Proof of principle: quality control of therapeutic cell preparations using senescence-associated DNA-methylation changes
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Tracking of replicative senescence is of fundamental relevance in cellular therapy. Cell preparations - such as mesenchymal stromal cells (MSCs) - undergo continuous changes during culture expansion, which is reflected by impaired proliferation and loss of differentiation potential. This process is associated with epigenetic modifications: during in vitro culture, cells acquire senescence-associated DNA methylation (SA-DNAm) changes at specific sites in the genome. We have recently described an Epigenetic-Senescence-Signature that facilitates prediction of the state of cellular aging by analysis of DNAm at six CpG sites (associated with the genes GRM7, CASR, PRAMEF2, SELP, CASP14 and KRTAP13-3), but this has not yet been proven over subsequent passages and with MSCs isolated under good manufacturing practice (GMP) conditions. FINDINGS: MSCs were isolated from human bone marrow and GMP-conform expanded for up to 11 passages. Cumulative population doublings (cPDs) and long-term growth curves were calculated based on cell numbers at each passage. Furthermore, 32 cryopreserved aliquots of these cell preparations were retrospectively analyzed using our Epigenetic-Senescence-Signature: DNAm-level was analyzed at six specific CpGs, and the results were used to estimate cPDs, time of culture expansion, and passage numbers. Overall, predicted and real parameters revealed a good correlation, particularly in cPDs. Based on predicted cPDs we could reconstruct long-term growth curves and demonstrated the continuous increase in replicative senescence on molecular level. CONCLUSION: Epigenetic analysis of specific CpG sites in the genome can be used to estimate the state of cellular aging for quality control of therapeutic cell products.
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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 | 0.009 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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 | 0.000 |
| 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 it