基于放射组学的支持向量机区分肺腺癌进展的分子事件

IF 21 1区 医学 Q1 ONCOLOGY
Hong-Ji Li, Zhen-Bin Qiu, Meng-Min Wang, Chao Zhang, Hui-Zhao Hong, Rui Fu, Li-Shan Peng, Chen Huang, Qian Cui, Jia-Tao Zhang, Jing-Yun Ren, Lei Jiang, Yi-Long Wu, Wen-Zhao Zhong
{"title":"基于放射组学的支持向量机区分肺腺癌进展的分子事件","authors":"Hong-Ji Li, Zhen-Bin Qiu, Meng-Min Wang, Chao Zhang, Hui-Zhao Hong, Rui Fu, Li-Shan Peng, Chen Huang, Qian Cui, Jia-Tao Zhang, Jing-Yun Ren, Lei Jiang, Yi-Long Wu, Wen-Zhao Zhong","doi":"10.1016/j.jtho.2024.09.1431","DOIUrl":null,"url":null,"abstract":"<p><strong>Introduction: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusions: </strong>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.</p>","PeriodicalId":17515,"journal":{"name":"Journal of Thoracic Oncology","volume":" ","pages":""},"PeriodicalIF":21.0000,"publicationDate":"2024-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Radiomics-Based Support Vector Machine Distinguishes Molecular Events Driving the Progression of Lung Adenocarcinoma.\",\"authors\":\"Hong-Ji Li, Zhen-Bin Qiu, Meng-Min Wang, Chao Zhang, Hui-Zhao Hong, Rui Fu, Li-Shan Peng, Chen Huang, Qian Cui, Jia-Tao Zhang, Jing-Yun Ren, Lei Jiang, Yi-Long Wu, Wen-Zhao Zhong\",\"doi\":\"10.1016/j.jtho.2024.09.1431\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Introduction: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusions: </strong>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.</p>\",\"PeriodicalId\":17515,\"journal\":{\"name\":\"Journal of Thoracic Oncology\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":21.0000,\"publicationDate\":\"2024-09-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Thoracic Oncology\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1016/j.jtho.2024.09.1431\",\"RegionNum\":1,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ONCOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Thoracic Oncology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1016/j.jtho.2024.09.1431","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ONCOLOGY","Score":null,"Total":0}
引用次数: 0

摘要

导言越来越多的早期肺腺癌(LUAD)以肺结节的形式被发现。与 LUAD 进展相关的放射学特征仍有待进一步研究。需要在肺结节的放射学特征和分子特征之间架起一座桥梁:方法:对 1,212 例患者的放射组学特征进行共识聚类,以建立稳定的聚类。利用临床病理学和下一代测序(NGS)对聚类进行了说明。构建了一个分类器,利用成对的CT和RNA-seq数据进一步研究患者的分子特征:结果:患者被分为 4 个群组。结果:患者被分为 4 个群组,群组 1 与低合并瘤比 (CTR)、前浸润、I 级疾病和良好预后相关。第 2 组和第 3 组的恶性程度越来越高,CTR 越高,病理分级越高,预后越差。第 2 组有更多的气隙扩散(STAS),第 3 组的胸膜侵犯比例较高。第 4 组的临床病理特征与第 1 组相似,但 II 级病变的比例较高。RNA-seq表明,第1组代表了生长缓慢、分化良好的结节,而第4组则显示了细胞发育的进展,但增殖活性仍然较低。高增殖的结节被归入第 2 组和第 3 组。此外,放射组学分类器还将第 2 组区分为具有活化免疫环境的结节,而第 3 组则代表具有抑制性免疫环境的结节。此外,与早期LUAD预后相关的基因特征也在外部数据集中得到了验证:结论:放射组学特征可显示肺腺癌进展的分子事件。我们的研究从分子角度揭示了放射组学特征,有助于早期肺腺癌的诊断和治疗。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Radiomics-Based Support Vector Machine Distinguishes Molecular Events Driving the Progression of Lung Adenocarcinoma.

Introduction: 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.

Methods: 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.

Results: 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.

Conclusions: 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.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Journal of Thoracic Oncology
Journal of Thoracic Oncology 医学-呼吸系统
CiteScore
36.00
自引率
3.90%
发文量
1406
审稿时长
13 days
期刊介绍: Journal of Thoracic Oncology (JTO), the official journal of the International Association for the Study of Lung Cancer,is the primary educational and informational publication for topics relevant to the prevention, detection, diagnosis, and treatment of all thoracic malignancies.The readship includes epidemiologists, medical oncologists, radiation oncologists, thoracic surgeons, pulmonologists, radiologists, pathologists, nuclear medicine physicians, and research scientists with a special interest in thoracic oncology.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信