Characterization of cancer-associated adipocytes by Raman spectroscopy and trajectory inference

Abstract Cancer-associated adipocytes (CAAs) have emerged as pivotal players in various cancers, particularly in such as breast cancer, significantly influencing their progression and therapy resistance. Understanding the adipocytes/cancer cells crosstalk is crucial for effective treatment strategies. Raman spectroscopy, a label-free optical technique, offers potential for characterizing biological samples by providing chemical-specific information. In this study, we used Raman spectroscopy and Trajectory Inference methods, specifically the Partition-based graph abstraction algorithm, to investigate the interactions between 3T3-L1 differentiated adipocytes and MDA-MB-231 breast cancer cells in a 2D co-culture model. We demonstrate the existence of subpopulations of adipocytes and the molecular changes associated with CAAs phenotype. This work contributes to understanding the role of CAAs in breast cancer progression and may guide the development of targeted therapies disrupting this interaction.