Premature thymic functional senescence is a hallmark of childhood acute lymphoblastic leukemia survivorship
Bibliographic record
Abstract
Childhood acute lymphoblastic leukemia (cALL) survivors suffer early-onset chronic diseases classically associated with aging. Normal aging is accompanied by organ dysfunctions, including immunological ones. We hypothesize that thymic immunosenescence occurs in cALL survivors and that its severity may correlate with early-onset chronic diseases. The PETALE study is a cALL survivor cohort with an extensive cardiovascular and metabolic evaluation. The thymic immunosenescence biomarker, signal joint T-cell receptor excision circles (TREC), was evaluated and was highly correlated with age in healthy participants (n = 281) and cALL survivors (n = 248). We observed a systematic thymic immunoage accentuation in each cALL survivor compared to controls ranging from 5.9 to 88.3 years. The immunoage gain was independent of age at diagnosis and treatment modalities and was more severe for females. Thymic aging was associated with several pathophysiological parameters, was greater in survivors suffering from metabolic syndrome, but there was no significant association with global physical condition. The decrease in TREC was independent from blood cell counts, which were normal, suggesting a segmental aging of the thymic compartment. Indeed, increased plasmatic T cell regulatory cytokines IL-6, IL-7 and GM-CSF accompanied high immunoage gain. Our data reveal that cALL or its treatment trigger a rapid immunoage gain followed by further gradual thymic immunosenescence, similar to normal aging. This leads to an enduring shift in accentuated immunoage compared to chronological age. Thus, accentuated thymic immunosenescence is a hallmark of cALL survivorship and TREC levels could be useful immunosenescence biomarkers to help monitoring the health of cancer survivors.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".