Pusztai Lajos
Department of Breast Medical Oncology, University of Texas M.D. Anderson Cancer Center, Houston, Texas 77230-1439, USA.
Oncologist. 2008 Apr;13(4):350-60. doi: 10.1634/theoncologist.2007-0216.
Breast cancer is a clinically heterogeneous disease that can affect individuals with seemingly identical clinicopathologic parameters differently. This clinical heterogeneity is driven to a large extent by abnormal gene expression within tumors. Investigators now have the ability to identify the gene-expression fingerprint of an individual's tumor. This information may be used to rationally design therapeutic targets in the future, and also to predict the clinical course of an individual's disease, including response to a specific treatment. Genetic profiles of tumors are now being correlated with clinical outcome, and several prognostic and predictive indicators have emerged based on this research. There are at least four commercially available predictive or prognostic tests, and several more are looming on the horizon. The data gathered from these tests augment standard diagnostic and prognostic information obtained from traditional clinical pathological variables. The advent of gene-profiling technologies started to change the conduct of clinical trials. In the not too distant future, prospective tissue collection for molecular analysis may become routine in order to stratify patients for treatment arms and to optimize treatment strategies based on molecular features of the cancer. Coordinated efforts among oncologists, pathologists, surgeons, laboratory scientists, statisticians, and regulators will be essential in the quest to incorporate genetic profiling and molecular hypotheses into clinical trial planning and conduct.
乳腺癌是一种临床异质性疾病,对于具有看似相同临床病理参数的个体,其影响可能不同。这种临床异质性在很大程度上是由肿瘤内异常的基因表达驱动的。研究人员现在有能力识别个体肿瘤的基因表达特征。这些信息未来可用于合理设计治疗靶点,还能预测个体疾病的临床进程,包括对特定治疗的反应。肿瘤的基因图谱现在正与临床结果相关联,基于这项研究已经出现了一些预后和预测指标。目前至少有四种商业可用的预测或预后测试,还有几种也即将出现。从这些测试中收集的数据丰富了从传统临床病理变量获得的标准诊断和预后信息。基因谱分析技术的出现开始改变临床试验的开展方式。在不久的将来,为进行分子分析而进行前瞻性组织收集可能会成为常规操作,以便根据癌症的分子特征对患者进行分层并优化治疗策略。肿瘤学家、病理学家、外科医生、实验室科学家、统计学家和监管机构之间的协同努力对于将基因谱分析和分子假说纳入临床试验规划与实施的探索至关重要。