1. This article discusses the potential of exosome-related genes (ERGs) to predict prognosis, immunotherapy efficacy, and tumor microenvironment in lung adenocarcinoma.
2. A predictive signature based on 10 overall survival (OS)-related ERGs was created and confirmed in two external cohorts via least absolute shrinkage and selection operator (LASSO) and Cox regression analysis.
3. The new signature revealed superior robustness and prognostic capacity for overall patient survival, as well as distinct immunological states, stemness index, immune subtypes, and immunotherapy response.
The article is generally reliable and trustworthy due to its use of multiple datasets from the TCGA database, GSE72094 dataset, GSE68465 dataset, GSE78220 dataset, and IMvigor dataset. The authors also used a variety of methods such as differential analysis, least absolute shrinkage and selection operator (LASSO), Cox regression analysis, univariate and multivariate Cox regression analyses, nomogram development for predicting 1-year/3-year/5-year OS of LUAD patients with C-index validation, etc., to support their claims. Furthermore, the authors have provided detailed information about the data sources used in this study which adds to its trustworthiness.
However there are some points that could be improved upon in terms of trustworthiness. For example, the authors did not provide any information about potential biases or sources of bias in their data sources which could affect the results of their study. Additionally, they did not explore any counterarguments or present both sides equally when discussing their findings which could lead to one-sided reporting or unsupported claims being made without sufficient evidence or exploration of other perspectives. Finally, there is no mention of possible risks associated with using exosomes for predicting prognosis or immunotherapy efficacy which should be noted in order to ensure that readers are aware of all potential implications before making decisions based on this research.