Wenzhou Hospital of Traditional Chinese Medicine Affiliated to Zhejiang Chinese Medicine University, No. 9 Jiaowei Road, Lucheng District, Wenzhou City, Zhejiang Province, China.
Department of Otolaryngology Head and Neck Surgery, The Central Hospital of Wuhan, Tongji Medical College Huazhong University of Science and Technology, Wuhan, Hubei, China.
BMC Pulm Med. 2022 Apr 7;22(1):133. doi: 10.1186/s12890-022-01924-0.
Lung cancer is one of the main results in tumor-related mortality. Methylation differences reflect critical biological features of the etiology of LUAD and affect prognosis.
In the present study, we constructed a prediction prognostic model integrating various DNA methylation used high-throughput omics data for improved prognostic evaluation.
Overall 21,120 methylation sites were identified in the training dataset. Overall, 237 promoter genes were identified by genomic annotation of 205 CpG loci. We used Akakike Information Criteria (AIC) to obtain the validity of data fitting, but to prevent overfitting. After AIC clustering, specific methylation sites of cg19224164 and cg22085335 were left. Prognostic analysis showed a significant difference among the two groups (P = 0.017). In particular, the hypermethylated group had a poor prognosis, suggesting that these methylation sites may be a marker of prognosis.
The model might help in the identification of unknown biomarkers in predicting patient prognosis in LUAD.
肺癌是肿瘤相关死亡的主要原因之一。甲基化差异反映了 LUAD 病因学的关键生物学特征，并影响预后。
本研究构建了一个整合了各种 DNA 甲基化的预测预后模型，利用高通量组学数据进行了改进的预后评估。
在训练数据集中鉴定出了 21120 个甲基化位点。总体而言，通过 205 个 CpG 位点的基因组注释鉴定出了 237 个启动子基因。我们使用赤池信息量准则 (AIC) 获得数据拟合的有效性，但要防止过度拟合。经过 AIC 聚类后，留下了 cg19224164 和 cg22085335 这两个特异性甲基化位点。预后分析显示两组间有显著差异（P=0.017）。特别是高甲基化组预后较差，提示这些甲基化位点可能是预后的标志物。
该模型可能有助于识别 LUAD 患者预后预测中未知的生物标志物。
