Till Örebro universitet

Traditional approaches to studying cellular morphology rely on geometric metrics from stained images. However, staining processes can disrupt the cell's natural state and diminish accuracy due to photobleaching, while conventional analysis techniques, which categorize cells based on shape to discern pathophysiological conditions, often fail to capture the continuous and asynchronous nature of biological processes such as cell differentiation, immune responses, and cancer progression. In this work, we propose the use of quantitative phase imaging for morphological assessment due to its label-free nature. For analysis, we repurposed the genomic analysis toolbox to perform trajectory inference analysis purely based on morphology information. We applied the developed framework to study the progression of leukemia and breast cancer metastasis. Applying this framework to leukemia and breast cancer metastasis, we identified key shape changes linked to disease progression, highlighting the method's potential to enhance understanding of complex biological dynamics.