Lifestyle Factors and Energy Intakes with Risks of Breast Cancer among Pre- and Post- Menopausal Women in Taiwan

A contemporary review of breast cancer risk factors and the role of artificial intelligence

Background

Breast cancer continues to be a significant global health issue, necessitating advancements in prevention and early detection strategies. This review aims to assess and synthesize research conducted from 2020 to the present, focusing on breast cancer risk factors, including genetic, lifestyle, and environmental aspects, as well as the innovative role of artificial intelligence (AI) in prediction and diagnostics.

Methods

A comprehensive literature search, covering studies from 2020 to the present, was conducted to evaluate the diversity of breast cancer risk factors and the latest advances in Artificial Intelligence (AI) in this field. The review prioritized high-quality peer-reviewed research articles and meta-analyses.

Results

Our analysis reveals a complex interplay of genetic, lifestyle, and environmental risk factors for breast cancer, with significant variability across different populations. Furthermore, AI has emerged as a promising tool in enhancing the accuracy of breast cancer risk prediction and the personalization of prevention strategies.

Conclusion

The review highlights the necessity for personalized breast cancer prevention and detection approaches that account for individual risk factor profiles. It underscores the potential of AI to revolutionize these strategies, offering clear recommendations for future research directions and clinical practice improvements.

The Contribution of Tissue Inhibitor of Metalloproteinase-2 Genotypes to Breast Cancer Risk in Taiwan

Tissue inhibitor of metalloproteinase-2 (TIMP-2) is an endogenous inhibitor of matrix metalloproteinase-2 and is highly expressed in breast cancer (BC) cases at diagnosis. However, the genetic investigations for the association of TIMP-2 genotypes with BC risk are rather limited. In this study, contribution of TIMP-2 rs8179090, rs4789936, rs2009196 and rs7342880 genotypes to BC risk was examined among Taiwan's BC population. TIMP-2 genotypic profiles were revealed among 1232 BC cases and 1232 controls about their contribution to BC using a PCR-based RFLP methodology. The TIMP-2 rs8179090 homozygous variant CC genotype was significantly higher in BC cases than controls (odds ratio (OR) = 2.76, 95% confidence interval (95%CI) = 1.78-4.28, p = 0.0001). Allelic analysis showed that C allele carriers have increased risk for BC (OR = 1.39, 95%CI = 1.20-1.62, p = 0.0001). Genotypic together with allelic analysis showed that TIMP-2 rs4789936, rs2009196 or rs7342880 were not associated with BC risk. Stratification analysis showed that TIMP-2 rs8179090 genotypes were significantly associated with BC risk among younger (≤55) aged women, not among those of an elder (>55) age. Last, rs8179090 genotypes were also associated with triple negative BC. This study sheds light into the etiology of BC in Taiwanese women. Rs8179090 may be incorporated into polygenic risk scores and risk prediction models, which could aid in stratifying individuals for targeted breast cancer screening.