The role of krüppel-like factor 4 (klf4) gene in breast cancer tissue samples: a systematic review and meta-analysis

Background: Breast cancer is the most common cancer and the primary cause of mortality due to cancer in female around the World. As a result, the aim of this research is to conduct a comprehensive systematic review and meta-analysis to determine the role of Krüppel-like factor 4 (KLF4) as the main g...

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Bibliographic Details
Main Authors: Salari, Nader, Rasoulpoor, Shabnam, Rasoulpoor, Shna, Mansouri, Kamran, Shohaimi, Shamarina, Mohammadi, Masoud
Format: Article
Published: Springer 2022
Online Access:http://psasir.upm.edu.my/id/eprint/103728/
https://link.springer.com/article/10.1007/s40944-022-00605-4
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Summary:Background: Breast cancer is the most common cancer and the primary cause of mortality due to cancer in female around the World. As a result, the aim of this research is to conduct a comprehensive systematic review and meta-analysis to determine the role of Krüppel-like factor 4 (KLF4) as the main gene expression in breast cancer tissue. Methods: The studies used in this systematic review were selected from the articles published from up to February 1, 2020, in national and international databases including SID, WoS, Magiran, PubMed, Scopus, IranDoc, Science Direct, IranMedix as well as Google Scholar. Results: From the systematic review, a meta-analysis was performed on 8 articles which were satisfied the inclusion criteria. The sample including 869 individuals was then selected to perform the meta-analysis. Based on the results derived from this meta-analysis, the total expression of klf4 gene in breast cancer tissue’s samples was 60.1% (95% CI: 45.1–73.4%). The highest and lowest Klf4 gene expression levels in breast cancer tissue samples were obtained 89.7% in Alabama in 2004 (95% CI: 83.7–93.7%) and 32.1% in Japan in 2016 (95% CI: 23.1–42.8%), respectively. The results showed that with increasing sample size and year of publication, klf4 gene expression was reduced in breast cancer tissue samples, which was statistically significant (P < 0.05). Conclusion: Identifying the expression profiles of genes involved in breast cancer using its various pathway inhibitors can address many challenges for researchers and is very important for advancing cancer health and treatment.