ArticleFrontiers in immunology2022
Effect of the m6ARNA gene on the prognosis of thyroid cancer, immune infiltration, and promising immunotherapy.
Article in Frontiers in immunology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 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
7 citing papers in PubMed, 10 citations in OpenAlex.
- RBM15 in diseases: Molecular mechanisms and clinical opportunities from RNA mGenes & diseases · 2026Review
- Immunotherapy in Thyroid Cancer: Current Strategies and Challenges.Cancer medicine · 2026Review
- Abnormal changes in metabolites caused by mJournal of advanced research · 2025Review
- Research trends and hotspots of radioiodine-refractory thyroid cancer treatment in the twenty-first century: a bibliometric analysis.Annals of nuclear medicine · 2025Article
- The role of epigenetic methylations in thyroid Cancer.World journal of surgical oncology · 2024Review
- Enhancing mHeliyon · 2024Article
- The emerging roles of N6-methyladenosine RNA modifications in thyroid cancer.European journal of medical research · 2023Review
Corrections and comments
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Accumulating evidence suggests that N6-methyladenosine (m6A) RNA methylation plays an important role in tumor proliferation and growth. However, its effect on the clinical prognosis, immune infiltration, and immunotherapy response of thyroid cancer patients has not been investigated in detail. Methods: Clinical data and RNA expression profiles of thyroid cancer were extracted from the Cancer Genome Atlas-thyroid carcinoma (TCGA-THCA) and preprocessed for consensus clustering. The risk model was constructed based on differentially expressed genes (DEGs) using Least Absolute Shrinkage and Selection Operator (LASSO) and Cox regression analyses. The associations between risk score and clinical traits, immune infiltration, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Set Enrichment Analysis (GSEA), immune infiltration, and immunotherapy were assessed. Immunohistochemistry was used to substantiate the clinical traits of our samples. Results: Gene expression analysis showed that 17 genes, except YHTDF2, had significant differences (vs healthy control, Conclusions: Our risk model can act as an independent marker for thyroid cancer and provides promising immunotherapy targets for its treatment.
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Registered trials
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