Spatial and temporal modulation of cell instructive cues in a filamentous supramolecular biomaterial

Supramolecular materials provide unique opportunities to mimic both the structure and mechanics of the biopolymer networks that compose the extracellular matrix. However, strategies to modify their filamentous structures in space and time in 3D cell culture to study cell behavior as encountered in development and disease are lacking. We herein disclose a multicomponent squaramide-based supramolecular material whose mechanics and bioactivity can be controlled by light through co-assembly of a 1,2-dithiolane (DT) monomer that forms disulfide cross-links. Remarkably, increases in storage modulus from ∼200 Pa to >10 kPa after stepwise photo-cross-linking can be realized without an initiator while retaining colorlessness and clarity. Moreover, viscoelasticity and plasticity of the supramolecular networks decrease upon photo-irradiation, reducing cellular protrusion formation and motility when performed at the onset of cell culture. When applied during 3D cell culture, force-mediated manipulation is impeded and cells move primarily along earlier formed channels in the materials. Additionally, we show photopatterning of peptide cues in 3D using either a photomask or direct laser writing. We demonstrate that these squaramide-based filamentous materials can be applied to the development of synthetic and biomimetic 3D in vitro cell and disease models, where their secondary cross-linking enables mechanical heterogeneity and shaping at multiple length scales

Community standards for open cell migration data

Cell migration research has become a high-content field. However, the quantitative information encapsulated in these complex and high-dimensional datasets is not fully exploited owing to the diversity of experimental protocols and non-standardized output formats. In addition, typically the datasets are not open for reuse. Making the data open and Findable, Accessible, Interoperable, and Reusable (FAIR) will enable meta-analysis, data integration, and data mining. Standardized data formats and controlled vocabularies are essential for building a suitable infrastructure for that purpose but are not available in the cell migration domain. We here present standardization efforts by the Cell Migration Standardisation Organisation (CMSO), an open community-driven organization to facilitate the development of standards for cell migration data. This work will foster the development of improved algorithms and tools and enable secondary analysis of public datasets, ultimately unlocking new knowledge of the complex biological process of cell migration

Uncovering the Signaling Landscape Controlling Breast Cancer Cell Migration Identifies Novel Metastasis Driver Genes

Ttriple-negative breast cancer (TNBC) is an aggressive and highly metastatic breast cancer subtype. Enhanced TNBC cell motility is a prerequisite of TNBC cell dissemination. Here, we apply an imaging-based RNAi phenotypic cell migration screen using two highly motile TNBC cell lines (Hs578T and MDA-MB-231) to provide a repository of signaling determinants that functionally drive TNBC cell motility. We have screened ~4,200 target genes individually and discovered 133 and 113 migratory modulators of Hs578T and MDA-MB-231, respectively, which are linked to signaling networks predictive for breast cancer progression. The splicing factors PRPF4B and BUD31 and the transcription factor BPTF are essential for cancer cell migration, amplified in human primary breast tumors and associated with metastasis-free survival. Depletion of PRPF4B, BUD31 and BPTF causes primarily down regulation of genes involved in focal adhesion and ECM-interaction pathways. PRPF4B is essential for TNBC metastasis formation in vivo, making PRPF4B a candidate for further drug developmen

Uncovering the signaling landscape controlling breast cancer cell migration identifies novel metastasis driver genes

Ttriple-negative breast cancer (TNBC) is an aggressive and highly metastatic breast cancer subtype. Enhanced TNBC cell motility is a prerequisite of TNBC cell dissemination. Here, we apply an imaging-based RNAi phenotypic cell migration screen using two highly motile TNBC cell lines (Hs578T and MDA-MB-231) to provide a repository of signaling determinants that functionally drive TNBC cell motility. We have screened ~4,200 target genes individually and discovered 133 and 113 migratory modulators of Hs578T and MDA-MB-231, respectively, which are linked to signaling networks predictive for breast cancer progression. The splicing factors PRPF4B and BUD31 and the transcription factor BPTF are essential for cancer cell migration, amplified in human primary breast tumors and associated with metastasis-free survival. Depletion of PRPF4B, BUD31 and BPTF causes primarily down regulation of genes involved in focal adhesion and ECM-interaction pathways. PRPF4B is essential for TNBC metastasis formation in vivo, making PRPF4B a candidate for further drug development

An improved model to study tumor cell autonomous metastasis programs using MTLn3 cells and the Rag2−/− γc−/− mouse

