Association between breast cancer risk factors and blood microbiome in patients with breast cancer

Abstract

This study investigated the relationship between risk factors for breast cancer (BC) and the microbiome by comparing the microbiomes of BC patients with fatty liver disease to those with a normal liver. Bacterial extracellular vesicles were collected from each blood sample, and next-generation sequencing was performed. The analysis identified specific microbiome profiles shared among groups with hyperglycaemia, hyperlipidaemia, and high body mass index (BMI), which were then compared with functional biomarkers. In particular, the genus Faecalibacterium was a specific bacterium found in the groups with high concentrations of low-density lipoprotein cholesterol, high BMI, and fatty liver disease. Therefore, when the prognosis of patients with BC was analysed based on Faecalibacterium presence, it was confirmed that patients' prognoses tended to deteriorate. In this study, BC risk factors, such as hyperglycaemia, hyperlipidaemia, fatty liver, and high BMI, were interconnected through the microbiome. This provides insights into how the risk factors for BC are linked and their impact on the microbiome and human health.

Keywords: Breast cancer; Fatty liver; Microbiome; Prognosis.

Fig. 1

Characteristics of patients with BC separated into normal and fatty liver groups. Characteristics according to (A) menstrual status, (B) dietary pattern, (C) age, (D) BMI, (E) HDL cholesterol, (F) LDL cholesterol, and (G) fasting blood glucose.

Fig. 2

Serum microbiome profiles of normal and fatty liver groups in patients with BC. (A) α-diversity (Jackknife) and (B) β-diversity (Jensen-Shannon, species level) in normal and fatty liver groups. Microbiome profiles from patients with (C) normal and (D) fatty liver disease at the phyla level.

Fig. 3

Significantly different taxa between each subgroup according to linear discriminant analysis effect size (LEfSe). The microbiomes specific to each group were analysed from phylum to species level by dividing the subjects into two groups according to (A) normal versus fatty liver disease, and by (B) LDL cholesterol (LDL-c), (C) BMI, (D) fasting blood glucose, and (E) HDL cholesterol (HDL-c) levels.

Fig. 4

Venn diagram showing overlapping genera or species of bacteria in each subgroup from significantly different taxa according to linear discriminant analysis effect size (LEfSe).

Fig. 5

Analysis demonstrating the bacterial proteins specific to each group. (A) A Venn diagram illustrating the number of specific bacterial proteins in each subgroup, (B) Identifying the specific bacterial proteins in fatty liver disease and (C) normal liver and analysing the relationship between proteins in String.

Fig. 6

Analysis of disease-free survival by microbiome composition in relation to BC risk factors. The prognosis of patients with BC according to the abundance of (A) Faecalibacterium genus and (B) Christensenellaceae family was analysed using Kaplan–Meier analysis.