Ultrasensitive Chimerism Enhances Measurable Residual Disease Testing Post-Allogeneic Hematopoietic Cell Transplantation.
Sami B KanaanFrancesca UrselliJerald P RadichJ Lee NelsonPublished in: Blood advances (2023)
Increasing mixed chimerism (reemerging recipient cells) after allogeneic hematopoietic cell transplantation (allo-HCT) can indicate relapse, the leading factor determining mortality in blood malignancies. Most clinical chimerism tests have limited sensitivity and are primarily designed to monitor engraftment. We developed a panel of qPCR assays using TaqMan chemistry capable of quantifying chimerism on the order of 1-in-a-million. At such analytic sensitivity, we hypothesized it could inform on relapse risk. As a proof-of-concept, we applied our panel on a retrospective cohort of acute leukemia patients with known outcomes post-allo-HCT. Recipient cells in bone marrow aspirates (BMA) remained detectable in 97.8% of tested samples. Absolute recipient chimerism proportions and rates at which these proportions increased in BMA in the first 540 days post-allo-HCT were associated with relapse. Detectable MRD (measurable residual disease) by flow cytometry in BMA post-allo-HCT showed limited correlation with relapse. This correlation noticeably strengthened when combined with increased recipient chimerism in BMA, demonstrating the ability of our ultrasensitive chimerism assay to augment MRD data. Our technology reveals an underappreciated usefulness of clinical chimerism. Used side-by-side with MRD assays, it promises to improve identification of patients with the highest risk of disease reoccurrence for a chance for early intervention.
Keyphrases
- allogeneic hematopoietic stem cell transplantation
- cell cycle arrest
- bone marrow
- induced apoptosis
- acute myeloid leukemia
- cell death
- flow cytometry
- acute lymphoblastic leukemia
- stem cell transplantation
- high throughput
- randomized controlled trial
- free survival
- pi k akt
- gold nanoparticles
- low dose
- cardiovascular disease
- electronic health record
- risk factors
- coronary artery disease
- adipose tissue
- high dose
- cardiovascular events
- machine learning
- deep learning
- skeletal muscle
- cord blood
- label free