A deep learning-based pipeline for analyzing the influences of interfacial mechanochemical microenvironments on spheroid invasion using differential interference contrast microscopic images.

Metastasis is the leading cause of cancer-related deaths. During this process, cancer cells are likely to navigate discrete tissue-tissue interfaces, enabling them to infiltrate and spread throughout the body. Three-dimensional (3D) spheroid modeling is receiving more attention due to its strengths in studying the invasive behavior of metastatic cancer cells. While microscopy is a conventional approach for investigating 3D invasion, post-invasion image analysis, which is a time-consuming process, remains a significant challenge for researchers. In this study, we presented an image processing pipeline that utilized a deep learning (DL) solution, with an encoder-decoder architecture, to assess and characterize the invasion dynamics of tumor spheroids. The developed models, equipped with feature extraction and measurement capabilities, could be successfully utilized for the automated segmentation of the invasive protrusions as well as the core region of spheroids situated within interfacial microenvironments with distinct mechanochemical factors. Our findings suggest that a combination of the spheroid culture and DL-based image analysis enable identification of time-lapse migratory patterns for tumor spheroids above matrix-substrate interfaces, thus paving the foundation for delineating the mechanism of local invasion during cancer metastasis.

The interface stiffness and topographic feature dictate interfacial invasiveness of cancer spheroids.

During cancer metastasis, tumor cells likely navigate, in a collective manner, discrete tissue spaces comprising inherently heterogeneous extracellular matrix microstructures where interfaces may be frequently encountered. Studies have shown that cell migration modes can be determined by adaptation to mechanical/topographic cues from interfacial microenvironments. However, less attention has been paid to exploring the impact of interfacial mechnochemical attributes on invasive and metastatic behaviors of tumor aggregates. Here, we excogitated a collagen matrix-solid substrate interface platform to investigate the afore-stated interesting issue. Our data revealed that stiffer interfaces stimulated spheroid outgrowth by motivating detachment of single cells and boosting their motility and velocity. However, stronger interfacial adhesive strength between matrix and substrate led to the opposite outcomes. Besides, this interfacial parameter also affected the morphological switch between migration modes of the detached cells and their directionality. Mechanistically, myosin II-mediated cell contraction, compared to matrix metalloproteinases-driven collagen degradation, was shown to play a more crucial role in the invasive outgrowth of tumor spheroids in interfacial microenvironments. Thus, our findings highlight the importance of heterogeneous interfaces in addressing and combating cancer metastasis.