Human osteosarcoma is a genetically heterogeneous bone malignancy with poor prognosis despite the employment of aggressive chemotherapy regimens. Because druggable driver mutations have not been established, dissecting the interactions between osteosarcoma cells and supporting stroma may provide insights into novel therapeutic targets. By using a bioluminescent orthotopic xenograft mouse model of osteosarcoma, we evaluated the effect of tumor extracellular vesicle (EV)-educated mesenchymal stem cells (TEMSC) on osteosarcoma progression. Characterization and functional studies were designed to assess the mechanisms underlying MSC education. Independent series of tissue specimens were analyzed to corroborate the preclinical findings, and the composition of patient serum EVs was analyzed after isolation with size-exclusion chromatography. We show that EVs secreted by highly malignant osteosarcoma cells selectively incorporate a membrane-associated form of TGFβ, which induces proinflammatory IL6 production by MSCs. TEMSCs promote tumor growth, accompanied with intratumor STAT3 activation and lung metastasis formation, which was not observed with control MSCs. Importantly, intravenous administration of the anti-IL6 receptor antibody tocilizumab abrogated the tumor-promoting effects of TEMSCs. RNA-seq analysis of human osteosarcoma tissues revealed a distinct TGFβ-induced prometastatic gene signature. Tissue microarray immunostaining indicated active STAT3 signaling in human osteosarcoma, consistent with the observations in TEMSC-treated mice. Finally, we isolated pure populations of EVs from serum and demonstrated that circulating levels of EV-associated TGFβ are increased in osteosarcoma patients. Collectively, our findings suggest that TEMSCs promote osteosarcoma progression and provide the basis for testing IL6- and TGFβ-blocking agents as new therapeutic options for osteosarcoma patients. .

Surface-enhanced Raman spectroscopy (SERS) is a good candidate for the development of fast and easy-to-use diagnostic tools, possibly used on biofluids in point-of-care or screening tests. In particular, label-free SERS spectra of blood serum and plasma, two biofluids widely used in diagnostics, could be used as a metabolic fingerprinting approach for biomarker discovery. This study aims at a systematic evaluation of SERS spectra of blood serum and plasma, using various Ag and Au aqueous colloids, as SERS substrates, in combination with three excitation lasers of different wavelengths, ranging from the visible to the near-infrared. The analysis of the SERS spectra collected from 20 healthy subjects under a variety of experimental conditions revealed that intense and repeatable spectra are quickly obtained only if proteins are filtered out from samples, and an excitation in the near-infrared is used in combination with Ag colloids. Moreover, common plasma anticoagulants such as EDTA and citrate are found to interfere with SERS spectra; accordingly, filtered serum or heparin plasma are the samples of choice, having identical SERS spectra. Most bands observed in SERS spectra of these biofluids are assigned to uric acid, a metabolite whose blood concentration depends on factors such as sex, age, therapeutic treatments, and various pathological conditions, suggesting that, even when the right experimental conditions are chosen, great care must be taken in designing studies with the purpose of developing diagnostic tests.

In clinical practice, one objective is to obtain diagnostic information while minimizing the invasiveness of the tests and the pain for the patients. To this end, tests based on the interaction of light with readily available biofluids including blood, urine, or saliva are highly desirable. In this review we examine the state of the art regarding the use of surface-enhanced Raman spectroscopy (SERS) to investigate biofluids, focusing on diagnostic applications. First, a critical evaluation of the experimental aspects involved in the collection of SERS spectra is presented; different substrate types are introduced, with a clear distinction between colloidal and non-colloidal metal nanostructures. Then the effect of the excitation wavelength is discussed, along with anomalous bands and artifacts which might affect SERS spectra of biofluids. The central part of the review examines the literature available on the SERS spectra of blood, plasma, serum, urine, saliva, tears, and semen. Finally, diagnostic applications are critically discussed in the context of the published evidence; this section clearly reveals that SERS of biofluids is most promising as a rapid, cheap, and non-invasive tool for mass screening for cancer.

No abstract

Surface-enhanced Raman scattering (SERS) spectra were obtained from urine samples from subjects diagnosed with prostate cancer as well as from healthy controls, using Au nanoparticles as substrates. Principal component analysis (PCA) of the spectral data, followed by linear discriminant analysis (LDA), leads to a classification model with a sensitivity of 100 %, a specificity of 89 %, and an overall diagnostic accuracy of 95 %. Even considering the very limited number of samples involved in this report, preliminary results from this approach are extremely promising, encouraging further investigation.