Exosomes (EXOs) are nano-sized vesicles secreted by most cell types. They are abundant in bio-fluids and harbor specific molecular constituents from their parental cells. Due to these characteristics, EXOs have a great potential in cancer diagnostics for liquid biopsy and personalized medicine. Despite this unique potential, EXOs are not yet widely applied in clinical settings, with two main factors hindering their translational process in diagnostics. Firstly, conventional extraction methods are time-consuming, require large sample volumes and expensive equipment, and often do not provide high-purity samples. Secondly, characterization methods have some limitations, because they are often qualitative, need extensive labeling or complex sampling procedures that can induce artifacts. In this context, novel label-free approaches are rapidly emerging, and are holding potential to revolutionize EXO diagnostics. These methods include the use of nanodevices for EXO purification, and vibrational spectroscopies, scattering, and nanoindentation for characterization. In this progress report, we summarize recent key advances in label-free techniques for EXO purification and characterization. We point out that these methods contribute to reducing costs and processing times, provide complementary information compared to the conventional characterization techniques, and enhance flexibility, thus favoring the discovery of novel and unexplored EXO-based biomarkers. In this process, the impact of nanotechnology is systematically highlighted, showing how the effectiveness of these techniques can be enhanced using nanomaterials, such as plasmonic nanoparticles and nanostructured surfaces, which enable the exploitation of advanced physical phenomena occurring at the nanoscale level.

Extracellular vesicles (EVs) are abundantly released into the systemic circulation, where they show remarkable stability and harbor molecular constituents that provide biochemical information about their cells of origin. Due to this characteristic, EVs are attracting increasing attention as a source of circulating biomarkers for cancer liquid biopsy and personalized medicine. Despite this potential, none of the discovered biomarkers has entered the clinical practice so far, and novel approaches for the label-free characterization of EVs are highly demanded. In this regard, Fourier Transform Infrared Spectroscopy (FTIR) has great potential as it provides a quick, reproducible, and informative biomolecular fingerprint of EVs. In this pilot study, we investigated, for the first time in the literature, the capability of FTIR spectroscopy to distinguish between EVs extracted from sera of cancer patients and controls based on their mid-IR spectral response. For this purpose, EV-enriched suspensions were obtained from the serum of patients diagnosed with Hepatocellular Carcinoma (HCC) of nonviral origin and noncancer subjects. Our data point out the presence of statistically significant differences in the integrated intensities of major mid-IR absorption bands, including the carbohydrate and nucleic acids band, the protein amide I and II bands, and the lipid CH stretching band. Additionally, we used Principal Component Analysis combined with Linear Discriminant Analysis (PCA-LDA) for the automated classification of spectral data according to the shape of specific mid-IR spectral signatures. The diagnostic performances of the proposed spectral biomarkers, alone and combined, were evaluated using multivariate logistic regression followed by a Receiving Operator Curve analysis, obtaining large Areas Under the Curve (AUC = 0.91, 95% CI 0.81–1.0). Very interestingly, our analyses suggest that the discussed spectral biomarkers can outperform the classification ability of two widely used circulating HCC markers measured on the same groups of subjects, namely alpha-fetoprotein (AFP), and protein induced by the absence of vitamin K or antagonist-II (PIVKA-II).

Hepatocellular carcinoma (HCC) represents a worldwide health matter with a major care burden, high prevalence, and poor prognosis. Its pathogenesis mainly varies depending on the underlying etiological factors, although it develops from liver cirrhosis in the majority of cases. This review summarizes the role of the most interesting soluble factors as biomarkers for early diagnosis and as recommended targets for treatment in accordance with the new challenges in precision medicine. In the premalignant environment, inflammatory cells release a wide range of cytokines, chemokines, growth factors, prostaglandins, and proangiogenic factors, making the liver environment more suitable for hepatocyte tumor progression that starts from acquired genetic mutations. A complex interaction of pro-inflammatory (IL-6, TNF-α) and anti-inflammatory cytokines (TGF-α and -β), pro-angiogenic molecules (including the Angiopoietins, HGF, PECAM-1, HIF-1α, VEGF), different transcription factors (NF-kB, STAT-3), and their signaling pathways are involved in the development of HCC. Since cytokines are expressed and released during the different stages of HCC progression, their measurement, by different available methods, can provide in-depth information on the identification and management of HCC.

Liposomal doxorubicin (L-DOX) is a popular drug formulation for the treatment of several cancer types (e.g., recurrent ovarian cancer, metastatic breast cancer, multiple myeloma, etc.), but poor nuclear internalization has hampered its clinical applicability so far. Therefore, novel drug-delivery nanosystems are actively researched in cancer chemotherapy. Here we demonstrate that DOX-loaded graphene oxide (GO), GO-DOX, exhibits much higher anticancer efficacy as compared to its L-DOX counterpart if administered to cellular models of breast cancer. Then, by a combination of live-cell confocal imaging and fluorescence lifetime imaging microscopy (FLIM), we suggest that GO-DOX may realize its superior performances by inducing massive intracellular DOX release (and its subsequent nuclear accumulation) upon binding to the cell plasma membrane. Reported results lay the foundation for future exploitation of these new adducts as high-performance nanochemotherapeutic agents.

The ongoing outbreak of coronavirus disease 2019 (COVID-19), which impairs the functionality of several organs, represents a major threat to human health. One of the hardest challenges in the fight against COVID-19 is the development of wide-scale, effective, and rapid laboratory tests to control disease severity, progression, and possible sudden worsening. Monitoring patients in real-time is highly demanded in this pandemic era when physicians need reliable and quantitative tools to prioritize patients’ access to intensive care departments. In this regard, salivary biomarkers are extremely promising, as they allow for the fast and non-invasive collection of specimens and can be repeated multiple times. Methods: We compare salivary levels of immunoglobulin A subclasses (IgA1 and IgA2) and free light chains (kFLC and λFLC) in a cohort of 29 SARS-CoV-2 patients and 21 healthy subjects. Results: We found that each biomarker differs significantly between the two groups, with p-values ranging from 10⁻⁸ to 10⁻⁴. A Receiving Operator Curve analysis shows that λFLC level is the best-suited candidate to discriminate the two groups (AUC = 0.96), with an accuracy of 0.94 (0.87–1.00 95% CI), a precision of 0.91 (0.81–1.00 95% CI), a sensitivity of 1.00 (0.96–1.00 95% CI), and a specificity of 0.86 (0.70–1.00 95% CI). Conclusion: These results suggest λFLC as an ideal indicator of patient conditions. This hypothesis is strengthened by the consideration that the λFLC half-life (approximately 6 h) is significantly shorter than the IgA one (21 days), thus confirming the potential of λFLC for effectively monitoring patients’ fluctuation in real-time.

Simultaneous detection of multiple analytes from a single biological sample is gaining more attention in the development of more reliable and point-of-care diagnostic devices. We developed a multiplexed strategy that combined outcomes of clinical biomarkers with analysis of the protein corona that forms around graphene oxide sheets upon exposure to patient’s plasma. As a paradigmatic case study, we selected pancreatic ductal adenocarcinoma (PDAC), mainly because of the absence of effective detection strategies that resulted in an extremely low five-year survival rate after diagnosis (<10%). Association of protein corona analysis and haemoglobin levels discriminated PDAC patients from healthy volunteers in up to 90% of cases. If further confirmed in larger-cohort studies, this approach may be used in the detection of PDAC.