T‐cell differentiation stage block bias confers hypermethylation and mediastinal preference in T‐cell lymphoblastic lymphoma
Bibliographic record
Abstract
BACKGROUND: The clinical guideline classifies T-LBL and T-ALL jointly, differentiating them merely by the bone marrow blast cell proportion. However, their distinct clinical manifestations, genetic profiles, and specific pathogenic requirements have prompted us to reevaluate the differences between them. METHODS AND RESULTS: We established the NCH-TALL-LBL cohort, which includes flow cytometry data and somatic mutation data from our center. Additionally, we collected T-LBL samples and implemented single-cell RNA sequencing and single-cell T-cell receptor sequencing. Combining the single-cell RNA sequencing data of T-ALL, expression array data, flow cytometry data, we discovered that malignant T cells in T-LBL are predominantly in the DN- and DP-stage blocking modes (DP cells dominate). This block mode in T-LBL generates signals that drive the development of an immunosuppressive microenvironment and the mediastinum preference. Additionally, E2F2, an active transcription factor in the DP and DN stages, upregulates the expression of UHRF1, resulting in hypermethylation of tumor suppressor genes. Findings from in vivo and in vitro research clearly show that demethylation therapy targeting this mechanism effectively inhibits tumor proliferation in T-LBL. CONCLUSION: From the perspective of differentiation blockage, T-LBL and T-ALL represent different stages of the same disease, and the stage block bias of T-cell contributes to their heterogeneity. KEY POINTS: Malignant T cells in T-LBL are primarily blocked in the DN and DP stages, which contributes to the immunosuppressive TME and mediastinum preference of T-LBL. The active transcription factor E2F2 in the DP and DN stages upregulates UHRF1 expression, leading to the hypermethylation of tumor suppressor genes in T-LBL. Demethylation therapy targeting the hypermethylation of tumor suppressor genes mediated by UHRF1 effectively inhibits tumor proliferation in T-LBL.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".