EZH2 inactivation cooperates with HOXA9 to induce leukemic transformation of human t-cell progenitors and sustain high-risk subsets of early t-cell precursor acute lymphoblastic leukemia (ETP-ALL)
Bibliographic record
Abstract
Abstract Early T-cell precursor (ETP) acute lymphoblastic leukemia/lymphoma (ALL) is an aggressive hematological malignancy characterized by the uncontrolled expansion of T-cell progenitors. Loss-of-function mutations in genes encoding epigenetic regulators, including core components of the Polycomb Repressive Complex 2 (PRC2), such as the EZH2 histone methyltransferase, are frequently observed in ETP-ALL patients.To investigate the role of EZH2 inactivation in human early T-cell leukemogenesis, we optimized a CRISPR/Cas9-based strategy to disrupt EZH2 gene expression by integrating a DNA cassette containing the constitutive human PGK-1 promoter followed by the GFP reporter. Specifically, human CD34⁺ hematopoietic stem/progenitor cells (HSPCs) derived from cord blood were first edited to knock out (KO) EZH2, then transduced with lentiviruses encoding different T-ALL oncogenes or an empty vector control, and maintained in serum-free medium supplemented to support T-cell progenitor expansion. We found that only HOXA9- and LYL1-transduced EZH2KO HSPCs expanded in vitro for up to 30 days, and were enriched for early T-cell subsets, as identified by single-cell RNA sequencing (scRNA-seq) and a 26-color flow cytometry assay. Notably, these same subsets were capable of initiating T-cell leukemia in immunocompromised (NSG) mice following transplantation, suggesting that EZH2 inactivation cooperates with HOXA9 or LYL1 overexpression to drive human T-cell transformation. To assess the relevance of these findings in primary human T-ALLs, we analyzed whether loss-of-function mutations in PRC2 genes (EZH2, EED, SUZ12) were enriched in specific T-ALL subgroups, particularly ETP-ALL, in a cohort of 1,335 patients from the Children's Oncology Group (COG) study. Interestingly, PRC2-mutated T-ALLs were significantly associated with the HOXA subgroup and the ETP-ALL phenotype, and exhibited higher levels of minimal residual disease (MRD) 30 days after therapy compared to other T-ALL cases. To further dissect the molecular effects of EZH2 loss and HOXA9 overexpression in ETP-like T-ALL, we knocked out EZH2 in the human Loucy and PEER cell lines using CRISPR/Cas9. These EZH2KOcells were then transduced with HOXA9-encoding lentiviruses or empty vectors and analyzed by RNA sequencing. In parallel, ChIP-seq analyses were performed to map HOXA9 binding sites and assess histone modifications affected by EZH2 loss. Integrated analysis of RNA-seq and ChIP-seq data revealed that HOXA9 expression in EZH2-deficient ETP-like cells led to the upregulation of a stem-like/immature T-cell gene signature enriched in transcriptional activators and chromatin remodelers (e.g., RUNX2, IRX3, SATB1, ARID5B, CHD1, INO80D).Furthermore, scRNA-seq profiling of primary PRC2-mutated T-ALL samples revealed distinct leukemic subsets with high HOXA9 expression and strong enrichment for the same gene signature, as determined by Gene Set Variation Analysis (GSVA). Importantly, this signature stratified PRC2-mutated T-ALLs and identified a HOXA positive subgroup associated with poor prognosis. Collectively, these findings uncover a critical epigenetic circuit involving EZH2 loss and HOXA9-driven transcriptional reprogramming that promotes stem-like, therapy-resistant T-ALL subsets and highlights novel vulnerabilities that could be therapeutically exploited to eliminate high-risk disease at its origin.
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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".