Evidence map›Paper›PMID 42120518›Full record

ArticleNPJ precision oncology2026

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

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

Abstract read
In one paragraph

Article in NPJ precision oncology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Qijia Han *Department of Radiology, The Affiliated Panyu Central Hospital, Guangzhou Medical University, Guangzhou, China.
Yunfeng Shi *Guangdong Engineering Research Center of Precision Detection and Modulation of Human Microbiome, Biomedical Research Center, Institute of Ecological Sciences, School of Life Sciences, South China Normal University, Guangzhou, China.
Xinzhu Yi *Guangdong Engineering Research Center of Precision Detection and Modulation of Human Microbiome, Biomedical Research Center, Institute of Ecological Sciences, School of Life Sciences, South China Normal University, Guangzhou, China.
Zhu AiDepartment of Radiology, The Affiliated Panyu Central Hospital, Guangzhou Medical University, Guangzhou, China.
Minyi WuDepartment of Radiology, The Affiliated Panyu Central Hospital, Guangzhou Medical University, Guangzhou, China.
Tianshuai HeDepartment of Radiology, The Affiliated Panyu Central Hospital, Guangzhou Medical University, Guangzhou, China.
Xinru JingDepartment of Radiology, The Affiliated Panyu Central Hospital, Guangzhou Medical University, Guangzhou, China.
Zhang WangGuangdong Engineering Research Center of Precision Detection and Modulation of Human Microbiome, Biomedical Research Center, Institute of Ecological Sciences, School of Life Sciences, South China Normal University, Guangzhou, China. wangz@m.scnu.edu.cn.
Zhiming XiangDepartment of Radiology, The Affiliated Panyu Central Hospital, Guangzhou Medical University, Guangzhou, China. xiangzhiming@pyhospital.com.cn.

Funding

Major Project of Guangzhou National Laboratory GZNL2023A02001National Key Research and Development Program of China 2022YFA1304300National Natural Science Foundation of China 82171931National Natural Science Foundation of China 82495200
6 · The paper itself

Abstract

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.

Identifiers

PMID42120518
PMCPMC13388699

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.