Evidence map›Paper›PMID 32982312›Full record

ArticleOncoTargets and therapy2020

Crosstalk Between AR and Wnt Signaling Promotes Castration-Resistant Prostate Cancer Growth.

Jun Luo, Dan Wang, Xuechao Wan, Yangguang Xu, Yali Lu, Zhe Kong, Dujian Li, Wei Gu, Chenji Wang, Yao Li and 3 more

Open access · goldAbstract read
In one paragraph

Article in OncoTargets and therapy, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
0.9field-weighted citation impact, top 27% 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

14 citing papers in PubMed, 22 citations in OpenAlex.

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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

13 authors at 2 institutions in 1 country.

Jun Luo *Department of Urology, Shanghai Fourth People's Hospital Affiliated to Tongji University School of Medicine, Shanghai, People's Republic of China.
Dan Wang *Shanghai Engineering Research Center of Industrial Microorganisms, School of Life Science, Fudan University, Shanghai 200433, People's Republic of China.
Xuechao WanShanghai Engineering Research Center of Industrial Microorganisms, School of Life Science, Fudan University, Shanghai 200433, People's Republic of China.
Yangguang XuShanghai Engineering Research Center of Industrial Microorganisms, School of Life Science, Fudan University, Shanghai 200433, People's Republic of China.
Yali LuShanghai Engineering Research Center of Industrial Microorganisms, School of Life Science, Fudan University, Shanghai 200433, People's Republic of China.
Zhe KongShanghai Engineering Research Center of Industrial Microorganisms, School of Life Science, Fudan University, Shanghai 200433, People's Republic of China.
Dujian LiDepartment of Urology, Shanghai Fourth People's Hospital Affiliated to Tongji University School of Medicine, Shanghai, People's Republic of China.
Wei GuDepartment of Urology, Shanghai Fourth People's Hospital Affiliated to Tongji University School of Medicine, Shanghai, People's Republic of China.
Chenji WangShanghai Engineering Research Center of Industrial Microorganisms, School of Life Science, Fudan University, Shanghai 200433, People's Republic of China.
Yao LiShanghai Engineering Research Center of Industrial Microorganisms, School of Life Science, Fudan University, Shanghai 200433, People's Republic of China.
Chaoneng JiShanghai Engineering Research Center of Industrial Microorganisms, School of Life Science, Fudan University, Shanghai 200433, People's Republic of China.
Shaohua GuShanghai Engineering Research Center of Industrial Microorganisms, School of Life Science, Fudan University, Shanghai 200433, People's Republic of China.
Yaoting XuDepartment of Urology, Shanghai Fourth People's Hospital Affiliated to Tongji University School of Medicine, Shanghai, People's Republic of China.
Fudan University · CNTongji University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionProstate cancer (PCa) is the most commonly diagnosed cancer and the third leading cause of cancer-related death in males in the United States. Despite the initial efficacy of androgen deprivation therapy in prostate cancer (PCa) patients, most patients progress to castration-resistant prostate cancer. However, the mechanisms underlying the androgen-independent progression of PCa remain largely unknown.

methodsIn this study, we established a PCa cell line (LNCaP-AI) by maintaining LNCaP cells under androgen-depleted conditions. To explore the cellular and molecular mechanisms of androgen-independent growth of PCa, we analyzed the gene expression patterns in androgen-independent prostate cancer (AIPC) compared with that in androgen-dependent prostate cancer (ADPC). KEGG pathway analysis revealed that Wnt signaling pathways were activated after androgen deprivation therapy (ADT). In vitro experiments showed that the inhibition of Wnt pathway reduced AIPC cell growth by inhibiting cell cycle progression and promoting apoptosis. Furthermore,

resultsIn the present study, we found a regulatory mechanism through which crosstalk between androgen receptor (AR) and Wnt signals promoted androgen-independent conversion of PCa. The Wnt pathway was inhibited by androgen in androgen-dependent prostate cancer cells, but this blocking effect was not elicited in androgen-independent prostate cancer (AIPC) cells. Moreover, Wnt pathway genes

conclusionIn summary, we revealed that crosstalk between AR and Wnt signaling pathways promotes androgen-independent growth of PCa, which may provide novel therapeutic opportunities for castration-resistant prostate cancer.

Indexed as

androgen deprivation therapyandrogen receptorprostate cancerWnt pathway

Identifiers

PMID32982312
PMCPMC7509333
OpenAlexW3087152049

What OpenQuestion holds

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LicenceCC BY-NC
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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.