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The Effects of Omega-3 Polyunsaturated Fatty Acids on Breast Cancer as a Preventive Measure or as an Adjunct to Conventional Treatments

Matheus H Theinel, M. Nucci, Arielly H. Alves, O. F. M. Dias, J. B. Mamani, M. M. Garrigós, F. Oliveira, Gabriel N. A. Rego et al.

Nutrients, 2023

30 citations

Abstract

In order to understand how omega-3 polyunsaturated fatty acid (ω-3 PUFA) supplements affect breast cancer prevention and treatment, a systematic review of articles published in the last 5 years in two databases was performed. Of the 679 articles identified, only 27 were included and examined based on five topics, taking into account: the induction type of the breast cancer used in animal models; the characteristics of the induction model by cell transplantation; the experimental design of the ω-3 supplementation—combined or not with a treatment antitumor drug; the fatty acids (FAs) composition used; the analysis of the studies’ outcomes. There are diverse and well-established animal models of breast cancer in the literature, with very relevant histological and molecular similarities depending on the specific objective of the study, such as whether the method of tumor induction was transgenic, by cell transplantation, or by oncogenic drugs. The analyses of outcomes were mainly focused on monitoring tumor growth, body/tumor weight, and molecular, genetic, or histological analyses, and few studies evaluated latency, survival, or metastases. The best results occurred when supplementation with ω-3 PUFA was associated with antitumor drugs, especially in the analysis of metastases and volume/weight of tumors or when the supplementation was started early and maintained for a long time. However, the beneficial effect of ω-3 PUFA supplementation when not associated with an antitumor…

How strong is the evidence?

Evidence Hub reads this as a review, done in animal, not in people. Its evidence level is 5 of 5 (Very low · case / narrative / animal / in vitro / in silico). Case reports, narrative reviews, and animal, cell or computer-model studies give the weakest evidence for human health.

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