Evidence map›Paper›PMID 31649873›Full record

ArticleFrontiers in oncology2019

ACAT1 and Metabolism-Related Pathways Are Essential for the Progression of Clear Cell Renal Cell Carcinoma (ccRCC), as Determined by Co-expression Network Analysis.

Liang Chen, Tianchen Peng, Yongwen Luo, Fenfang Zhou, Gang Wang, Kaiyu Qian, Yu Xiao, Xinghuan Wang

Open access · goldAbstract read
In one paragraph

Article in Frontiers in oncology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
37citing papers in PubMed, 1 pooled it
7.7field-weighted citation impact, top 2% 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

37 citing papers in PubMed, 1 synthesis or guideline pooled it, 62 citations in OpenAlex.

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  17. [Identification of onco-miRNAs in hepatocellular carcinoma and analysis of their regulatory network].Nan fang yi ke da xue xue bao = Journal of Southern Medical University · 2022
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  20. Bioinformatics Analysis of Prognostic Value ofInternational journal of general medicine · 2022
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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 2 institutions in 1 country.

Liang ChenDepartment of Urology, Zhongnan Hospital of Wuhan University, Wuhan, China.
Tianchen PengDepartment of Urology, Zhongnan Hospital of Wuhan University, Wuhan, China.
Yongwen LuoDepartment of Urology, Zhongnan Hospital of Wuhan University, Wuhan, China.
Fenfang ZhouDepartment of Urology, Zhongnan Hospital of Wuhan University, Wuhan, China.
Gang WangDepartment of Biological Repositories, Zhongnan Hospital of Wuhan University, Wuhan, China.
Kaiyu QianDepartment of Biological Repositories, Zhongnan Hospital of Wuhan University, Wuhan, China.
Yu XiaoDepartment of Urology, Zhongnan Hospital of Wuhan University, Wuhan, China.
Xinghuan WangDepartment of Urology, Zhongnan Hospital of Wuhan University, Wuhan, China.
Wuhan University · CNZhongnan Hospital of Wuhan University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Kidney cancer ranks as one of the top 10 causes of cancer death; this cancer is difficult to detect, difficult to treat, and poorly understood. The most common subtype of kidney cancer is clear cell renal cell carcinoma (ccRCC) and its progression is influenced by complex gene interactions. Few clinical studies have investigated the molecular markers associated with the progression of ccRCC. In this study, we collected microarray profiles of 72 ccRCCs and matched normal samples to identify differentially expressed genes (DEGs). Then a weighted gene co-expression network analysis (WGCNA) was conducted to identify co-expressed gene modules. By relating all co-expressed modules to clinical features, we found that the brown module and Fuhrman grade had the highest correlation (

Indexed as

ACAT1clear cell renal cell carcinoma (ccRCC)Fuhrman gradesurvival prognosisweighted gene co-expression network analysis (WGCNA)

Identifiers

PMID31649873
PMCPMC6795108
OpenAlexW2979674006

What OpenQuestion holds

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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 OpenQuestion graph.