Evidence map›Paper›PMID 39649426›Full record

ArticleJournal of inflammation research2024

Analysis of the Potential Link Between Dermatomyositis and Cancer.

Jianwei Guo, Tianyi Lei, Xiang Yu, Peng Wang, Hongyuan Xie, Guilin Jian, Quanbo Zhang, Yufeng Qing

Abstract read
In one paragraph

Article in Journal of inflammation research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

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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

2 citing papers in PubMed.

  1. 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

8 authors.

Jianwei Guo *Research Center of Hyperuricemia and Gout, Affiliated Hospital of North Sichuan Medical College, Nanchong, 637000, People's Republic of China.
Tianyi Lei *Research Center of Hyperuricemia and Gout, Affiliated Hospital of North Sichuan Medical College, Nanchong, 637000, People's Republic of China.
Xiang YuResearch Center of Hyperuricemia and Gout, Affiliated Hospital of North Sichuan Medical College, Nanchong, 637000, People's Republic of China.
Peng WangResearch Center of Hyperuricemia and Gout, Affiliated Hospital of North Sichuan Medical College, Nanchong, 637000, People's Republic of China.ORCID 0000-0001-7136-9401
Hongyuan XieResearch Center of Hyperuricemia and Gout, Affiliated Hospital of North Sichuan Medical College, Nanchong, 637000, People's Republic of China.
Guilin JianResearch Center of Hyperuricemia and Gout, Affiliated Hospital of North Sichuan Medical College, Nanchong, 637000, People's Republic of China.
Quanbo Zhang *Research Center of Hyperuricemia and Gout, Affiliated Hospital of North Sichuan Medical College, Nanchong, 637000, People's Republic of China.
Yufeng QingResearch Center of Hyperuricemia and Gout, Affiliated Hospital of North Sichuan Medical College, Nanchong, 637000, People's Republic of China.ORCID 0000-0001-6709-7570

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Dermatomyositis (DM) is an inflammatory muscle disease that increases the risk of cancer, although the precise connection is not fully understood. The aim of this study was to investigate the mechanisms linking DM to cancer and identify potential therapeutic targets. Methods: We conducted differential gene expression analysis on the GSE128470 dataset and employed WGCNA to pinpoint key genes related to DM. Central genes were identified with the LASSO and SVM-RFE methods. The expression levels and diagnostic relevance of these genes were confirmed via the GSE1551 dataset. Immune cell infiltration was analyzed in relation to central genes, and RT‒qPCR was utilized to evaluate the expression of key genes across various cancers. Results: In total, differentially expressed genes (DEGs), involved mainly in innate immunity, cytokine responses, and autoimmune diseases, were identified. In the WGCNA, 399 significant genes related to DM were identified, with central genes including MIF, C1QA, and CDKN1A. Immune infiltration analysis revealed diverse immune cell populations in DM patients, with significant correlations between central genes and these immune cells. MIF levels were notably elevated in various tumors and correlated with the prognosis of specific cancers. Furthermore, MIF was negatively associated with most immune cells but positively correlated with CD4+ Th1 cells, NKT cells, and MDSCs. Factors such as immune regulatory elements, TMB, and MSI indicated that MIF may affect immunotherapy outcomes. The increased expression of MIF mRNA was confirmed via RT‒qPCR. Conclusion: The findings demonstrate that MIF, C1QA, and CDKN1A are differentially expressed in DM patients, with MIF showing significant alterations in DM patients with cancer. MIF may serve as a crucial prognostic biomarker and therapeutic target for various cancers, playing a pivotal role in linking DM to cancer through the modulation of CD4+ Th1 cells, NKT cells, and MDSCs.

Indexed as

dermatomyositisimmune infiltrationmachine learningMIFpan-cancerWGCNA

Identifiers

PMID39649426
PMCPMC11624688

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