Programmable Bispecific Nano-immunoengager That Captures T Cells and Reprograms Tumor Microenvironment.

Immune checkpoint blockade (ICB) therapy has revolutionized clinical oncology. However, the efficacy of ICB therapy is limited by the ineffective infiltration of T effector (Teff) cells to tumors and the immunosuppressive tumor microenvironment (TME). Here, we report a programmable tumor cells/Teff cells bispecific nano-immunoengager (NIE) that can circumvent these limitations to improve ICB therapy. The peptidic nanoparticles (NIE-NPs) bind tumor cell surface α3ß1 integrin and undergo in situ transformation into nanofibrillar network nanofibers (NIE-NFs). The prolonged retained nanofibrillar network at the TME captures Teff cells via the activatable α4ß1 integrin ligand and allows sustained release of resiquimod for immunomodulation. This bispecific NIE eliminates syngeneic 4T1 breast cancer and Lewis lung cancer models in mice, when given together with anti-PD-1 antibody. The in vivo structural transformation-based supramolecular bispecific NIE represents an innovative class of programmable receptor-mediated targeted immunotherapeutics to greatly enhance ICB therapy against cancers.

Tetraspanins are unevenly distributed across single extracellular vesicles and bias sensitivity to multiplexed cancer biomarkers.

BACKGROUND: Tetraspanin expression of extracellular vesicles (EVs) is often used as a surrogate for their detection and classification, a practice that typically assumes their consistent expression across EV sources. RESULTS: Here we demonstrate that there are distinct patterns in colocalization of tetraspanin expression of EVs enriched from a variety of in vitro and in vivo sources. We report an optimized method for the use of single particle antibody-capture and fluorescence detection to identify subpopulations according to tetraspanin expression and compare our findings with nanoscale flow cytometry. We found that tetraspanin profile is consistent from a given EV source regardless of isolation method, but that tetraspanin profiles are distinct across various sources. Tetraspanin profiles measured by flow cytometry do not totally agree, suggesting that limitations in subpopulation detection significantly impact apparent protein expression. We further analyzed tetraspanin expression of single EVs captured non-specifically, revealing that tetraspanin capture can bias the apparent multiplexed tetraspanin profile. Finally, we demonstrate that this bias can have significant impact on diagnostic sensitivity for tumor-associated EV surface markers. CONCLUSION: Our findings may reveal key insights into protein expression heterogeneity of EVs that better inform EV capture and detection platforms for diagnostic or other downstream use.

Multimodal Nonlinear Optical Imaging for Sensitive Detection of Multiple Pharmaceutical Solid-State Forms and Surface Transformations.

Two nonlinear imaging modalities, coherent anti-Stokes Raman scattering (CARS) and sum-frequency generation (SFG), were successfully combined for sensitive multimodal imaging of multiple solid-state forms and their changes on drug tablet surfaces. Two imaging approaches were used and compared: (i) hyperspectral CARS combined with principal component analysis (PCA) and SFG imaging and (ii) simultaneous narrowband CARS and SFG imaging. Three different solid-state forms of indomethacin-the crystalline gamma and alpha forms, as well as the amorphous form-were clearly distinguished using both approaches. Simultaneous narrowband CARS and SFG imaging was faster, but hyperspectral CARS and SFG imaging has the potential to be applied to a wider variety of more complex samples. These methodologies were further used to follow crystallization of indomethacin on tablet surfaces under two storage conditions: 30 °C/23% RH and 30 °C/75% RH. Imaging with (sub)micron resolution showed that the approach allowed detection of very early stage surface crystallization. The surfaces progressively crystallized to predominantly (but not exclusively) the gamma form at lower humidity and the alpha form at higher humidity. Overall, this study suggests that multimodal nonlinear imaging is a highly sensitive, solid-state (and chemically) specific, rapid, and versatile imaging technique for understanding and hence controlling (surface) solid-state forms and their complex changes in pharmaceuticals.

Fluorescence-suppressed time-resolved Raman spectroscopy of pharmaceuticals using complementary metal-oxide semiconductor (CMOS) single-photon avalanche diode (SPAD) detector.

