Jiafeng Shou1, Yucheng Lai2, Jinming Xu3, Jian Huang4. 1. Cancer Institute (Key Laboratory of Cancer Prevention and Intervention, National Ministry of Education, Provincial Key Laboratory of Molecular Biology in Medical Sciences), The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 31009, China. Electronic address: 3100102375@zju.edu.cn. 2. Cancer Institute (Key Laboratory of Cancer Prevention and Intervention, National Ministry of Education, Provincial Key Laboratory of Molecular Biology in Medical Sciences), The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 31009, China. Electronic address: 704960737@qq.com. 3. Cancer Institute (Key Laboratory of Cancer Prevention and Intervention, National Ministry of Education, Provincial Key Laboratory of Molecular Biology in Medical Sciences), The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 31009, China. Electronic address: xujingming0110@163.com. 4. Cancer Institute (Key Laboratory of Cancer Prevention and Intervention, National Ministry of Education, Provincial Key Laboratory of Molecular Biology in Medical Sciences), The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 31009, China; Department of Oncology, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310009, China. Electronic address: drhuangjian@zju.edu.cn.
Abstract
BACKGROUND: Despite some published papers analyzing the prognostic role of forkhead-box A1 (FOXA1) in breast cancer, it has not yet been considered as an established prognostic factor in clinical practice. The present meta-analysis evaluated the prognostic value of FOXA1 in breast cancer. METHODS: PubMed, Web of Science and Embase databases were searched for relevant published literature that evaluated the correlation between FOXA1 and breast cancer. Either a fixed or random effect model was applied to estimate the pooled hazard ratio (HR) for FOXA1 prognosis in breast cancer. RESULT: A total of nine articles comprising 6386 breast cancer patients met the inclusion criteria. Among these nine studies, five studies and four studies investigated the prognostic association with disease-free survival (DFS), and overall survival (OS), respectively. Meta-analysis results suggested that high FOXA1 expression was positively associated with DFS (pooled HR: 0.43, 95% CI: 0.23-0.81; P < 0.05) and OS (pooled HR: 0.39, 95% CI: 0.26-0.60; P < 0.05) in breast cancer patients. No publication bias was discovered by Begg's test in this meta-analysis. CONCLUSION: The results from this meta-analysis indicated that elevated FOXA1 expression level was associated with better outcome in breast cancer.
BACKGROUND: Despite some published papers analyzing the prognostic role of forkhead-box A1 (FOXA1) in breast cancer, it has not yet been considered as an established prognostic factor in clinical practice. The present meta-analysis evaluated the prognostic value of FOXA1 in breast cancer. METHODS: PubMed, Web of Science and Embase databases were searched for relevant published literature that evaluated the correlation between FOXA1 and breast cancer. Either a fixed or random effect model was applied to estimate the pooled hazard ratio (HR) for FOXA1 prognosis in breast cancer. RESULT: A total of nine articles comprising 6386 breast cancerpatients met the inclusion criteria. Among these nine studies, five studies and four studies investigated the prognostic association with disease-free survival (DFS), and overall survival (OS), respectively. Meta-analysis results suggested that high FOXA1 expression was positively associated with DFS (pooled HR: 0.43, 95% CI: 0.23-0.81; P < 0.05) and OS (pooled HR: 0.39, 95% CI: 0.26-0.60; P < 0.05) in breast cancerpatients. No publication bias was discovered by Begg's test in this meta-analysis. CONCLUSION: The results from this meta-analysis indicated that elevated FOXA1 expression level was associated with better outcome in breast cancer.
Authors: Jiaxuan Liu; Wei Zhao; Farah Ammous; Stephen T Turner; Thomas H Mosley; Xiang Zhou; Jennifer A Smith Journal: Epigenetics Date: 2019-03-14 Impact factor: 4.528
Authors: Suzie K Hight; Allison Mootz; Rahul K Kollipara; Elizabeth McMillan; Paul Yenerall; Yoichi Otaki; Long-Shan Li; Kimberley Avila; Michael Peyton; Jaime Rodriguez-Canales; Barbara Mino; Pamela Villalobos; Luc Girard; Patrick Dospoy; Jill Larsen; Michael A White; John V Heymach; Ignacio I Wistuba; Ralf Kittler; John D Minna Journal: Neoplasia Date: 2020-05-13 Impact factor: 5.715