The physical microenvironment regulates cell behavior during tissue development and homeostasis. How single cells decode information about their geometrical shape under mechanical stress and physical space constraints within tissues remains largely unknown. Here, using a zebrafish model, we show that the nucleus, the biggest cellular organelle, functions as an elastic deformation gauge that enables cells to measure cell shape deformations. Inner nuclear membrane unfolding upon nucleus stretching provides physical information on cellular shape changes and adaptively activates a calcium-dependent mechanotransduction pathway, controlling actomyosin contractility and migration plasticity. Our data support that the nucleus establishes a functional module for cellular proprioception that enables cells to sense shape variations for adapting cellular behavior to their microenvironment.

Exosome-like vesicles (ELVs) are a novel class of biomarkers that are receiving a lot of attention for the detection of cancer in an early stage. In this study the feasibility of using a Surface Enhanced Raman Spectroscopy (SERS) based method to distinguish between ELVs derived from different cellular origins is evaluated. A gold nanoparticle based shell is deposited on the surface of ELVs derived from cancerous and healthy cells which enhances the Raman signal while maintaining a colloidal suspension of individual vesicles. This nano-coating allows the recording of SERS spectra from single vesicles. By using Partial Least Square Discriminative Analysis (PLS-DA) on the obtained spectra, vesicles from different origin can be distinguished, even when present in the same mixture. This proof-of-concept study paves the way for non-invasive (cancer) diagnostic tools based on exosomal SERS fingerprinting in combination with multivariate statistical analysis.

Although molecular classification brings interesting insights into breast cancer taxonomy, its implementation in daily clinical care is questionable because of its expense and the information supplied in a single sample allocation is not sufficiently reliable. New approaches, based on a panel of small molecules derived from the global or targeted analysis of metabolic profiles of cells, have found a correlation between activation of de novo lipogenesis and poorer prognosis and shorter disease-free survival for many tumors. We hypothesized that the lipid content of breast cancer cells might be a useful indirect measure of a variety of functions coupled to breast cancer progression. Raman microspectroscopy was used to characterize metabolism of breast cancer cells with different degrees of malignancy. Raman spectra from MDA-MB-435, MDA-MB-468, MDA-MB-231, SKBR3, MCF7 and MCF10A cells were acquired with an InVia Raman microscope (Renishaw) with a backscattered configuration. We used Principal Component Analysis and Partial Least Squares Discriminant Analyses to assess the different profiling of the lipid composition of breast cancer cells. Characteristic bands related to lipid content were found at 3014, 2935, 2890 and 2845 cm−1, and related to lipid and protein content at 2940 cm−1. A classificatory model was generated which segregated metastatic cells and non-metastatic cells without basal-like phenotype with a sensitivity of 90% and a specificity of 82.1%. Moreover, expression of SREBP-1c and ABCA1 genes validated the assignation of the lipid phenotype of breast cancer cells. Indeed, changes in fatty acid unsaturation were related with the epithelial-to-mesenchymal transition phenotype. Raman microspectroscopy is a promising technique for characterizing and classifying the malignant phenotype of breast cancer cells on the basis of their lipid profiling. The algorithm for the discrimination of metastatic ability is a first step towards stratifying breast cancer cells using this rapid and reagent-free tool.

Little is known about metastatic pathways that are specific to the lung rather than other organs. We previously showed that antioxidant proteins such as peroxiredoxins were specifically upregulated in lung metastatic breast cancer cells. We hypothesize that cancer cells that live under aerobic conditions, as might be the case in lungs, protect themselves against the damage caused by reactive oxygen species (ROS). To examine this hypothesis, we studied the role of peroxiredoxin-2 (PRDX2) in lung vs bone metastasis formation. A metastatic variant of MDA-MB-435 breast cancer cells that specifically metastasize to lungs (435-L3) was transduced with short hairpin RNAs to specifically silence PRDX2. Conversely, a bone metastatic variant of MDA-MB-231 cells (BO2) was stably transfected to overexpress PRDX2. The 435-L3 cells silenced for PRDX2 were significantly more sensitive to H(2)O(2)-induced oxidative stress than the parental and scrambled transfected cells. BO2/PRDX2 cells produced less ROS than BO2/green fluorescent protein control cells under oxidative stress. Moreover, PRDX2 knockdown inhibited the growth of 435-L3 cells in the lungs, whereas lymph node metastasis remained unaffected. In contrast, PRDX2 overexpression in bone metastatic BO2 breast cancer cells led to drastic inhibition of the skeletal tumor burden and reduction of bone destruction. Furthermore, PRDX2 expression in breast cancer cells was associated with a glucose-dependent phenotype, different from bone metastatic cells. Overall, our results strongly suggest that PRDX2 is a targetable 'metabolic adaptor' driver protein implicated in the selective growth of metastatic cells in the lungs by protecting them against oxidative stress.

The stromal Clp protease complex influences chromoplast differentiation and ensures proper carotenoid metabolism during tomato fruit ripening, probably in co-ordination with plastidial chaperones.