Killer-cell immunoglobulin-like receptor assessment algorithms in haemopoietic progenitor cell transplantation: current perspectives and future opportunities

Donor KIR2DL1 Allelic Polymorphism Influences Posthematopoietic Progenitor Cell Transplantation Outcomes in the T Cell Depleted and Reduced Intensity Conditioning Setting

The majority of established KIR clinical assessment algorithms used for donor selection for hematopoietic progenitor cell transplantation (HPCT) evaluate gene content (presence/absence) of the KIR gene complex. In comparison, relatively little is known about the impact of KIR allelic polymorphism. By analyzing donors of T cell depleted (TcD) reduced intensity conditioning (RIC) HPCT, this study investigated the influence on post-transplant outcome of 2 polymorphic residues of the inhibitory KIR2DL1. The aim of this study was to expand upon existing research into the influence of KIR2DL1 allelic polymorphism upon post-transplant outcome. The effects of allele groups upon transplant outcomes were investigated within a patient cohort using a defined treatment protocol of RIC with TcD. Using phylogenetic data, KIR2DL1 allelic polymorphism was categorized into groups on the basis of variation within codons 114 and 245 (positive or negative for the following groups: KIR2DL1*002/001g, KIR2DL1*003, KIR2DL1*004g) and the identification of null alleles. The influence of these KIR2DL1 allele groups in hematopoietic progenitor cell transplantation (HPCT) donors was assessed in the post-transplant data of 86 acute myelogenous leukemia patients receiving RIC TcD HPCT at a single center. KIR2DL1 allele groups in the donor significantly impacted upon 5-year post-transplant outcomes in RIC TcD HPCT. Donor KIR2DL1*003 presented the greatest influence upon post-transplant outcomes, with KIR2DL1*003 positive donors severely reducing 5-year post-transplant overall survival (OS) compared to those receiving a transplant from a KIR2DL1*003 negative donor (KIR2DL1*003 pos versus neg: 27.0% versus 60.0%, P = .008, pc = 0.024) and disease-free survival (DFS) (KIR2DL1*003 pos versus neg: 23.5% versus 60.0%, P = .004, pc = 0.012), and increasing 5-year relapse incidence (KIR2DL1*003 pos versus neg: 63.9% versus 27.2%, P = .009, pc = 0.027). KIR2DL1*003 homozygous and KIR2DL1*003 heterozygous grafts did not present significantly different post-transplant outcomes. Donors possessing the KIR2DL1*002/001 allele group were found to significantly improve post-transplant outcomes, with donors positive for the KIR2DL1*004 allele group presenting a trend towards improvement. KIR2DL1*002/001 allele group (KIR2DL1*002/001g) positive donors improved 5-year OS (KIR2DL1*002/001g pos versus neg: 56.4% versus 27.2%, P = .009, pc = 0.024) and DFS (KIR2DL1*002/001g pos versus neg: 53.8% versus 25.5%, P = .018, pc = 0.036). KIR2DL1*004 allele group (KIR2DL1*004g) positive donors trended towards improving 5-year OS (KIR2DL1*004g pos versus neg: 53.3% versus 35.5%, P = .097, pc = 0.097) and DFS (KIR2DL1*004g pos versus neg: 50.0% versus 33.9%, P = .121, pc = 0.121), and reducing relapse incidence (KIR2DL1*004g pos versus neg: 33.1% versus 54.0%, P = .079, pc = 0.152). The presented findings suggest donor selection algorithms for TcD RIC HPCT should consider avoiding KIR2DL1*003 positive donors, where possible, and contributes to the mounting evidence that KIR assessment in donor selection algorithms should reflect the conditioning regime protocol used.

KIR in Allogeneic Hematopoietic Stem Cell Transplantation: Need for a Unified Paradigm for Donor Selection

Allogeneic hematopoietic stem cell transplantation (aHSCT) is a lifesaving therapy for hematological malignancies. For years, a fully matched HLA donor was a requisite for the procedure. However, new immunosuppressive strategies have enabled the recruitment of viable alternative donors, particularly haploidentical donors. Over 95% of patients have at least two potential haploidentical donors available to them. To identify the best haploidentical donor, the assessment of new immunogenetic criteria could help. To this end, the clinical benefit of KIR genotyping in aHSCT has been widely studied but remains contentious. This review aims to evaluate the importance of KIR-driven NK cell alloreactivity in the context of aHSCT and explain potential reasons for the discrepancies in the literature. Here, through a non-systematic review, we highlight how the studies in this field and their respective predictive models or scoring strategies could be conceptually opposed, explaining why the role of NK cells remains unclear in aHCST outcomes. We evaluate the limitations of each published prediction model and describe how every scoring strategy to date only partly delivers the requirements for optimally effective NK cells in aHSCT. Finally, we propose approaches toward finding the optimal use of KIR genotyping in aHSCT for a unified criterion for donor selection.

