Hypermethylation of ITGBL1 is associated with poor prognosis in acute myeloid leukemia
Bibliographic record
Abstract
The current study was aimed to investigate integrin beta-like 1 (ITGBL1) methylation pattern and its clinical relevance in patients with acute myeloid leukemia (AML). Real-time methylation-specific polymerase chain reaction (PCR; RQ-MSP) and bisulfite sequencing PCR (BSP) were performed to detect the methylation of ITGBL1 promoter. Real-time quantitative PCR (RT-qPCR) was performed to analyze ITGBL1 transcript level. The results showed that ITGBL1 methylation level in 131 patients with AML was significantly higher than 29 controls (p < 0.001). The ITGBL1-hypermethylated group tended to have a higher bone marrow (BM) blasts ( p = 0.076). Meanwhile, ITGBL1-hypermethylated patients tended to have a lower complete remission (CR) rate ( p = 0.102). ITGBL1-hypermethylated patients had significantly shorter overall survival (OS) and leukemia-free survival (LFS) than ITGBL1 hypomethylated patients in whole AML cohort ( p = 0.009 and 0.043, respectively) and patients with nonacute promyelocytic leukemia (APL ; p = 0.023 and 0.039, respectively). Multivariate analysis confirmed that the ITGBL1 methylation served as an independent prognostic factor in both patients with whole-cohort AML ( p = 0.030) and patients with non-APL ( p = 0.020). Furthermore, the ITGBL1 methylation level was significantly decreased in follow-up AML patients who achieved complete remission after induction therapy ( P = 0.001). ITGBL1 methylation negatively correlated with ITGBL1 expression in patients with AML ( R = -0.328, p = 0.008). Moreover, demethylation of ITGBL1 could increase the ITGBL1 expression in the K562 leukemic cell line ( p < 0.05). In conclusion, the ITGBL1 hypermethylation is a potential biomarker for predicting prognosis and monitoring disease status in patients with AML.
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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 | 0.000 |
| 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 | 0.000 |
| 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".