Back to Search Start Over

Adipogenesis biomarkers as the independent predictive factors for breast cancer recurrence: a systematic review and meta-analysis.

Authors :
Hu S
Tey SK
Kwong A
Source :
BMC cancer [BMC Cancer] 2024 Sep 27; Vol. 24 (1), pp. 1181. Date of Electronic Publication: 2024 Sep 27.
Publication Year :
2024

Abstract

Background: Comprehensive analysis of clinical evidence for breast cancer adipogenesis with prognosis is lacking. This study aims to consolidate the latest evidence on the relationship between adipogenesis and breast cancer outcomes.<br />Data Sources: Medline, Web of Science, Embase, Scopus, Clinicaltrials.gov, Cochrane library.<br />Methods: A systematic review was conducted according to the PRISMA guidelines. Studies that reported the correlation between tumor adipogenesis and cancer recurrence or empirical pathological markers were included for meta-analysis. The standard reference for pathological markers determination was set as histopathological examination. The PROSPERO ID was CRD489135.<br />Results: Eleven studies were included in this systematic review and meta-analysis. Several adipogenesis biomarkers involved in the synthesis, elongation, and catabolism of fatty acids, such as FASN, Spot 14, pS6K1, lipin-1, PLIN2, Elovl6, and PPARĪ³, were identified as the potential biomarkers for predicting outcomes. Through meta-analysis, the predictive value of adipogenesis biomarkers for 5-year recurrence rate was calculated, with a pooled predictive risk ratio of 2.19 (95% CI: 1.11-4.34). In terms of empirical pathological markers, a negative correlation between adipogenesis biomarkers and ki-67 was observed (RR: 0.69, 95% CI: 0.61-0.79). However, no significant correlation was found between the adipogenesis and ER, PR, HER2, or p53 positivity.<br />Conclusions: Biomarker of adipogenesis in breast cancer is a significant predictor of long-term recurrence, and this prediction is independent of HR, HER2, and ki-67. The diverse roles of adipogenesis in different breast cancer subtypes highlight the need for further research to uncover specific biomarkers that can used for diagnosis and prediction.<br />Protocol Registration: PROSPERO ID: CRD489135.<br /> (© 2024. The Author(s).)

Details

Language :
English
ISSN :
1471-2407
Volume :
24
Issue :
1
Database :
MEDLINE
Journal :
BMC cancer
Publication Type :
Academic Journal
Accession number :
39333940
Full Text :
https://doi.org/10.1186/s12885-024-12931-1