Biopsy bacterial signature can predict patient tissue malignancy

Area of Science:

• Microbiology
• Oncology
• Bioinformatics

Background:

• Recent research confirms bacteria presence in human tumors and normal tissues.
• The study shifts focus from identifying bacteria in tumors to using bacterial profiles for histology and malignancy assessment.

Purpose of the Study:

• To differentiate between malignant and non-malignant fresh breast biopsy specimens using only bacterial sequence data.
• To establish if bacterial signatures can predict breast cancer malignancy.

Main Methods:

• 16S rRNA gene sequencing of fresh breast tissue biopsies from cancer patients.
• Rigorous microbiological and bioinformatic contamination control.
• Statistical and machine-learning analyses to compare tumor and normal tissue microbiomes.

Main Results:

• Breast tumor and matched normal tissue microbiome profiles showed significant differences.
• A classification model using bacterial biomarkers achieved 84.78% accuracy in identifying malignant breast tissue.
• The model demonstrated a high diagnostic performance with an area under the ROC curve of 0.888.

Conclusions:

• Bacterial signatures in tissue biopsies hold potential for identifying malignancy status.
• This study provides proof-of-concept for using the tissue microbiome to diagnose breast cancer.
• Bacterial biomarkers offer a novel strategy for breast cancer detection and diagnosis.