摘 要：胰腺癌（PAAD）是一种发生在胰腺的恶性肿瘤，起病隐匿，早期诊断困难，进展迅速，生存时间短，是预后最差的恶性肿瘤之一，被称为“癌中之王”。胰腺癌的致病因素目前还尚不清楚，但生物标志物的发现为胰腺癌的预后诊断指明了一个方向。文章采用了数据挖掘的方法对多个胰腺癌的 RNA 基因表达数据进行分析，挖掘出可能用于胰腺癌诊断的生物标志物。最后经生存分析验证，发现 NDC80，CDC20，CCNB1，KIF11 这四个标志物可能对胰腺癌的治疗起到减轻疼痛和降低病情恶化程度的作用。
关键词：胰腺癌；生物标志物；基因表达；limma；Kaplan-Meier；数据挖掘
DOI:10.19850/j.cnki.2096-4706.2023.05.029
中图分类号：TP391 文献标识码：A 文章编号：2096-4706（2023）05-0120-04
Application of Data Mining in Pancreatic Adenocarcinoma
XIA Wentao, WANG Yun, YAN Xinping
(School of Information Engineering, Jingdezhen Ceramic University, Jingdezhen 333403, China)
Abstract: Pancreatic Adenocarcinoma (PAAD) is a malignant tumor that occurs in the pancreas with insidious onset, difficult early diagnosis, rapid progression and short survival time. It is one of the malignant tumors with the worst prognosis. Pancreatic Adenocarcinoma is known as the “king of cancers”. The pathogenic factors of Pancreatic Adenocarcinoma are currently unclear, but the discovery of biomarkers points to another direction for the prognosis and diagnosis of Pancreatic Adenocarcinoma. In this paper, the method of data mining is used to analyze the RNA gene expression data of multiple patients with Pancreatic Adenocarcinoma, and the biomarkers that may be used for the diagnosis of Pancreatic Adenocarcinoma are mined. Finally, after verification by survival analysis, it is found that the four biomarkers of NDC80, CDC20, CCNB1 and KIF11 may play a role in reducing pain and the degree of disease deterioration in the treatment of Pancreatic Adenocarcinoma.
Keywords: Pancreatic Adenocarcinoma; biomarker; gene expression; limma; Kaplan-Meier; data mining
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作者简介：夏文韬（1996—），男，汉族，江苏宜兴人，硕士研究生在读，主要研究方向：数据挖掘和生物大数据处理；通信作者：王筠（1992—），女，汉族，江西景德镇人，助教，主要研究方向：统计学理论与应用研究。