) was optimal. For Group 1, 40mM dntp proved to be the ideal concentration because the 10mM dntp concentration had missing bands (Figure 2, top part of the picture). 47

59 Figure 6. shows the 10mM and 40mM dntp concentrations for selected cell lines with Group 1 primers. After determining the optimal dntp concentration, it was necessary to optimize the concentration of each primer, as the bands from the 40mM dtnp concentration were weak (refer to Figure 6). KIR2DL3 primer concentrations were adjusted from 5pmol/ul to 10pmol/ul, which resulted in a strong PCR band intensity. Fortunately, after this primer concentration increment, it was not necessary to alter Group 1 primers concentrations further as they already produced specific and intense PCR bands. For Group 1 primers, the optimal concentrations were: KIR2DL1 at 5pmol/ul, KIR2DL3 and KIR3DL1 at 10pmol/ul (Figure 7). 48

60 Figure 7. Shows the gels of the optimized PCR-SSP Group 1 primers on 20-cell line panel. (Refer to APPENDIX A, for genotypes of the validated cell line panel) Optimization of PCR-SSP Group 2 The first step in the optimization of Group 2 was to test which dntp concentration was optimal. For Group 2, 10mM dntp proved to be the ideal concentration, even though both dntp concentrations produced intense defined bands, 10mM dntp produced stronger band intensities. (Figure 8) Figure 8. Gel picture of the two different dntp concentrations from Group 2. 49

61 Fortunately, the initial Group 2 primer concentrations produced specific and intense bands. The optimized primer concentrations were: KIR2DS3 at 30pmol/ul, KIR3DL3 at 25pmol/ul, KIR2DS5 at 10pmol/ul and KIR3DS1 at 7.5pmol/ul (Figure 9). Figure 9. Optimized PCR-SSP Group 2 on the 20-cell line panel. (Refer to APPENDIX A, for genotypes of the validated 20-cell line panel) Optimization of PCR-SSP Group 3 The first step of the optimization of Group 3 was to test which dntp concentration was optimal. For Group 3, 40mM dntp proved to be the ideal concentration, as 10mM dntp produced many non-specific PCR bands (Figure 10). Figure 10. Gel picture of the PCR products produced using 10mM and 40mM dntp concentrations from Group 3. The initial optimization of Group 3, which included primers that amplified: KIR2DL4, KIR2DL2, KIR2DL5 and KIR2DS2 (Figure 11). 50

62 Figure 11. The initial Group 3 (before the swapping of KIR primers). However, as a result of resolving issues associated with the optimization of Group 4, where it was necessary to swap KIR2DS2 (from Group 3) with KIR2DS1 (from Group 4), a problem was encountered with the new Group 3. The new Group 3 now included primers for KIR2DL5, KIR2DL2, KIR2DL4 and KIR2DS1. The PCR products of KIR2DS1 and KIR2DL2 migrated to the same amplicon size in the electrophoresis gel, resulting in indistinguishable band separation in samples containing both KIR2DL2 and KIR2DS1 (Figure 12). The PCR product of KIR2DS1 migrated to a larger than expected size, at an approximate 165bp instead of its predicted amplicon size of 143bp. The theoretical expected product size of KIR2DL2 was 173bp. Figure 12. The first PCR run for new group 3 primers (after the swapping of KIR genes). The PCR products of this particular gel were run for 60minutes instead of the usual 40minutes in an attempt to better separate the PCR products. 51

63 To resolve this new problem, the 33bp M13F and M13R sequencing primer tags were removed from the KIR2DS1 primers in order to reduce the PCR product size. The initial results following the removal of KIR2DS1 sequencing primer tags were promising, in that the bands for KIR2DS1 and KIR2DL2 were now distinct (Figure 13). Figure 13. The first PCR run for the new group 3 after the removal of KIR2DS1 sequencing primer tags. As the intensity of the bands for KIR2DL5 and KIR2DL2 were much stronger than those for KIR2DS1 and KIR2DL4, the primer concentrations were readjusted. The KIR2DL2 primer concentrations were reduced from 20pmol/ul to 15pmol/ul and those of KIR2DL5 were decreased from 15pmol/ul to 10pmol/ul. This resulted in the final primer concentrations being: KIR2DL4 at 5pmol/ul, KIR2DL5 at 10pmol/ul, KIR2DL2 and KIR2DS1 at 15pmol/ul (Figure 14). 52

