Comparative bioinformatics analysis of the Wnt pathway in breast cancer: Selection of novel biomarker panels associated with ER status
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View abstract on PubMed
Summary
This summary is machine-generated.This study identifies novel Wnt-associated gene panels for breast cancer (BC) diagnosis and prognosis. These biomarkers can help classify BC subtypes and improve patient outcomes.
Area Of Science
- Oncology
- Genomics
- Bioinformatics
Background
- Breast cancer (BC) is a leading cause of cancer death globally, necessitating improved diagnostic and prognostic tools.
- The Wnt signaling pathway is implicated in BC progression, affecting cell cycle regulation and stem cell renewal.
- Identifying novel biomarkers is crucial for early BC classification and enhanced patient outcomes.
Purpose Of The Study
- To identify novel Wnt-associated biomarker panels for breast cancer (BC) patients.
- To develop molecular signatures for BC subtype classification and survival prediction.
- To leverage bioinformatic analyses for discovering diagnostic and prognostic markers.
Main Methods
- Weighted gene co-expression network analysis (WGCNA)
- Differential gene expression analysis
- Kaplan-Meier survival analysis, logistic regression, and receiver operating characteristic (ROC) curve construction using The Cancer Genome Atlas (TCGA) data.
Main Results
- Four distinct gene signatures were developed.
- Two signatures differentiate ER+ from ER-BC: TTC8, SLC5A7, PLCH1 (overall survival - OS); ZNF695, SLC7A5, PLCH1 (disease-free survival - DFS).
- Two signatures distinguish tumor from normal samples: SPC25, ANLN, KPNA2, SLC7A5 (OS); SPC25, KIF20A, SKA3, DTL, CDCA3, ANLN, TTK, RAD54L, MYBL2, ZNF695, SLC7A5 (DFS).
Conclusions
- The identified gene signatures show potential as diagnostic and prognostic tools for breast cancer.
- These Wnt-associated biomarkers could aid in classifying BC subtypes and predicting patient survival.
- Comprehensive bioinformatic analysis of TCGA data provides a foundation for novel BC biomarker discovery.
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