KIR Sequencing and Typing for Allograft in Nancy

Study Overview
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Brief Summary
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The use of haploidentical donors for aHSCT has greatly increased this past decade leading to a major paradigm shift: while finding 10/10 HLA-matched donors represented the prior difficulty for decades, the current problem is about finding the best haploidentical donor among several potential ones. The prediction of NK cells alloreactivity toward leukemic cells provides promising perspectives, although the underlying biological processes remain unclear. To date, many prediction models based on KIR and MHC genotyping have been designed and used across studies, which contribute to blur clinical conclusions. The investigators hypothesized that the diversity of models used to predict NK alloreactivity in aHSCT could partly be responsible for the current literature discrepancies. The main objective of this work consisted of applying the major KIR-based prediction models in D/R couples undergoing aHSCT in different fashions - with MSD and haploidentical donors - to describe their heterogeneity and potential correlations. As clinical data were available for these two cohorts, the investigators described correlations that could be assessed between the scoring strategies and the clinical outcomes. As suspected, it was highlighted that the different scoring strategies greatly impact the assessment of alloreactivity within D/R couples. As an example, two broadly used scoring strategies - educational models and missing-ligand models - show clear opposite predictions. Moreover, some scoring strategies seem to be better adapted to genoidentical or haploidentical cohorts, whereas others are robust across the different cohorts. Concerning the clinical-biological correlations, it was highlighted that (i) each scoring strategy is differentially associated to the different outcomes (ii) the different scoring strategies predict one particular outcome with different efficacy (iii) the D/R compatibility greatly impacts the pertinence of the scoring strategy. This work therefore contributes to unravel the KIR-based alloreactivity prediction of NK cells in aHSCT. This would help to overcome the current literature discrepancies in this field as in making new hypotheses to better understand and predict NK alloreactivity to further develop its use in medical practice.

Official Title
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Application of the Major Predictive Scoring Strategies Assessing KIR-based NK Alloreactivity to Donor/Recipient Couples

Conditions
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Stem Cell Transplant Complications

Intervention / Treatment
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* Genetic: MHC typing
* Genetic: KIR typing
* Genetic: Assessment of KIR-based prediction scores


Participation Criteria
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Eligibility Criteria
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COHORT 1 = Matched Sibling Donors couples (MSD couples) INCLUSION CRITERIA recipient of HSCT selected from the French national database CRYOSTEM adult patients (18-50 years old) transplanted in first remission receiving myeloablative conditioning without anti-thymoglobulin 16 couples without any sign of GVH (8 males and 8 females) 16 couples with aGVH without cGVH 9 couples with cGVH without aGVH 9 couples with both cGVH and aGVH. EXCLUSION CRITERIA insufficient DNA material after Miltenyi extraction COHORT 2 = Haploidentical couples INCLUSION CRITERIA patient undergoing a haploidentical HSCT in the Hematology Department of Nancy's University Hospital, Lorraine, France (French Minister registration number : DC-2020-4068) EXCLUSION CRITERIA insufficient DNA material after Miltenyi extraction (7 MSD couples)
Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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No

Study Plan
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How is the study designed?
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Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| Donor/recipient couple with Matched Sibling Donor<br>Donor/recipient couple = Patient undergoing a hematopoietic stem cell transplantation + its 10/10 HLA-matched donor recruited among his siblings | Genetic: MHC typing<br>* Allelic genotyping resolution of MHC genes (HLA-A, -B, -C, -DRB1, -DQA1, -DQB1, -DPA1, -DPB1 and -DRB3/4/5) using Illumina technology.<br>Genetic: KIR typing<br>* Allelic genotyping resolution of all 13 KIR genes (KIR2DL1, KIR2DL2/2DL3, KIR2DL4, KIR2DL5A, KIR2DL5B, KIR2DS1, KIR2DS2, KIR2DS3, KIR2DS3/2DS5, KIR2DS4, KIR3DL1/3DS1, KIR3DL2, KIR3DL3), 2 KIR pseudogenes (KIR2DP1 and -3DP1) using Illumina technology.<br>Genetic: Assessment of KIR-based prediction scores<br>* Compiling donor/recipient MHC and KIR typings into 28 major KIR-based prediction scores<br>|
| Donor/recipient couple with Haploidentical Donor<br>Donor/recipient couple = Patient undergoing a hematopoietic stem cell transplantation + its 5/10 HLA-matched donor recruited among his relatives | Genetic: MHC typing<br>* Allelic genotyping resolution of MHC genes (HLA-A, -B, -C, -DRB1, -DQA1, -DQB1, -DPA1, -DPB1 and -DRB3/4/5) using Illumina technology.<br>Genetic: KIR typing<br>* Allelic genotyping resolution of all 13 KIR genes (KIR2DL1, KIR2DL2/2DL3, KIR2DL4, KIR2DL5A, KIR2DL5B, KIR2DS1, KIR2DS2, KIR2DS3, KIR2DS3/2DS5, KIR2DS4, KIR3DL1/3DS1, KIR3DL2, KIR3DL3), 2 KIR pseudogenes (KIR2DP1 and -3DP1) using Illumina technology.<br>Genetic: Assessment of KIR-based prediction scores<br>* Compiling donor/recipient MHC and KIR typings into 28 major KIR-based prediction scores<br>|

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Describe the heterogeneity of the major KIR-based prediction models in assessing alloreactivity |  | At inclusion | 
| Describe the potential correlations between a KIR-based prediction models and post-allograft outcomes |  | at least 4 months | 

 Terms related to the study
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Keywords Provided by Centre Hospitalier Valida
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Hematopoietic Stem Cell Transplantation, acute Graft versus Host Disease, chronic Graft versus Host Disease, Killer Immunoglobulin-like Receptors, NK-mediated alloreactivity