Causal association of breast cancer with immune cells: new evidence from bi-directional Mendelian randomization using GWAS summary statistics

• Published in: BMC cancer Vol. 25; no. 1; pp. 609 - 9
• Main Authors: Wu, Zhixuan, Zhang, Rongrong, Wu, Xue, Meng, Xinyu, Wu, Haodong, Wang, Xiaowu, Zheng, Danni, Shen, Yanyan
• Format: Journal Article
• Language: English
• Published: England BioMed Central Ltd 03.04.2025; BioMed Central; BMC
• Subjects: Analysis; B cells; Breast cancer; Breast Neoplasms - genetics; Breast Neoplasms - immunology; Breast Neoplasms - pathology; Cancer; Cancer therapies; Care and treatment; Causal inference; Cells; Confounding (Statistics); Datasets; Development and progression; Female; Fibroblasts; Genetic aspects; Genetic Predisposition to Disease; Genome wide association study; Genome-wide association studies; Genomes; Genomics; Health aspects; Humans; Immune cells; Lymphocytes; Medical prognosis; Mendelian randomization; Mendelian Randomization Analysis; Oncology, Experimental; Phenotypes; Pleiotropy; Polymorphism, Single Nucleotide; Population studies; Prognosis; Software; Statistics; Tumor microenvironment; Tumor Microenvironment - genetics; Tumor Microenvironment - immunology; China; Causal inference; Breast cancer; Mendelian randomization; Genome wide association study; Immune cells
• ISSN: 1471-2407; 1471-2407
• DOI: 10.1186/s12885-025-13875-w

The tumor microenvironment of breast cancer encompasses a broad spectrum of immune cell populations. These cell populations are biologically/clinically relevant to varying degrees. The causal relationship between these immune cells and breast cancer remains uncertain despite their relevance. Bi-directional two-sample Mendelian randomization (MR) analyses were conducted to investigate the causal relationship between 731 immune cell phenotypes and breast cancer, utilizing genome-wide association study (GWAS) statistics. The primary analytical methods employed were the weighted median (WM) and random effects inverse variance weighting (IVW). The MR-Egger method, MR-PRESSO and Cochran's Q-statistic were utilized to evaluate heterogeneity and pleiotropy among the instrumental variables. The study found a causal relationship between 27 immune cell traits and the onset of breast cancer using instrumental variables derived from GWAS data. Elevated levels of 13 immune cell populations and reduced levels of 14 immune cell populations were involved in triggering the development of breast cancer. Furthermore, the study revealed a causal relationship where breast cancer development had a causal effect on immune cell levels. Specifically, the onset of breast cancer may lead to elevated levels of 7 immune cell populations and reduced levels of 10 immune cell populations. This study utilized genetic approaches to establish a causal relationship between immune cell traits and breast cancer. These findings offer potential novel targets for diagnosing and treating breast cancer.