Division of Clinical Research, The First Hospital of Jilin University, 71 Xinmin Street, Changchun, 130021, Jilin, China.
BMC Bioinformatics. 2019 Apr 11;20(1):177. doi: 10.1186/s12859-019-2775-8.
Monotonically expressed genes (MEGs) are genes whose expression values increase or decrease monotonically as a disease advances or time proceeds. Non-small cell lung cancer (NSCLC) is a multistage progression process resulting from genetic sequences mutations, the identification of MEGs for NSCLC is important.
With the aid of a feature selection algorithm capable of identifying MEGs - the MFSelector method - two sets of potential MEGs were selected in this study: the MEGs across the different pathologic stages and the MEGs across the risk levels of death for the NSCLC patients at early stages. For the lung adenocarcinoma (AC) subtypes no statistically significant MEGs were identified across pathologic stages, however dozens of MEGs were identified across the risk levels of death. By contrast, for the squamous cell lung carcinoma (SCC) there were no statistically significant MEGs as either stage or risk level advanced.
The pathologic stage of non-small cell lung cancer patients at early stages has no prognostic value, making the identification of prognostic gene signatures for them more meaningful and highly desirable.
单调表达基因（MEGs）是指随着疾病的进展或时间的推移，其表达值单调增加或减少的基因。非小细胞肺癌（NSCLC）是一个多阶段的进展过程，源于遗传序列突变，因此识别 NSCLC 的 MEGs 非常重要。
本研究借助一种能够识别 MEGs 的特征选择算法 - MFSelector 方法 - 选择了两组潜在的 MEGs：跨越不同病理阶段的 MEGs 和早期 NSCLC 患者死亡风险水平跨越的 MEGs。对于肺腺癌（AC）亚型，在病理阶段没有发现具有统计学意义的 MEGs，但是在死亡风险水平上鉴定出了数十个 MEGs。相比之下，对于鳞状细胞肺癌（SCC），无论是阶段还是风险水平的进展，都没有统计学意义的 MEGs。
早期非小细胞肺癌患者的病理阶段没有预后价值，因此，为他们鉴定预后基因特征更有意义，也更受期望。
