Prognostic Model of Stage II/III Colon Cancer Constructed using Gene Expression Subtypes and KRAS Mutation Status

Kengo Gotoh, E. Shinto, Y. Yoshida, H. Ueno, Y. Kajiwara, M. Yamadera, K. Nagata, H. Tsuda, J. Yamamoto, K. Hase
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引用次数: 6

Abstract

Objectives: Cancer subtypes classified according to DNA microarray data predict prognosis with high accuracy. Here we constructed a new colon cancer (CC) subtype classification based on only of genes with known biological functions with the aim of establishing a new prognostic model for clinical use. Methods: We performed an expression correlation analysis using data for 73 primary CC cases in the public dataset (learning set), focusing on genes located on the long arms of chromosomes 18 and 20 and stromal-related genes. We determined the representation of each gene in the modules with closely correlated expression levels in the same module. Mutations in KRAS, BRAF and TP53 were assessed using direct sequencing. Microsatellite instability (MSI) was analyzed using the Bethesda reference panel. Results: We constructed a discriminant model with a view to classifying CC into three subtypes (“stromal”, “chromosomal instability [CIN]-like”, “MSI-like”) based on the expression levels of 55 genes of the Learning set. When we applied this predictor to microarray data from other patients with stage II/III colon cancer (n=258, test set), we discovered a significant difference in diseasefree survival between the stromal subtype and the other subtypes (p=1.25e-03). Accordingly, we created an integrated prognostic model for classifying the patients into high- and low-risk groups according to the expression levels of the 55 genes and KRAS mutations (p=1.56e-06). Analysis of independent specimens from patients with stage II/III colon cancer who underwent radical resection (n=59, validation set) confirmed the prognostic value of our model (p=4.75e-02). Conclusion: The model produced a biologically discriminatory classifier that associated MSI status with the risk of recurrence that may be clinically applicable to the selection of patients with Stage II/ III CC for adjuvant therapy.
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利用基因表达亚型和KRAS突变状态构建II/III期结肠癌预后模型
目的:通过DNA微阵列数据对肿瘤亚型进行分类,准确预测预后。在这里,我们构建了一个新的结肠癌(CC)亚型分类,仅基于已知的生物学功能基因,目的是建立一个新的预后模型,供临床使用。方法:我们使用公共数据集(学习集)中的73例原发性CC病例的数据进行表达相关性分析,重点关注位于18号和20号染色体长臂上的基因以及基质相关基因。我们确定了每个基因在模块中的代表性,在同一模块中具有密切相关的表达水平。使用直接测序评估KRAS、BRAF和TP53的突变。采用Bethesda参考面板对微卫星不稳定性进行了分析。结果:基于Learning集合中55个基因的表达水平,我们构建了一个判别模型,将CC分为三种亚型(“基质型”、“染色体不稳定性[CIN]样”、“msi样”)。当我们将该预测因子应用于其他II/III期结肠癌患者的微阵列数据(n=258,测试集)时,我们发现基质亚型和其他亚型之间的无病生存率存在显著差异(p=1.25e-03)。因此,我们创建了一个综合预后模型,根据55个基因的表达水平和KRAS突变将患者分为高危组和低危组(p=1.56e-06)。对接受根治性切除术的II/III期结肠癌患者的独立标本(n=59,验证组)的分析证实了我们的模型的预后价值(p=4.75e-02)。结论:该模型产生了一个生物学区分分类器,将MSI状态与复发风险联系起来,可能在临床上适用于II/ III期CC患者进行辅助治疗的选择。
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