Mary Babb Randolph Cancer Center/Community Medicine, West Virginia University, Morgantown, WV, USA.
Int J Biol Markers. 2010 Oct-Dec;25(4):219-28. doi: 10.5301/jbm.2010.6079.
Genomic instability, as reflected in specific chromosomal aneuploidies and variation in the nuclear DNA content, is a defining feature of human carcinomas. It is solidly established that the degree of genomic instability influences clinical outcome. We have recently identified a 12-gene expression signature that discerned genomically stable from unstable breast carcinomas. This gene expression signature was also useful to predict, with high accuracy, the clinical course in independent multiple published breast cancer cohorts. From a biological point of view, this result confirmed the central role of genomic instability for a tumor's ability to adapt to external challenges and selective pressure, and hence for continued survival fitness. This prompted us to investigate whether this genomic instability signature could also predict clinical outcome in other cancer types of epithelial origin, including colorectal tumors, non-small cell lung carcinomas, and ovarian cancer.
The results show that the gene expression signature that defines genomic instability and poor outcome in breast cancer contributes significantly more accurate (p<0.05 compared with random prediction) prognostic information in multiple cancer types independent of established clinical parameters. The 12-gene genomic instability signature stratified patients into high- and low-risk groups with distinct postoperative survival in three non-small cell lung cancer cohorts (n=637) in Kaplan-Meier analyses (log-rank p<0.05). It predicted recurrence in colon cancer patients (n=92) with an overall accuracy greater than 69% (p=0.04) in cross-cohort validation. It quantified relapse-free survival in ovarian cancer (n=124; log-rank p<0.05). Functional pathway analysis revealed interactions between the 12 signature genes and well-known cancer hallmarks.
The degree of genomic instability has diagnostic and prognostic implications. It is tempting to speculate that pursuing genomic instability therapeutically could provide entry points for a target that is unique to cancer cells.
基因组不稳定性,反映在特定的染色体非整倍体和核 DNA 含量的变化上,是人类癌的一个明确特征。已有确凿的证据表明,基因组不稳定性的程度影响临床结果。我们最近确定了一个 12 基因表达特征,可以区分基因组稳定和不稳定的乳腺癌。该基因表达特征也可用于准确预测独立的多个已发表的乳腺癌队列的临床过程。从生物学的角度来看,这一结果证实了基因组不稳定性对于肿瘤适应外部挑战和选择压力的核心作用,因此对于持续的生存适应性。这促使我们研究这个基因组不稳定性特征是否也可以预测其他上皮来源的癌症类型的临床结果,包括结直肠肿瘤、非小细胞肺癌和卵巢癌。
结果表明,在乳腺癌中定义基因组不稳定性和不良预后的基因表达特征在多种独立于既定临床参数的癌症类型中提供了更准确的预后信息(与随机预测相比,p<0.05)。在三个非小细胞肺癌队列(n=637)的 Kaplan-Meier 分析中(对数秩检验 p<0.05),12 个基因基因组不稳定性特征将患者分层为高风险和低风险组,具有明显不同的术后生存。它预测了结肠癌患者(n=92)的复发,在跨队列验证中的整体准确性大于 69%(p=0.04)。它量化了卵巢癌(n=124)的无复发生存(对数秩检验 p<0.05)。功能途径分析显示,12 个特征基因与已知的癌症标志之间存在相互作用。
基因组不稳定性的程度具有诊断和预后意义。人们不禁推测,从治疗基因组不稳定性入手可能为癌症细胞所特有的靶点提供切入点。