ArticleJournal of oncology2022
Identification of an Exosome-Related Signature for Predicting Prognosis, Immunotherapy Efficacy, and Tumor Microenvironment in Lung Adenocarcinoma.
Article in Journal of oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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
4 citing papers in PubMed, 5 citations in OpenAlex.
- Machine learning-based coagulation-related signature for predicting the prognosis and therapy benefits in lung adenocarcinoma.Discover oncology · 2025Article
- Integrating RNA-seq and scRNA-seq to explore the prognostic features and immune landscape of exosome-related genes in breast cancer metastasis.Annals of medicine · 2025Article
- Bioinformatics analysis of an immunotherapy responsiveness-related gene signature in predicting lung adenocarcinoma prognosis.Translational lung cancer research · 2024Article
- Identification of exosomes-related lncRNAs in clear cell renal cell carcinoma based on Bayesian spike-and-slab lasso approach.Functional & integrative genomics · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Accumulating evidence suggests that exosomes can affect lung adenocarcinoma (LUAD) progression. However, there is still a lack of understanding of the global influence of exosome-related genes (ERGs) on prognostic relevance, tumor microenvironment features, and immunotherapy responsiveness in patients with LUAD. In the TCGA dataset, differential analysis of 490 LUAD samples and 59 normal samples yielded 30 ERGs with differential expression. We have created a predictive signature based on 10 overall survival (OS)-related ERGs and confirmed it in two external cohorts (GSE72094 and GSE68465) via the least absolute shrinkage and selection operator (LASSO) and Cox regression analysis in the TCGA dataset. The new signature revealed superior robustness and prognostic capacity for overall patient survival. Univariate and multivariate Cox regression analyses indicated that this signature was an independent risk factor for survival in patients with LUAD. In addition, for predicting the 1-year, 3-year, and 5-year OS of LUAD patients, we developed a nomogram and confirmed its predictive ability via the C-index and calibration curve. In addition, patients categorized by risk score exhibited distinct immunological states, stemness index, immune subtypes, and immunotherapy response. In conclusion, we created a risk signature for LUAD that was tightly associated with the immune landscape and therapeutic response. Also, such a risk signature effectively promotes the ability of the clinicians in making more precise and individualized treatment recommendations for patients with LUAD.
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.