Tracking mammary tumor progression over time by analysis of urinary volatile organic compounds

Previous studies have shown that volatile organic compounds (VOCs) are potential biomarkers of breast cancer in murine models. However, an unanswered question is how urinary VOCs change over time. To explore this, BALB/c mice were injected with 4T1.2 murine tumor cells in the tibia. This typically leads to tumor progression and induces osteolytic lesions in 1-2 weeks. Samples were collected prior to tumor injection (n = 20) and periodically over the next three weeks (12, 15, and 18 samples collected during weeks 1, 2, and 3). Samples were analyzed by headspace-solid phase microextraction (HS-SPME) coupled to gas chromatography–mass spectrometry quadrupole time-of-flight (GC-MS QTOF). Univariate analysis identified VOCs that were biomarkers for cancer and showed that some VOCs varied significantly over time, presumably due to tumor progression and formation of osteolytic lesions, and other biomarkers did not. Principal component analysis (PCA) utilizing a panel of VOCs was able to distinguish Cancer Weeks 1-3 from Control and Cancer Week 1 from Cancer Week 3 with over 90% accuracy. Forward feature selection and linear discriminant analysis (LDA) identified a panel of five VOCs that could identify tumor presence (Cancer from Control) with 94% accuracy (using five-fold cross-validation) and distinguish progression (Cancer Week 1 from Cancer Week 3) with 97% accuracy (five-fold cross-validation). Principal component regression analysis identified a model with R² = 0.71 and adjusted R² = 0.63, correlating the number of days since tumor injection. The results of this study show that volatile chemical profiles convert over time and because of this, VOCs may be used to monitor breast cancer progression in mouse models.