Gene expression-based, individualized outcome prediction for surgically treated lung cancer patients
Gene expression-based, individualized outcome prediction for surgically treated lung cancer patients
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DOI：
10.1038/sj.onc.1207697
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发表时间：
2004-07-08
期刊：
影响因子：
8
通讯作者：
Takahashi, T
中科院分区：
文献类型：
--
作者：
Tomida, S;Koshikawa, K;Takahashi, T
通过表达pro成功构建了个性化结果预测分类器。对50例非小细胞肺癌（NSCLC）病例中总共8644个基因进行了分析，这些病例在规定的短时间内连续进行了手术，并随访了5年以上。由此产生的 NSCLC 分类器对于预测特定患者术后 5 年的生存或死亡的准确度为 82%。此外，由于两个主要组织学类别在结果相关表达特征方面可能有所不同，因此还构建了组织学类型特异性结果分类器。由此产生的高度预测分类器专为非鳞状细胞癌设计，显示出超过 90% 的预测准确性，与疾病阶段无关。除了腺癌中存在异质性之外，我们的无监督分层聚类分析首次揭示了鳞状细胞癌临床病理学相关亚类的存在，这些亚类在侵袭性生长和预后方面具有显着差异。这一发现清楚地表明，非小细胞肺癌包含不同的亚类，即使在一种组织学类型中也具有相当大的异质性。总的来说，这些发现不仅可以增进我们对肺癌生物学的理解，而且可以提高我们根据预测结果进行个体化术后治疗的能力。
Individualized outcome prediction classifiers were successfully constructed through expression pro. ling of a total of 8644 genes in 50 non-small-cell lung cancer (NSCLC) cases, which had been consecutively operated on within a defined short period of time and followed up for more than 5 years. The resultant classifier of NSCLCs yielded 82% accuracy for forecasting survival or death 5 years after surgery of a given patient. In addition, since two major histologic classes may differ in terms of outcome-related expression signatures, histologic-type-specific outcome classifiers were also constructed. The resultant highly predictive classifiers, designed specifically for nonsquamous cell carcinomas, showed a prediction accuracy of more than 90% independent of disease stage. In addition to the presence of heterogeneities in adenocarcinomas, our unsupervised hierarchical clustering analysis revealed for the first time the existence of clinicopathologically relevant subclasses of squamous cell carcinomas with marked differences in their invasive growth and prognosis. This finding clearly suggests that NSCLCs comprise distinct subclasses with considerable heterogeneities even within one histologic type. Overall, these findings should advance not only our understanding of the biology of lung cancer but also our ability to individualize postoperative therapies based on the predicted outcome.