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Related Concept Videos

Genome-wide Association Studies-GWAS01:11

Genome-wide Association Studies-GWAS

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Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
GWAS does not require the identification of the target gene involved in...
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Evaluating the Impact of Folate on Male Infertility Using Mendelian Randomization: A Comprehensive Analysis.

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Single-Cell Analysis Combined with Mendelian Randomization Identifies Genes Associated with Prostate Cancer Cells.

Weizhuo Wang1, Kaiyu Lu1, Xi Zhang2

  • 1Department of Urology, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Nanjing Medical University, Suzhou, China.

The World Journal of Men'S Health
|June 29, 2025
PubMed
Summary

This study identifies TMEM59 as a key gene in prostate cancer progression. Lower TMEM59 levels correlate with increased cancer invasion, suggesting its potential as a prognostic marker.

Keywords:
BiomarkersMendelian randomization analysisProstatic neoplasmsSingle-cell gene expression analysisTumor microenvironment

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Area of Science:

  • Oncology
  • Genomics
  • Bioinformatics

Background:

  • Prostate cancer incidence rises with age, with capsular invasion significantly altering prognosis.
  • Identifying genes associated with advanced prostate cancer is crucial for improving patient outcomes.

Purpose of the Study:

  • To investigate prognostic genes linked to prostate cancer capsular invasion.
  • To integrate single-cell sequencing data with Mendelian randomization (MR) analysis for gene discovery.

Main Methods:

  • Single-cell RNA sequencing data analyzed using hdWGCNA to identify key gene modules.
  • Mendelian randomization (MR) analysis utilized UK Biobank data to assess gene associations.
  • TCGA and GEO data, alongside cellular experiments and immunohistochemistry, validated gene prognostic value.

Main Results:

  • hdWGCNA identified 200 candidate genes; MR analysis highlighted TMEM59, JUNB, NECTIN2, OSBPL10, ATF3, and WLS.
  • TMEM59 emerged as a potential protective factor, with its knockdown enhancing prostate cancer cell proliferation and invasion.
  • Immunohistochemistry confirmed reduced TMEM59 expression in tumor tissues.

Conclusions:

  • TMEM59 plays a significant role in prostate cancer progression.
  • TMEM59 demonstrates potential as a prognostic predictor and therapeutic target for prostate cancer.