Evidence map›Paper›PMID 39331265›Full record

ArticleDiscover oncology2024

Identification of hsa-miR-193a-5p-SURF4 axis related to the gut microbiota-metabolites- cytokines in lung cancer based on Mendelian randomization study and bioinformatics analysis.

Jie Yu, Sibo Meng, Tiantian Xuan, Zhanmei Wang, Linli Qu, Fangli Cao, Jiaxin Li

Abstract read
In one paragraph

Article in Discover oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–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

3 citing papers in PubMed.

  1. Multi-Omics Analysis of the Effects ofInternational journal of molecular sciences · 2026
    Article
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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.

Jie Yu *Qilu Hospital (Qingdao), Cheeloo College of Medicine, Shandong University, 758 Hefei Road, Qingdao, 266035, Shandong, China.
Sibo Meng *Qilu Hospital (Qingdao), Cheeloo College of Medicine, Shandong University, 758 Hefei Road, Qingdao, 266035, Shandong, China.
Tiantian XuanQilu Hospital (Qingdao), Cheeloo College of Medicine, Shandong University, 758 Hefei Road, Qingdao, 266035, Shandong, China.
Zhanmei WangQilu Hospital (Qingdao), Cheeloo College of Medicine, Shandong University, 758 Hefei Road, Qingdao, 266035, Shandong, China.
Linli QuQilu Hospital (Qingdao), Cheeloo College of Medicine, Shandong University, 758 Hefei Road, Qingdao, 266035, Shandong, China.
Fangli CaoQilu Hospital (Qingdao), Cheeloo College of Medicine, Shandong University, 758 Hefei Road, Qingdao, 266035, Shandong, China.
Jiaxin LiQilu Hospital (Qingdao), Cheeloo College of Medicine, Shandong University, 758 Hefei Road, Qingdao, 266035, Shandong, China. jiaxinli_sdu@163.com.

Funding

2021 Clinical Research Fund of Shandong Medical Association YXH2022X02023Key Projects of the In-Hospital Fund of Qilu Hospital QDKY2021ZD02
6 · The paper itself

Abstract

backgroundLung cancer is a significant disease that affects people's physical and mental health. Currently, the treatment outcomes still do not meet clinical needs, and the causes of the disease are still unclear, therefore further exploration is needed.

methodsWe analyzed the exposure factors of lung cancer, including gut microbiota, serum metabolites, and cytokines, through Mendelian randomization studies and bioinformatics analysis. We identified common SNPs and performed gene annotation, leading to the discovery of the key gene SURF4, which may affect the onset of lung cancer. We validated the oncogenic function and mechanism of SURF4 through public data analysis using GO and KEGG, and constructed a ceRNA network, revealing the lung cancer oncogenic pathway involving lncRNA/pseudogene-microRNA-SURF4.

resultsWe first conducted a Mendelian randomization analysis on 418 gut microbiota, 1400 serum metabolites, and 41 cytokines in relation to lung cancer. We found that 16 gut microbiota, 29 serum metabolites, and 2 cytokines were closely associated with lung cancer. Further comparison of all differential SNPs revealed that rs550057 on chromosome 9 was a common SNP among these three exposure factors, indicating its crucial role in lung cancer formation. Through gene functional annotation using R language, we found that the expression of 15 genes, including SURF4, was influenced by rs550057. By querying these 15 genes from public databases for their differential expression and prognosis in lung cancer, we found significant differences in SURF4, MED22, and RPL7A. Furthermore, by querying the expression and correlation coefficients of upstream microRNAs of these three genes through the starBase website, we found that hsa-miR-193a-5p-SURF4 had the most significant effect on lung cancer. Through GO and KEGG analysis of SURF4-related genes, we identified the molecular pathways associated metabolic synthesis and microbial infection related to the promotion of lung cancer by SURF4. This validated the results of the previous Mendelian randomization study. Furthermore, we constructed a ceRNA network for SURF4 and identified two upstream differentially expressed pseudogenes and nine lncRNAs, confirming the functionality of the pseudogene/lncRNA-microRNA-SUFR4 pathway.

conclusionsIn summary, we have elucidated the regulatory role of the pseudogene/lncRNA-microRNA-SUFR4 pathway in the progression of lung cancer, combining the research hotspots of gut microbiota-serum metabolites-cytokines. We have also confirmed the pathway and mechanism through SURF4 and its related genes promoting lung cancer formation. This may provide effective therapeutic methods for lung cancer and serve as a potential prognostic marker.

Indexed as

Bioinformatics analysisCytokinesGut microbiotaLung cancerMendelian randomizationMetabolites

Identifiers

PMID39331265
PMCPMC11436685

What Socratic holds

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LicenceCC BY-NC-ND
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Registered trials

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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 Socratic graph.