Kratz Johannes R, Jablons David M
Department of Surgery, University of California San Francisco Cancer Center, CA 94143-0128, USA.
Clin Lung Cancer. 2009 May;10(3):151-7. doi: 10.3816/CLC.2009.n.021.
Patients with early-stage lung cancer demonstrate significant recurrence rates and lower-than-expected survival rates after surgical resection, indicating that our current staging methods do not adequately predict outcome. Since the last revision of the TNM staging system, a number of genomic models have been proposed which more accurately predict prognosis in patients with early-stage lung cancer. A variety of prognostic genomic models based on gene-expression profiling and quantitative polymerase chain reaction (PCR) are able to stratify patients with early-stage lung cancer into high- and low-risk groups with respect to disease-free and overall survival. In the future, clinical application of these models may ultimately dictate both the use of adjuvant therapy as well as the choice of surgical procedure in patients with early-stage lung cancer. An effort to develop a robust genomic model for use in the clinical setting should be prompted by encouraging results obtained by the use of a quantitative PCR-based genomic signature in the field of breast oncology.
早期肺癌患者在手术切除后显示出显著的复发率和低于预期的生存率，这表明我们目前的分期方法无法充分预测预后。自TNM分期系统上次修订以来，已经提出了一些基因组模型，这些模型能更准确地预测早期肺癌患者的预后。多种基于基因表达谱分析和定量聚合酶链反应（PCR）的预后基因组模型能够将早期肺癌患者根据无病生存期和总生存期分为高风险组和低风险组。未来，这些模型的临床应用最终可能会决定早期肺癌患者辅助治疗的使用以及手术方式的选择。乳腺癌肿瘤学领域中基于定量PCR的基因组特征所取得的鼓舞人心的结果，应促使我们努力开发一种适用于临床的强大基因组模型。
