A novel multimodal prediction model based on DNA methylation biomarkers and low-dose computed tomography images for identifying early-stage lung cancer  

作　　者：Jing Zhang Haohua Yao Chunliu Lai Xue Sun Xiujuan Yang Shurong Li Yubiao Guo Junhang Luo Zhihua Wen Kejing Tang 

机构地区：[1]Division of Pulmonary and Critical Care Medicine,the First Affiliated Hospital of Sun Yat-sen University,Guangzhou 510080,China [2]Department of Urology,Guangdong Provincial People’s Hospital,Guangdong Academy of Medical Sciences,Guangzhou 510080,China [3]Department of Respiratory and Critical Care Medicine,the Fourth People’s Hospital of Shenyang,Shenyang 110031,China [4]Department of Pharmacy,Zhujiang Hospital,Southern Medical University,Guangzhou 510280,China [5]Department of Radiology,the First Affiliated Hospital of Sun Yat-sen University,Guangzhou 510080,China [6]Department of Urology,the First Affiliated Hospital of Sun Yat-sen University,Guangzhou 510080,China [7]Department of Pharmacy,the First Affiliated Hospital of Sun Yat-Sen University,Guangzhou 510080,China

出　　处：《Chinese Journal of Cancer Research》2023年第5期511-525,共15页中国癌症研究（英文版）

基　　金：supported by the National Natural Science Foundation of China(No.81600065 and No.82073805).

摘　　要：Objective:DNA methylation alterations are early events in carcinogenesis and immune signalling in lung cancer.This study aimed to develop a model based on short stature homeobox 2 gene (SHOX2)/prostaglandin E receptor 4gene (PTGER4) DNA methylation in plasma,appearance subtype of pulmonary nodules (PNs) and low-dose computed tomography (LDCT) images to distinguish early-stage lung cancers.Methods:We developed a multimodal prediction model with a training set of 257 individuals.The performance of the multimodal prediction model was further validated in an independent validation set of 42 subjects.In addition,we explored the association between SHOX2/PTGER4 DNA methylation and driver gene mutations in lung cancer based on data from The Cancer Genome Atlas (TCGA) portal.Results:There were significant differences between the early-stage lung cancers and benign groups in the methylation levels.The area under a receiver operator characteristic curve (AUC) of SHOX2 in patients with solid nodules,mixed ground-glass opacity nodules and pure ground-glass opacity nodules were 0.693,0.497 and 0.864,respectively,while the AUCs of PTGER4 were 0.559,0.739 and 0.619,respectively.With the highest AUC of0.894,the novel multimodal prediction model outperformed the Mayo Clinic model (0.519) and LDCT-based deep learning model (0.842) in the independent validation set.Database analysis demonstrated that patients with SHOX2/PTGER4 DNA hypermethylation were enriched in TP53 mutations.Conclusions:The present multimodal prediction model could more efficiently distinguish early-stage lung cancer from benign PNs.A prognostic index based on DNA methylation and lung cancer driver gene alterations may separate the patients into groups with good or poor prognosis.

关 键 词：Pulmonary nodules susceptible loci serum tumor biomarkers polygenic risk score diagnosis 

分 类 号：R73[医药卫生—肿瘤]