Evaluation of a gene expression biomarker to identify operationally tolerant liver transplant recipients: the LITMUS trial
Bibliographic record
Abstract
LITMUS was a single-centre, Phase 2a study designed to investigate whether the gene biomarker FGL2/IFNG previously reported for the identification of tolerance in murine models could identify operationally tolerant liver transplant recipients. Multiplex RT-PCR was used to amplify eight immunoregulatory genes in peripheral blood mononuclear cells (PBMC) from 69 adult liver transplant recipients. Patients with PBMC FGL2/IFNG ≥ 1 and a normal liver biopsy underwent immunosuppression (IS) withdrawal. The primary end point was the development of operational tolerance. Secondary end points included correlation of tolerance with allograft gene expression and immune cell markers. Twenty-eight of 69 patients (38%) were positive for the PBMC tolerance biomarker and 23 proceeded to IS withdrawal. Nine of the 23 patients had abnormal baseline liver biopsies and were excluded. Of the 14 patients with normal biopsies, eight (57%) have achieved operational tolerance and are off IS (range 12-57 months). Additional studies revealed that all of the tolerant patients and only one non-tolerant patient had a liver gene ratio of FOXP3/IFNG ≥ 1 prior to IS withdrawal. Increased CD4+ T regulatory T cells were detected both in PBMC and livers of tolerant patients following IS withdrawal. Higher expression of SELE (gene for E-selectin) and lower expression of genes associated with inflammatory responses (GZMB, CIITA, UBD, LSP1, and CXCL9) were observed in the pre-withdrawal liver biopsies of tolerant patients by RNA sequencing. These results suggest that measurement of PBMC FGL2/IFNG may enrich for the identification of operationally tolerant liver transplant patients, especially when combined with intragraft measurement of FOXP3/IFNG. Clinical Trial Registration: ClinicalTrials.gov (LITMUS: NCT02541916).
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
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".