Functional GSTA1 Haplotypes Affect Clearance and Toxicity of Busulfan When Administered in 16 Doses to Pediatric Patients Undergoing Hematopoietic Stem Cell Transplantation: A Multicenter Prospective Study on Behalf of the Pediatric Disease Working Party of the European Society for Blood and Marrow Transplantation (EBMT)
Bibliographic record
Abstract
Abstract Busulfan (BU) dose adjustment following therapeutic drug monitoring (TDM) contributes to better outcome of hematopoietic stem cell transplantation (HSCT). The therapeutic target window can be reached in approximately 51% to 74% of pediatric cases and 45% to 64% of infants depending on the dosing guideline used. We hypothesize that a higher proportion of pediatric patients could achieve the target BU area-under-the-curve (AUC) of 900-1500 µM.min per dose in a four times dosing schedule through genotype-guided initial BU dosing. Previous investigations by our group and others showed association of glutathione -S- transferase alpha 1 (GSTA1) with reduced BU clearance (CL), likely due to altered expression of GSTA1 enzyme, principally involved in BU metabolism. To delineate and investigate the association of each GSTA1 haplotype with the CL of BU, promoter haplotypes of GSTA1 gene were assessed in vitro with reporter gene-assay and clinically in a pediatric multi-center study (N =138) through association with BU CL, AUC, dose change and clinical outcomes. All patients received BU based myeloablative conditioning regimen. BU PK parameters from 1st dose were estimated and further doses were adjusted to have a steady state concentrations of 600-900 ng/mL and GSTA1promoter SNPs at -69, -513, -631, -1142 positions were genotyped using allele specific oligo hybridization method. Reporter-gene assays confirmed significant differences between the haplotype subgroups and supported their importance in capturing PK variability. Four GSTA1 diplotype groups (I-IV) that significantly correlated with CL (p=0.009) were distinguished. GSTA1 diplotypes (group I) underlying fast metabolizing capacity (*A2*A2&*A2*A3) had lower cumulative AUC and a higher dose increase after TDM whereas those with slow metabolizing capacity (group IV, *B1a*B1a /*B1a*B1b /*B2*B1a / *A1*B1b)had highest AUC and least dose change (p=0.02). Multivariate linear model included GSTA1 diplotype groups and non-genetic factors such as age, gender, first BU dose in mg/kg and patients origin. Dose (p<0.0005), gender (p=0.05) and GSTA1 diplotypes (p=0.01) were retained in the final model that explained 34% of overall variability. Analysis with clinical outcomes indicated higher incidences of sinusoidal obstruction syndrome in Group IV diplotype carriers (HR=7.1; 95% CI: 2.5-20.4) compared to patients with other GSTA1diplotypes. A similar association was also seen with acute graft versus host disease (aGvHD grade I-4) and combined treatment-related toxicity (TRT) (p≤0.003). In conclusion, this study has replicated and provided additional evidence for the association of GSTA1 with BU PK and clinical outcomes of HSCT. GSTA1 diplotypes can explain in some models ~20% of the variability seen in BU CL and can contribute to HSCT-related complications acting within and beyond BU metabolism. Genotyping therefore may be helpful in deciding the first BU dose, thus decreasing consequences like TRT due to inaccurate first and subsequent dosing. This may be particularly important for GSTA1 diplotype Group IV carriers. Disclosures Bittencourt: Jazz Pharmaceuticals: Consultancy, Other: Educational Grant; Seattle Genetics: Consultancy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".