ArticleHeliyon2022
Construction of a prognostic immune-related lncRNA model and identification of the immune microenvironment in middle- or advanced-stage lung squamous carcinoma patients.
Article in Heliyon, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Effects of LncRNA HOXC13-AS on the Prognosis of Non-small Cell Lung Cancer Patients and Its Mechanism of Disease Progression.Biochemical genetics · 2026Article
- Comorbidity of hypertension and lung cancer: interplay of genetics and environment.Discover oncology · 2025Review
- Prognostic and therapeutic relevance of IL2RG-related LncRNAs in clear cell renal cell carcinoma.Scientific reports · 2025Article
- A novel prognostic model based on migrasome-related LncRNAs for gastric cancer.Scientific reports · 2025Article
- EBV-Induced LINC00944: A Driver of Oral Cancer Progression and Influencer of Macrophage Differentiation.Cancers · 2025Article
- Decoding LncRNA in COPD: Unveiling Prognostic and Diagnostic Power and Their Driving Role in Lung Cancer Progression.International journal of molecular sciences · 2024Review
- Identification of a lactate metabolism-related lncRNAs signature for predicting the prognosis in patients with kidney renal clear cell carcinoma.Translational andrology and urology · 2024Article
- Screening of Immune-related lncRNAs in Lung Adenocarcinoma and Establishing a Survival Prognostic Risk Prediction Model.Combinatorial chemistry & high throughput screening · 2024Article
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Authors and funding
7 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Background: Globally, non-small-cell lung cancer (NSCLC) has a high incidence, and NSCLC patients have poor prognoses. Lung squamous carcinoma (LUSC) is a major pathological type of NSCLC. LncRNAs play important roles in tumor progression and immune system functions. The aim of this study was to construct a predictive model with immune-related lncRNAs and to assess the immune microenvironment in middle- or advanced-stage LUSC patients. Methods: RNA sequencing data and corresponding clinical LUSC data were downloaded from The Cancer Genome Atlas. Immune genes were obtained from the Molecular Signatures Database. Immune-related lncRNAs were identified by Pearson correlation analysis in R. The model was constructed using univariate and multivariate Cox regression analyses. Finally, we validated the prognostic immune-related lncRNA model in a cohort from the Fudan University Shanghai Cancer Center. Results: Our risk model included four immune-related lncRNAs (LINC00944, AL034550.2, AC020907.1 and AC027682.6). Survival analysis revealed that overall and disease-free survival were shorter in the high-risk group than in the low-risk group. Independent prognostic analysis showed that our model could be used as an independent prognostic predictor. The high-risk group was positively associated with CD8+ T cells, B cells, myeloid dendritic cells, macrophages, regulatory T cells (Tregs) and cancer-associated fibroblasts and high expression of PD1 and CTLA4. Additionally, a low-risk score was correlated with lower half maximal inhibitory concentrations (IC Conclusion: We established a risk score model including four immune-related lncRNAs. The model accurately predicts the prognosis of middle- or advanced-stage LUSC patients and provides an important reference for individualized treatment.
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