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Correlation Between PIK3R1 Expression and Cell Growth in Human Breast Cancer Cell Line BT-474 and Clinical Outcomes
Yi-Fang Tsai1,2,3, Jiun-I Lai1,3,4, Chun-Yu Liu1,3,4
1Comprehensive Breast Health Center, Department of Surgery, Taipei Veterans General Hospital, Taipei 112201, Taiwan.
World Journal of Oncology
|January 24, 2025
Summary
Downregulating PIK3R1 in breast cancer cells increased proliferation and AKT-mTOR signaling. High PIK3R1 expression in early-stage breast cancer patients correlated with better survival outcomes.
Area of Science:
- Oncology
- Molecular Biology
- Genetics
Background:
- PIK3CA mutations are key in breast cancer development.
- PIK3R1 gene alterations represent actionable targets for cancer therapy.
- Understanding PIK3R1's role in breast carcinoma is crucial for treatment strategies.
Purpose of the Study:
- To investigate the role of PIK3R1 in breast carcinoma cell proliferation.
- To correlate PIK3R1 expression levels with patient outcomes in breast cancer.
- To analyze the impact of PIK3R1 on overall survival (OS) and disease-free survival (DFS).
Main Methods:
- Utilized the BT-474 (ER+/HER2-high) breast cancer cell line for in vitro studies.
- Performed PIK3R1 gene knockdown (ΔPIK3R1) to assess effects on cell proliferation.
- Retrospectively reviewed data from 440 breast cancer patients (2000-2015).
- Employed human breast cancer tissue arrays for immunostaining and correlation analysis.
Main Results:
- PIK3R1 knockdown in BT-474 cells led to increased cell proliferation and altered cell cycle distribution (increased S and G2M fractions).
- Reduced PIK3R1 protein levels correlated with increased p-AKT and p-mTOR signaling.
- High PIK3R1 expression in early-stage (I/II) breast cancer patients was associated with improved DFS and OS.
Conclusions:
- Downregulation of PIK3R1 promotes cell growth and activates AKT-mTOR signaling in breast cancer cells.
- Elevated PIK3R1 protein expression is a positive prognostic marker for early-stage breast cancer patients.
- PIK3R1 status may inform treatment decisions and predict outcomes in specific breast cancer stages.
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