The occurrence of metastases is a critical determinant of the prognosis for breast cancer patients. Effective treatment of breast cancer metastases is hampered by a poor understanding of the mechanisms involved in the formation of these secondary tumor deposits. To study the processes of metastasis, valid in vivo tumor metastasis models are required. Here, we show that increased expression of the EGF receptor in the MTLn3 rat mammary tumor cell-line is essential for efficient lung metastasis formation in the Rag mouse model. EGFR expression resulted in delayed orthotopic tumor growth but at the same time strongly enhanced intravasation and lung metastasis. Previously, we demonstrated the critical role of NK cells in a lung metastasis model using MTLn3 cells in syngenic F344 rats. However, this model is incompatible with human EGFR. Using the highly metastatic EGFR-overexpressing MTLn3 cell-line, we report that only Rag2−/−γc−/− mice, which lack NK cells, allow efficient lung metastasis from primary tumors in the mammary gland. In contrast, in nude and SCID mice, the remaining innate immune cells reduce MTLn3 lung metastasis formation. Furthermore, we confirm this finding with the orthotopic transplantation of the 4T1 mouse mammary tumor cell-line. Thus, we have established an improved in vivo model using a Rag2−/− γc−/− mouse strain together with MTLn3 cells that have increased levels of the EGF receptor, which enables us to study EGFR-dependent tumor cell autonomous mechanisms underlying lung metastasis formation. This improved model can be used for drug target validation and development of new therapeutic strategies against breast cancer metastasis formation

Systems microscopy approaches to understand cancer cell migration and metastasis

Cell migration is essential in a number of processes, including wound healing, angiogenesis and cancer metastasis. Especially, invasion of cancer cells in the surrounding tissue is a crucial step that requires increased cell motility. Cell migration is a well-orchestrated process that involves the continuous formation and disassembly of matrix adhesions. Those structural anchor points interact with the extra-cellular matrix and also participate in adhesion-dependent signalling. Although these processes are essential for cancer metastasis, little is known about the molecular mechanisms that regulate adhesion dynamics during tumour cell migration. In this review, we provide an overview of recent advanced imaging strategies together with quantitative image analysis that can be implemented to understand the dynamics of matrix adhesions and its molecular components in relation to tumour cell migration. This dynamic cell imaging together with multiparametric image analysis will help in understanding the molecular mechanisms that define cancer cell migration

Circumventing the Crabtree effect in cell culture: A systematic review

Metabolic reprogramming and mitochondrial dysfunction are central elements in a broad variety of physiological and pathological processes. While cell culture established itself as a versatile technique for the elaboration of physiology and disease, studying metabolism using standard cell culture protocols is profoundly interfered by the Crabtree effect. This phenomenon refers to the adaptation of cultured cells to a glycolytic phenotype, away from oxidative phosphorylation in glucose-containing medium, and questions the applicability of cell culture in certain fields of research. In this systematic review we aim to provide a comprehensive overview and critical appraisal of strategies reported to circumvent the Crabtree effect

Model-based translation of DNA damage signaling dynamics across cell types.

Interindividual variability in DNA damage response (DDR) dynamics may evoke differences in susceptibility to cancer. However, pathway dynamics are often studied in cell lines as alternative to primary cells, disregarding variability. To compare DDR dynamics in the cell line HepG2 with primary human hepatocytes (PHHs), we developed a HepG2-based computational model that describes the dynamics of DDR regulator p53 and targets MDM2, p21 and BTG2. We used this model to generate simulations of virtual PHHs and compared the results to those for PHH donor samples. Correlations between baseline p53 and p21 or BTG2 mRNA expression in the absence and presence of DNA damage for HepG2-derived virtual samples matched the moderately positive correlations observed for 50 PHH donor samples, but not the negative correlations between p53 and its inhibitor MDM2. Model parameter manipulation that affected p53 or MDM2 dynamics was not sufficient to accurately explain the negative correlation between these genes. Thus, extrapolation from HepG2 to PHH can be done for some DDR elements, yet our analysis also reveals a knowledge gap within p53 pathway regulation, which makes such extrapolation inaccurate for the regulator MDM2. This illustrates the relevance of studying pathway dynamics in addition to gene expression comparisons to allow reliable translation of cellular responses from cell lines to primary cells. Overall, with our approach we show that dynamical modeling can be used to improve our understanding of the sources of interindividual variability of pathway dynamics