ArticleJournal of thoracic disease2022
Molecular typing and prognostic model of lung adenocarcinoma based on cuprotosis-related lncRNAs.
Article in Journal of thoracic disease, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.
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Who cites it
5 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Quality of life after robotic versus conventional minimally invasive cancer surgery: a systematic review and meta-analysis.Journal of robotic surgery · 2024Pooled it
- Machine learning-based characterization of a PANoptosis-associated model for enhancing prognosis and immunotherapy response in lung adenocarcinoma patients.Discover oncology · 2025Article
- Copper homeostasis dysregulation in respiratory diseases: a review of current knowledge.Frontiers in physiology · 2024Review
- Targeting copper metabolism: a promising strategy for cancer treatment.Frontiers in pharmacology · 2023Review
- NJournal of hepatocellular carcinoma · 2023Article
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Authors and funding
6 authors.
Funding
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Abstract
Background: Previous research has shown the heterogeneity of lung adenocarcinoma (LUAD) accounts for the different effects and prognoses of the same treatment. Cuprotosis is a newly discovered form of programmed cell death involved in the development of tumors. Therefore, it is important to study the long non-coding RNAs (lncRNAs) that regulate cuprotosis to identify molecular subtypes and predict survival of LUAD. Methods: The expression profile, clinical, and mutation data of LUAD were downloaded from The Cancer Genome Atlas (TCGA), and the "ConsensusClusterPlus" package was used to cluster LUADs based on cuprotosis-related lncRNAs (CR-lncRNAs). The least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression were used to construct a prognostic model. CIBERSORT and single-sample gene set enrichment analysis (ssGSEA) were used for assessing immune cells infiltration and immune function. The tumor microenvironment (TME) score was calculated by ESTIMATE, and the tumor mutational burden (TMB) and Tumor Immune Dysfunction and Exclusion (TIDE) were used to evaluate the efficacy of immunotherapy. Results: Firstly, 501 CR-lncRNAs were identified based on the co-expression relationship of 19 cuprotosis genes. And univariate Cox further obtained 34 prognosis-related CR-lncRNAs. The unsupervised consensus clustering divided LUAD samples into cluster A and cluster B, and showed cluster A had better prognosis, more immune cells infiltration, stronger immune function, and a higher TME score. Subsequently, we used Lasso Cox regression to construct a prognostic model, and univariate and multivariate Cox analyses showed the risk score could be an independent prognostic indicator. Immune cells infiltration, immune function, and TME score were increased markedly in the low-risk group, while TMB and TIDE suggested the efficacy of immunotherapy might be increased in high-risk group. Conclusions: Our research identified two new molecular subtypes and constructed a novel prognostic model of LUAD which could provide new direction for its diagnosis, treatment, and prognosis.
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