Imaging and RNA sequencing-based radiogenomic analysis of occult lymph node metastasis and survival in lung adenocarcinoma staged non-metastatic

基于影像学和RNA测序的放射基因组学分析在非转移性肺腺癌中对隐匿性淋巴结转移和生存率的影响

阅读:2

Abstract

BACKGROUND: We aimed to explore the value of a PET/CT-based radiomics signature in predicting occult lymph node metastasis (OLM) and outcomes in clinical N0 (cN0) lung adenocarcinoma (LUAD), to uncover the biologic meaning of OLM-associated radiomics phenotypes and to validate the reproducibility of the identified radiomics-correlated key genes. METHODS: A radiomics signature for OLM prediction was developed in a training cohort and validated across multiple validation and testing cohorts in this multicenter study. Prognostic implications of the radiomics score (Radscore) were assessed by measuring recurrence-free survival. Biologic processes and pathways were enriched and correlated with Radscore and each of the 8 radiomics phenotypes using paired PET/CT and RNA sequencing data. The reproducibility of identified radiomics-associated key genes was validated using a public database, clinical tissue samples, and in vitro experiments. RESULTS: Here we show OLM is detected in 127 (19.9%) of 637 patients. The proposed signature achieves AUCs of 0.82, 0.81, 0.78 and 0.79 in the training, internal validation, prospective testing and external testing cohort, respectively. In addition, Radscore is identified as an independent predictive factor in predicting the risk of recurrence of LUAD. Furthermore, Radscore and OLM-related radiomics features are mostly associated with immune response. Finally, four key genes (MIR600HG, FAM13A-AS1, AQP4 and GRIA1), especially the MIR600HG gene, play important roles in OLM and prognosis of early-stage LUAD. CONCLUSIONS: We demonstrate that radiogenomics performed on PET/CT images provides complementary clinical, prognostic and molecular information with great potential for the prediction of OLM and risk stratification in cN0 LUAD.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。