Rheology biomarkers for gene-based therapy

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Allogeneic hematopoietic stem cell transplant (alloHSCT) can provide a cure for sickle cell disease (SCD), but is typically available only to the 10-15% of patients who have a matched related donor. Fortunately, there are viable gene therapy (lentivirus based) and gene editing (CRISPR/Cas9 based) approaches available in limited clinical trials. However, questions remain regarding the level of sickle Hb (HbS) correction or fetal hemoglobin (HbF) induction and degree of engraftment of gene modified stem cells needed to achieve a cure. Despite years of experience with pharmacologic HbF induction with hydroxyurea (HU), and epidemiological studies of baseline HbF levels and symptom correlation, it is not known what level of HbF is needed for significant amelioration of SCD complications, or what %HbS can be tolerated when unequally distributed throughout the red blood cells (RBCs). It is essential that we functionally evaluate patients who have undergone gene-based therapy, rather than rely solely on Hb profiles to assess response. The quality, or rheology, of SCD blood is markedly abnormal, and these abnormalities correlate strongly with disease complications. The goal of any gene-based SCD cure should be to normalize blood rheology of each patient to at least the level of an individual with sickle cell trait (SCT). Non-curative therapies like HU and transfusion relieve symptoms and improve rheology in patients with SCD, although not to the SCT values. We propose to validate rheological biomarkers first in patients with SCD, testing the ability of biomarkers to differentiate HbAA, HbAS, and HbSS samples. Next, we will assess the biomarker performance in SCD patients who have undergone alloHSCT, asking if our biomarkers predict an asymptomatic outcome consistent with a cure. Finally, we will apply these validated biomarkers to patients treated with gene-based therapy. Strategies which do not achieve rheological correction comparable to HbAS or successful alloHSCT may need further optimization.