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  11. Hub Metastatic Gene Signature And Risk Score Of Breast Cancer Patients With Small Tumor Sizes Using Wgcna

Hub metastatic gene signature and risk score of breast cancer patients with small tumor sizes using WGCNA

Yu-Tien Chang1, Zhi-Jie Hong2, Hsueh-Han Tsai2

  • 1School of Public Health, National Defense Medical Center, Taipei City, Taiwan.

Breast Cancer (Tokyo, Japan)
|August 27, 2024

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View abstract on PubMed

Summary
This summary is machine-generated.

A new gene signature predicts distant metastasis-free survival (DMFS) in early-stage breast cancer (BC). This prognostic model identifies high-risk patients with small tumors, aiding in early intervention for breast cancer metastasis.

Area of Science:

  • Oncology
  • Genomics
  • Bioinformatics

Background:

  • Breast cancer (BC) is a leading cause of cancer death in women globally.
  • The mechanisms driving distant metastasis (DM) in patients with small tumors remain unclear.
  • Early prediction of metastasis is crucial for effective breast cancer treatment.

Purpose of the Study:

  • To develop a genetic prediction model for distant metastasis-free survival (DMFS) in breast cancer patients with small tumors (≤2 cm).
  • To identify key genes and pathways associated with metastasis in early-stage breast cancer.

Main Methods:

  • Integrated gene expression data from ten RNA-seq datasets.
  • Utilized Weighted Gene Co-expression Network Analysis (WGCNA) and LASSO Cox regression.
  • Developed a risk score and nomogram model for predicting DMFS.
Keywords:
Breast cancerDistant metastasis-free survivalLASSO cox regressionSmall tumor size

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Main Results:

  • Identified nine hub metastatic genes (ABHD11, DDX39A, G3BP2, GOLM1, IL1R1, MMP11, PIK3R1, SNRPB2, VAV3) for a risk score.
  • High-risk score significantly correlated with increased risk of DM in training and validation cohorts (HR 4.51-5.48).
  • Nomogram model demonstrated good prediction accuracy (C-indices 0.72-0.76) for 3-, 5-, and 7-year DMFS.
  • Enriched pathways included immune regulation and cell-cell signaling.
  • EGFR acts as a hub gene in the protein-protein interaction network of key metastatic genes.

Conclusions:

  • A prognostic gene signature effectively predicts DMFS in early-stage breast cancer patients.
  • The identified gene signature and associated protein-protein interaction network provide insights into metastasis mechanisms.
  • Further experimental validation is warranted to elucidate the role of EGFR and its interacting genes in breast cancer progression.
Weighted gene co-expression network analysis