Evidence map›Paper›PMID 36245843›Full record

ArticleComputational and mathematical methods in medicine2022

Identification of the Key Genes Involved in the Tumorigenesis and Prognosis of Prostate Cancer.

Wenxuan Wang, Qinghui Wu, Ali Mohyeddin, Yousheng Liu, Zhitao Liu, Jianqiang Ge, Bao Zhang, Gan Shi, Weifu Wang, Dinglan Wu and 1 more

Open access · hybridAbstract read
In one paragraph

Article in Computational and mathematical methods in medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.1field-weighted citation impact, top 60% 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

1 citing paper in PubMed, 1 citations in OpenAlex.

  1. Article
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

11 authors at 4 institutions in 1 country.

Wenxuan WangDepartment of Urology, Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Haikou 570100, China.ORCID https://orcid.org/0000-0002-0788-705X
Qinghui WuDepartment of Urology, Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Haikou 570100, China.ORCID https://orcid.org/0000-0002-9437-9036
Ali MohyeddinDepartment of Plastic Surgery, Zhujiang Hospital, Southern Medical University, Guangzhou, Guangdong Province, 510280, China.ORCID https://orcid.org/0000-0002-7137-9666
Yousheng LiuDepartment of Urology, Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Haikou 570100, China.ORCID https://orcid.org/0000-0001-8927-7396
Zhitao LiuDepartment of Urology, Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Haikou 570100, China.ORCID https://orcid.org/0000-0002-1827-9105
Jianqiang GeDepartment of Urology, Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Haikou 570100, China.ORCID https://orcid.org/0000-0001-5869-6192
Bao ZhangDepartment of Urology, Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Haikou 570100, China.ORCID https://orcid.org/0000-0002-9930-4973
Gan ShiDepartment of Urology, Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Haikou 570100, China.ORCID https://orcid.org/0000-0002-6134-8399
Weifu WangDepartment of Urology, Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Haikou 570100, China.ORCID https://orcid.org/0000-0002-9713-1159
Dinglan WuShenzhen Key Laboratory of Viral Oncology, The Clinical Innovation & Research Centre, Shenzhen Hospital, Southern Medical University, Shenzhen 518100, China.ORCID https://orcid.org/0000-0002-5057-9626
Fei WangDepartment of Urology, Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Haikou 570100, China.ORCID https://orcid.org/0000-0001-6990-636X
Hainan General Hospital · CNGuangdong Provincial Hospital of Traditional Chinese Medicine · CNSouthern Medical University Shenzhen Hospital · CNZhujiang Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Prostate cancer (PCa) is a malignant tumor in males, with a majority of the cases advancing to metastatic castration resistance. Metastasis is the leading cause of mortality in PCa. The traditional early detection and prediction approaches cannot differentiate between the different stages of PCa. Therefore, new biomarkers are necessary for early detection and clear differentiation of PCa stages to provide precise therapeutic intervention. Methods: The objective of the study was to find significant differences in genes and combine the three GEO datasets with TCGA-PRAD datasets (DEG). Weighted gene coexpression network analysis (WGCNA) determined the gene set and PCa clinical feature correlation module utilizing the TGGA-PRAD clinical feature data. The correlation module genes were rescreened using the biological information analysis tools, with the three hub genes (TOP2A, NCAPG, and BUB1B) for proper verification. Finally, internal (TCGA) and external (GSE32571, GSE70770) validation datasets were used to validate and predict the value of last hub genes. Results: The hub gene was abnormally upregulated in PCa samples during verification. The expression of each gene was favorably connected with the Gleason score and TN tumor grade in clinical samples but negatively correlated with the overall survival rate. The expression of these genes was linked to CD8 naive cells and macrophages, among other cells. Antitumor immune cells like NK and NKT were favorably and adversely correlated with infiltrating cells, respectively. Simultaneously, the GSCV and GSEA indicated that the hub gene is connected with cell proliferation, death, and androgen receptor, among other signaling pathways. Therefore, these genes could influence the incidence and progression of PCa by participating in or modulating various signaling pathways. Furthermore, using the online tool of CMap, we examined the individual medications for Hughes and determined that tipifarnib could be useful for the clinical therapy of PCa. Conclusion: TOP2A, NCAPG, and BUB1B are important genes intimately linked to the clinical prognosis of PCa and can be employed as reliable biomarkers for early diagnosis and prognosis. Moreover, these genes can provide a theoretical basis for precision differentiation and treatment of PCa.

Indexed as

Prostatic NeoplasmsReceptors, AndrogenBiomarkers, TumorCarcinogenesisGene Expression ProfilingHumansMalePrognosisBiomarkers, TumorReceptors, Androgen

Identifiers

PMID36245843
PMCPMC9556187
OpenAlexW4302023700

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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.