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Related Experiment Video

Updated: May 31, 2026

Microarray-based Identification of Individual HERV Loci Expression: Application to Biomarker Discovery in Prostate Cancer
13:19

Microarray-based Identification of Individual HERV Loci Expression: Application to Biomarker Discovery in Prostate Cancer

Published on: November 2, 2013

Identifying novel prostate cancer associated pathways based on integrative microarray data analysis.

Ying Wang1, Jiajia Chen, Qinghui Li

  • 1Center for Systems Biology, Soochow University, No. 1. Shizi Street, Suzhou 215006, China.

Computational Biology and Chemistry
|June 28, 2011
PubMed
Summary
This summary is machine-generated.

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This study analyzed prostate cancer gene expression data, revealing that pathway-level analysis is more consistent than gene-level analysis. It identified novel pathways crucial for understanding prostate cancer and developing targeted therapies.

Area of Science:

  • Genomics
  • Bioinformatics
  • Cancer Research

Background:

  • Meta-analysis is crucial for expression data analysis using microarray and next-generation sequencing.
  • Pathway-level analysis is more reproducible than reductionist approaches.
  • Prostate cancer molecular signatures at the pathway level have not been extensively explored.

Purpose of the Study:

  • To perform a meta-analysis of prostate cancer expression datasets.
  • To identify common gene and pathway-level signatures.
  • To explore novel prostate cancer-associated pathways.

Main Methods:

  • Meta-analysis of 10 prostate cancer microarray datasets.
  • Enrichment analysis using GeneGo and KEGG databases.
  • Gene Set Enrichment Analysis (GSEA).

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miRNA Expression Analyses in Prostate Cancer Clinical Tissues
11:29

miRNA Expression Analyses in Prostate Cancer Clinical Tissues

Published on: September 8, 2015

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Last Updated: May 31, 2026

Microarray-based Identification of Individual HERV Loci Expression: Application to Biomarker Discovery in Prostate Cancer
13:19

Microarray-based Identification of Individual HERV Loci Expression: Application to Biomarker Discovery in Prostate Cancer

Published on: November 2, 2013

miRNA Expression Analyses in Prostate Cancer Clinical Tissues
11:29

miRNA Expression Analyses in Prostate Cancer Clinical Tissues

Published on: September 8, 2015

Main Results:

  • Pathway-level signatures showed higher similarity than gene-level signatures (97.8% GeneGo, 66.7% KEGG).
  • 15 enriched pathways overlapped in at least eight datasets.
  • Eight novel prostate cancer-associated pathways were identified, including the endothelin-1/EDNRA transactivation of the EGFR pathway.

Conclusions:

  • Pathway-level meta-analysis is a robust approach for identifying prostate cancer signatures.
  • Novel pathways identified offer potential for developing network biomarkers.
  • Findings support the development of individualized therapy strategies for prostate cancer.