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组织和血浆中的 microRNA 特征可预测 CT 检测肺癌的发生和预后。

MicroRNA signatures in tissues and plasma predict development and prognosis of computed tomography detected lung cancer.

机构信息

Tumor Genomics Unit, Department of Experimental Oncology and Molecular Medicine, and Unit of Thoracic Surgery, Fondazione IRCCS Istituto Nazionale Tumori, 20133 Milan, Italy.

出版信息

Proc Natl Acad Sci U S A. 2011 Mar 1;108(9):3713-8. doi: 10.1073/pnas.1100048108. Epub 2011 Feb 7.

Abstract

The efficacy of computed tomography (CT) screening for early lung cancer detection in heavy smokers is currently being tested by a number of randomized trials. Critical issues remain the frequency of unnecessary treatments and impact on mortality, indicating the need for biomarkers of aggressive disease. We explored microRNA (miRNA) expression profiles of lung tumors, normal lung tissues and plasma samples from cases with variable prognosis identified in a completed spiral-CT screening trial with extensive follow-up. miRNA expression patterns significantly distinguished: (i) tumors from normal lung tissues, (ii) tumor histology and growth rate, (iii) clinical outcome, and (iv) year of lung cancer CT detection. Interestingly, miRNA profiles in normal lung tissues also displayed remarkable associations with clinical features, suggesting the influence of a permissive microenvironment for tumor development. miRNA expression analyses in plasma samples collected 1-2 y before the onset of disease, at the time of CT detection and in disease-free smokers enrolled in the screening trial, resulted in the generation of miRNA signatures with strong predictive, diagnostic, and prognostic potential (area under the ROC curve ≥ 0.85). These signatures were validated in an independent cohort from a second randomized spiral-CT trial. These results indicate a role for miRNAs in lung tissues and plasma as molecular predictors of lung cancer development and aggressiveness and have theoretical and clinical implication for lung cancer management.

摘要

计算机断层扫描(CT)筛查在重度吸烟者中早期肺癌检测的疗效目前正在一些随机试验中进行测试。仍存在关键问题是不必要的治疗频率和对死亡率的影响,这表明需要有侵袭性疾病的生物标志物。我们探索了在一项已完成的螺旋 CT 筛查试验中,根据预后变量确定的病例的肺肿瘤、正常肺组织和血浆样本中的 microRNA(miRNA)表达谱,并进行了广泛的随访。miRNA 表达模式显著区分:(i)肿瘤与正常肺组织,(ii)肿瘤组织学和生长速度,(iii)临床结果,以及(iv)肺癌 CT 检测的年份。有趣的是,正常肺组织中的 miRNA 谱也与临床特征显示出显著关联,这表明肿瘤发展的许可微环境的影响。在疾病发生前 1-2 年、在 CT 检测时以及在筛查试验中招募的无疾病吸烟者采集的血浆样本中的 miRNA 表达分析,产生了具有强大预测、诊断和预后潜力的 miRNA 特征(ROC 曲线下面积≥0.85)。这些特征在第二个随机螺旋 CT 试验的独立队列中得到了验证。这些结果表明,miRNA 在肺组织和血浆中作为肺癌发生和侵袭性的分子预测因子具有作用,并且对肺癌管理具有理论和临床意义。

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