Evidence map›Paper›PMID 41102678›Full record

ArticleBiological procedures online2025

Uncovering Novel Susceptible Genes and Therapeutic Targets of Prostate Cancer: a Multi-omics Study Integrating Summary-based Mendelian Randomization Analysis and Molecular Docking.

Xuemeng Qiu, Yifei Zhang, Jiyue Wu, Zihao Gao, Xinyi Chai, Xihao Shen, Zejia Sun, Wei Wang

Abstract read
In one paragraph

Article in Biological procedures online, 2025. 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
–field-weighted citation impact
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. 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

8 authors.

Xuemeng Qiu *Department of Urology, Beijing Chao-Yang Hospital, Capital Medical University, 8 Gongrentiyuchang South Rd, Chaoyang District, Beijing, 100020, China.
Yifei Zhang *Department of Urology, Beijing Chao-Yang Hospital, Capital Medical University, 8 Gongrentiyuchang South Rd, Chaoyang District, Beijing, 100020, China.
Jiyue Wu *Department of Urology, Beijing Chao-Yang Hospital, Capital Medical University, 8 Gongrentiyuchang South Rd, Chaoyang District, Beijing, 100020, China.
Zihao GaoDepartment of Urology, Beijing Chao-Yang Hospital, Capital Medical University, 8 Gongrentiyuchang South Rd, Chaoyang District, Beijing, 100020, China.
Xinyi ChaiBeijing Children's Hospital, Capital Medical University, Beijing, China.
Xihao ShenDepartment of Urology, Beijing Chao-Yang Hospital, Capital Medical University, 8 Gongrentiyuchang South Rd, Chaoyang District, Beijing, 100020, China.
Zejia SunDepartment of Urology, Beijing Chao-Yang Hospital, Capital Medical University, 8 Gongrentiyuchang South Rd, Chaoyang District, Beijing, 100020, China. mnwkszj5076@163.com.ORCID https://orcid.org/0000-0003-1079-3019
Wei WangDepartment of Urology, Beijing Chao-Yang Hospital, Capital Medical University, 8 Gongrentiyuchang South Rd, Chaoyang District, Beijing, 100020, China. weiwang0920@163.com.ORCID https://orcid.org/0000-0003-2642-3338

Funding

Beijing Municipal Science and Technology Commission, Adminitrative Commission of Zhongguancun Science Park Z221100007422029Clinical Research Incubation Project of Beijing Chao-yang Hospital, Capital Medical University CYFH202203
6 · The paper itself

Abstract

backgroundUnderstanding the role of causal genes of prostate cancer (PrCa) can reveal key biological pathways and identify potential targets for treatment.

methodsWe investigated associations between genetically predicted gene expression levels and PrCa risk using cis-eQTL summary-based Mendelian randomization (SMR) and colocalization analysis. Findings were replicated using two independent PrCa GWAS. We then intersected the identified genes with differentially expressed genes (DEGs) identified from TCGA-PRAD dataset to obtain key genes. Furthermore, enrichment, protein-molecule network, immune infiltration, and epigenetic analyses were conducted to explore their biological pathways. Lastly, phenome-wide association study (PheWAS), drug prediction, and molecular docking simulation analysis were utilized to identify potential drugs.

resultsWe identified 15 genes in blood whose expression levels are putatively associated with PrCa, validated in at least one replication GWAS dataset. Using open-access mRNA-sequencing data, we found that ZNF217 and BNIP2 were key genes potentially important in PrCa pathogenesis. Single-cell RNA-sequencing analysis revealed that BNIP2 was predominantly expressed in a subset of endothelial cells, whereas ZNF217 was mainly enriched in epithelial cells. Downstream analysis revealed their involvement in epigenetic modulation-related pathways, while upstream analysis showed that upregulation of ZNF217 notably correlated with increased CpG methylation. Molecular docking simulation suggested doxorubicin, alsterpaullone, and camptothecin as potential drugs targeting these key genes.

conclusionsThese findings provide robust leads for understanding pathogenic mechanisms and developing therapeutic interventions for PrCa.

Indexed as

Drug discoveryEpigeneticMendelian randomizationMolecular dockingProstate cancer

Identifiers

PMID41102678
PMCPMC12532825

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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.