Interferon-Gamma–Producing CD8+ Tissue Resident Memory T Cells Are a Targetable Hallmark of Immune Checkpoint Inhibitor–Colitis
Bibliographic record
Abstract
Background & Aims The pathogenesis of immune checkpoint inhibitor (ICI)–colitis remains incompletely understood. We sought to identify key cellular drivers of ICI-colitis and their similarities to idiopathic ulcerative colitis, and to determine potential novel therapeutic targets. Methods We used a cross-sectional approach to study patients with ICI-colitis, those receiving ICI without the development of colitis, idiopathic ulcerative colitis, and healthy controls. A subset of patients with ICI-colitis were studied longitudinally. We applied a range of methods, including multiparameter and spectral flow cytometry, spectral immunofluorescence microscopy, targeted gene panels, and bulk and single-cell RNA sequencing. Results We demonstrate CD8 + tissue resident memory T (T RM ) cells are the dominant activated T cell subset in ICI-colitis. The pattern of gastrointestinal immunopathology is distinct from ulcerative colitis at both the immune and epithelial-signaling levels. CD8 + T RM cell activation correlates with clinical and endoscopic ICI-colitis severity. Single-cell RNA sequencing analysis confirms activated CD8 + T RM cells express high levels of transcripts for checkpoint inhibitors and interferon-gamma in ICI-colitis. We demonstrate similar findings in both anti–CTLA-4/PD-1 combination therapy and in anti–PD-1 inhibitor-associated colitis. On the basis of our data, we successfully targeted this pathway in a patient with refractory ICI-colitis, using the JAK inhibitor tofacitinib. Conclusions Interferon gamma–producing CD8 + T RM cells are a pathological hallmark of ICI-colitis and a novel target for therapy.
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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 | 0.000 | 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) | 0.001 | 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".