In this work, we utilize a short-wavelength, 532-nm picosecond pulsed laser coupled with a time-gated complementary metal-oxide semiconductor (CMOS) single-photon avalanche diode (SPAD) detector to acquire Raman spectra of several drugs of interest. With this approach, we are able to reveal previously unseen Raman features and suppress the fluorescence background of these drugs. Compared to traditional Raman setups, the present time-resolved technique has two major improvements. First, it is possible to overcome the strong fluorescence background that usually interferes with the much weaker Raman spectra. Second, using the high photon energy excitation light source, we are able to generate a stronger Raman signal compared to traditional instruments. In addition, observations in the time domain can be performed, thus enabling new capabilities in the field of Raman and fluorescence spectroscopy. With this system, we demonstrate for the first time the possibility of recording fluorescence-suppressed Raman spectra of solid, amorphous and crystalline, and non-photoluminescent and photoluminescent drugs such as caffeine, ranitidine hydrochloride, and indomethacin (amorphous and crystalline forms). The raw data acquired by utilizing only the picosecond pulsed laser and a CMOS SPAD detector could be used for identifying the compounds directly without any data processing. Moreover, to validate the accuracy of this time-resolved technique, we present density functional theory (DFT) calculations for a widely used gastric acid inhibitor, ranitidine hydrochloride. The obtained time-resolved Raman peaks were identified based on the calculations and existing literature. Raman spectra using non-time-resolved setups with continuous-wave 785- and 532-nm excitation lasers were used as reference data. Overall, this demonstration of time-resolved Raman and fluorescence measurements with a CMOS SPAD detector shows promise in diverse areas, including fundamental chemical research, the pharmaceutical setting, process analytical technology (PAT), and the life sciences.

A Multi-Fluorophore Staining Scheme for Identification and Quantification of Vomocytosis.

Vomocytosis is a process by which fungal pathogens, for instance, Cryptococcus neoformans (CN), escape from the digestive phagolysosome of phagocytic cells after ingestion. Interestingly, this expulsion leaves both the pathogen and phagocyte unharmed, and is believed to be an important mechanism by which CNs disseminate throughout infected hosts. This phenomenon was discovered in 2006, and research to date has relied almost entirely on quantification via manual counting of vomocytosis events in time-lapse microscopy videos. This archaic method has the significant disadvantages of requiring excessive labor in manual analysis, limited throughput capabilities, and low accuracy due to subjectivity. Here, we present an alternative method to measure vomocytosis rates using a multi-fluorophore reporter system comprised of two in situ staining steps during infection and a flow cytometry readout. This approach overcomes the limitations of conventional time lapse microscopy methods, with key advantages of high throughput capability, simple procedural steps, and accurate objective readouts. This study rigorously characterizes this vomocytosis reporter system in CN-infected MΦ and DC cultures via fluorescence microscopy, confocal microscopy, and flow cytometry. Here, this fluorescent tool is used to observe differences in expulsion rates after phagosome-modifying drug treatments and additionally utilized to distinguish differences in biochemical compositions among fluorescence-activated cell sorted fungal populations via Raman spectroscopy. Furthermore, this reporter scheme is demonstrated to be adaptable for use in measuring potential biomaterial particle expulsion events. Ultimately, the fluorescent reporter system presented here provides a universal tool for vomocytosis rate measurement of phagocytosed material. This facile approach opens the door to previously unfeasible types of vomocytosis-related studies such as high throughput treatment mechanistic screening and downstream characterization of expelled material.

Machine Learning-Assisted Sampling of Surfance-Enhanced Raman Scattering (SERS) Substrates Improve Data Collection Efficiency.

Surface-enhanced Raman scattering (SERS) is a powerful technique for sensitive label-free analysis of chemical and biological samples. While much recent work has established sophisticated automation routines using machine learning and related artificial intelligence methods, these efforts have largely focused on downstream processing (e.g., classification tasks) of previously collected data. While fully automated analysis pipelines are desirable, current progress is limited by cumbersome and manually intensive sample preparation and data collection steps. Specifically, a typical lab-scale SERS experiment requires the user to evaluate the quality and reliability of the measurement (i.e., the spectra) as the data are being collected. This need for expert user-intuition is a major bottleneck that limits applicability of SERS-based diagnostics for point-of-care clinical applications, where trained spectroscopists are likely unavailable. While application-agnostic numerical approaches (e.g., signal-to-noise thresholding) are useful, there is an urgent need to develop algorithms that leverage expert user intuition and domain knowledge to simplify and accelerate data collection steps. To address this challenge, in this work, we introduce a machine learning-assisted method at the acquisition stage. We tested six common algorithms to measure best performance in the context of spectral quality judgment. For adoption into future automation platforms, we developed an open-source python package tailored for rapid expert user annotation to train machine learning algorithms. We expect that this new approach to use machine learning to assist in data acquisition can serve as a useful building block for point-of-care SERS diagnostic platforms.

