Non-small cell lung cancer (NSCLC) is the most popular and dangerous type of lung cancer. Adjuvant chemotherapy (ACT) is the main treatment after surgery resection to prevent the patient from cancer recurrence. However, ACT could be toxic and unhelpful in some cases. Therefore, it is highly desired in clinical applications to predict the treatment outcomes of chemotherapy. Conventional methods of predicting cancer treatment rely solely on histopathology and the results are not reliable in some cases. This study aims at building a predictive model to identify who needs ACT treatment and who should avoid it. To this end, the authors propose an innovative method to identify NSCLC-related prognostic genes from microarray gene-expression datasets. They also propose a new model using gene-expression programming algorithm for ACT classification. The proposed model was evaluated on integrated microarray datasets from four institutes and compared with four representative methods: general regression neural network, decision tree, support vector machine and naive Bayes. Evaluation results demonstrated the effectiveness of the proposed model with accuracy 89.8% which is higher than other representative models. They obtained four probes (four genes) that can get good prediction results. These genes are 204891_s_at (LCK), 208893_s_at (DUSP6), 202454_s_at (ERBB3) and 201076_at (MMD).

中文翻译：

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非小细胞肺癌的癌症辅助化疗预测模型。

非小细胞肺癌 (NSCLC) 是最流行和最危险的肺癌类型。辅助化疗（ACT）是手术切除后预防癌症复发的主要治疗方法。然而，在某些情况下，ACT 可能有毒且无益。因此，在临床应用中非常需要预测化疗的治疗结果。预测癌症治疗的传统方法仅依赖于组织病理学，在某些情况下结果并不可靠。本研究旨在建立一个预测模型，以确定哪些人需要 ACT 治疗以及哪些人应该避免治疗。为此，作者提出了一种从微阵列基因表达数据集中识别 NSCLC 相关预后基因的创新方法。他们还提出了一种使用基因表达编程算法进行 ACT 分类的新模型。所提出的模型在来自四个研究所的集成微阵列数据集上进行了评估，并与四种代表性方法进行了比较：一般回归神经网络、决策树、支持向量机和朴素贝叶斯。评估结果证明了所提模型的有效性，准确率为 89.8%，高于其他代表性模型。他们获得了可以得到很好预测结果的四个探针（四个基因）。这些基因是 204891_s_at (LCK)、208893_s_at (DUSP6)、202454_s_at (ERBB3) 和 201076_at (MMD)。8%，高于其他代表性机型。他们获得了可以得到很好预测结果的四个探针（四个基因）。这些基因是 204891_s_at (LCK)、208893_s_at (DUSP6)、202454_s_at (ERBB3) 和 201076_at (MMD)。8%，高于其他代表性机型。他们获得了可以得到很好预测结果的四个探针（四个基因）。这些基因是 204891_s_at (LCK)、208893_s_at (DUSP6)、202454_s_at (ERBB3) 和 201076_at (MMD)。