Evidence map›Paper›PMID 33691643›Full record

ArticleBMC cancer2021

Integrative genomic expression analysis reveals stable differences between lung cancer and systemic sclerosis.

Heng Li, Liping Ding, Xiaoping Hong, Yulan Chen, Rui Liao, Tingting Wang, Shuhui Meng, Zhenyou Jiang, Dongzhou Liu

Open access · goldAbstract read
In one paragraph

Article in BMC cancer, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact, top 97% of its field
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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3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 1 citations in OpenAlex.

  1. Article
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 at 2 institutions in 1 country.

Heng LiDepartment of Rheumatology and Immunology, Shenzhen People's Hospital, The Second Clinical Medical College of Jinan University, Shenzhen, 518020, China.
Liping DingDepartment of Rheumatology and Immunology, Shenzhen People's Hospital, The Second Clinical Medical College of Jinan University, Shenzhen, 518020, China.
Xiaoping HongDepartment of Rheumatology and Immunology, Shenzhen People's Hospital, The Second Clinical Medical College of Jinan University, Shenzhen, 518020, China.
Yulan ChenDepartment of Rheumatology and Immunology, Shenzhen People's Hospital, The Second Clinical Medical College of Jinan University, Shenzhen, 518020, China.
Rui LiaoDepartment of Rheumatology and Immunology, Shenzhen People's Hospital, The Second Clinical Medical College of Jinan University, Shenzhen, 518020, China.
Tingting WangDepartment of Rheumatology and Immunology, Shenzhen People's Hospital, The Second Clinical Medical College of Jinan University, Shenzhen, 518020, China.
Shuhui MengDepartment of Rheumatology and Immunology, Shenzhen People's Hospital, The Second Clinical Medical College of Jinan University, Shenzhen, 518020, China.
Zhenyou JiangDepartment of Microbiology and Immunology, College of Basic Medicine and Public Hygiene, Jinan University, Guangzhou, 510632, China. tjzhy@jnu.edu.cn.
Dongzhou LiuDepartment of Rheumatology and Immunology, Shenzhen People's Hospital, The Second Clinical Medical College of Jinan University, Shenzhen, 518020, China. liu_dz2001@sina.com.
Jinan University · CNSouthern University of Science and Technology · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe incidence and mortality of lung cancer are the highest among all cancers. Patients with systemic sclerosis show a four-fold greater risk of lung cancer than the general population. However, the underlying mechanism remains poorly understood.

methodsThe expression profiles of 355 peripheral blood samples were integratedly analyzed, including 70 cases of lung cancer, 61 cases of systemic sclerosis, and 224 healthy controls. After data normalization and cleaning, differentially expressed genes (DEGs) between disease and control were obtained and deeply analyzed by bioinformatics methods. The gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed online by DAVID and KOBAS. The protein-protein interaction (PPI) networks were constructed from the STRING database.

resultsFrom a total of 14,191 human genes, 299 and 1644 genes were identified as DEGs in systemic sclerosis and lung cancer, respectively. Among them, 64 DEGs were overlapping, including 36 co-upregulated, 10 co-downregulated, and 18 counter-regulated DEGs. Functional and enrichment analysis showed that the two diseases had common changes in immune-related genes. The expression of innate immune response and response to virus-related genes increased significantly, while the expression of negative regulation of cell cycle-related genes decreased notably. In contrast, the expression of mitophagy regulation, chromatin binding and fatty acid metabolism-related genes showed distinct trends.

conclusionsStable differences and similarities between systemic sclerosis and lung cancer were revealed. In peripheral blood, enhanced innate immunity and weakened negative regulation of cell cycle may be the common mechanisms of the two diseases, which may be associated with the high risk of lung cancer in systemic sclerosis patients. On the other hand, the counter-regulated DEGs can be used as novelbiomarkers of pulmonary diseases. In addition, fat metabolism-related DEGs were consideredto be associated with clinical blood lipid data.

Indexed as

Gene Regulatory NetworksBiomarkers, TumorCase-Control StudiesComputational BiologyDatasets as TopicGene Expression ProfilingGene Expression Regulation, NeoplasticHealthy VolunteersHumansLung NeoplasmsProtein Interaction MappingProtein Interaction MapsRisk FactorsScleroderma, SystemicBiomarkers, TumorBioinformaticsImmunityLung cancerSystemic sclerosis

Identifiers

PMID33691643
PMCPMC7944918
OpenAlexW3134138509

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