CT-based radiomic phenotypes of lung adenocarcinoma: a preliminary comparative analysis with targeted next-generation sequencing

Liu, Xiaowen1; Xu, Ting1; Wang, Shuxing1; Chen, Yaxi1; Jiang, Changsi2; Xu, Wuyan3; Gong, Jingshan2

2023-08-17

10.3389/fmed.2023.1191019

FRONTIERS IN MEDICINE   Impact Factor & Quartile

2296-858X

["Objectives: This study aimed to explore the relationship between computed tomography (CT)-based radiomic phenotypes and genomic profiles, including expression of programmed cell death-ligand 1 (PD-L1) and the 10 major genes, such as epidermal growth factor receptor (EGFR), tumor protein 53 (TP53), and Kirsten rat sarcoma viral oncogene (KRAS), in patients with lung adenocarcinoma (LUAD).","Methods: In total, 288 consecutive patients with pathologically confirmed LUAD were enrolled in this retrospective study. Radiomic features were extracted from preoperative CT images, and targeted genomic data were profiled through next-generation sequencing. PD-L1 expression was assessed by immunohistochemistry staining (chi-square test or Fisher's exact test for categorical data and the Kruskal-Wallis test for continuous data). A total of 1,013 radiomic features were obtained from each patient's CT images. Consensus clustering was used to cluster patients on the basis of radiomic features.","Results: The 288 patients were classified according to consensus clustering into four radiomic phenotypes: Cluster 1 (n = 11) involving mainly large solid masses with a maximum diameter of 5.1 +/- 2.0 cm; Clusters 2 and 3 involving mainly part-solid and solid masses with maximum diameters of 2.1 +/- 1.4 cm and 2.1 +/- 0.9 cm, respectively; and Cluster 4 involving mostly small ground-glass opacity lesions with amaximumdiameter of 1.0 +/- 0.9 cm. Di erences inmaximum diameter, PD-L1 expression, and TP53, EGFR, BRAF, ROS1, and ERBB2 mutations among the four clusters were statistically significant. Regarding targeted therapy and immunotherapy, EGFR mutations were highest in Cluster 2 (73.1%); PD-L1 expression was highest in Cluster 1 (45.5%).","Conclusion: Our findings provide evidence that CT-based radiomic phenotypes could non-invasively identify LUADs with di erent molecular characteristics, showing the potential to provide personalized treatment decision-making support for LUAD patients."]

radiomics consensus clustering targeted therapy immunotherapy lung adenocarcinoma

SCI

English

Corresponding

null[82172026]

General & Internal Medicine

Medicine, General & Internal

WOS:001058948200001

FRONTIERS MEDIA SA

Web of Science

1.Jinan Univ, Clin Med Coll 2, Shenzhen, Peoples R China
2.Jinan Univ, Southern Univ Sci & Technol, Shenzhen Peoples Hosp, Clin Med Coll 2,Affiliated Hosp 1,Dept Radiol, Shenzhen, Peoples R China
3.Jinan Univ, Guangzhou Red Cross Hosp, Guangzhou, Guangdong, Peoples R China

Liu, Xiaowen,Xu, Ting,Wang, Shuxing,et al. CT-based radiomic phenotypes of lung adenocarcinoma: a preliminary comparative analysis with targeted next-generation sequencing[J]. FRONTIERS IN MEDICINE,2023,10.

Liu, Xiaowen.,Xu, Ting.,Wang, Shuxing.,Chen, Yaxi.,Jiang, Changsi.,...&Gong, Jingshan.(2023).CT-based radiomic phenotypes of lung adenocarcinoma: a preliminary comparative analysis with targeted next-generation sequencing.FRONTIERS IN MEDICINE,10.

Liu, Xiaowen,et al."CT-based radiomic phenotypes of lung adenocarcinoma: a preliminary comparative analysis with targeted next-generation sequencing".FRONTIERS IN MEDICINE 10(2023).