Identification of key immune genes related to lymphatic metastasis of papillary thyroid cancer via bioinformatics analysis and experimental validation

被引:1
|
作者
Yu, Yang [1 ,2 ]
Guo, Xing [3 ]
Chai, Jian [1 ]
Han, Zhuoyi [2 ]
Ji, Yaming [4 ,5 ]
Sun, Jirui [4 ,5 ]
Zhang, Huiqing [1 ,6 ]
机构
[1] Baoding First Cent Hosp, Dept Gen Surg, Baoding, Hebei, Peoples R China
[2] Hebei Med Univ, Grad Sch, Shijiazhuang, Hebei, Peoples R China
[3] Baoding First Cent Hosp, Dept Oncol, Baoding, Hebei, Peoples R China
[4] Baoding First Cent Hosp, Dept Pathol, Baoding, Hebei, Peoples R China
[5] Hebei Key Lab Mol Pathol & Early Diag Canc, Baoding, Hebei, Peoples R China
[6] Baoding Key Lab Gastrointestinal Canc Diag & Treat, Baoding, Hebei, Peoples R China
来源
FRONTIERS IN ONCOLOGY | 2023年 / 13卷
关键词
papillary thyroid carcinoma; lymphatic metastasis; immune infiltration; prediction model; machine learning; C-MET; EXPRESSION;
D O I
10.3389/fonc.2023.1181325
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
ObjectiveThe current research aimed to development and validation in signature immune genes for lymphatic metastasis in papillary thyroid cancer (PTC). MethodWeighted 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 via immunohistochemistry to detect the expression of hub genes. ResultIn 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. ConclusionVia bioinformatics analysis and experimental validation, MET and ICAM1 were found to be upregulated in lymph node metastasis from papillary thyroid carcinoma. Further, the two hub genes were closely correlated with activated natural killer cells, monocytes, resting dendritic cells, and eosinophils. Therefore, these two genes may be novel molecular biomarkers and therapeutic targets in lymph node metastasis from papillary thyroid carcinoma.
引用
收藏
页数:13
相关论文
共 50 条
  • [21] Identification and validation of an immune-related prognostic signature and key gene in papillary thyroid carcinoma
    Qin, Rujia
    Li, Chunyan
    Wang, Xuemin
    Zhong, Zhaoming
    Sun, Chuanzheng
    CANCER CELL INTERNATIONAL, 2021, 21 (01)
  • [22] Identification of Key Pathways and Genes in Anaplastic Thyroid Carcinoma via Integrated Bioinformatics Analysis
    Hu, Shengqing
    Liao, Yunfei
    Chen, Lulu
    MEDICAL SCIENCE MONITOR, 2018, 24 : 6438 - 6448
  • [23] Identification and Validation of Dilated Cardiomyopathy-Related Genes via Bioinformatics Analysis
    Wang, Li-Jun
    Qiu, Bai-Quan
    Yuan, Ming-Ming
    Zou, Hua-Xi
    Gong, Cheng-Wu
    Huang, Huang
    Lai, Song-Qing
    Liu, Ji-Chun
    INTERNATIONAL JOURNAL OF GENERAL MEDICINE, 2022, 15 : 3663 - 3676
  • [24] Identification of key genes and miRNAs markers of papillary thyroid cancer
    Qiu, Jie
    Zhang, Wenwei
    Zang, Chuanshan
    Liu, Xiaomin
    Liu, Fuxue
    Ge, Ruifeng
    Sun, Yan
    Xia, Qingsheng
    BIOLOGICAL RESEARCH, 2018, 51
  • [25] Identification of key genes and miRNAs markers of papillary thyroid cancer
    Jie Qiu
    Wenwei Zhang
    Chuanshan Zang
    Xiaomin Liu
    Fuxue Liu
    Ruifeng Ge
    Yan Sun
    Qingsheng Xia
    Biological Research, 51
  • [26] Identification and analysis of genes associated with papillary thyroid carcinoma by bioinformatics methods
    Zhang, Shulong
    Wang, Quan
    Han, Qi
    Han, Huazhong
    Lu, Pinxiang
    BIOSCIENCE REPORTS, 2019, 39
  • [27] Identification of significant immune-related genes for epilepsy via bioinformatics analysis
    Luo, Xiaodan
    Xiang, Tao
    Huang, Hongmi
    Ye, Lin
    Huang, Yifei
    Wu, Yuan
    ANNALS OF TRANSLATIONAL MEDICINE, 2021, 9 (14)
  • [28] Identification of Key Genes Associated with Brain Metastasis from Breast Cancer: A Bioinformatics Analysis
    Zeng, Cheng
    Lin, Mingxi
    Jin, Yizi
    Zhang, Jian
    MEDICAL SCIENCE MONITOR, 2022, 28
  • [29] Identification of key immune-related genes in dilated cardiomyopathy using bioinformatics analysis
    Feng Li
    Tong-Yue Du
    Li-Da Wu
    Lei Zhang
    Huan-Huan Liu
    Zhen-Ye Zhang
    Jie Zhang
    Zhi-Yuan Zhang
    Ling-Ling Qian
    Ru-Xing Wang
    Jian-Feng Hao
    Scientific Reports, 13
  • [30] Bioinformatics Analysis and Experimental Validation to Identify Key Glycosylation-Related Genes in Asthma
    Li, Yue
    Wu, Ruhao
    Tian, Xiaoying
    Zhang, Mengting
    Cheng, Zhe
    JOURNAL OF INFLAMMATION RESEARCH, 2024, 17 : 9469 - 9484