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血清和尿液作为检测卵巢癌的miRNA标志物来源的比较

Comparison of Serum and Urine as Sources of miRNA Markers for the Detection of Ovarian Cancer.

作者信息

Kupec Tomas, Bleilevens Andreas, Klein Birgit, Hansen Thomas, Najjari Laila, Wittenborn Julia, Stickeler Elmar, Maurer Jochen

机构信息

Department of Gynecology and Obstetrics, University Hospital RWTH Aachen, 52074 Aachen, Germany.

出版信息

Biomedicines. 2023 Sep 11;11(9):2508. doi: 10.3390/biomedicines11092508.

Abstract

Ovarian cancer is the second most fatal gynecological cancer. Early detection, which could be achieved through widespread screening, has not yet had an impact on mortality. The aim of our pilot study was to investigate the expression of miRNAs analyzed by a human miRNA microarray chip in urine and serum of patients with ovarian cancer. We analyzed three serum and three urine samples from healthy donors and five serum and five urine samples from patients with ovarian cancer taken at first diagnosis, before any treatment. We selected the seven miRNAs with the highest expression fold change in the microarray chip (cancer vs. control) in urine and serum, for validation by qPCR. We were able to validate two of the seven miRNAs in serum. In contrast to these findings, we were able to validate all of the top seven miRNAs identified in urine using qPCR. The top seven miRNAs in urine identified by microarray chip showed significantly greater differences in expression between patients with ovarian cancer and healthy donors compared to serum. Based on our finding, we can suggest that urine as a biomaterial is more suitable than serum for miRNA profiling by microarray chip in the search for new biomarkers in ovarian cancer.

摘要

卵巢癌是第二大致命的妇科癌症。通过广泛筛查可实现的早期检测尚未对死亡率产生影响。我们的初步研究目的是调查通过人类miRNA微阵列芯片分析的miRNA在卵巢癌患者尿液和血清中的表达情况。我们分析了来自健康供体的三份血清和三份尿液样本,以及在首次诊断时、未进行任何治疗前采集的五份卵巢癌患者的血清和五份尿液样本。我们选择了在微阵列芯片中(癌症组与对照组相比)尿液和血清中表达倍数变化最高的七种miRNA,通过qPCR进行验证。我们能够在血清中验证七种miRNA中的两种。与这些结果相反,我们能够通过qPCR验证在尿液中鉴定出的所有七种顶级miRNA。与血清相比,通过微阵列芯片在尿液中鉴定出的七种顶级miRNA在卵巢癌患者和健康供体之间的表达差异显著更大。基于我们的发现,我们可以认为在寻找卵巢癌新生物标志物时,尿液作为一种生物材料比血清更适合用于通过微阵列芯片进行miRNA分析。

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