A Survival Model Based on the ASB Genes and Used to Predict the Prognosis of Kidney Renal Clear Cell Carcinoma

IF 1.4 4区 生物学 Q4 GENETICS & HEREDITY
Deqian Xie, Lu Dai, Xiaolei Yang, Tao Huang, Wei Zheng
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Abstract

Kidney renal clear cell carcinoma (KIRC) is increasing in incidence worldwide, with poor and unpredictable patient prognosis limited by diagnostic and therapeutic approaches. New genes are urgently needed to improve this situation. The ankyrin repeat and suppressor of the cytokine signaling (SOCS) box (ASB) family are a promising class of tumorigenesis-related genes. We examined the expression and mutation of 18 ASB genes in various tumors for this study. The findings revealed that ASB genes exhibit significant copy number variation (CNV) and single nucleotide variation (SNV). There were substantial variations in ASB gene expression in different tumor tissues, and different levels of methylation of ASB genes affected the gene expression and tumor progression. By applying LASSO regression analysis, we established a KIRC survival model based on five ASB genes (ASB6, ASB7, ASB8, ASB13, and ASB17). Additionally, ROC curve analysis was used to assess the survival model’s accuracy. Through univariate and multivariate COX regression analysis, we demonstrated that the model’s risk score might be an independent risk factor for individuals with KIRC. In summary, our KIRC survival model could accurately predict patients’ future survival. Further, we also quantified the survival model through a nomogram. This series of findings confirmed that ASB genes are potential predictive markers and targeted therapies for KIRC. Our KIRC survival model based on five ASB genes can help more clinical practitioners make accurate judgments about the prognosis of KIRC patients.
基于ASB基因预测肾透明细胞癌预后的生存模型
肾透明细胞癌(KIRC)在世界范围内的发病率正在上升,由于诊断和治疗方法的限制,患者预后不良且不可预测。迫切需要新的基因来改善这种状况。细胞因子信号(SOCS) box (ASB)家族的锚定蛋白重复序列和抑制因子是一类很有前途的肿瘤发生相关基因。在本研究中,我们检测了18个ASB基因在不同肿瘤中的表达和突变。结果表明,ASB基因存在显著的拷贝数变异(CNV)和单核苷酸变异(SNV)。ASB基因在不同肿瘤组织中的表达存在较大差异,不同水平的ASB基因甲基化影响基因表达和肿瘤进展。通过LASSO回归分析,我们建立了基于5个ASB基因(ASB6、ASB7、ASB8、ASB13和ASB17)的KIRC生存模型。此外,采用ROC曲线分析来评估生存模型的准确性。通过单因素和多因素COX回归分析,我们证明该模型的风险评分可能是KIRC个体的独立危险因素。综上所述,我们的KIRC生存模型可以准确预测患者的未来生存。此外,我们还通过nomogram对生存模型进行了量化。这一系列的研究结果证实ASB基因是KIRC潜在的预测标记和靶向治疗。我们基于5个ASB基因的KIRC生存模型可以帮助更多的临床从业者对KIRC患者的预后做出准确的判断。
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来源期刊
Genetics research
Genetics research 生物-遗传学
自引率
6.70%
发文量
74
审稿时长
>12 weeks
期刊介绍: Genetics Research is a key forum for original research on all aspects of human and animal genetics, reporting key findings on genomes, genes, mutations and molecular interactions, extending out to developmental, evolutionary, and population genetics as well as ethical, legal and social aspects. Our aim is to lead to a better understanding of genetic processes in health and disease. The journal focuses on the use of new technologies, such as next generation sequencing together with bioinformatics analysis, to produce increasingly detailed views of how genes function in tissues and how these genes perform, individually or collectively, in normal development and disease aetiology. The journal publishes original work, review articles, short papers, computational studies, and novel methods and techniques in research covering humans and well-established genetic organisms. Key subject areas include medical genetics, genomics, human evolutionary and population genetics, bioinformatics, genetics of complex traits, molecular and developmental genetics, Evo-Devo, quantitative and statistical genetics, behavioural genetics and environmental genetics. The breadth and quality of research make the journal an invaluable resource for medical geneticists, molecular biologists, bioinformaticians and researchers involved in genetic basis of diseases, evolutionary and developmental studies.
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