TOX Regulates Growth, DNA Repair, and Genomic Instability in T-cell Acute Lymphoblastic Leukemia
Bibliographic record
Abstract
Abstract T-cell acute lymphoblastic leukemia (T-ALL) is an aggressive malignancy of thymocytes. Using a transgenic screen in zebrafish, thymocyte selection–associated high mobility group box protein (TOX) was uncovered as a collaborating oncogenic driver that accelerated T-ALL onset by expanding the initiating pool of transformed clones and elevating genomic instability. TOX is highly expressed in a majority of human T-ALL and is required for proliferation and continued xenograft growth in mice. Using a wide array of functional analyses, we uncovered that TOX binds directly to KU70/80 and suppresses recruitment of this complex to DNA breaks to inhibit nonhomologous end joining (NHEJ) repair. Impaired NHEJ is well known to cause genomic instability, including development of T-cell malignancies in KU70- and KU80-deficient mice. Collectively, our work has uncovered important roles for TOX in regulating NHEJ by elevating genomic instability during leukemia initiation and sustaining leukemic cell proliferation following transformation. Significance: TOX is an HMG box–containing protein that has important roles in T-ALL initiation and maintenance. TOX inhibits the recruitment of KU70/KU80 to DNA breaks, thereby inhibiting NHEJ repair. Thus, TOX is likely a dominant oncogenic driver in a large fraction of human T-ALL and enhances genomic instability. Cancer Discov; 7(11); 1336–53. ©2017 AACR. This article is highlighted in the In This Issue feature, p. 1201
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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) | 0.000 | 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) | 0.000 | 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".