Predictive value of microRNA let-7a expression for efficacy and prognosis of radiotherapy in patients with lung cancer brain metastasis: A case-control study

微小RNA let-7a表达对肺癌脑转移患者放疗疗效和预后的预测价值:一项病例对照研究

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Abstract

BACKGROUND: As a well-known cancer with high mortality, lung cancer has been implied to be closely associated with brain metastasis. Despite notable advances, effective treatment methods are still in urgent need. This study aims to investigate the value of serum microRNA-let-7a (miR-let-7a) expression in predicting efficacy and prognosis of radiotherapy in patients with lung cancer brain metastasis. METHODS: To begin with, reverse transcription quantitative polymerase chain reaction (RT-qPCR) was performed for better understand of the correlation between miR-let-7a and lung cancer. Afterwards, the relationship between serum miR-let-7a expression and radiotherapy efficacy was analyzed by receiver operating characteristic curve analysis. Following successful transfection, RT-qPCR and Western blot assay were utilized for evaluating the involvement of miR-let-7a in regulation of DICER1 expression in lung cancer cell line. Then, whether miR-let-7a was implicated in proliferation and cell cycle distribution of lung cancer cells were confirmed by cell counting kit-8 assay and flow cytometry respectively. RESULTS: Initially, it was revealed that serum miR-let-7a expression was decreased in lung cancer. Later, we found that decreased miR-let-7a displayed an unfavorable role in radiotherapy efficacy and overall survival rate of patients with lung cancer brain metastasis. After the successful transfection, the inverse relationship between miR-let-7a and DICER1 expression was uncovered. Meanwhile, biological behaviors of lung cancer cells were presented to be limited after transfection of overexpressed miR-let-7a. CONCLUSION: Our findings demonstrated that the lower expression of miR-let-7a in patients with lung cancer brain metastasis was closely related to unfavorable efficacy and prognosis of radiotherapy, and it may be an important predictive biomarker by regulation of DICER1.

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