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基因表达谱分析将如何挑战肺癌的未来管理?

How is gene-expression profiling going to challenge the future management of lung cancer?

机构信息

Hematology/Oncology Fellowship Program, University of Miami Miller School of Medicine, Sylvester Comprehensive Cancer Center, 1475 NW 12th Avenue, Miami, FL 33136, USA.

出版信息

Future Oncol. 2009 Aug;5(6):827-35. doi: 10.2217/fon.09.60.

Abstract

Lung cancer has a very high recurrence rate and mortality, even in early stages of the disease. Current clinical staging techniques have limitations in terms of predicting which patients have an increased risk of recurrence, and they are not capable of sorting out who will benefit most from adjuvant therapy in term of survival advantage. The study of genomics has revolutionized how researchers are able to identify new molecular targets and improve patient care through the identification of 'genetic fingerprints or profiles' that might be able to predict responsiveness to therapy or prognosis. Techniques such as microarray-based gene-expression profiling have also allowed investigators to reveal different non-small-cell lung cancer subtypes that have been associated with different clinical outcomes, independently of histology and current clinical staging techniques. We review the current advances in gene-expression profiling and its potential role as a diagnostic and prognostic/predictive biomarker, and how this may translate into a 'personalized medicine' for lung cancer.

摘要

肺癌的复发率和死亡率都非常高,即使在疾病早期也是如此。目前的临床分期技术在预测哪些患者复发风险增加方面存在局限性,并且无法区分谁将从生存优势方面受益于辅助治疗。基因组学的研究改变了研究人员识别新的分子靶标和通过识别“可能能够预测对治疗的反应或预后的遗传指纹或特征”来改善患者护理的方式。基于微阵列的基因表达谱分析等技术还使研究人员能够揭示不同的非小细胞肺癌亚型,这些亚型与不同的临床结果相关,与组织学和当前的临床分期技术无关。我们回顾了基因表达谱分析的最新进展及其作为诊断和预后/预测生物标志物的潜在作用,以及这如何转化为肺癌的“个性化医疗”。

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