ArticleJournal of cellular and molecular medicine2021
Systematic profiling of invasion-related gene signature predicts prognostic features of lung adenocarcinoma.
Article in Journal of cellular and molecular medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.
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27 citing papers in PubMed, 38 citations in OpenAlex.
- Risk stratification of lung adenocarcinoma using a nomogram combined with ferroptosis-related LncRNAs and subgroup analysis with immune and N6-methyladenosine modification.BMC medical genomics · 2022Trial
- CRTAC1 inhibits progression of lung adenocarcinoma by suppressing integrin/FAK signaling.Oncogene · 2026Article
- Identification and validation of prognostic genes for lung adenocarcinoma prognosis based on PANoptosis-related genes.Discover oncology · 2025Article
- Two inflammation-related genes model could predict risk in prognosis of patients with lung adenocarcinoma.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2025Article
- PRSS3 is a potential prognostic biomarker for lung adenocarcinoma.Translational cancer research · 2025Article
- Single-Cell Transcriptomic Profiling Reveals KRAS/TP53-Driven Neutrophil Reprogramming in Luad: A Multi-Gene Prognostic Model and Therapeutic Targeting of RHOV.Oncology research · 2025Article
- FAT1 mutation-related signature predicts survival risk and tumor immunogenicity in lung adenocarcinoma.Frontiers in genetics · 2025Article
- Exploring the role of LOX family in glioma progression and immune modulation.Frontiers in immunology · 2025Article
- Machine learning-based prognostic model of lactylation-related genes for predicting prognosis and immune infiltration in patients with lung adenocarcinoma.Cancer cell international · 2024Article
- Construction and validation of a prognostic model based on oxidative stress-related genes in non-small cell lung cancer (NSCLC): predicting patient outcomes and therapy responses.Translational lung cancer research · 2024Article
- CRTAC1 identified as a promising diagnosis and prognostic biomarker in lung adenocarcinoma.Scientific reports · 2024Article
- The Tumor Stemness Indice mRNAsi can Act as Molecular Typing Tool for Lung Adenocarcinoma.Biochemical genetics · 2023Article
- Investigating subtypes of lung adenocarcinoma by oxidative stress and immunotherapy related genes.Scientific reports · 2023Article
- CRTAC1 enhances the chemosensitivity of non-small cell lung cancer to cisplatin by eliciting RyR-mediated calcium release and inhibiting Akt1 expression.Cell death & disease · 2023Article
- Integrative analysis of TP53 mutations in lung adenocarcinoma for immunotherapies and prognosis.BMC bioinformatics · 2023Article
- Clustering analysis and prognostic signature of lung adenocarcinoma based on the tumor microenvironment.Scientific reports · 2022Article
- Article
- Identification of N7-methylguanosine related signature for prognosis and immunotherapy efficacy prediction in lung adenocarcinoma.Frontiers in medicine · 2022Article
- The prognostic value of immune-related genesFrontiers in oncology · 2022Article
- Predicting Chemo-Radiotherapy Sensitivity With Concordant Survival Benefit in Non-Small Cell Lung CancerFrontiers in oncology · 2022Article
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Due to the high heterogeneity of lung adenocarcinoma (LUAD), molecular subtype based on gene expression profiles is of great significance for diagnosis and prognosis prediction in patients with LUAD. Invasion-related genes were obtained from the CancerSEA database, and LUAD expression profiles were downloaded from The Cancer Genome Atlas. The ConsensusClusterPlus was used to obtain molecular subtypes based on invasion-related genes. The limma software package was used to identify differentially expressed genes (DEGs). A multi-gene risk model was constructed by Lasso-Cox analysis. A nomogram was also constructed based on risk scores and meaningful clinical features. 3 subtypes (C1, C2 and C3) based on the expression of 97 invasion-related genes were obtained. C3 had the worst prognosis. A total of 669 DEGs were identified among the subtypes. Pathway enrichment analysis results showed that the DEGs were mainly enriched in the cell cycle, DNA replication, the p53 signalling pathway and other tumour-related pathways. A 5-gene signature (KRT6A, MELTF, IRX5, MS4A1 and CRTAC1) was identified by using Lasso-Cox analysis. The training, validation and external independent cohorts proved that the model was robust and had better prediction ability than other lung cancer models. The gene expression results showed that the expression levels of MS4A1 and KRT6A in tumour tissues were higher than in normal tissues, while CRTAC1 expression in tumour tissues was lower than in normal tissues. The 5-gene signature prognostic stratification system based on invasion-related genes could be used to assess prognostic risk in patients with LUAD.
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