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

作者机构：Division of Pulmonary and Critical Care Medicinethe First Affiliated Hospital of Sun Yat-sen UniversityGuangzhou 510080China Department of UrologyGuangdong Provincial People’s HospitalGuangdong Academy of Medical SciencesGuangzhou 510080China Department of Respiratory and Critical Care Medicinethe Fourth People’s Hospital of ShenyangShenyang 110031China Department of PharmacyZhujiang HospitalSouthern Medical UniversityGuangzhou 510280China Department of Radiologythe First Affiliated Hospital of Sun Yat-sen UniversityGuangzhou 510080China Department of Urologythe First Affiliated Hospital of Sun Yat-sen UniversityGuangzhou 510080China Department of Pharmacythe First Affiliated Hospital of Sun Yat-Sen UniversityGuangzhou 510080China 

出 版 物：《Chinese Journal of Cancer Research》 (中国癌症研究（英文版）)

年 卷 期：2023年第35卷第5期

页      面：511-525页

核心收录：

学科分类：1002[医学-临床医学] 100214[医学-肿瘤学] 10[医学] 

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

主　　题：Pulmonary nodules susceptible loci serum tumor biomarkers polygenic risk score diagnosis 

摘      要：Objective:DNA methylation alterations are early events in carcinogenesis and immune signalling in lung *** 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 ***:We developed a multimodal prediction model with a training set of 257 *** performance of the multimodal prediction model was further validated in an independent validation set of 42 *** 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) ***:There were significant differences between the early-stage lung cancers and benign groups in the methylation *** 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,*** 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 *** analysis demonstrated that patients with SHOX2/PTGER4 DNA hypermethylation were enriched in TP53 ***: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.