64 Figure 14. The optimized new group 3 primers on the validated panel. (Refer to APPENDIX A, for genotypes of the validated 20-cell line panel) Optimization of PCR-SSP Group 4 The first step of the optimization of group 4 was to test which dntp concentration was optimal. 40mM dntp was found to be the ideal concentration, because 10mM dntp produced non-specific bands (Figure 15). Figure 15. PCR products produced using 10mM and 40mM dntp concentrations for group 4 primers. The problem with the initial group 4 primers (before the primer swap between KIR2DS1 and KIR2DS2) was that we could not distinguish between KIR3DL2 and KIR2DS1 in the electrophoresis gels (Figure 15). This was because both KIR3DL2 and KIR2DS1 PCR products did not migrate as the expected amplicon size. KIR3DL2 migrated at 180bp while KIR2DS2 migrated at about 165bp. We tested the ability of capillary electrophoresis to distinguish the PCR products but the results were inconclusive. To resolved this issue, we resorted to the gene swap with Group 3, swapping KIR2DS1 (from Group 4) with KIR2DS2 (from Group 3). The results were great, KIR2DS4d (largest band, migrated at 198bp), KIR3DL2 (second largest band, 53

65 migrated at ~170bp), modified KIR2DS1 (third largest band, migrated at ~140bp) and KIR2DS4 (smallest band, migrated at 119bp). The preliminary tests with 8 selected cell lines (from the validated cell line panel) showed clear band separations and strong band intensities (Figure 16). Figure 16. The preliminary PCR run test on the new group 4 primers on selected cell lines from the validated panel. As the PCR products for KIR2DS4 were relatively weak in other PCR runs (not shown), the concentration of KIR2DS4 primers was increased from 5pmol/ul to 10pmol/ul. The optimal primer concentrations for group 4 primers were: KIR3DL2 at 5pmol/ul, KIR2DS4, KIR2DS4d and KIR2DS2 at 10pmol/ul (Figure 17). Figure 17. The optimized PCR-SSP Group 4 on selected cell lines. (Refer to APPENDIX A for genotypes of the validated 20-cell line panel) 54

66 3.2 KIR Genotyping of the 146 Donors PCR reactions were scored based on PCR band intensity as follows: 0= no band 1= weak band. 2=definite band 3=strong band 4=very strong band. All gels were read independently by two readers student and supervisor. For all genes except KIR2DS1, all samples had scores of 0 or > 2. For these genes it was clear that 0 represented the absence of the gene while scores of > 2 represented the presence of the gene. For KIR2DS1, 4 samples produced weak bands (score = 1). Repeating these samples at different DNA concentrations still resulted in weak bands. It was therefore decided that these 4 samples would not be called positive or negative for KIR2DS1. They would be left as indeterminate and omitted from any analyses of the effect of KIR2DS1 on transplant outcome. 3.3 Transplant Characteristics and Statistics This section of the results describes the transplant cohorts including characteristics of the donor cohorts, patient diagnoses, conditioning regimens, etc. 55

67 Number of Transplants Year of Bone Marrow Transplants Haematopoietic Stem Cell Transplants Transplant Year Figure 18. The frequency of haematopoietic stem cell transplants performed in each year. The haematopoietic stem cell transplant dates ranged from 1994 to 2012 (Figure 18) Transplant Centre and Number of Transplants Table 2 shows the number of transplants performed at the two different transplant centres that were analyzed in this study. The majority (90%) of the transplants were performed at Royal Perth Hospital. Transplant Centre Royal Perth Hospital (RPH) Princess Margret Hospital (PMH) Number of Transplants Percentage (%) Total: Table 2. Transplant numbers performed at the two transplant centres. 56

