Li Hong-Ji, Qiu Zhen-Bin, Wang Meng-Min, Zhang Chao, Hong Hui-Zhao, Fu Rui, Peng Li-Shan, Huang Chen, Cui Qian, Zhang Jia-Tao, Ren Jing-Yun, Jiang Lei, Wu Yi-Long, Zhong Wen-Zhao
School of Medicine, South China University of Technology, Guangzhou, People's Republic of China; Guangdong Lung Cancer Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, People's Republic of China; Guangdong Provincial Key Laboratory of Translational Medicine in Lung Cancer, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, People's Republic of China.
Guangdong Lung Cancer Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, People's Republic of China; Guangdong Provincial Key Laboratory of Translational Medicine in Lung Cancer, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, People's Republic of China.
J Thorac Oncol. 2025 Jan;20(1):52-64. doi: 10.1016/j.jtho.2024.09.1431. Epub 2024 Sep 19.
An increasing number of early-stage lung adenocarcinomas (LUAD) are detected as lung nodules. The radiological features related to LUAD progression warrant further investigation. Exploration is required to bridge the gap between radiomics-based features and molecular characteristics of lung nodules.
Consensus clustering was applied to the radiomic features of 1212 patients to establish stable clustering. Clusters were illustrated using clinicopathological and next-generation sequencing. A classifier was constructed to further investigate the molecular characteristics in patients with paired computed tomography and RNA sequencing data.
Patients were clustered into four clusters. Cluster 1 was associated with a low consolidation-to-tumor ratio, preinvasion, grade I disease, and good prognosis. Clusters 2 and 3 reported increasing malignancy with a higher consolidation-to-tumor ratio, higher pathologic grade, and poor prognosis. Cluster 2 possessed more spread through air spaces and cluster 3 reported a higher proportion of pleural invasion. Cluster 4 had similar clinicopathological features as cluster 1 except but a proportion of grade II disease. RNA sequencing indicated that cluster 1 represented nodules with indolent growth and good differentiation, whereas cluster 4 reported progression in cell development but still had low proliferative activity. Nodules with high proliferation were classified into clusters 2 and 3. In addition, the radiomics classifier distinguished cluster 2 as nodules harboring an activated immune environment, whereas cluster 3 represented nodules with a suppressive immune environment. Furthermore, signatures associated with the prognosis of early-stage LUAD were validated in external datasets.
Radiomics features can manifest molecular events driving the progression of LUAD. Our study provides molecular insight into radiomics features and assists in the diagnosis and treatment of early-stage LUAD.
越来越多的早期肺腺癌（LUAD）被检测为肺结节。与LUAD进展相关的放射学特征值得进一步研究。需要进行探索以弥合基于放射组学的特征与肺结节分子特征之间的差距。
对1212例患者的放射组学特征应用共识聚类以建立稳定的聚类。使用临床病理和下一代测序对聚类进行说明。构建一个分类器以进一步研究具有配对计算机断层扫描和RNA测序数据的患者的分子特征。
患者被聚类为四个簇。簇1与低实变与肿瘤比率、原位癌、I级疾病和良好预后相关。簇2和簇3显示恶性程度增加，实变与肿瘤比率更高、病理分级更高且预后不良。簇2具有更多的气腔播散，簇3显示胸膜侵犯比例更高。簇4具有与簇1相似的临床病理特征，但有一部分为II级疾病。RNA测序表明，簇1代表生长缓慢且分化良好的结节，而簇4显示细胞发育有进展但增殖活性仍然较低。高增殖性结节被分类为簇2和簇3。此外，放射组学分类器将簇2识别为具有激活免疫环境的结节，而簇3代表具有抑制免疫环境的结节。此外，与早期LUAD预后相关的特征在外部数据集中得到验证。
放射组学特征可以体现驱动LUAD进展的分子事件。我们的研究为放射组学特征提供了分子层面的见解，并有助于早期LUAD的诊断和治疗。
