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<p>Lung adenocarcinoma (LUAD) accounts for approximately 40% of non-small cell lung cancer. Although the microbiome may play a role in LUAD, a comprehensive understanding of its ecological landscape and interactions with the tumor host, particularly during early development of LUAD, remains lacking. Here we employed a multi-omic approach to assess the dynamics of the tumor microbiota-host interaction across stages of early LUAD, including benign nodules, adenocarcinoma in situ (AIS), minimally invasive adenocarcinoma (MIA), and invasive adenocarcinoma (IAC). We found a strong and intricate interaction between the microbiome and host immune and metabolic pathways in AIS, while microbiome-host interactions substantially diminish in MIA and IAC. Serum metabolites and CT-based radiological features, such as atropaldehyde, sterculic acid, nodule morphology and maximum nodule diameter, were closely associated with the microbiome-host interaction network, suggesting they could be non-invasive markers indicating tumor ecological and pathological changes. Multi-omic integration revealed an optimal performance in classifying individual LUAD stages, particularly between AIS and MIA that was otherwise challenging to differentiate using a single data type. Our results highlight the dynamic interaction between microbiome and host during early LUAD, which can be partially reflected in systemic metabolic and radiological manifestations, providing a novel framework for understanding early-stage LUAD.</p>

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Dynamic microbiome-host interactions and their associations with systemic metabolism and radiological characteristics during early lung adenocarcinoma

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年5月12日

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  • Qijia Han,
  • Yunfeng Shi,
  • Xinzhu Yi,
  • Zhu Ai,
  • Minyi Wu,
  • Tianshuai He,
  • Xinru Jing,
  • Zhang Wang,
  • Zhiming Xiang

摘要

Lung adenocarcinoma (LUAD) accounts for approximately 40% of non-small cell lung cancer. Although the microbiome may play a role in LUAD, a comprehensive understanding of its ecological landscape and interactions with the tumor host, particularly during early development of LUAD, remains lacking. Here we employed a multi-omic approach to assess the dynamics of the tumor microbiota-host interaction across stages of early LUAD, including benign nodules, adenocarcinoma in situ (AIS), minimally invasive adenocarcinoma (MIA), and invasive adenocarcinoma (IAC). We found a strong and intricate interaction between the microbiome and host immune and metabolic pathways in AIS, while microbiome-host interactions substantially diminish in MIA and IAC. Serum metabolites and CT-based radiological features, such as atropaldehyde, sterculic acid, nodule morphology and maximum nodule diameter, were closely associated with the microbiome-host interaction network, suggesting they could be non-invasive markers indicating tumor ecological and pathological changes. Multi-omic integration revealed an optimal performance in classifying individual LUAD stages, particularly between AIS and MIA that was otherwise challenging to differentiate using a single data type. Our results highlight the dynamic interaction between microbiome and host during early LUAD, which can be partially reflected in systemic metabolic and radiological manifestations, providing a novel framework for understanding early-stage LUAD.