68 3.3.3 Transplant Source of Graft Table 3 shows the three different graft source analyzed in this study, however only the bone marrow and peripheral blood transplants were used in the donor KIR genotype and transplant variables interaction analysis. Source of Graft Frequency (n) Percentage (%) Cord Blood Bone Marrow Peripheral Blood Total: Table 3. Frequency of the different transplant graft source Donors Ages and Genders Table 4 shows the age range of the donors. The average age of the donors was 36. Total n = 140 Minimum Maximum Mean Age Table 4. Age range of the donors amongst the different transplants. Table 5 shows the distribution of gender ratios amongst the patient and donor cohorts. Gender of Patients Frequency Percentage (%) (n = 140) Male Female Total: Gender of Donors Frequency Percentage (%) (n = 140) Male Female Total: Table 5. Gender of patients and donors of the transplants analyzed in this study. 57

69 3.3.5 Patient Diagnosis Table 6 shows the frequency and percentage of patients with different diagnoses. The largest group was AML (31.1%), followed by ALL (17.6%) patients. In the survival analyses only malignant diagnoses (n = 130) were analyzed. Diagnosis Frequency (n) Percentage (%) ALL (Acute Lymphoid Leukaemia) AML (Acute Myeloid Leukaemia) BMF (Bone Marrow Failure) CLL (Chronic Lymphoid Leukaemia) CML (Chronic Myeloid Leukaemia) HD (Hodgkins Disease) IMD (Inherited Metabolic Disorder) MDS (Myelodysplastic Syndrome) MM (Multiple Myelomas) NHL (Non-Hodgkins Lymphoma) OTH (Other) RCC (Renal Cell Carcinoma) SAA (Severe Aplastic Anemia) Total: Table 6. Frequency of the different diagnoses in the entire cohort of patients. 58

70 3.3.6 Cytomegalovirus (CMV) Status Table 7 shows the patient, donor and overall transplant CMV status. The transplant (Tx) CMV status: Tx CMV Negative represents the transplants in which both donor and patient were CMV negative, while Tx CMV Positive represents transplants in which either donor, patient or both were CMV positive. Patient CMV Status Frequency Percentage (%) (n = 140) Negative Positive Not Available Donor CMV Status Frequency Percentage (%) (n = 140) Negative Positive Not Valid Total Transplants CMV Frequency Percentage (%) Status (n = 140) Tx CMV Negative (0) Tx CMV Positive (>1) Total Table 7. Frequency of patient, donor CMV status and Transplant CMV Status Conditioning Regimens Table 8 shows the distribution of conditioning regimens, the two major conditioning regimens were: busulphan/melphalan (21.4%) and cyclophosphamide/total body irradiation (24.3%). (For the conditioning regimens used in patients with different diagnoses refer to APPENDIX B.) 59

71 Conditioning Regimens Frequency (n) Percentage (%) AraC 1 /Camp 2 /Cy 3 /TBI 4 ATG 5 /Bu 6 /Cy ATG/Bu/Flu 7 /Mel 8 ATG/Cy/TBI BEAM Bu/Camp/Cy Bu/Camp/Mel Bu/Cy Bu/CY Bu/Flu Bu/Flu/Mel Bu/Mel Camp/Cy/TBI Cy/Camp Cy/Etop 9 /TBI Cy/Flu/Mel Cy/Flu/TBI Cy/TBI Cy/Thio 10 /TBI Flu/Ida/Mel Flu/Mel Mel/TBI Nil Total: Arabinoside, 2 Campath, 3 Cyclophosphamide, 4 Total Body Irradiation, 5 Anti-thymocyte Globulin, 6 Busulphan, 7 Fludarabine, 8 Melphalan, 9 Etoposide, 10 Thiotepa Table 8. Frequency of the different conditioning regimens used Acute Graft-versus-Host Disease (GvHD) Table 9 shows the frequency of the prevalence of different grades of agvhd in the study cohort. Type 0 represents patients that did not have agvhd, type I represented patients that had mild agvhd, type II represented patients that had mild to moderate 60

