Over the past decades, lipid‐based nanoparticle drug delivery systems (DDS) have caught the attention of researchers worldwide, encouraging the field to rapidly develop improved ways for effective drug delivery. One of the most prominent examples is liposomes, which are spherical shaped artificial vesicles composed of lipid bilayers and able to encapsulate both hydrophilic and hydrophobic materials. At the same time, biological nanoparticles naturally secreted by cells, called extracellular vesicles (EVs), have emerged as promising more complex biocompatible DDS. In this review paper, the differences and similarities in the composition of both vesicles are evaluated, and critical mediators that affect their pharmacokinetics are elucidate. Different strategies that have been assessed to tweak the pharmacokinetics of both liposomes and EVs are explored, detailing the effects on circulation time, targeting capacity, and cytoplasmic delivery of therapeutic cargo. Finally, whether a hybrid system, consisting of a combination of only the critical constituents of both vesicles, could offer the best of both worlds is discussed. Through these topics, novel leads for further research are provided and, more importantly, gain insight in what the liposome field and the EV field can learn from each other.

A key aspect for successful drug delivery via lipid‐based nanoparticles is their internalization in target cells. Two prominent examples of such drug delivery systems are artificial phospholipid‐based carriers, such as liposomes, and their biological counterparts, the extracellular vesicles (EVs). Despite a wealth of literature, it remains unclear which mechanisms precisely orchestrate nanoparticle‐mediated cargo delivery to recipient cells and the subsequent intracellular fate of therapeutic cargo. In this review, internalization mechanisms involved in the uptake of liposomes and EVs by recipient cells are evaluated, also exploring their intracellular fate after intracellular trafficking. Opportunities are highlighted to tweak these internalization mechanisms and intracellular fates to enhance the therapeutic efficacy of these drug delivery systems. Overall, literature to date shows that both liposomes and EVs are predominantly internalized through classical endocytosis mechanisms, sharing a common fate: accumulation inside lysosomes. Studies tackling the differences between liposomes and EVs, with respect to cellular uptake, intracellular delivery and therapy efficacy, remain scarce, despite its importance for the selection of an appropriate drug delivery system. In addition, further exploration of functionalization strategies of both liposomes and EVs represents an important avenue to pursue in order to control internalization and fate, thereby improving therapeutic efficacy.

Introduction: The hypoxia-inducible factor (HIF)-1 pathway can stimulate tumor cell migration and metastasis. Furthermore, hypoxic tumors are associated with a poor prognosis. Besides the HIF-1 pathway, the unfolded protein response (UPR) is also induced by hypoxic conditions. The PKR-like ER kinase (PERK)/activating transcription factor 4 (ATF4)-arm of the UPR induces expression of lysosomal-associated membrane protein 3 (LAMP3), a factor that has been linked to metastasis and poor prognosis in solid tumors. In this study the role of UPR-induced LAMP3 in hypoxia-mediated migration of breast cancer cells was examined. Methods: A number of in vitro metastasis models were used to study the migration and invasion of MDA-MB-231 breast cancer cells under hypoxic conditions. PERK, ATF4 and their downstream factor LAMP3 were knocked down to examine their role in cell migration. In addition, multicellular tumor spheroids were used to study the involvement of the tumor microenvironment in invasion. Results: Using transwell assays, migration of different breast cancer cell lines was assessed. A direct correlation was found between cell migration and baseline LAMP3 expression. Furthermore, moderate hypoxia (1% O₂) was found to be optimal in stimulating migration of MDA-MB-231 cells. siRNA mediated knockdown of PERK, ATF4 and LAMP3 reduced migration of cells under these conditions. Using gap closure assays, similar results were found. In a three-dimensional invasion assay into collagen, LAMP3 knockdown cells showed a diminished capacity to invade compared to control cells when collectively grown in multicellular spheroids. Conclusions: Thus, the PERK/ATF4/LAMP3-arm of the UPR is an additional pathway mediating hypoxia-induced breast cancer cell migration.

Label-free surface-enhanced Raman spectroscopy (SERS) can interrogate systems by directly fingerprinting their components’ unique physicochemical properties. In complex biological systems however, this can yield highly overlapping spectra that hinder sample identification. Here, we present an artificial-nose inspired SERS fingerprinting approach where spectral data is obtained as a function of sensor surface chemical functionality. Supported by molecular dynamics modeling, we show that mildly selective self-assembled monolayers can influence the strength and configuration in which analytes interact with plasmonic surfaces, diversifying the resulting SERS fingerprints. Since each sensor generates a modulated signature, the implicit value of increasing the dimensionality of datasets is shown using cell lysates for all possible combinations of up to 9 fingerprints. Reliable improvements in mean discriminatory accuracy towards 100% are achieved with each additional surface functionality. This arrayed label-free platform illustrates the wide-ranging potential of high-dimensionality artificial-nose based sensing systems for more reliable assessment of complex biological matrices.

Extracellular vesicles (EVs) secreted by cancer cells provide an important insight into cancer biology and could be leveraged to enhance diagnostics and disease monitoring. This paper details a high-throughput label-free extracellular vesicle analysis approach to study fundamental EV biology, toward diagnosis and monitoring of cancer in a minimally invasive manner and with the elimination of interpreter bias. We present the next generation of our single particle automated Raman trapping analysis─SPARTA─system through the development of a dedicated standalone device optimized for single particle analysis of EVs. Our visualization approach, dubbed dimensional reduction analysis (DRA), presents a convenient and comprehensive method of comparing multiple EV spectra. We demonstrate that the dedicated SPARTA system can differentiate between cancer and noncancer EVs with a high degree of sensitivity and specificity (>95% for both). We further show that the predictive ability of our approach is consistent across multiple EV isolations from the same cell types. Detailed modeling reveals accurate classification between EVs derived from various closely related breast cancer subtypes, further supporting the utility of our SPARTA-based approach for detailed EV profiling.