Causal relationship between breast cancer and acute myeloid leukemia based on two-sample bidirectional Mendelian randomization and transcriptome overlap analysis.

Abstract

Background: Breast cancer is the most prevalent malignancy and the leading cause of cancer-related deaths among women worldwide. Several case reports have shown that some breast cancer patients subsequently develop acute myeloid leukemia (AML) within a short period. However, the causal relationship and pathogenic mechanisms between breast cancer and AML remain incompletely understood.

Methods: Mendelian randomization (MR) analyses were conducted to explore the bidirectional causal relationships between breast cancer and AML. Additionally, we applied the Bayesian Weighted Mendelian Randomization (BWMR) approach to validate the results of the MR analysis. Subsequently, we utilized RNA-seq data from various sources to explore the potential molecular signaling pathways between breast cancer and AML.

Results: Both IVW method and BWMR approach demonstrated that data from three distinct sources consistently indicated breast cancer as a risk factor for AML, with all sources showing statistically significant results (all P < 0.05, Odds Ratios [ORs] > 1). Bioinformatic analyses suggested that extracellular vesicle functions and p53 signaling pathway may mediate molecular links between breast cancer and AML. Using machine learning, we identified 8 genes with high diagnostic efficacy for predicting the occurrence of AML in breast cancer patients.

Conclusions: MR analyses indicated a causal relationship between breast cancer and AML. Additionally, transcriptome analysis offered a theoretical basis for understanding the potential mechanisms and therapeutic targets of AML in breast cancer patients.