Surface-enhanced Raman scattering (SERS) is a powerful and sensitive technique for the detection of fingerprint sig-nals of molecules and for the investigation of a series of surface chemical reactions. Many studies introduced quantita-tive applications of SERS in various fields and several SERS methods have been implemented for each specific applica-tion, ranging in performance characteristics, analytes used, instruments, and analytical matrices. In general, very few methods have been validated according to international guidelines. As a consequence, the application of SERS in high-ly-regulated environments is still considered risky and the perception of a poorly reproducible and insufficiently robust analytical technique has persistently retarded its routine implementation. Collaborative trials are a type of interlabora-tory study (ILS) frequently performed to ascertain the quality of a single analytical method. The idea of an ILS of quan-tification with SERS arose within the framework of Working Group 1 (WG1) of the COST Action BM1401 Ra-man4Clinics32 in an effort to overcome the problematic perception of quantitative SERS methods. Here we report the first interlaboratory SERS study ever conducted, involving 15 laboratories and 41 researchers. In this study we tried to define a methodology to assess the reproducibility and trueness of a quantitative SERS method, and to compare differ-ent methods. In our opinion, this is a first important step toward a “standardization” process of SERS protocols, not proposed by a single laboratory but by a larger community.

Extracellular vesicles (EVs) from mesenchymal stromal cells (MSC) are emerging as valuable therapeutic agents for tissue regeneration and immunomodulation, but their clinical applications have so far been limited by the technical restraints of current isolation and characterisation procedures. This study shows for the first time the successful application of Raman spectroscopy as label-free, sensitive and reproducible means of carrying out the routine bulk characterisation of MSC-derived vesicles before their use in vitro or in vivo, thus promoting the translation of EV research to clinical practice. The Raman spectra of the EVs of bone marrow and adipose tissue-derived MSCs were compared with human dermal fibroblast EVs in order to demonstrate the ability of the method to distinguish the vesicles of the three cytotypes automatically with an accuracy of 93.7%. Our data attribute a Raman fingerprint to EVs from undifferentiated and differentiated cells of diverse tissue origin, and provide insights into the biochemical characteristics of EVs from different sources and into the differential contribution of sphingomyelin, gangliosides and phosphatidilcholine to the Raman spectra themselves.

Cancer-associated fibroblasts (CAF) are the most abundant cells of the tumor stroma and they critically influence cancer growth through control of the surrounding tumor microenvironment (TME). CAF-orchestrated reactive stroma, composed of pro-tumorigenic cytokines and growth factors, matrix components, neovessels, and deregulated immune cells, is associated with poor prognosis in multiple carcinomas, including breast cancer. Therefore, beyond cancer cells killing, researchers are currently focusing on TME as strategy to fight breast cancer. In recent years, nanomedicine has provided a number of smart delivery systems based on active targeting of breast CAF and immune-mediated overcome of chemoresistance. Many efforts have been made both to eradicate breast CAF and to reshape their identity and function. Nano-strategies for CAF targeting profoundly contribute to enhance chemosensitivity of breast tumors, enabling access of cytotoxic T-cells and reducing immunosuppressive signals. TME rearrangement also includes reorganization of the extracellular matrix to enhance permeability to chemotherapeutics, and nano-systems for smart coupling of chemo- and immune-therapy, by increasing immunogenicity and stimulating antitumor immunity. The present paper reviews the current state-of-the-art on nano-strategies to target breast CAF and TME. Finally, we consider and discuss future translational perspectives of proposed nano-strategies for clinical application in breast cancer.