Predicting Tumor Mutation Burden and EGFR Mutation Using Clinical and Radiomic Features in Patients with Malignant Pulmonary Nodules

Author:

Yin Wenda,Wang Wei,Zou Chong,Li Ming,Chen Hao,Meng Fanchen,Dong Guozhang,Wang Jie,Yu Qian,Sun Mengting,Xu Lin,Lv Yang,Wang Xiaoxiao,Yin Rong

Abstract

Pulmonary nodules (PNs) shown as persistent or growing ground-glass opacities (GGOs) are usually lung adenocarcinomas or their preinvasive lesions. Tumor mutation burden (TMB) and somatic mutations are important determinants for the choice of strategy in patients with lung cancer during therapy. A total of 93 post-operative patients with 108 malignant PNs were enrolled for analysis (75 cases in the training cohort and 33 cases in the validation cohort). Radiomics features were extracted from preoperative non-contrast computed tomography (CT) images of the entire tumor. Using commercial next generation sequencing, we detected TMB status and somatic mutations of all FFPE samples. Here, 870 quantitative radiomics features were extracted from the segmentations of PNs, and pathological and clinical characteristics were collected from medical records. The LASSO (least absolute shrinkage and selection operator) regression and stepwise logistic regressions were performed to establish the predictive model. For the epidermal growth factor receptor (EGFR) mutation, the AUCs of the clinical model and the integrative model validated by the validation set were 0.6726 (0.4755–0.8697) and 0.7421 (0.5698–0.9144). For the TMB status, the ROCs showed that AUCs of the clinical model and the integrative model validated by the validation set were 0.7808 (0.6231–0.9384) and 0.8462 (0.7132–0.9791). The quantitative radiomics signatures showed potential value in predicting the EGFR mutant and TMB status in GGOs. Moreover, the integrative model provided sufficient information for the selection of therapy and deserves further analysis.

Funder

National Science Foundation of China

Six Talent Project of Jiangsu Province

general project of medical scientific research of Jiangsu Provincial Health Commission

Natural Science Fund for Distinguished Young Scholars of Jiangsu Province

Natural Science Fund of Nanjing University Of Chinese Medicine

Publisher

MDPI AG

Subject

Medicine (miscellaneous)

全球学者库

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"全球学者库"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前全球学者库共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2023 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3