Evidence map›Paper›PMID 30405806›Full record

ArticleOncology letters2018

Identification of the key genes and pathways in prostate cancer.

Shutong Fan, Zumu Liang, Zhiqin Gao, Zhiwei Pan, Shaojie Han, Xiaoying Liu, Chunling Zhao, Weiwei Yang, Zhifang Pan, Weiguo Feng

Open access · diamondAbstract read
In one paragraph

Article in Oncology letters, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed
4.4field-weighted citation impact, top 5% 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

29 citing papers in PubMed, 52 citations in OpenAlex.

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  16. Genomic pan-cancer classification using image-based deep learning.Computational and structural biotechnology journal · 2021
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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

10 authors at 1 institution in 1 country.

Shutong FanCollege of Bioscience and Technology, Weifang Medical University, Weifang, Shandong 261053, P.R. China.
Zumu LiangCollege of Bioscience and Technology, Weifang Medical University, Weifang, Shandong 261053, P.R. China.
Zhiqin GaoCollege of Bioscience and Technology, Weifang Medical University, Weifang, Shandong 261053, P.R. China.
Zhiwei PanDepartment of Internal Medicine, Laizhou Development Zone Hospital, Yantai, Shandong 261400, P.R. China.
Shaojie HanAnimal Epidemic Prevention and Epidemic Control Center, Changle County Bureau of Animal Health and Production, Weifang, Shandong 262400, P.R. China.
Xiaoying LiuCollege of Bioscience and Technology, Weifang Medical University, Weifang, Shandong 261053, P.R. China.
Chunling ZhaoCollege of Bioscience and Technology, Weifang Medical University, Weifang, Shandong 261053, P.R. China.
Weiwei YangCollege of Bioscience and Technology, Weifang Medical University, Weifang, Shandong 261053, P.R. China.
Zhifang PanCollege of Bioscience and Technology, Weifang Medical University, Weifang, Shandong 261053, P.R. China.
Weiguo FengCollege of Bioscience and Technology, Weifang Medical University, Weifang, Shandong 261053, P.R. China.
Weifang Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Prostate cancer (PCa) is one of the most common malignancies in men globally. The aim of the present study was to identify the key genes and pathways involved in the occurrence of PCa. Gene expression profile (GSE55945) was downloaded from Gene Expression Omnibus, and the differentially expressed genes (DEGs) were identified. Subsequently, Gene ontology analysis, KEGG pathway analysis and protein-protein interaction (PPI) analysis of DEGs were performed. Finally, the identified key genes were confirmed by immunohistochemistry. The GO analysis results showed that the DEGs were mainly participated in cell cycle, cell division, cell development and cell junction. The KEGG pathway analysis showed that the DEGs were mainly enriched in proteoglycans in cancer, endocytosis, focal adhesion and hippo signaling pathway. The PPI analysis results showed that RPS21, FOXO1, BIRC5, POLR2H, RPL22L1 and NPM1 were the key genes involved in the occurrence of PCa, and the Module analysis indicated that the occurrence of PCa was associated with cell cycle, oocyte meiosis and ribosome biogenesis. IHC result showed that the expression of RPS21, BIRC5, POLR2H, RPL22L1 and NPM1 were significantly upregulated in PCa, while the expression of FOXO1 was significantly downregulated in PCa, matching with the bioinformatics analysis. Taken together, several key genes and pathways were identified involved in PCa, which might provide the potential biomarker for prognosis, diagnosis and drug targets.

Indexed as

bioinformatics analysisdifferentially expressed geneidentificationpathwaysprostate cancer

Identifiers

PMID30405806
PMCPMC6202544
OpenAlexW2892095211

What OpenQuestion holds

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LicenceCC BY-NC-ND
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.