ArticleTranslational lung cancer research2026
Correlation analysis between growth heterogeneity and genetic mutations in resected subsolid lung adenocarcinoma based on long-term computed tomography (CT) follow-up.
Article in Translational lung cancer research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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Who cites it
1 citing paper in PubMed.
- [Advances in the Growth Risk Assessment and Precision Management of Pulmonary Subsolid Nodules].Zhongguo fei ai za zhi = Chinese journal of lung cancer · 2026Review
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8 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Background: Persistent pulmonary subsolid nodules (SSNs) are pathologically classified as invasive adenocarcinoma (IA) or precancerous glandular lesions. Pulmonary SSNs demonstrate significant heterogeneity in their growth patterns. Some SSNs remain stable during long-term follow-up, some grow slowly, and some grow rapidly. However, the molecular mechanisms that trigger or regulate the growth of SSNs remain incompletely understood. This study aimed to investigate the correlation between growth pattern of pulmonary SSNs and common gene mutations and help explore key genes that trigger or regulate SSN growth based on long-term computed tomography (CT) follow-up. Methods: We retrospectively included SSNs that underwent ≥3 years of CT follow-up or showed growth within 3 years between November 2010 and December 2024, and underwent pathological diagnosis and genetic testing. Enrolled SSNs were divided into growth and non-growth groups. According to the growth rate, the growth group was further divided into rapidly growing [volume doubling time (VDT) ≤800 days] and slowly growing (VDT >800 days) subgroups. Gene mutations including epidermal growth factor receptor (EGFR), Kirsten rat sarcoma viral oncogene homolog (KRAS), and v-raf murine sarcoma viral oncogene homolog B1 (BRAF) were identified via routine genetic testing. The Mann-Whitney Results: A total of 164 SSNs [median diameter, 10.0 mm; interquartile range (IQR), 7.5-13.0 mm] from 159 patients (median age, 57.0 years; IQR, 50.0-62.0 years) were included. The majority of patients were non-smokers (82.3%). A significantly higher prevalence of IA in the growing group than in the non-growing group (82.8% Conclusions: Growing SSNs during identified on CT follow-up were significantly correlated with IA and EGFR mutations. EGFR may serve as a pivotal gene in driving the growth of SSNs; however, it is not a key gene in regulating their growth rate. This finding may help promote personalized management for SSN patients and uncover potential biomarkers and therapeutic targets with value.
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