72 agvhd, type III represented patients that had moderate to severe agvhd and type IV represented patients that had severe to very severe agvhd. Type of GVHD Frequency (n) Percentage (%) 0 (No GvHD) I (Mild) II (Moderate) III (Severe) IV (Very Severe) Total: Table 9. Prevalence of different grades of agvhd KIR Gene Frequencies of the Entire Cohort Table 10 shows the frequency of the individual donor KIR genes. The KIR gene frequencies in this study were similar to the frequencies of the Western Australian population previously found in Witt et al (2004). KIR Gene Frequency (Total n = 140) 2DL DL2 71 2DL DL4 (framework gene) 140 2DL5 70 3DL DL2 (framework gene) 140 3DL3 (framework gene) 140 2DS1 61 2DS2 72 2DS3 36 2DS DS4d 113 2DS5 43 3DS1 57 A/A Haplotype 38 B/x Haplotype 100 N/A 2 Table 10. Frequency of the individual KIR genes. Percentage (%)

73 The top section of Table 11 shows the frequency of donors with differing numbers of activating KIR genes. The middle section of Table 11 shows the frequency of donors with differing numbers of inhibitory KIR genes. The bottom section of Table 11 shows the frequency of donor with differing total number of KIR genes. Number of Activating KIR Number of Donors Percentage (%) N/A Total: Number of Number of Percentage (%) Inhibitory KIR Donors N/A Total: Total Number of KIR Frequency (n) Percentage (%) N/A Total: Table 11. Frequency of donors with different numbers of activating, inhibitory and total number of KIR genes. 62

74 3.4 Analysis of Acute Graft-versus-Host Disease (agvhd) and KIR genes Acute graft-versus-host disease (agvhd) is a complication associated with bone marrow transplants wherein donor immune lymphocytes in the graft recognize the patient as foreign and attacks the patient s tissues. Analysis of the effect of KIR genotype on the prevalence of agvhd was performed using Pearson Chi-square analysis for contingency tables. agvhd was analysed as two variables. The variable GvHD2 was created by dividing all transplants into those with agvhd grade less than II and those with agvhd grade > II. The variable GVHD3 was created by dividing all transplants into those with agvhd grade less than III and those with agvhd >= III Effect of KIR Genotype on Prevalence of Acute GVHD Table 12 (second and third columns) shows the relationship between KIR genotype and prevalence of grade II and grade III agvhd without considering interaction variables. There were no significant associations between the prevalence of agvhd and the presence of individual KIR genes, the number of KIR genes or KIR-A or B haplotypes Effect of interactions between KIR Genotype and other Transplant Variables on the Prevalence of Acute GVHD The following variables from Table 12 require explanation: ATG/CAMP: transplants in which either anti-thymocyte globulin (ATG) or Campath (CAMP) was used (or not). ATG/CAMP- refers to transplants that did not use ATG or Campath, while ATG/CAMP+ refers to transplants that used either ATG or Campath. ATG and Campath have similar T cells eradicating effects. 63

75 Transplant Cytomegalovirus status (Tx CMV): Tx CMV- refers to the transplants in which both donor and patient are CMV negative while Tx CMV+ refers to the transplants in which either the donor or patient are CMV positive. Graft Source: Transplants were divided into those in which the stem cell source was peripheral blood or bone marrow. The 4 cord blood transplants were excluded from analyses of graft source. Total body irradiation (TBI): TBI- represented transplants in which TBI was not used while TBI+ represented transplants in which TBI was used. Cyclophosphamide (Cy): Cy- represents transplants in which cyclophosphamide was not used while Cy+ represents transplants in which cyclophosphamide was used. The majority of analyses did not show any significant interaction between KIR and other transplant variables that affected agvhd prevalence. A modest increase in the prevalence of grade III agvhd (p=0.018) was observed in ATG/Campath negative transplants with donors having KIR2DS1, which was not present in ATG/Campath positive transplants. This was also true for a higher number of KIR genes (p=0.034). However, the same trend was not apparent for grade II agvhd. 64

