ArticleHeliyon2022
A novel metabolic-immune related signature predicts prognosis and immunotherapy response in lung adenocarcinoma.
Article in Heliyon, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- Development and Validation of a Prognostic Nomogram for Lung Adenocarcinoma: A Population-Based Study.Journal of healthcare engineering · 2022Trial
- RAS pathway activity subtypes identified by machine learning define prognostic and immune microenvironment characteristics in lung adenocarcinoma.Discover oncology · 2026Article
- Unraveling lung cancer dynamics: a new metabolic signature improving the prediction of recurrence in resected lung adenocarcinoma.Journal of translational medicine · 2026Article
- Tumor prognostic risk stratification based on pseudo-time analysis of single-cell sequencing for patients with lung adenocarcinoma.Journal of thoracic disease · 2025Article
- Applying integrated transcriptome and single-cell sequencing analysis to develop a prognostic signature based on M2-like tumor-associated macrophages for breast cancer.Discover oncology · 2025Article
- Establishment of a Lactylation-Related Gene Signature for Hepatocellular Carcinoma Applying Bulk and Single-Cell RNA Sequencing Analysis.International journal of genomics · 2025Article
- A Prognostic Riskscore Model Related toInternational journal of genomics · 2025Article
- Integration of the bulk transcriptome and single-cell transcriptome reveals efferocytosis features in lung adenocarcinoma prognosis and immunotherapy by combining deep learning.Cancer cell international · 2024Article
- Article
- Construction of a prognostic model based on memory CD4+ T cell-associated genes for lung adenocarcinoma and its applications in immunotherapy.CPT: pharmacometrics & systems pharmacology · 2024Article
- Camrelizumab combined with apatinib and nanoparticle albumin-bound paclitaxel in lung adenocarcinoma (CAPAP-lung): a single-arm phase II study.EClinicalMedicine · 2024Article
- The mitotic cell cycle-associated nomogram predicts overall survival in lung adenocarcinoma.Cancer medicine · 2023Article
- Review
- Characterization of molecular subtypes based on chromatin regulators and identification of the role of NPAS2 in lung adenocarcinoma.Clinical epigenetics · 2023Article
- High Expression of DLGAP5 Indicates Poor Prognosis and Immunotherapy in Lung Adenocarcinoma and Promotes Proliferation through Regulation of the Cell Cycle.Disease markers · 2023Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Lung adenocarcinoma (LUAD) is one of the most frequent types of lung cancer, with a high mortality and recurrence rate. This study aimed to design a RiskScore to predict the prognosis and immunotherapy response of LUAD patients due to a lack of metabolic and immune-related prognostic models. Methods: To identify prognostic genes and generate a RiskScore, we conducted differential gene expression analysis, bulk survival analysis, Lasso regression analysis, and univariate and multivariate Cox regression analysis using TCGA-LUAD as a training subset. GSE31210 and GSE50081 were used as validation subsets to validate the constructed RiskScore. Following that, we explored the connection between RiskScore and clinicopathological characteristics, immune cells infiltration, and immunotherapy. In addition, we investigated into RiskScore's biological roles and constructed a Nomogram model. Results: A RiskScore was identified consisting of five genes (DKK1, CCL20, NPAS2, GNPNAT1 and MELTF). In the RiskScore-high group, LUAD patients showed decreased overall survival rates and shorter progression-free survival. Multiple clinicopathological characteristics and immune cells infiltration in TME, in particular, have been linked to RiskScore. Of note, RiskScore-related genes have been implicated to substance metabolism, carcinogenesis, and immunological pathways, among other things. Finally, the C-index of the RiskScore-based Nomogram model was 0.804 (95% CI: 0.783-0.825), and time-dependent ROC predicted probabilities of 1-, 3- and 5-year survival for LUAD patients were 0.850, 0.848 and 0.825, respectively. Conclusion: The RiskScore, which integrated metabolic and immunological features with DKK1, CCL20, NPAS2, GNPNAT1, and MELTF, could reliably predict prognosis and immunotherapy response in LUAD patients. Moreover, the RiskScore-based Nomogram model had a promising clinical application.
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