ArticleCancer science2024
Nivolumab receptor occupancy on effector regulatory T cells predicts clinical benefit.
Article in Cancer science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it, 6 citations in OpenAlex.
- Comparative efficacy and safety of distinct PD-1 antibodies in unresectable advanced or recurrent gastric and gastroesophageal junction cancer: a network meta-analysis of randomized controlled trials.BMC gastroenterology · 2025Pooled it
- The Immune Checkpoint Inhibitors Journey: From Early Promise to Lasting Impact.Journal of immunotherapy and precision oncology · 2026Review
- PD-1 Blockade-Induced DKK1 Expression by CD8+ T Cells Promotes Blood-Brain Barrier Permeabilization.Cancer discovery · 2026Article
- Peripheral blood biomarkers for predicting response to PD-1/PD-L1 inhibitors.Biomarker research · 2026Review
- Ki-67 expression in anti-programmed cell death protein-1 antibody-bound CD8Discover oncology · 2025Article
- Predictive biomarkers for immune checkpoint efficacy: is multi-omics breaking the deadlock?Translational lung cancer research · 2024Article
- Nivolumab receptor occupancy on effector regulatory T cells predicts clinical benefit.Cancer science · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
26 authors at 1 institution in 1 country.
Funding
Abstract
Immune checkpoint inhibitor discovery represents a turning point in cancer treatment. However, the response rates of solid tumors remain ~10%-30%; consequently, prognostic and immune-related adverse event (irAE) predictors are being explored. The programmed cell death protein 1 (PD-1) receptor occupancy (RO) of PD-1 inhibitors depends on the number of peripheral blood lymphocytes and their PD-1 expression levels, suggesting that the RO may be related to efficacy and adverse events. As PD-1 inhibition affects each T-cell subset differently, the RO of each cell population must be characterized. However, relevant data have not been reported, and the prognostic relevance of this parameter is not known. In this study, we aimed to clarify the association between the nivolumab RO in each T-cell population and patient prognosis and reveal the development of irAEs in nivolumab-treated patients. Thirty-two patients were included in the study, and the mean follow-up period was 364 days. The nivolumab RO on effector regulatory T cells (eTregs) was significantly lower in the group that presented clinical benefits, and a significant negative association was observed between PD-1 occupancy on eTregs and all-cause mortality. The results suggest that the nivolumab RO on eTregs may be a prognostic factor in PD-1 inhibitor therapy, implying that the inhibition of PD-1/PD-ligand 1 (PD-L1) signaling on eTregs may attenuate antitumor effects.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.