Proteomic and metabolomic characterization of bone, liver, and lung metastases in plasma of breast cancer patients

Area of Science:

• Oncology
• Proteomics
• Metabolomics

Background:

• Breast cancer (BC) is a leading cause of cancer death in women, with metastasis being the primary driver of mortality.
• Identifying reliable biomarkers for early detection of BC metastasis is crucial for improving patient survival rates.

Purpose of the Study:

• To identify and validate plasma-based proteomic and metabolomic biomarkers for detecting bone, liver, and lung metastases in breast cancer patients.
• To develop accurate diagnostic models for different types of breast cancer metastasis.

Main Methods:

• Comprehensive plasma proteomics and metabolomics analysis in 51 BC patients.
• Biomarker screening using Least Absolute Shrinkage and Selection Operator (LASSO) regression and Random Forest algorithms.
• Validation of prognostic biomarkers using enzyme-linked immunosorbent assay (ELISA) kits and untargeted metabolomics in an independent cohort.

Main Results:

• Extracellular matrix (ECM)-related functional enrichments were observed in breast cancer with bone metastases.
• Proteins involved in retinol metabolism (liver) and leukocyte transendothelial migration (lung) were identified as key in metastasis.
• Machine learning models achieved high diagnostic accuracy (AUC > 0.94) for bone, liver, and lung metastases.

Conclusions:

• Validated biomarkers for bone metastasis include leucyl-tryptophan, LysoPC(P-16:0/0:0), FN1, and HSPG2.
• Biomarkers dUDP, LPE(18:1/0:0), and aspartylphenylalanine were confirmed for liver metastasis.
• Established biomarkers for lung metastasis are dUDP, testosterone sulfate, and PE(14:0/20:5).