Selenoprotein P (SELENOP) acts as a crucial mediator, distributing selenium from the liver to other tissues within the body. Despite its established role in selenium metabolism, the specific functions of SELENOP in the development of liver cancer remain enigmatic. This study aims to unravel SELENOP’s associations in hepatocellular carcinoma (HCC) by scrutinizing its expression in correlation with disease characteristics and investigating links to hormonal and lipid/triglyceride metabolism biomarkers as well as its potential as a prognosticator for overall survival and predictor of hypoxia. SELENOP mRNA expression was analyzed in 372 HCC patients sourced from The Cancer Genome Atlas (TCGA), utilizing statistical methodologies in R programming and machine learning techniques in Python. SELENOP expression significantly varied across HCC grades (p< 0.000001) and among racial groups (p= 0.0246), with lower levels in higher grades and Asian individuals, respectively. Gender significantly influenced SELENOP expression (p< 0.000001), with females showing lower altered expression compared to males. Notably, the Spearman correlation revealed strong positive connections of SELENOP with hormonal markers (AR, ESR1, THRB) and key lipid/triglyceride metabolism markers (PPARA, APOC3, APOA5). Regarding prognosis, SELENOP showed a significant association with overall survival (p= 0.0142) but explained only a limited proportion of variability (~10%). Machine learning suggested its potential as a predictive biomarker for hypoxia, explaining approximately 18.89% of the variance in hypoxia scores. Future directions include validating SELENOP’s prognostic and diagnostic value in serum for personalized HCC treatment. Large-scale prospective studies correlating serum SELENOP levels with patient outcomes are essential, along with integrating them with clinical parameters for enhanced prognostic accuracy and tailored therapeutic strategies.
硒蛋白P（SELENOP）作为关键介质，负责将硒从肝脏输送至体内其他组织。尽管其在硒代谢中的作用已明确，但SELENOP在肝癌发展中的具体功能仍不清楚。本研究通过分析SELENOP在肝细胞癌（HCC）中的表达与疾病特征的相关性，探讨其与激素及脂质/甘油三酯代谢生物标志物的关联，并评估其作为总生存期预后指标和缺氧预测因子的潜力，旨在揭示SELENOP在HCC中的作用机制。研究利用来自癌症基因组图谱（TCGA）的372例HCC患者数据，通过R编程的统计方法和Python的机器学习技术分析SELENOP mRNA表达。结果显示，SELENOP表达在不同HCC分级（p<0.000001）和种族群体（p=0.0246）间存在显著差异，分别在高分级和亚洲个体中表达较低。性别对SELENOP表达有显著影响（p<0.000001），女性表达变化较男性更低。值得注意的是，斯皮尔曼相关性分析显示SELENOP与激素标志物（AR、ESR1、THRB）及关键脂质/甘油三酯代谢标志物（PPARA、APOC3、APOA5）呈强正相关。在预后方面，SELENOP与总生存期显著相关（p=0.0142），但仅能解释有限的变异比例（约10%）。机器学习分析提示其作为缺氧预测生物标志物的潜力，可解释约18.89%的缺氧评分变异。未来研究方向包括验证血清SELENOP在个体化HCC治疗中的预后和诊断价值，需开展大规模前瞻性研究将血清SELENOP水平与患者结局相关联，并将其与临床参数整合以提高预后准确性和制定个体化治疗策略。
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