Breast cancer is the most prevalent malignant tumor in women, with distant metastasis being the leading cause of mortality. Triple-negative breast cancer (TNBC) carries an exceptionally high lung metastasis risk, and once metastatic, the 5-year survival rate is merely ∼10.94%. A critical clinical gap lies in the lack of noninvasive biomarkers for early metastasis prediction, as conventional imaging fails to detect early micrometastasis and dynamic metabolic perturbations. This study aimed to characterize the temporal dynamics of glycolytic flux, lactate metabolism, and hypoxia during breast cancer lung metastasis, and validate metabolic imaging biomarkers for early prediction. Orthotopic TNBC models were established by implanting 4T1 cells into BALB/c mice, followed by longitudinal monitoring using photoacoustic (PA) imaging, deuterium metabolic imaging (DMI), computed tomography (CT), and hematoxylin-eosin staining. A distinct metastatic timeline was identified: lung micrometastases emerged at Week 2, while CT detected macro-metastases only at Week 3. PA imaging revealed the onset of compensatory hypoxia at Week 2 (oxygen saturation decreased from ∼70% to ∼60%). Concurrently, DMI demonstrated a ∼2-fold increase in glucose uptake and >2-fold accumulation of lactate, indicating enhanced aerobic glycolysis. Hypoxia-inducible factor-1α was significantly upregulated at Weeks 2 and 3, coinciding with macro-metastasis progression. The temporal coupling between Week 2 metabolic reprogramming and micrometastasis initiation highlights lactate as a key pro-metastatic metabolite. DMI, combined with PA imaging, enables noninvasive detection of metabolic and hypoxic alterations preceding CT-detectable macro-metastases, providing a predictive biomarker and technical platform for early warning of breast cancer metastasis and precision intervention.
Hang et al. (Thu,) studied this question.