Homogenous high enhancement surface-enhanced Raman scattering (SERS) substrates by simple hierarchical tuning of gold nanofoams.

Surface enhanced Raman scattering (SERS) is a powerful tool for vibrational spectroscopy, providing orders of magnitude increase in chemical sensitivity compared to spontaneous Raman scattering. Yet it remains a challenge to synthesize robust, uniform SERS substrates quickly and easily. Lithographic approaches to produce substrates can achieve high, uniform sensitivity but are expensive and complex, thus difficult to scale. Facile solution-phase chemical approaches often result in unreliable SERS substrates due to heterogeneous arrangement of "hot spots" throughout the material. Here we demonstrate the synthesis and characterization of a homogeneous gold nanofoam (AuNF) substrate produced by a rapid, one-pot, four-ingredient synthetic approach. AuNFs are rapidly nucleated with macroscale porosity and then chemically roughened to produce nanoscale features that confer homogeneous and high signal enhancement (~109) across large areas, a comparable performance to lithographically produced substrates.

Novel Stilbene-Nitroxyl Hybrid Compounds Display Discrete Modulation of Amyloid Beta Toxicity and Structure.

Several neurodegenerative diseases are driven by misfolded proteins that assemble into soluble aggregates. These "toxic oligomers" have been associated with a plethora of cellular dysfunction and dysregulation, however the structural features underlying their toxicity are poorly understood. A major impediment to answering this question relates to the heterogeneous nature of the oligomers, both in terms of structural disorder and oligomer size. This not only complicates elucidating the molecular etiology of these disorders, but also the druggability of these targets as well. We have synthesized a class of bifunctional stilbenes to modulate both the conformational toxicity within amyloid beta oligomers (AßO) and the oxidative stress elicited by AßO. Using a neuronal culture model, we demonstrate this bifunctional approach has the potential to counter the molecular pathogenesis of Alzheimer's disease in a powerful, synergistic manner. Examination of AßO structure by various biophysical tools shows that each stilbene candidate uniquely alters AßO conformation and toxicity, providing insight towards the future development of structural correctors for AßO. Correlations of AßO structural modulation and bioactivity displayed by each provides insights for future testing in vivo. The multi-target activity of these hybrid molecules represents a highly advantageous feature for disease modification in Alzheimer's, which displays a complex, multifactorial etiology. Importantly, these novel small molecules intervene with intraneuronal AßO, a necessary feature to counter the cycle of dysregulation, oxidative stress and inflammation triggered during the earliest stages of disease progression.

Surface enhanced Raman scattering of extracellular vesicles for cancer diagnostics despite isolation dependent lipoprotein contamination.

Given the emerging diagnostic utility of extracellular vesicles (EVs), it is important to account for non-EV contaminants. Lipoprotein present in EV-enriched isolates may inflate particle counts and decrease sensitivity to biomarkers of interest, skewing chemical analyses and perpetuating downstream issues in labeling or functional analysis. Using label free surface enhanced Raman scattering (SERS), we confirm that three common EV isolation methods (differential ultracentrifugation, density gradient ultracentrifugation, and size exclusion chromatography) yield variable lipoprotein content. We demonstrate that a dual-isolation method is necessary to isolate EVs from the major classes of lipoprotein. However, combining SERS analysis with machine learning assisted classification, we show that the disease state is the main driver of distinction between EV samples, and largely unaffected by choice of isolation. Ultimately, this study describes a convenient SERS assay to retain accurate diagnostic information from clinical samples by overcoming differences in lipoprotein contamination according to isolation method.

Tumor Receptor-Mediated In Vivo Modulation of the Morphology, Phototherapeutic Properties, and Pharmacokinetics of Smart Nanomaterials.