76 Pearson Chi-Square Analysis of Acute Graft-versus-Host Disease (agvhd) KIR (Column 1 and 2) Type 2 GvHD Type 3 GvHD Type 2 GvHD Type 3 GvHD Genes Type 2 GvHD Type 3 GvHD ATG/CA MP- ATG/CA MP+ ATG/CA MP- ATG/CA MP+ Tx CMV- Tx CMV+ Tx CMV- Tx CMV+ 2DL DL DS DS DS DS DS A/A vs. B/x HiKIR akir akir KIR Type 2 GvHD Type 3 GvHD Type 2 GvHD Type 3 GvHD Type 2 GvHD Type 3 GvHD Genes Peri. Bone Peri. Bone TBI - TBI + TBI - TBI + Cy - Cy + Cy - Cy + Blood Marrow Blood Marrow 2DL DL DS DS DS DS DS A/A vs. B/x HiKIR akir akir Table 12. P values for Pearson chi-square analysis of contingency tables relating KIR genotype, or KIR genotype in different transplant subgroups, to grade of acute GVHD. 65

77 1 A/A vs. B/x divides transplants into donors with homozygous A/A KIR haplotypes and donors with heterozygous B/x haplotypes. 2 HIKIR divides transplants into those with donors having >7 KIR genes and those having <= 6 KIR genes. 3 akir1 divides transplants into donors with at least 1 activating KIR and donors with >1 akir genes. 4 akir2 divides transplants into donors with at least 2 akir genes and donors with >2 akir genes. 66

78 3.5 Selection of KIR Genes for Survival Analysis All KIR genes except the framework genes were analyzed in the Kaplan-Meier analysis of the effect of individual KIR genes on survival. However, only KIR2DS1, KIR2DS2, KIR2DS3, KIR2DS5, KIR3DS1, KIR2DL2 and KIR2DL5 were selected for analysis of interactions between KIR and other transplant variables. The criterion for gene selection was that the gene had to have a population frequency between 25% and 75% so that there would be adequate numbers of transplants with and without the gene Univariate Kaplan-Meier Analysis of KIR genes on Survival 130 transplants were analyzed in this univariate Kaplan-Meier analysis. These 130 transplants only included patients with haematological malignancies so that the analysis would be based on a more clinically homogenous cohort. In some instances myelogenous (AML, CML, MDS) and acute lymphocytic leukaemia (ALL) subsets were also separately analyzed. Table 15 shows that none of the KIR genes was associated with significantly better or worse survival (on the entire malignant cohort, n=130). 67

79 KIR Genes P. Value (Kaplan-Meier) 2DL DL DL DL4 (Framework Gene) - 2DL DL DL2 (Framework Gene) - 3DL3 (Framework Gene) - 2DS DS DS DS DS DS Table 13. Kaplan-Meier p-values for the association of individual donor KIR genes on survival Univariate Kaplan-Meier Analysis of KIR Genes on Survival in patients with Myelogenous leukaemias. The literature includes several reports showing an effect of KIR genotype on survival but only in patients with myelogenous leukaemia and not in ALL patients. The analysis was therefore repeated in the myeloid and non-myeloid patient subsets. Table 14 shows that there were no significant effects of KIR genotype on survival in myelogenous and non-myelogenous subsets. 68

80 KIR Gene MYO 1 - MYO 2 + 2DL2 2DL5 3DL1 2DS1 2DS2 2DS3 2DS4 2DS5 3DS1 A/A vs. B/x 3 HIKIR 4 (>7 KIR) akir1 5 akir Acute/Chronic lymphoid Leukaemia cohort subset, 2 Mylogenous Leukaemia cohort subset, 3 KIR Haplotype A/A vs B/x, 4 High Number of KIR, 5 Subset of donors with at least 1 activating KIR gene, 6 Subset of donors with at least 2 activating KIR genes. Table 14. P. values of individual KIR genes on the survival rate of the myelogenous and non-mylogenous cohort. 69

