ArticleFrontiers in oncology2023
Identification of key immune genes related to lymphatic metastasis of papillary thyroid cancer via bioinformatics analysis and experimental validation.
Article in Frontiers in oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Multiomics identifies a prognostic signature and SPIB as a potential regulator of gastric cancer lymph node metastasis.iScience · 2026Article
- Multiplex Immune Profiling Reveals the Role of Serum Immune Proteomics in Predicting Response to Radioiodine after Total Resection of Papillary Thyroid Carcinoma.Journal of proteome research · 2026Article
- A bioinformatics pipeline for identifying clinically relevant immune and adhesion biomarkers in thyroid risk stratification.Frontiers in molecular biosciences · 2026Article
- Combination of inflammatory proteins in serum can be used to diagnose papillary thyroid carcinoma with lymph node metastasis.Discover oncology · 2025Article
- Identification of Novel Gene Signature Predicting Lymph Node Metastasis in Papillary Thyroid Cancer via Bioinformatics Analysis and in vitro Validation.International journal of general medicine · 2025Article
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Authors and funding
7 authors.
Funding
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Abstract
Objective: The current research aimed to development and validation in signature immune genes for lymphatic metastasis in papillary thyroid cancer (PTC). Method: Weighted correlation network analysis (WGCNA) was performed to identify genes closely correlated with lymphatic metastasis in PTC from TCGA database. Information on immune-related genes (IRGs) was obtained from the ImmPort database. Crossover genes were used with the R package clusterProfiler for Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment. Key genes in the protein-protein interaction network of cross-targets were obtained using Cytoscape. Lasso and Random Forest (RF) models were utilized to identify pivotal genes. We constructed a nomogram based on the hub genes. The correlation between hub genes and immune cell infiltration was explored. We collected and assessed clinical samples Result: In total, 122 IRGs were correlated with lymphatic metastases from PTC. There are 10 key IRGs in the protein-protein interaction network. Then, three hub genes including PTGS2, MET, and ICAM1 were established using the LASSO and RF models. The expression of these hub genes was upregulated in samples collected from patients with lymphatic metastases. The average area under the curve of the model reached 0.83 after a 10-fold and 200-time cross-validation, which had a good prediction ability. Immuno-infiltration analysis showed that the three hub genes were significantly positively correlated with resting dendritic cells and were negatively correlated with activated natural cells, monocytes, and eosinophils. Immunohistochemistry results revealed that lymph node metastasis samples had a higher expression of the three hub genes than non-metastasis samples. Conclusion:
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