医学
甲状腺癌
内科学
比例危险模型
危险系数
肿瘤科
逻辑回归
生存分析
甲状腺
优势比
癌症
病态的
置信区间
作者
Zherui Fu,Yi Lai,Qianfei Wang,Feng Lin,Jiaping Fang
摘要
Background The diagnostic and prognostic value of the leucine-rich alpha-2-glycoprotein 1 ( LRG1 ) gene in thyroid cancer remains unclear. Using the Cancer Genome Atlas (TCGA) database, we conducted a bioinformatics analysis to determine the role of LRG1 in thyroid cancer. Methods Data from 512 patients with thyroid cancer and 59 normal individuals were collected from TCGA database. The Kruskal–Wallis test and logistic analysis were used to examine the relationship between LRG1 expression and clinicopathologic characteristics. Cox regression and Kaplan–Meier analysis were used to determine the predictive value of LRG1 on clinical outcomes. Single-sample gene set enrichment analysis (ssGSEA) was used to reveal associations between LRG1 expression and immune infiltration levels in thyroid cancer. Results LRG1 was highly expressed in thyroid cancer (P < 0.001) and could effectively distinguish tumor tissue (area under the curve = 0.875) from normal tissue. Moreover, LRG1 was significantly correlated with pathological N stage (odds ratio (OR) = 2.411 (1.659–3.505), P < 0.001). Kaplan–Meier survival analysis revealed that patients with high LRG1 expression had better overall survival (hazard ratio (HR) = 0.30, P = 0.038). Cox regression analysis indicated that pathological M stage was a risk factor for progression-free interval (HR = 5.964 (2.010–17.694), P < 0.001). Using ssGSEA, we found that LRG1 expression was positively correlated with the number of T helper 1 cells ( R = 0.435, P < 0.001), dendritic cells ( R = 0.442, P < 0.001), and macrophages ( R = 0.459, P < 0.001). Conclusion LRG1 may be an important biomarker for predicting the prognosis of thyroid cancer and represent a suitable target for immunotherapy associated with immune infiltration.
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