81 3.6 Effect of Interactions between KIR Genes and other Transplant Variables on Survival Table 15 (below, refer to page 80) shows the p-values from the Kaplan-Meier analyses of KIR genotype in the presence or absence of other transplant variables. KIR2DS1, KIR2DS5, KIR3DS1 and KIR2DL5, interacted with stem cell source (particularly, with peripheral blood transplants), the strongest interaction being with KIR3DS1. The Kaplan-Meier survival curves (Figure 19) showed that the absence of KIR3DS1 was associated with better survival in PBSC transplants (p=0.008) but not in bone marrow transplants. The trend was the same for KIR2DS1, KIR2DS5 and KIR2DL5. That is, the absence of the gene conferred an advantage. This was also reflected in transplants in which donors having a high number of KIR genes, denoted by High KIR in Table 15 (p=0.023) and donors having at least two activating KIR genes denoted by akir2 in Table 15 (p=0.046). The Kaplan-Meier survival graphs of peripheral blood transplants for KIR2DS1 (p=0.028), KIR2DS5 (p=0.039), KIR2DL5 (p=0.032), donors having high KIR numbers ( High KIR variable in Table 15) (p=0.023) and donors having at least 2 activating KIR genes ( akir2 variable in Table 15) (p=0.046), are not shown but they showed the same trends as the interactions between KIR3DS1 and stem cell source (Figure 19). 70

82 Figure 19a. (Left) The presence of KIR3DS1 in peripheral blood transplant was associated with a poorer survival while there was no observable difference in bone marrow transplants, Figure 19b. (Right) There was no difference in the presence or absence of KIR3DS1 in bone marrow transplants. Table 15 shows that the same KIR genes that interacted with stem cell source also interacted with the CMV status of the transplant. In this case, the strongest interaction occurred with KIR2DS5 (p=0.001). In all cases, better survival was observed when the donor lacked KIR2DS5 in CMV negative transplants (KIR2DS5- /CMV-) (Figure 20a). This same effect was also reflected in interactions with KIR2DS1 (p=0.005, Figure 21a), KIR3DS1 (p=0.008, Figure 22a), KIR2DL5 (p=0.025, Figure 23a), donors having a high number of KIR genes denoted by High KIR in Table 14 (p=0.009, Figure 23a) and donors having at least 2 activating KIR genes denoted by akir2 in Table 15 (p=0.025). The Kaplan-Meier survival graphs for akir2 is not shown. However, KIR genotype had no significant effect in CMV positive transplants. 71

83 Figure 20a. (Left) Donors without KIR2DS5 in CMV negative transplants were associated with an improved survival while donors with KIR2DS5 results in a worse survival. Figure 20b. (Right) There was no difference in survival for CMV positive transplants, in the presence or absence of KIR2DS5. Figure 21a. (Left) KIR2DS1 was associated with a poorer survival in CMV negative transplants. Figure 21b. (Right) There was no difference in the presence or absence of KIR2DS1 in CMV positive transplants. 72

84 Figure 22a. (Left) KIR3DS1 in CMV negative transplants was associated with a poorer survival. Figure 22b. (Right) There was no difference in the presence or absence of KIR3DS1 in CMV positive transplants. Figure 23a. (Left) KIR2DL5 in CMV negative transplants was associated with a poorer survival. Figure 23b. (Right) There was no difference in the presence or absence of KIR2DL5 in CMV positive transplants. 73

85 Figure 24a. (Left) Donors with high number of KIR genes were associated with a poorer survival in CMV negative. Figure 24b. (Right) No significant difference in survival was observed in transplants with donor with a high number of KIR genes. Table 15 (refer to page 80) shows that KIR2DS2 (p=0.034) and KIR2DL2 (p=0.028) interacted with total body irradiation (TBI) to influence survival. The presence of these genes was associated with improved survival in TBI+ transplants (Figure 25b and 25d) and poorer survival in TBI- transplants (Figure 25a and 25c). These two genes are in very strong linkage disequilibrium with each other such that only one donor in this cohort was discordant for KIR2DL2 and KIR2DS2. 74

