Know-how & Technologies

Know-how & Technologies


Our team has discovered the first genomic “donor” signature for predicting GVHD.

Predicting GVHD Using a Novel Molecular Signature:
We are developing a genetic test for predicting GVHD and encourage the more frequent use of AHCT.

Our work has shown, for the first time, that it is possible to predict the risk that a given donor will cause GVHD. Indeed, using gene expression profiling in a cohort of 50 matched-related (sibling) donors, we have identified a unique molecular signature allowing categorization of AHCT donors as “weak” or “strong” alloresponders (donor genetic make-up correlates with GVHD severity).

This proprietary signature predicts GVHD occurrence with overall accuracy ranging from 63% to 80%.

Using larger cohorts we are in the process of:

  1. Optimizing the predictive value of our proprietary molecular signature;
  2. Developing a prediction algorithm;
  3. Creating a final test format that is optimally suited for widespread use in the clinic.

Our ultimate goal is to develop a predictive test that will identify GVHD+ or GVHD- donors with an accuracy of at least 90%. This will dramatically change medical practice as we know it by:

  1. Decreasing the GVHD rate from 50-60%, to less than 10%;
  2. Broadening the use of AHCT to patients who would otherwise be ineligible because they cannot withstand the risk of GVHD.

Further Avenues:
Beyond predicting the risk of GVHD occurrence and timing (acute versus chronic), donor gene expression profiling will be used to determine whether gene expression might also predict GVHD severity and specific end-organ involvement.