Using Gene Expression Profiling to Predict Response and Prognosis in Gastrointestinal Cancers-The Promise and the Perils
Using Gene Expression Profiling to Predict Response and Prognosis in Gastrointestinal Cancers-The Promise and the Perils
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DOI：
10.1245/s10434-010-1433-1
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发表时间：
2011-05-01
影响因子：
3.7
通讯作者：
Phillips, Wayne A.
中科院分区：
文献类型：
--
作者：
Brettingham-Moore, Kate H.;Duong, Cuong P.;Phillips, Wayne A.
癌症治疗现在正朝着个性化的方向发展，有望提高反应率和生存率。许多研究已经使用微阵列来研究胃肠道（GI）癌症患者中表达谱的预测潜力。然而，虽然已经为GI癌症患者生成了许多与反应和预后相关的鲁棒预测分类器，但这些分类器尚未过渡到临床。主要障碍是针对相同肿瘤类型和结果鉴定的预测基因列表之间的有限交叉验证。实验设计、分析和结果解释的差异都导致了这种变化，许多因素影响哪些基因被突出显示为预测基因。虽然预测基因组学显示出巨大的潜力，但它仍然是一个相对较新的领域，并且来自微阵列数据的预测基因列表的验证仍然是一个挑战。未来的研究必须仔细考虑实验设计的各个方面，以确保可以开发出临床适用的预测性测试。考虑到这一点，在基于微阵列的平台可以常规用于定制GI癌症治疗和改变临床实践之前，必须进行更广泛的合作研究。更大的队列和方法的一致性将使这项研究的结果能够过渡到临床。
Cancer treatment is now moving toward a personalized approach, promising improved rates of response and survival. A number of studies have employed the use of microarrays to investigate the predictive potential of expression profiling in gastrointestinal (GI) cancer patients. However while many robust predictive classifiers relating to response and prognosis have been generated for GI cancer patients, these have yet to make the transition to the clinic. The main obstacle is the limited cross validation between predictive gene lists identified for the same tumor type and outcome. Differences in the experimental design, analysis, and interpretation of results all contribute to this variation, with numerous factors influencing which genes are highlighted as predictive. While predictive genomics shows immense potential, it is still a relatively new field and the validation of predictive gene lists derived from microarray data remains a challenge. Future studies must carefully consider all aspects of experimental design to ensure a clinically applicable predictive test can be developed. With this in mind, more extensive and collaborative research must be undertaken before microarray-based platforms can be used routinely in tailoring GI cancer treatment and change clinical practice. Larger cohorts and consistency in methodology will enable the findings from this research to make the transition to the clinic.