Evidence map›Paper›PMID 31422942›Full record

ArticleAging2019

Identification of 9 key genes and small molecule drugs in clear cell renal cell carcinoma.

Yongwen Luo, Dexin Shen, Liang Chen, Gang Wang, Xuefeng Liu, Kaiyu Qian, Yu Xiao, Xinghuan Wang, Lingao Ju

Open access · greenAbstract read
In one paragraph

Article in Aging, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 51 papers.

0numbers the graph read from it
0cells of the map it votes in
51citing papers in PubMed
7.3field-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

51 citing papers in PubMed, 69 citations in OpenAlex.

  1. A FOXO1-G6PC transcriptional axis restrains renal cell carcinoma progression: multi-omics, epigenetic, and mechanistic evidence.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026
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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

9 authors at 3 institutions in 2 countries.

Yongwen LuoDepartment of Urology, Zhongnan Hospital of Wuhan University, Wuhan, China.
Dexin ShenDepartment of Urology, Zhongnan Hospital of Wuhan University, Wuhan, China.
Liang ChenDepartment of Urology, Zhongnan Hospital of Wuhan University, Wuhan, China.
Gang WangDepartment of Biological Repositories, Zhongnan Hospital of Wuhan University, Wuhan, China.
Xuefeng LiuDepartment of Pathology, Lombardi Comprehensive Cancer Center, Georgetown University Medical School, Washington, DC 20007, USA.
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.
Lingao JuDepartment of Biological Repositories, Zhongnan Hospital of Wuhan University, Wuhan, China.
Wuhan University · CNZhongnan Hospital of Wuhan University · CNGeorgetown University Medical Center · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Clear cell renal cell carcinoma (ccRCC) is a heterogeneous tumor that the underlying molecular mechanisms are largely unclear. This study aimed to elucidate the key candidate genes and pathways in ccRCC by integrated bioinformatics analysis. 1387 differentially expressed genes were identified based on three expression profile datasets, including 673 upregulated genes and 714 downregulated genes. Then we used weighted correlation network analysis to identify 6 modules associated with pathological stage and grade, blue module was the most relevant module. GO and KEGG pathway analyses showed that genes in blue module were enriched in cell cycle and metabolic related pathways. Further, 25 hub genes in blue module were identified as hub genes. Based on GEPIA database, 9 genes were associated with progression and prognosis of ccRCC patients, including PTTG1, RRM2, TOP2A, UHRF1, CEP55, BIRC5, UBE2C, FOXM1 and CDC20. Then multivariate Cox regression showed that the risk score base on 9 key genes signature was a clinically independent prognostic factor for ccRCC patients. Moreover, we screened out several new small molecule drugs that have the potential to treat ccRCC. Few of them were identified as biomarkers in ccRCC. In conclusion, our research identified 9 potential prognostic genes and several candidate small molecule drugs for ccRCC treatment.

Indexed as

Gene Expression Regulation, NeoplasticAntineoplastic AgentsCarcinoma, Renal CellComputational BiologyDisease ProgressionDrug Evaluation, PreclinicalGene Expression ProfilingGene Regulatory NetworksHumansKidney NeoplasmsPrognosisAntineoplastic Agentsbiomarkerclear cell renal cell carcinoma (ccRCC)Gene Set Enrichment Analysis (GSEA)Weighted Gene Co-expression Network Analysis (WGCNA)

Identifiers

PMID31422942
PMCPMC6738436
OpenAlexW2969691609

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.