To be clinically efficacious, nanotherapeutic drugs need to reach disease tissues reliably and cause limited side effects to normal organs and tissues. Here, we report a proof-of-concept study on the development of a smart peptidic nanophototherapeutic agent in line with clinical requirements, which can transform its morphology from nanoparticles to nanofibrils at the tumor sites. This in vivo receptor-mediated transformation process resulted in the formation and prolonged tumor-retention of highly ordered (J-aggregate type of photosensitizer) photosensitive peptide nanofibrillar network with greatly enhanced photothermal and photodynamic properties. This strategy of "multiple daily low-intensity laser radiation after each intravenous injection of significantly low-dose of nanomaterials" demonstrated effective elimination of 4T1 orthotopic syngeneic breast cancer in mice. The technology for nanomaterial modulation based on living cell surface receptors, in this case tumor-associated α3ß1 integrin, has great potential for clinical translation and is expected to improve the therapeutic efficacy against many cancers.

Identification of amyloid beta in small extracellular vesicles via Raman spectroscopy.

One of the hallmarks of Alzheimer's disease (AD) pathogenesis is believed to be the production and deposition of amyloid-beta (Aß) peptide into extracellular plaques. Existing research indicates that extracellular vesicles (EVs) can carry Aß associated with AD. However, characterization of the EVs-associated Aß and its conformational variants has yet to be realized. Raman spectroscopy is a label-free and non-destructive method that is able to assess the biochemical composition of EVs. This study reports for the first time the Raman spectroscopic fingerprint of the Aß present in the molecular cargo of small extracellular vesicles (sEVs). Raman spectra were measured from sEVs isolated from Alzheimer's disease cell culture model, where secretion of Aß is regulated by tetracycline promoter, and from midbrain organoids. The averaged spectra of each sEV group showed considerable variation as a reflection of the biochemical content of sEVs. Spectral analysis identified more intense Raman peaks at 1650 cm-1 and 2930 cm-1 attributable to the Aß peptide incorporated in sEVs produced by the Alzheimer's cell culture model. Subsequent analysis of the spectra by principal component analysis differentiated the sEVs of the Alzheimer's disease cell culture model from the control groups of sEVs. Moreover, the results indicate that Aß associated with secreted sEVs has a α-helical secondary structure and the size of a monomer or small oligomer. Furthermore, by analyzing the lipid content of sEVs we identified altered fatty acid chain lengths in sEVs that carry Aß that may affect the fluidity of the EV membrane. Overall, our findings provide evidence supporting the use of Raman spectroscopy for the identification and characterization of sEVs associated with potential biomarkers of neurological disorders such as toxic proteins.

Superhydrophobic bowl-like SERS substrates patterned from CMOS sensors for extracellular vesicle characterization.

Using a regular CMOS sensor as a template, we are able to fabricate a simple but highly effective superhydrophobic SERS substrate. Specifically, we decorated the microlens layer of the sensor with 7 µm polystyrene beads to obtain a PDMS patterned replica. The process resulted in a uniform pattern of voids in the PDMS (denoted nanobowls) that are intercalated with a few larger voids (denoted here microbowls). The voids act as superhydrophobic substrates with analyte concentration capabilities in bigger bowl-like structures. Silver nanoparticles were directly grown on the patterned PDMS substrate inside both the nano- and microbowls, and serve as strong electromagnetic field enhancers for the SERS substrate. After systematic characterization of the fabricated SERS substrate by atomic force microscopy and scanning electron microscopy, we demonstrated its SERS performance using 4-aminothiophenol as a reporter molecule. Finally, we employed this innovative substrate to concentrate and analyze extracellular vesicles (EVs) isolated from an MC65 neural cell line in an ultralow sample volume. This substrate can be further exploited for the investigation of various EV biomarkers for early diagnosis of different diseases using liquid biopsy.

Hybrid Nanoplasmonic Porous Biomaterial Scaffold for Liquid Biopsy Diagnostics Using Extracellular Vesicles.

For more effective early-stage cancer diagnostics, there is a need to develop sensitive and specific, non- or minimally invasive, and cost-effective methods for identifying circulating nanoscale extracellular vesicles (EVs). Here, we report the utilization of a simple plasmonic scaffold composed of a microscale biosilicate substrate embedded with silver nanoparticles for surface-enhanced Raman scattering (SERS) analysis of ovarian and endometrial cancer EVs. These substrates are rapidly and inexpensively produced without any complex equipment or lithography. We extensively characterize the substrates with electron microscopy and outline a reproducible methodology for their use in analyzing EVs from in vitro and in vivo biofluids. We report effective chemical treatments for (i) decoration of metal surfaces with cysteamine to nonspecifically pull down EVs to SERS hotspots and (ii) enzymatic cleavage of extraluminal moieties at the surface of EVs that prevent localization of complementary chemical features (lipids/proteins) to the vicinity of the metal-enhanced fields. We observe a major loss of sensitivity for ovarian and endometrial cancer following enzymatic cleavage of EVs' extraluminal domain, suggesting its critical significance for diagnostic platforms. We demonstrate that the SERS technique represents an ideal tool to assess and measure the high heterogeneity of EVs isolated from clinical samples in an inexpensive, rapid, and label-free assay.

