Evidence map›Paper›PMID 39543109›Full record

ArticleNature communications2024

Multi-omics with dynamic network biomarker algorithm prefigures organ-specific metastasis of lung adenocarcinoma.

Xiaoshen Zhang, Kai Xiao, Yaokai Wen, Fengying Wu, Guanghui Gao, Luonan Chen, Caicun Zhou

Abstract read
In one paragraph

Article in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

21 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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

7 authors.

Xiaoshen Zhang *School of Medicine, Tongji University, 200092, Shanghai, China.
Kai Xiao *Key Laboratory of Systems Biology, Institute of Biochemistry and Cell Biology, Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences, 201100, Shanghai, China.ORCID 0009-0007-6355-1992
Yaokai Wen *School of Medicine, Tongji University, 200092, Shanghai, China.
Fengying WuDepartment of Medical Oncology, Shanghai Pulmonary Hospital, Tongji University School of Medicine, 200433, Shanghai, China.
Guanghui GaoDepartment of Medical Oncology, Shanghai Pulmonary Hospital, Tongji University School of Medicine, 200433, Shanghai, China.
Luonan ChenKey Laboratory of Systems Biology, Institute of Biochemistry and Cell Biology, Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences, 201100, Shanghai, China. lnchen@sibcb.ac.cn.ORCID 0000-0002-3960-0068
Caicun ZhouDepartment of Medical Oncology, Shanghai Pulmonary Hospital, Tongji University School of Medicine, 200433, Shanghai, China. caicunzhoudr@163.com.ORCID 0009-0001-5314-0790

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Efficacious strategies for early detection of lung cancer metastasis are of significance for improving the survival of lung cancer patients. Here we show the marker genes and serum secretome foreshadowing the lung cancer site-specific metastasis through dynamic network biomarker (DNB) algorithm, utilizing two clinical cohorts of four major types of lung cancer distant metastases, with single-cell RNA sequencing (scRNA-seq) of primary lesions and liquid chromatography-mass spectrometry data of sera. Also, we locate the intermediate status of cancer cells, along with its gene signatures, in each metastatic state trajectory that cancer cells at this stage still have no specific organotropism. Furthermore, an integrated neural network model based on the filtered scRNA-seq data is successfully constructed and validated to predict the metastatic state trajectory of cancer cells. Overall, our study provides an insight to locate the pre-metastasis status of lung cancer and primarily examines its clinical application value, contributing to the early detection of lung cancer metastasis in a more feasible and efficacious way.

Indexed as

Adenocarcinoma of LungAlgorithmsBiomarkers, TumorLung NeoplasmsNeoplasm MetastasisFemaleGene Expression Regulation, NeoplasticHumansMaleMultiomicsNeural Networks, ComputerSingle-Cell AnalysisBiomarkers, Tumor

Identifiers

PMID39543109
PMCPMC11564768

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

None linked

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.