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首页> 外文期刊>Majallah-i pizishki-i Urumiyah. >STUDY OF GENES AS BIOMARKERS IN DISTINGUISH CANCEROUS FROM NORMAL TISSUE SAMPLES IN PROSTATE CANCER
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STUDY OF GENES AS BIOMARKERS IN DISTINGUISH CANCEROUS FROM NORMAL TISSUE SAMPLES IN PROSTATE CANCER

机译:前列腺癌与正常组织样本中癌基因的生物标志物研究

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Background &?Aims : Prostate cancer (PCa) is the second most common cancer in men worldwide. The identification of sensitive and specific biomarkers in tissue and serum is of utmost importance to reduce the mortality of prostate cancer. Since that, early detection of cancer has an important role in treatment, in this study we tried to identify genes that could potentially effective in early screening for prostate cancer. Using logistic regression, suitable model to screen tumor samples from normal samples was designed. Materials & Methods : In this study, gene expression data of metastatic and non-metastatic cancer samples and normal prostate samples were collected from the NCBI database. By examining the expression level of genes in these samples, valuable genes for screening were identified. Results : Using logistic regression two model were designed based on the increase or decrease in the expression of genes. The Area under the curve, sensitivity and specificity for the first model were, respectively, 0.968, 0.911 and 0.914 and for the second model 0.991, 0.951 and 0.956, respectively. Conclusion : Due to the high value of sensitivity and specificity in the designed models, studied Genes have the potential for screening prostate cancer in the early stages and metastasis stages of cancer.
机译:背景与目的:前列腺癌(PCa)是全球男性中第二大最常见的癌症。在组织和血清中鉴定敏感和特异性生物标志物对于降低前列腺癌的死亡率至关重要。从那以后,癌症的早期发现在治疗中起着重要的作用,在这项研究中,我们试图确定可能对前列腺癌的早期筛查有效的基因。使用逻辑回归,设计了合适的模型来从正常样品中筛选肿瘤样品。材料与方法:在这项研究中,从NCBI数据库中收集了转移性和非转移性癌症样品以及正常前列腺样品的基因表达数据。通过检查这些样品中基因的表达水平,可以鉴定出有价值的基因。结果:使用逻辑回归分析,根据基因表达的增加或减少设计了两个模型。第一个模型的曲线下面积,灵敏度和特异性分别为0.968、0.911和0.914,第二个模型的曲线下面积分别为0.991、0.951和0.956。结论:由于设计模型中敏感性和特异性的高价值,研究的基因具有筛查前列腺癌的早期和转移阶段的潜力。

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