KIR Sequencing and Typing for Allograft in Nancy

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.

Conditions

• Stem Cell Transplant Complications

Interventions

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

Sponsors & Collaborators

• University of Cambridge

  collaborator OTHER

• Central Hospital, Nancy, France

  lead OTHER

Eligibility

Sex

ALL

Healthy Volunteers

No

Timeline & Regulatory

Start

2015-03-23

Primary Completion

2019-07-25

Completion

2019-07-25