High-resolution human KIR genotyping

Killer immunoglobulin-like receptors (KIR) regulate the function of natural killer cells through interactions with various ligands on the surface of cells, thereby determining whether natural killer (NK) cells are to be activated or inhibited from killing the cell being interrogated. The genes encoding these proteins display extensive variation through variable gene content, copy number and allele polymorphism. The combination of KIR genes and their ligands is implicated in various clinical settings including haematopoietic stem cell and solid organ transplant and infectious disease progression. The determination of KIR genes has been used as a factor in the selection of optimal stem cell donors with haplotype variations in recipient and donor giving differential clinical outcomes. Methods to determine KIR genes have primarily involved ascertaining the presence or absence of genes in an individual. With the more recent introduction of massively parallel clonal next-generation sequencing and single molecule very long read length third-generation sequencing, high-resolution determination of KIR alleles has become feasible. Determining the extent and functional impact of allele variation has the potential to lead to further optimisation of clinical outcomes as well as a deeper understanding of the functional properties of the receptors and their interactions with ligands. This review summarizes recently published high-resolution KIR genotyping methods and considers the various advantages and disadvantages of the approaches taken. In addition the application of allele level genotyping in the setting of transplantation and infectious disease control is discussed.

Practical Considerations and Workflow in Utilizing KIR Genotyping in Transplantation Medicine

This chapter is intended to serve as a practical guide for establishing a workflow using sequence-specific polymorphism PCR (SSP-PCR) for killer cell immunoglobulin-like receptor (KIR) genotyping in a clinical setting, especially in allogeneic hematopoietic stem cell transplantation (HSCT). As clinical evidence accumulates on the application of KIR and HLA genetics to guide donor selection in HSCT, there is an increasing need for KIR genotyping in clinical settings, and thus medical institutes may need to build this capability. Among the various KIR genotyping approaches now available, SSP-PCR methods are well-established and are the most cost-effective and will likely be the method of choice especially when expenses will be passed on to the patient. The protocol described in this chapter developed by Vilches et al. features small amplicon PCR and is suitable for KIR genotyping using FFPE-derived DNA as well as DNA extracted from blood samples. Setting up a laboratory workflow for in-house KIR genotyping is relatively straightforward; in this chapter, considerations for KIR genotyping to guide clinical decisions are discussed.In HSCT, a main objective of KIR genotyping is to apply the genetic analysis to predict donor and recipient combinations that have the most potential to produce NK cell alloresponses either through the missing-self mechanism or by action associated with activating KIR. The desired effects are reduction in acute GVHD and relapse rates and enhancement of overall survival. The information herein may also be useful to clinical laboratories considering the application of KIR genotyping in areas such as solid organ transplantation, NK cell-based treatment in other forms of cancer and autoimmune diseases, humanized antibody treatment, regenerative medicine, and reproductive medicine. Some background knowledge on KIR genetics will be necessary in managing a KIR genotyping platform. This chapter aims to address the main difficulties often encountered by physicians in understanding the KIR system, such as basic aspects of the nomenclature of KIR genes and haplotypes, genotypes, and determining presence/absence of KIR ligands in the patient and donor from the extensively diversified HLA class I allotypes. In describing the workflow, emphasis has been placed on the processes after genotype PCR and gel image acquisition: haplotype inference, generating B content scores, deduction of KIR ligands from HLA typing results, and the emerging algorithms for donor selection based on KIR and HLA genetics.

Accurate and Efficient KIR Gene and Haplotype Inference From Genome Sequencing Reads With Novel K-mer Signatures

The killer-cell immunoglobulin-like receptor (KIR) proteins evolve to fight viruses and mediate the body's reaction to pregnancy. These roles provide selection pressure for variation at both the structural/haplotype and base/allele levels. At the same time, the genes have evolved relatively recently by tandem duplication and therefore exhibit very high sequence similarity over thousands of bases. These variation-homology patterns make it impossible to interpret KIR haplotypes from abundant short-read genome sequencing data at population scale using existing methods. Here, we developed an efficient computational approach for in silico KIR probe interpretation (KPI) to accurately interpret individual's KIR genes and haplotype-pairs from KIR sequencing reads. We designed synthetic 25-base sequence probes by analyzing previously reported haplotype sequences, and we developed a bioinformatics pipeline to interpret the probes in the context of 16 KIR genes and 16 haplotype structures. We demonstrated its accuracy on a synthetic data set as well as a real whole genome sequences from 748 individuals from The Genome of the Netherlands (GoNL). The GoNL predictions were compared with predictions from SNP-based predictions. Our results show 100% accuracy rate for the synthetic tests and a 99.6% family-consistency rate in the GoNL tests. Agreement with the SNP-based calls on KIR genes ranges from 72%-100% with a mean of 92%; most differences occur in genes KIR2DS2, KIR2DL2, KIR2DS3, and KIR2DL5 where KPI predicts presence and the SNP-based interpretation predicts absence. Overall, the evidence suggests that KPI's accuracy is 97% or greater for both KIR gene and haplotype-pair predictions, and the presence/absence genotyping leads to ambiguous haplotype-pair predictions with 16 reference KIR haplotype structures. KPI is free, open, and easily executable as a Nextflow workflow supported by a Docker environment at https://github.com/droeatumn/kpi.