ArticleBioMed research international2022
Comprehensive Analysis of Immune Cell Infiltration of m6a-Related lncRNA in Lung Squamous Cell Carcinoma and Construction of Relevant Prognostic Models.
Article in BioMed research international, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
4 citing papers in PubMed, 4 citations in OpenAlex.
- Research progress on the characteristics and functions of m6A modification in lung cancer tumor stem cells.American journal of cancer research · 2026Review
- Non-coding RNA-Mediated N6-Methyladenosine (mNon-coding RNA research · 2024Review
- Deubiquitylase USP31 Induces Autophagy and Promotes the Progression in Lung Squamous Cell Carcinoma Cells by Stabilizing E2F1 Expression.Current cancer drug targets · 2024Article
- Targeting immune cell types of tumor microenvironment to overcome resistance to PD-1/PD-L1 blockade in lung cancer.Frontiers in pharmacology · 2023Review
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Lung squamous cell carcinoma (LUSC) is the main cause of cancer-related mortality. Some studies demonstrate that m6a and long noncoding RNA (lncRNA) are vital in the pathogenesis of LUSC. In this study, we aimed to further understand the prognostic value of m6a-related lncRNAs in LUSC and their role in the immune microenvironment. For this, we obtained LUSC transcriptome and clinical data from the TCGA database. Further, the identified m6a-related and prognostically relevant lncRNAs were clustered into groups based on prognostic lncRNA expression. Further analysis of the differences between clusters was performed. Five m6A-related lncRNAs were used for model construction using the LASSO regression. The receiver-operating characteristic curve (ROC curves) and decision curve analysis (DCA) were used to assess the model accuracy. Finally, the model was validated using polymerase chain reaction (PCR). We identified 12 m6a-related lncRNAs that were associated with prognosis and were lowly expressed in tumors. Cytotoxic T-lymphocyte-associated protein 4 (CTLA4) highly correlated with prognostic genes, and differential analysis indicated that it was highly expressed in the tumor group and cluster 1. In cluster 2 TIME, tumor cells were less pure and more immune, and stromal-associated cells were present. A prognostic model was constructed based on five m6a-lncRNAs. The area under the curve (AUC) was >0.5 in test group and train group. The PCR results showed that the genes in the prognostic model were lowly expressed in the tumor and were statistically significant (
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.