86 Figure 25a. (Top left) Donors with KIR2DS2 had poorer survival in TBI negative transplants. Figure 25b. (Top right) Donors with KIR2DS2 had better survival in TBI+ transplants. Figure 25c. (Bottom left) Donors with KIR2DL2 had poorer survival in TBI negative transplants. Figure 25d. (Bottom right) Donors with KIR2DL2 had better survival in TBI+ transplants. As TBI is invariably combined with cyclophosphamide in transplants for ALL, it was of interest to determine whether TBI might be acting as a surrogate marker for cyclophosphamide. Table 15 shows that KIR2DL2 (Cy- transplants p=0.032/ Cy+ transplants p=0.002) and KIR2DS2 (p=0.032/p=0.002) showed stronger interactions with the use of cyclophosphamide (Cy) than with TBI. As for TBI, in Cy+ transplants the survival was improved if the donor had KIR2DS2/2DL2 (Figure 26b and 26d) 75

87 while in Cy- transplants the survival was improved if the donor lacked KIR2DS2/2DL2 (Figure 26a and 26c). KIR3DS1 (p=0.049) only showed a just significant interaction on survival in Cy- transplants (Kaplan-Meier survival graph not shown). Figure 26a. (Top left) KIR2DS2 was associated with a poorer survival in cyclophosphamide negative transplants. Figure 26b. (Top right) KIR2DS2 was associated with an improved survival in cyclophosphamide positive transplants. Figure 26c. (Bottom left) KIR2DL2 was associated with a poorer survival in cyclophosphamide negative transplants. Figure 26d. (Bottom right) KIR2DL2 was associated with an improved survival in cyclophosphamide positive transplants. As TBI and cyclophosphamide are used almost invariably together when conditioning ALL patients, the possibility was considered that these two agents were simply 76

88 identifying ALL patients. Further analyses were therefore undertaken on ALL patients alone (n= 26) and myelogenous leukaemia patients (AML, CML, MDS) (n=89) to see if the interaction between KIR2DS2 and Cy was preserved in the different diagnoses. It was not possible to examine ALL patients who were not treated with Cy as there were very few of these. Figure 27 shows that as anticipated, the presence of KIR2DS2 resulted in an improved survival in ALL patients (p=0.08). Figure 28 shows that the interaction between KIR2DS2 and Cy was also preserved in patients with myeloid leukaemia. Although the p-values are not quite significant, there are clear trends that are similar to those seen in the entire cohort (Figure 26). These analyses supports the observations made in the interaction analysis of KIR2DS2/KIR2DL2 and Cy on the entire malignant cohort, in that the presence of KIR2DS2 in Cy positive transplants is beneficial and detrimental in Cy negative transplants. The interactions between KIR genes and Cy were preserved even in the different specific diagnoses cohorts (ALL only and Myelogenous (MYO) only cohort). Figure 27. KIR2DS2 was associated with an improved survival in cyclophosphamide positive transplants in the ALL cohort. 77

89 Figure 28a. (Left) Presence of KIR2DS2 in cyclophosphamide negative transplants was associated with worse survival in the MYO cohort. Figure 28b. (Right) KIR2DS2 was associated with an improved survival in cyclophosphamide positive transplants in the MYO cohort. KIR2DL2 (melphalan negative transplants p=0.020/ melphalan positive transplants p=0.064) and KIR2DS2 (p=0.024/p=0.064) also showed significant interactions with melphalan (Mel) (Table 15). Interestingly, the effect of KIR2DS2/2DL2 was the opposite of that seen with cyclophosphamide and TBI. That is, the presence of KIR2DS2/2DL2 resulted in poorer survival in Mel+ transplants (Figure 29b) and improved survival in Mel- transplants (Figure 29a). A similar phenomenon was observed in transplants that used fludarabine (Figure 30a and Figure 30b). The Kaplan-Meier survival graphs are not shown for KIR2DL2 (for both melphalan and fludarabine transplants) however, they showed the same trend as KIR2DS2. 78

90 Figure 29a. (Left) The absence of KIR2DS2 in melphalan negative transplant was associated with poorer survival. Figure 29b. (Right) The absence of KIR2DS2 in melphalan positive transplants was associated with better survival. Figure 30a. (Left) The absence of KIR2DS2 in fludarabine negative transplant was associated with poorer survival. Figure 30b. (Right) The absence of KIR2DS2 in fludarabine positive transplants was associated with better survival. No significant interactions were observed between KIR genotype and the use of busulphan in transplants (Table 15). 79