ArticleInternational journal of general medicine2021
An Autophagy-Related Long Non-Coding RNA Prognostic Signature for Patients with Lung Squamous Carcinoma Based on Bioinformatics Analysis.
Article in International journal of general medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 7 citations in OpenAlex.
- Cuproptosis in lung cancer: a nexus of ncRNA regulation, epigenetics, and tumor microenvironment Remodeling.Clinical and experimental medicine · 2025Review
- Vinorelbine Alters lncRNA Expression in Association with EGFR Mutational Status and Potentiates Tumor Progression Depending on NSCLC Cell Lines' Genetic Profile.Biomedicines · 2023Article
- Article
- Comprehensive landscape and future perspective of long noncoding RNAs in non-small cell lung cancer: it takes a village.Molecular therapy : the journal of the American Society of Gene Therapy · 2023Review
- Identification of Clinical Prognostic Regulators and Analysis of Ferroptosis-Related Signatures in the Tumor Immune Microenvironment in Lung Squamous Cell Carcinoma.Disease markers · 2023Article
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Authors and funding
3 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeLung cancer is the most common and deadly cancer type affecting humans. Although huge progress has been made on early diagnosis and precision treatment, the overall 5 year survival rate remains low. In this study, we constructed an autophagy-related long non-coding RNA (lncRNA) prognostic signature for guiding clinical practice.
methodsFrom The Cancer Genome Atlas, we retrieved mRNA and lncRNA expression matrices of patients with lung squamous carcinoma. We then established a prognostic risk model using Lasso regression and multivariate Cox regression. The model generated a risk score to differentiate high- and low-risk groups. An ROC curve and nomogram were used to visualize the predictive ability of the current signatures. Finally, we used Gene Set Enrichment Analysis to determine gene ontology and pathway enrichment.
resultsAfter screening 1248 autophagy-related lncRNAs, we selected seven lncRNAs (LUCAT1, AC022150.2, AL035425.3, AC138976.2, AC106786.1, GPRC5D-AS1 and AP006545.2) for our signature. Univariate (hazard ratio [HR] = 2.147, 95% confidence interval [CI]: 1.681-2.743,
conclusionOur prognostic model successfully predicted patient prognosis in lung cancer.
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