ArticleTranslational lung cancer research2026
A T-cell exhaustion-related signature for predicting response to immunotherapy among patients with lung adenocarcinoma.
Article in Translational lung cancer research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Lung adenocarcinoma (LUAD) remains a leading cause of cancer-related mortality, and although immunotherapy has improved outcomes for a proportion of patients, reliable predictive biomarkers of response are lacking. T-cell exhaustion-associated transcriptional states are increasingly recognized as relevant to antitumor immunity, yet their prognostic and predictive associations in LUAD remain incompletely defined. The aim of this study was to evaluate transcription factors previously linked to T-cell exhaustion and to construct a prognostic gene signature for stratifying patients with LUAD and estimating potential benefit from immunotherapy. Methods: Ten transcription factors previously linked to T-cell exhaustion were identified from the literature. Using LUAD transcriptomic data, we evaluated their prognostic relevance and identified four factors associated with overall survival (OS). Based on these, patients were divided into high- and low-risk exhaustion groups, and differentially expressed genes (DEGs) were derived. Univariate Cox regression and least absolute shrinkage and selection operator (LASSO) Cox analysis were applied to screen prognosis-related DEGs, through which a six-gene T-cell exhaustion-related prognostic score (TEXRGPS) was constructed. The expression of these six genes was validated via reverse-transcription quantitative polymerase chain reaction (RT-qPCR) in 20 pairs of LUAD and adjacent normal tissues from our hospital. Associations of TEXRGPS with clinical characteristics, immune cell infiltration, and predicted response to immune checkpoint inhibitors (ICIs) were also assessed. Results: Four of the ten transcription factors were associated with prognosis and were used to stratify patients. Six key DEGs- Conclusions: The TEXRGPS was associated with prognosis, computational estimates of immune infiltration, and predicted immunotherapy response in retrospective LUAD cohorts. The signature may support future risk-stratification research, but it does not establish a direct functional relationship between the selected genes and exhausted T cells. Prospective multicenter validation, together with single-cell, protein-level, and functional studies, is required before clinical use.
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.