Effects of mechanical properties on tumor invasion: insights from a cellular model

Extracellular vesicles derived from cancer-associated fibroblasts induce the migration and invasion of oral squamous cell carcinoma

As one of the most abundant constituents of the tumour microenvironment (TME), cancer-associated fibroblasts (CAF) display critical roles during tumour progression and metastasis. Multiple classes of molecules including growth factors, cytokines, proteases and extracellular matrix proteins, are produced by CAF to act as mediators of the stroma-tumour interactions. One of the main channels for this communication is associated with extracellular vesicles (EV), which are secreted particles loaded with protein and genetic information. In this study, we evaluated the effects of EV derived from CAF primary human cell lines (n = 5) on proliferation, survival, migration, and invasion of oral squamous cell carcinoma (OSCC) cells. As controls, EV from human primary-established normal oral fibroblasts (NOF, n = 5) were used. Our in vitro assays showed that CAF-EV significantly induces migration and invasion of OSCC cells and promote a disseminated pattern of HSC-3 cell invasion in the 3D organotypic assay. Furthermore, gene expression analysis of EV-treated cancer cells revealed changes in the pathways associated with tumour metabolism and up-regulation of tumour invasion genes. Our findings suggest a significant role of CAF-EV in promoting the migration and invasion of OSCC cells, which are related to the activation of cancer-related pathways.

Evaluating Nuclear Membrane Irregularity for the Classification of Cervical Squamous Epithelial Cells

Pap test involves searching of morphological changes in cervical squamous epithelial cells by pathologists or cytotechnologists to identify potential cancerous cells in the cervix. Nuclear membrane irregularity is one of the morphological changes of malignancy. This paper proposes two novel techniques for the evaluation of nuclear membrane irregularity. The first technique, namely, penalty-driven smoothing analysis, introduces different penalty values for nuclear membrane contour with different degrees of irregularity. The second technique, which can be subdivided into mean- or median-type residual-based analysis, computes the number of points of nuclear membrane contour that deviates from the mean or median of the nuclear membrane contour. Performance of the proposed techniques was compared to three state-of-the-art techniques, namely, radial asymmetric, shape factor, and rim difference. Friedman and post hoc tests using Holm, Shaffer, and Bergmann procedures returned significant differences for all the three classes, i.e., negative for intraepithelial lesion or malignancy (NILM) versus low grade squamous intraepithelial lesion (LSIL), NILM versus high grade squamous intraepithelial lesion (HSIL), and LSIL versus HSIL when the span value equaled 3 was employed with linear penalty function. When span values equaled 5, 7, and 9, NILM versus LSIL and HSIL showed significant differences regardless of the penalty functions. In addition, the results of penalty-driven smoothing analysis were comparable with those of other state-of-the-art techniques. Residual-based analysis returned significant differences for the comparison among the three diagnostic classes. Findings of this study proved the significance of nuclear membrane irregularity as one of the features to differentiate the different diagnostic classes of cervical squamous epithelial cells.

Multiscale Modeling of Cellular Epigenetic States: Stochasticity in Molecular Networks, Chromatin Folding in Cell Nuclei, and Tissue Pattern Formation of Cells

Genome sequences provide the overall genetic blueprint of cells, but cells possessing the same genome can exhibit diverse phenotypes. There is a multitude of mechanisms controlling cellular epigenetic states and that dictate the behavior of cells. Among these, networks of interacting molecules, often under stochastic control, depending on the specific wirings of molecular components and the physiological conditions, can have a different landscape of cellular states. In addition, chromosome folding in three-dimensional space provides another important control mechanism for selective activation and repression of gene expression. Fully differentiated cells with different properties grow, divide, and interact through mechanical forces and communicate through signal transduction, resulting in the formation of complex tissue patterns. Developing quantitative models to study these multi-scale phenomena and to identify opportunities for improving human health requires development of theoretical models, algorithms, and computational tools. Here we review recent progress made in these important directions.