Literature DB >> 31699841

Genomic characterisation of pulmonary subsolid nodules: mutational landscape and radiological features.

Yanmeng Li1,2, Xiao Li1,2, Hao Li1,2, Yifan Zhao1,2, Ziyang Liu1,2, Kunkun Sun3, Xiang Zhu4, Qingyi Qi5, Bei An5, Danhua Shen3, Ruoyan Li1, Taorui Liu1, Jiahui Mi1, Lientu Wang6, Fan Yang1,2, Fan Bai1,2, Jun Wang7,2.   

Abstract

BACKGROUND: Lung adenocarcinomas (LUADs) that display radiologically as subsolid nodules (SSNs) exhibit more indolent biological behaviour than solid LUADs. SSNs, commonly encompassing pre-invasive and invasive yet early-stage adenocarcinomas, can be categorised as pure ground-glass nodules and part-solid nodules. The genomic characteristics of SSNs remain poorly understood.
METHODS: We subjected 154 SSN samples from 120 treatment-naïve Chinese patients to whole-exome sequencing. Clinical parameters and radiological features of these SSNs were collected. The genomic landscape of SSNs and differences from that of advanced-stage LUADs were defined. In addition, we investigated the intratumour heterogeneity and clonal relationship of multifocal SSNs and conducted radiogenomic analysis to link imaging and molecular characteristics of SSNs. Fisher's exact and Wilcoxon rank sum tests were used in the statistical analysis.
RESULTS: The median somatic mutation rate across the SSN cohort was 1.12 mutations per Mb. Mutations in EGFR were the most prominent and significant variation, followed by those in RBM10, TP53, STK11 and KRAS. The differences between SSNs and advanced-stage LUADs at a genomic level were unravelled. Branched evolution and remarkable genomic heterogeneity were demonstrated in SSNs. Although multicentric origin was predominant, we also detected early metastatic events among multifocal SSNs. Using radiogenomic analysis, we found that higher ratios of solid components in SSNs were accompanied by significantly higher mutation frequencies in EGFR, TP53, RBM10 and ARID1B, suggesting that these genes play roles in the progression of LUADs.
CONCLUSIONS: Our study provides the first comprehensive description of the mutational landscape and radiogenomic mapping of SSNs.
Copyright ©ERS 2020.

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Year:  2020        PMID: 31699841     DOI: 10.1183/13993003.01409-2019

Source DB:  PubMed          Journal:  Eur Respir J        ISSN: 0903-1936            Impact factor:   16.671


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