Cell migration and invasiveness significantly contribute to desirable physiological processes, such as wound healing or embryogenesis, as well as to serious pathological processes such as the spread of cancer cells to form tumor metastasis. The availability of appropriate methods for studying these processes is essential for understanding the molecular basis of cancer metastasis and for identifying suitable therapeutic targets for anti-metastatic treatment. This review summarizes the current status of these methods: In vitro methods for studying cell migration involve two-dimensional (2D) assays (wound-healing/scratch assay), and methods based on chemotaxis (the Dunn chamber). The analysis of both cell migration and invasiveness in vitro require more complex systems based on the Boyden chamber principle (Transwell migration/invasive test, xCELLigence system), or microfluidic devices with three-dimensional (3D) microscopy visualization. 3D culture techniques are rapidly becoming routine and involve multicellular spheroid invasion assays or array chip-based, spherical approaches, multi-layer/multi-zone culture, or organoid non-spherical models, including multi-organ microfluidic chips. The in vivo methods are mostly based on mice, allowing genetically engineered mice models and transplant models (syngeneic mice, cell line-derived xenografts and patient-derived xenografts including humanized mice models). These methods currently represent a solid basis for the state-of-the art research that is focused on understanding metastatic fundamentals as well as the development of targeted anti-metastatic therapies, and stratified treatment in oncology.

Accurate classification of breast tumors is vital for patient management decisions and enables more precise cancer treatment. Here, we present a quantitative proteotyping approach based on sequential windowed acquisition of all theoretical fragment ion spectra (SWATH) mass spectrometry and establish key proteins for breast tumor classification. The study is based on 96 tissue samples representing five conventional breast cancer subtypes. SWATH proteotype patterns largely recapitulate these subtypes; however, they also reveal varying heterogeneity within the conventional subtypes, with triple negative tumors being the most heterogeneous. Proteins that contribute most strongly to the proteotype-based classification include INPP4B, CDK1, and ERBB2 and are associated with estrogen receptor (ER) status, tumor grade status, and HER2 status. Although these three key proteins exhibit high levels of correlation with transcript levels (R > 0.67), general correlation did not exceed R = 0.29, indicating the value of protein-level measurements of disease-regulated genes. Overall, this study highlights how cancer tissue proteotyping can lead to more accurate patient stratification.

Streptavidin-PEG-neridronate-UCNP nanoconjugates enable the specific detection of tumor markers on the surface of cancer cells with outstanding signal-to-background ratio.