Evidence map›Paper›PMID 33731144›Full record

ArticleCancer cell international2021

Identifying SLC27A5 as a potential prognostic marker of hepatocellular carcinoma by weighted gene co-expression network analysis and in vitro assays.

Fan Zhang, Mengjuan Xue, Xin Jiang, Huiyuan Yu, Yixuan Qiu, Jiaming Yu, Fan Yang, Zhijun Bao

Open access · goldAbstract read
In one paragraph

Article in Cancer cell international, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
2.2field-weighted citation impact, top 12% 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

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

16 citing papers in PubMed, 19 citations in OpenAlex.

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  7. A computational framework to in silico screen for drug-induced hepatocellular toxicity.Toxicological sciences : an official journal of the Society of Toxicology · 2024
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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 at 1 institution in 1 country.

Fan Zhang *Department of Geriatric Medicine, Huadong Hospital, Shanghai Medical College, Fudan University, No. 221 Yan'an West Road, Shanghai, 200040, People's Republic of China.
Mengjuan Xue *Department of Geriatric Medicine, Huadong Hospital, Shanghai Medical College, Fudan University, No. 221 Yan'an West Road, Shanghai, 200040, People's Republic of China.
Xin JiangDepartment of Geriatric Medicine, Huadong Hospital, Shanghai Medical College, Fudan University, No. 221 Yan'an West Road, Shanghai, 200040, People's Republic of China.
Huiyuan YuDepartment of Geriatric Medicine, Huadong Hospital, Shanghai Medical College, Fudan University, No. 221 Yan'an West Road, Shanghai, 200040, People's Republic of China.
Yixuan QiuDepartment of Geriatric Medicine, Huadong Hospital, Shanghai Medical College, Fudan University, No. 221 Yan'an West Road, Shanghai, 200040, People's Republic of China.
Jiaming YuDepartment of Geriatric Medicine, Huadong Hospital, Shanghai Medical College, Fudan University, No. 221 Yan'an West Road, Shanghai, 200040, People's Republic of China.
Fan YangDepartment of Geriatric Medicine, Huadong Hospital, Shanghai Medical College, Fudan University, No. 221 Yan'an West Road, Shanghai, 200040, People's Republic of China. fdyangfan@fudan.edu.cn.
Zhijun BaoDepartment of Geriatric Medicine, Huadong Hospital, Shanghai Medical College, Fudan University, No. 221 Yan'an West Road, Shanghai, 200040, People's Republic of China. zhijunbao@fudan.edu.cn.ORCID http://orcid.org/0000-0002-1382-5306
Shanghai Medical College of Fudan University · CN

Funding

National Key Research and Development Program of China 2018YFC2002000National Natural Science Foundation of China 81901408Shanghai Medical Leadership Training Program 2019LJ09Shanghai Sailing program 19YF1414500
6 · The paper itself

Abstract

backgroundThe incidence and mortality rates of hepatocellular carcinoma are among the highest of all cancers all over the world. However the survival rates are relatively low due to lack of effective treatments. Efforts to elucidate the mechanisms of HCC and to find novel prognostic markers and therapeutic targets are ongoing. Here we tried to identify prognostic genes of HCC through co-expression network analysis.

methodsWe conducted weighted gene co-expression network analysis with a microarray dataset GSE14520 of HCC from Gene Expression Omnibus database and identified a hub module associated with HCC prognosis. Function enrichment analysis of the hub module was performed. Clinical information was analyzed to select candidate hub genes. The expression profiles and survival analysis of the selected genes were performed using additional datasets (GSE45267 and TCGA-LIHC) and the hub gene was identified. GSEA and in vitro experiments were conducted to further verify the function of the hub gene.

resultsGenes in the hub module were mostly involved in the metabolism pathway. Four genes (SLC27A5, SLC10A1, PCK2 and FMO4) from the module were identified as candidate hub genes according to correlation analysis with prognostic indicators. All these genes were significantly down-regulated in tumor tissues compared with non-tumor tissues in additional datasets. After survival analysis and network construction, SLC27A5 was selected as a prognostic marker. GSEA analysis and in vitro assays suggested that SLC27A5 downregulation promoted tumor cell migration via enhancing epithelial-mesenchymal transition.

conclusionSLC27A5 is a potential biomarker of HCC and SLC27A5 downregulation promoted HCC progression by enhancing EMT.

Indexed as

Epithelial–mesenchymal transitionHepatocellular carcinomaMigrationSLC27A5WGCNA

Identifiers

PMID33731144
PMCPMC7968262
OpenAlexW3138266528

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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 OpenQuestion graph.