The significance of <i>TP53</i> in lymphoid malignancies: mutation prevalence, regulation, prognostic impact and potential as a therapeutic target
Bibliographic record
Abstract
The tumour suppressor TP53 (previously termed p53) mediates a pathway that is considered to be one of the most important mechanisms in the maintenance of genomic stability. The function of TP53 can be abrogated by genomic deletion, mutation, or deregulation of upstream and downstream participants in the TP53 pathway. While aberrations of TP53 are widely prevalent in non-haematological malignancies (over 60%), they are present in much lower frequency in haematological malignancies (<20%). Nevertheless, in those cases where TP53 function or expression is aberrant, correlation with inferior clinical outcome (such as overall survival and progression or transformation) has generally been strong. In this review, we focus our discussion on the relationship between TP53 and lymphoid malignancies as defined by the World Health Organization. Specifically, we examine the prevalence of TP53 aberrations and their prognostic significance in various types of lymphoid cancer. Next, we discuss the various mechanisms of TP53 inactivation. Finally, we summarize progress in the use of recent therapeutic modalities that target TP53.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".