Evidence map›Paper›PMID 38347841›Full record

ArticleFrontiers in oncology2024

Untargeted metabolomics yields insight into extramammary Paget's disease mechanisms.

Long Jiang, Xiaoxiang Xu, Guorong Yan, Yuhao Wu, Ningyuan Xi, Yongxian Lai, Guolong Zhang, Yeqiang Liu

Open access · goldAbstract read
In one paragraph

Article in Frontiers in oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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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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3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 0 citations in OpenAlex.

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4 · The record

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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 at 2 institutions in 1 country.

Long Jiang *Department of Dermatologic Surgery, Shanghai Skin Disease Hospital, School of Medicine, Tongji University, Shanghai, China.
Xiaoxiang Xu *Skin Cancer Center, Shanghai Skin Disease Hospital, School of Medicine, Tongji University, Shanghai, China.
Guorong YanSkin Cancer Center, Shanghai Skin Disease Hospital, School of Medicine, Tongji University, Shanghai, China.
Yuhao WuSkin Cancer Center, Shanghai Skin Disease Hospital, School of Medicine, Tongji University, Shanghai, China.
Ningyuan XiSkin Cancer Center, Shanghai Skin Disease Hospital, School of Medicine, Tongji University, Shanghai, China.
Yongxian LaiDepartment of Dermatologic Surgery, Shanghai Skin Disease Hospital, School of Medicine, Tongji University, Shanghai, China.
Guolong ZhangSkin Cancer Center, Shanghai Skin Disease Hospital, School of Medicine, Tongji University, Shanghai, China.
Yeqiang LiuSkin Cancer Center, Shanghai Skin Disease Hospital, School of Medicine, Tongji University, Shanghai, China.
Tongji University · CNShanghai Skin Disease Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Extramammary Paget's disease (EMPD) is a rare cutaneous malignancy, commonly affecting the external genitalia and perianal area of the elderly with unclear pathogenesis. Metabolomics provides a novel perspective for uncovering the metabolic mechanisms of a verity of cancers. Materials and methods: Here, we explored the metabolome of EMPD using an untargeted strategy. In order to further investigate the potential relationship between metabolites and gene expression, we re-analyzed the gene expression microarray data (GSE117285) using differential expression analysis and functional enrichment analyses. Results: Results showed that a total of 896 metabolites were identified and 87 metabolites including 37 upregulated and 50 downregulated significantly in EMPD were sought out. In the following feature selection analyses, four metabolites, namely, cyclopentyl fentanyl-d5, LPI 17:0, guanosine-3',5'-cyclic monophosphate, kynurenine (KYN, high in EMPD) were identified by both random forest and support vector machine analyses. We then identified 1,079 dysfunctional genes: 646 upregulated and 433 downregulated in EMPD. Specifically, the tryptophan-degrading enzyme including indoleamine-2,3-dioxygenase-1 ( Conclusion: In conclusion, this study was the first to reveal the metabolome profile of EMPD. Our results demonstrate that

Indexed as

extramammary Paget’s diseaseIDO1kynurenine pathwayTDO2untargeted metabolomics

Identifiers

PMID38347841
PMCPMC10859479
OpenAlexW4391320553

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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.