GSTM1 and GSTT1 double null genotypes determining cell fate and proliferation as potential risk factors of relapse in children with hematological malignancies after hematopoietic stem cell transplantation
Bibliographic record
Abstract
PURPOSE: This study aimed to retrospectively evaluate the genetic association of null variants of glutathione S-transferases GSTM1 and GSTT1 with relapse incidence in children with hematological malignancies (HMs) undergoing busulfan (BU)- containing allogeneic hematopoietic stem cell transplantation (HSCT) and to assess the impact of these variants on BU-induced cytotoxicity on the immortalized lymphoblastoid cell lines (LCLs) and tumor THP1 GST gene-edited cell models. METHODS: GSTM1- and GSTT1-null alleles were genotyped using germline DNA from whole blood prior to a conditioning BU-based regimen. Association of GSTM1- and GSTT1-null variants with relapse incidence was analyzed using multivariable competing risk analysis. BU-induced cell death studies were conducted in GSTs- null and non-null LCLs and CRISPR-Cas9 gene-edited THP1 leukemia cell lines. RESULTS: as shown by decreased viability, increased necrosis and levels of the oxidized form of glutathione compared to null cells, while GSTT1 non-null cells showed increased baseline proliferation. CONCLUSION: The clinical association suggests that GSTM1/GSTT1 double null genotype could serve as genetic stratification biomarker for the high risk of post-HSCT relapse. Functional studies have indicated that GSTM1 status modulates BU-induced cell death. On the other hand, GSTT1 is proposed to be involved in baseline cell proliferation.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".