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BackgroundBreast and thyroid cancer are increasingly prevalent, but it remains unclear whether the observed associations are due to heightened medical surveillance or intrinsic etiological factors. Observational studies are vulnerable to residual confounding, reverse causality, and bias, which can compromise causal inference. In this study, we employed a two-sample Mendelian randomization (MR) analysis to establish a causal link between breast cancer and heightened thyroid cancer risk.MethodsWe obtained the single nucleotide polymorphisms (SNPs) associated with breast cancer from a genome-wide association study (GWAS) conducted by the Breast Cancer Association Consortium (BCAC). The FinnGen consortium’s latest and largest accessible GWAS thyroid cancer data at the summary level. We performed four MR analyses, including the inverse-variance-weighted (IVW), weighted median, MR-Egger regression, and weighted mode, to evaluate the potential causal connection between genetically predicted breast cancer and higher risk for thyroid cancer. Sensitivity analysis, heterogeneity and pleiotropy tests were used to ensure the reliability of our findings.ResultsOur study revealed causal relationship between genetically predicted breast cancer and thyroid cancer (IVW method, odds ratio (OR) = 1.135, 95% confidence interval (CI): 1.006 to 1.279, P = 0.038). However, there was no causal association between genetically predicted triple-negative breast cancer and thyroid cancer (OR = 0.817, 95% CI: 0.610 to 1.095, P = 0.177). There was no directional pleiotropy or horizontal pleiotropy in the present study.ConclusionThis two-sample MR study supports a causal link between ER-positive breast cancer and heightened the risk of thyroid cancer. Our analysis did not reveal a direct correlation between triple-negative breast cancer and thyroid cancer.

Introduction: Matrix metalloproteinase 1 (MMP1) is overexpressed in multiple human tumors. However, the role of MMP1 in breast cancer (BRCA) has not been explored. Material and methods: The relationship between MMP1 expression and immune cell infiltration was conducted using Tumor Immune Estimation Resource (TIMER, https:// cistrome.shinyapps.io/timer/), and the survival curve was plotted using Kaplan-Meier with log-rank test. The influence of MMP1 on immune infiltration, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses, immunologic infiltration analysis, and drug sensitivity were conducted through R 4.2.0. Immunohistochemistry (IHC) and immunofluorescence (IF) were used to verify MMP1 expression in BC and the correlation between MMP1 and CD20, CD86 immune cells. Results: MMP1 was overexpressed in BRCA tumors (p<0.05), and its high expression was related to poor prognosis (p=0.01). In addition, MMP1 was an independent prognostic biomarker in BRCA. Our findings provide information to further understand the biological functions and signaling pathways of MMP1 in BRCA. IHC and IF have proven the relationship between MMP1 and BRCA. Conclusions: These results implied a critical role of MMP1 in the prognosis and immune infiltration of BRCA. In addition, MMP1 expression participated in regulating multiple oncogenes and tumorigenesis.