Classifying Hypoxia in Breast Cancer Xenografts Using a Single-Cell Mass Spectrometry Imaging Model

Abstract

Hypoxia is a common feature in solid tumors that arises when there is insufficient oxygen available. This lack of oxygen causes molecular adaptations required for the tumor cells to survive. Additionally, oxygen-deprived cancer cells tend to become less responsive to conventional cancer therapies. Hence, hypoxia plays an important role in contributing to tumor aggressiveness and therapy resistance. Hypoxia-related markers are gaining interest as prognostic and predictive markers for tumor response and treatment strategies. However, the detection of hypoxia in the tumor microenvironment without employing any labeling strategies poses significant challenges. Here, we present a classification model based on lipidomic single-cell mass spectrometry imaging data to classify hypoxia in breast cancer xenografts. Our approach is based on a classification model built from the lipid profiles of single breast cancer cells cultured under various oxygen conditions. Lipidomic alterations caused by differences in available oxygen concentrations were subsequently used to classify and spatially determine hypoxic regions in breast cancer xenografts without the need for any labeling. This approach, using cells as hypoxia markers, contributes to a better understanding of tumor biology and provides a foundation for improving diagnostic and therapeutic strategies for cancer treatments.