CD26 is a senescence marker associated with reduced immunopotency of human adipose tissue-derived multipotent mesenchymal stromal cells
Bibliographic record
Abstract
Abstract Introduction Human mesenchymal stromal cells (MSCs) have immunomodulatory, anti-inflammatory, and tolerogenic effects. Long-term in vitro expansion of MSCs to generate clinical grade products results in the accumulation of senescent-functionally impaired MSCs. Markers to assess the ‘senescent load’ of MSC products are needed. Methods Early and late passage human adipose tissue (AT) MSCs from pediatric and adult donors were characterized using established senescent markers [i.e., MSC size, granularity, and autofluorescence by flow cytometry; β-galactosidase staining (SA-β-gal); CDKN2A and CDKN1A by qRT-PCR]. In gene set enrichment analysis, DPP4 (also known as adenosine deaminase complexing protein 2 or CD26) was found as a prominent dysregulated transcript that was increased in late passage MSC(AT). This was confirmed in a larger number of MSC samples by PCR, flow cytometry, Western blotting, and immunofluorescence. In vitro immunopotency assays compared the function of CD26 high and CD26 low MSC(AT). The effect of senolytics on the CD26 high subpopulation was evaluated in senescent MSC(AT). Results Late passage MSC(AT) had a senescence transcriptome signature. DPP4 was the most differentially enriched gene in senescent MSCs. Late passage senescent MSC(AT) had higher CD26 surface levels and total protein abundance. Moreover, CD26 surface levels were higher in early passage MSC(AT) from adults compared to pediatric donors. CD26 abundance correlated with established senescence markers. CD26 high MSC(AT) had reduced immunopotency compared to CD26 low MSC(AT). Senolytic treatment induced MSC apoptosis, which decreased the frequencies of CD26 high MSC(AT). Conclusions DPP4 gene expression and DPP4/CD26 protein abundance are markers of replicative senescence in MSC(AT). Samples enriched in CD26 high MSC(AT) have reduced immunopotency and CD26 high MSCs are reduced with senolytics.
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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 | 0.001 | 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) | 0.002 | 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".