The ability of tissues and cells to move and rearrange is central to a broad range of diverse biological processes such as tissue remodeling and rearrangement in embryogenesis, cell migration in wound healing, or cancer progression. These processes are linked to a solid-like to fluid-like transition, also known as unjamming transition, a not rigorously defined framework that describes switching between a stable, resting state and an active, moving state. Various mechanisms, that is, proliferation and motility, are critical drivers for the (un)jamming transition on the cellular scale. However, beyond the scope of these fundamental mechanisms of cells, a unifying understanding remains to be established. During embryogenesis, the proliferation rate of cells is high, and the number density is continuously increasing, which indicates number-density-driven jamming. In contrast, cells have to unjam in tissues that are already densely packed during tumor progression, pointing toward a shape-driven unjamming transition. Here, we review recent investigations of jamming transitions during embryogenesis and cancer progression and pursue the question of how they might be interlinked. We discuss the role of density and shape during the jamming transition and the different biological factors driving it.
Background: Abnormal lipid metabolism plays an essential role in breast cancer progression and metastasis. Lipid droplets (LD) have multifunctional tasks as they store and transfer lipids and act as molecular messengers. In particular, they are known to be involved in reprogramming tumor cells, invasion, and migration of breast cancer cells. In this study, we aimed to identify lipid droplet-associated genes as prognostic markers in breast cancer. Methods: Established lipid droplet-associated proteins were used to create the research gene lists. Bioinformatics analysis on the GEPIA platform was carried out for the list of the genes to identify differential expression in breast cancer versus healthy breast tissues. Differentially expressed genes were analyzed regarding significant changes during the metastatic transition and detected genes which play a role in breast cancer patients. Changes in lipid composition were monitored by mass spectrometry. In more detail, immunohistochemistry and cell culture studies were performed to understand the LD-related proteins and lipids in the cell lines. Results: 143 genes were identified as lipid droplet-associated factors by literature research. Bioinformatics analysis of 1085 breast cancer samples and 291 normal breast tissue samples identified 48 differentially expressed genes in breast cancer with 3 over-expressed genes (SQLE, FADS2, MUCI) and 45 under-expressed genes. Among 48 differentially expressed genes, only one over-expressed gene (SQLE) and 5 under-expressed genes (FABP7, SAA4, CHKB, RBP4, PLA2G4A) were significantly associated with the overall survival of breast cancer patients. While 26 of these genes were also found in the metastatic transition, the expression of only 13 of them changed in cancer. SELP, FABP4, and PLIN1 were detected as the highest F-value in the transitions of metastatic stages. OSBPL2, CPA4, DGAT1, and FADS6 were effective genes in both overall survival and metastatic transition. Among all these genes, only FABP7 showed a statistically significant rank in all criteria as a prognostic factor. Changes in the lipid compositions, size and radii of lipid droplets were also be monitored and combined with bioinformatics analysis. Conclusions: Through bioinformatics analysis, 29 prognostically relevant differentially expressed genes were identified. 26 genes play a role during the metastatic transition highlighting the role of lipid droplet-associated factors in breast cancer.
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