Transcriptional Factor FOXP3 in Renal Allograft Biopsies Predicts Tolerance in Non-Human Primates
Bibliographic record
Abstract
NIH NHP Transplantation Tolerance Cooperative Study Group. Identification of reliable biomarkers for tolerance is critically important in transplantation. We reasoned that intragraft transcripts may be more revealing than those in peripheral blood leukocytes if tolerance is mediated in part by events in the graft. Using the NanoString nCounter platform, we retrospectively studied 256 kidney allograft formalin-fixed paraffin-embedded (FFPE) serial samples taken from non-human primate recipients after combined kidney and bone marrow transplantation (CKBMT) to measure 49 genes, which were previously reported significantly associated with tolerance or rejection. We found dynamic time-dependent kinetics of intragraft biomarkers, which indicated the timing of analysis is critical to interpret the results (Figure 1).. To identify biomarkers that can predict the transplant outcome at the early post-transplant period, we focused on analyzing mRNAs in biopsies taken between 30 and 120 days after CKBMT when no rejection was yet observed. The recipients that subsequently achieved tolerance (TOL, n=11, allograft survival>1995 ± 557 days) showed significantly higher mRNA expression of FOXP3, BCL2, GATA3 and RPS6KB1 compared with biopsies from recipients that later developed chronic antibody-mediated rejection (cAMR, n=11, 850 ± 134 days) or T cell mediated rejection (TCMR, n=9, 109 ± 22 days). In contrast, transcripts of inflammatory cytokines or adaptive immunity (IFNG, CXCL11, FCGR3A, GNLY, GZMB, IL4 and CD4) were higher in TCMR, while endothelium associated transcripts, such as PECAM1 and TEK, were higher in cAMR (Figure 2A and 2B). The ROC curve analyses revealed that intragraft FOXP3 mRNA alone reliably differentiate TOL from both cAMR and TCMR, and that ratios of FOXP3 to several inflammatory cytokine signatures showed better AUC to differentiate TOL from TCMR The significance of intragraft FOXP3 for tolerance was validated by the prospective study with 11 CKBMT recipients. We conclude that intragraft mRNA transcripts, especially FOXP3, measured early post transplantation can serve as biomarkers to reliably predict subsequent tolerance induction via the mixed chimerism approach. Grant 5U19AI102405.
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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 | 0.001 | 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) | 0.001 | 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 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".