KIR-STAN: KIR Sequencing and Typing for Allograft in Nancy
Study Details
Study Description
Brief Summary
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.
| Condition or Disease | Intervention/Treatment | Phase |
|---|---|---|
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Study Design
Arms and Interventions
| Arm | Intervention/Treatment |
|---|---|
| Donor/recipient couple with Matched Sibling Donor Donor/recipient couple = Patient undergoing a hematopoietic stem cell transplantation + its 10/10 HLA-matched donor recruited among his siblings |
Genetic: MHC typing
Allelic genotyping resolution of MHC genes (HLA-A, -B, -C, -DRB1, -DQA1, -DQB1, -DPA1, -DPB1 and -DRB3/4/5) using Illumina technology.
Genetic: KIR typing
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.
Genetic: Assessment of KIR-based prediction scores
Compiling donor/recipient MHC and KIR typings into 28 major KIR-based prediction scores
|
| Donor/recipient couple with Haploidentical Donor Donor/recipient couple = Patient undergoing a hematopoietic stem cell transplantation + its 5/10 HLA-matched donor recruited among his relatives |
Genetic: MHC typing
Allelic genotyping resolution of MHC genes (HLA-A, -B, -C, -DRB1, -DQA1, -DQB1, -DPA1, -DPB1 and -DRB3/4/5) using Illumina technology.
Genetic: KIR typing
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.
Genetic: Assessment of KIR-based prediction scores
Compiling donor/recipient MHC and KIR typings into 28 major KIR-based prediction scores
|
Outcome Measures
Primary Outcome Measures
- 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]
Eligibility Criteria
Criteria
COHORT 1 = Matched Sibling Donors couples (MSD couples) INCLUSION CRITERIA
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recipient of HSCT selected from the French national database CRYOSTEM
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adult patients (18-50 years old)
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transplanted in first remission
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receiving myeloablative conditioning without anti-thymoglobulin
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16 couples without any sign of GVH (8 males and 8 females)
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16 couples with aGVH without cGVH
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9 couples with cGVH without aGVH
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9 couples with both cGVH and aGVH. EXCLUSION CRITERIA
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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)
Contacts and Locations
Locations
No locations specified.Sponsors and Collaborators
- Central Hospital, Nancy, France
- University of Cambridge
Investigators
None specified.Study Documents (Full-Text)
None provided.More Information
Publications
None provided.- 2020PI142