ArticleHeliyon2024
A novel nomogram model for lung adenocarcinoma subtypes based on RNA-modification regulatory genes.
Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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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
1 citing paper in PubMed.
- Targeting NLRC4 for potential therapeutic strategies in lung adenocarcinoma.Discover oncology · 2025Article
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: In non-small cell lung cancer (NSCLC), lung adenocarcinoma (LUAD) is the most common subtype. RNA modification has become the frontier and hotspot of current tumor research. Results: In this study, 109 genes that regulate RNA modifications were identified according to The Cancer Genome Atlas (TCGA). A differential gene expression analysis identified 46 differentially expressed RNA modification regulatory genes (DERRGs). LUAD samples were stratified into two distinct clusters based on the expression of these DERRGs. A significant correlation was observed between these clusters and patient survival rates, as well as clinical features. Furthermore, a four-DERRG signature (EIF3B, HNRNPC, IGF2BP1, and METTL3) developed using LASSO regression. According to the calculated risk scores from this signature, LUAD patients were categorized into high-risk and low-risk groups. Patients in the low-risk group exhibited a more favorable prognosis. A prognostic nomogram was crafted, integrating the four-DERRGs signature with clinical parameters. The nomogram was revealed that OS, age, clinical stage, immune cell infiltration, and immune checkpoint molecule expression were significantly linked to the OS of LUAD. GSEA analysis found that the DERRGs were primarily regulated immune pathways. Conclusions: This study developed four DERRGs signatures and formulated a nomogram model for precise prognosis estimation in LUAD patients. The study's insights are instrumental for advancing diagnosis, prognosis, and therapeutic strategies for LUAD.
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