Label-free characterization and real-time monitoring of cell uptake of extracellular vesicles.

Extracellular vesicles (EVs) have the ability to function as molecular vehicles and could therefore be harnessed to deliver drugs to target cells in diseases such as cancer. The composition of EVs determines their function as well as their interactions with cells, which consequently affects the cell uptake efficacy of EVs. In this study, we present two novel label-free approaches for studying EVs; characterization of EV composition by time-gated surface-enhanced Raman spectroscopy (TG-SERS) and monitoring the kinetics and amount of cellular uptake of EVs by surface plasmon resonance (SPR) in real-time. Using these methods, we characterized the most abundant EVs of human blood, red blood cell (RBC)- and platelet (PLT)-derived EVs and studied their interactions with prostate cancer cells. Complementary studies were performed with nanoparticle tracking analysis for concentration and size determinations of EVs, zeta potential measurements for surface charge analysis, and fluorophore-based confocal imaging and flow cytometry to confirm EV uptake. Our results revealed distinct biochemical features between the studied EVs and demonstrated that PLT-derived EVs were more efficiently internalized by PC-3 cells than RBC-derived EVs. The two novel label-free techniques introduced in this study were found to efficiently complement conventional techniques and paves the way for further use of TG-SERS and SPR in EV studies.

Transformable peptide nanoparticles arrest HER2 signalling and cause cancer cell death in vivo.

Human epidermal growth factor receptor 2 (HER2) is overexpressed in >20% of breast cancers. Dimerization of HER2 receptors leads to the activation of downstream signals enabling the proliferation and survival of malignant phenotypes. Owing to the high expression levels of HER2, combination therapies are currently required for the treatment of HER2+ breast cancer. Here, we designed non-toxic transformable peptides that self-assemble into micelles under aqueous conditions but, on binding to HER2 on cancer cells, transform into nanofibrils that disrupt HER2 dimerization and subsequent downstream signalling events leading to apoptosis of cancer cells. The phase transformation of peptides enables specific HER2 targeting, and inhibition of HER2 dimerization blocks the expression of proliferation and survival genes in the nucleus. We demonstrate, in mouse xenofraft models, that these transformable peptides can be used as a monotherapy in the treatment of HER2+ breast cancer.

Nanoplasmonic Approaches for Sensitive Detection and Molecular Characterization of Extracellular Vesicles.

All cells release a multitude of nanoscale extracellular vesicles (nEVs) into circulation, offering immense potential for new diagnostic strategies. Yet, clinical translation for nEVs remains a challenge due to their vast heterogeneity, our insufficient ability to isolate subpopulations, and the low frequency of disease-associated nEVs in biofluids. The growing field of nanoplasmonics is poised to address many of these challenges. Innovative materials engineering approaches based on exploiting nanoplasmonic phenomena, i.e., the unique interaction of light with nanoscale metallic materials, can achieve unrivaled sensitivity, offering real-time analysis and new modes of medical and biological imaging. We begin with an introduction into the basic structure and function of nEVs before critically reviewing recent studies utilizing nanoplasmonic platforms to detect and characterize nEVs. For the major techniques considered, surface plasmon resonance (SPR), localized SPR, and surface enhanced Raman spectroscopy (SERS), we introduce and summarize the background theory before reviewing the studies applied to nEVs. Along the way, we consider notable aspects, limitations, and considerations needed to apply plasmonic technologies to nEV detection and analysis.

One-bead one-compound combinatorial library derived targeting ligands for detection and treatment of oral squamous cancer.

Oral squamous cancers (OSC) are hallmarked by poor prognosis, delayed clinical detection, and a lack of defined, characteristic biomarkers. By screening combinatorial one-bead one-compound (OBOC) peptide libraries against oral squamous cancer cell lines, two cyclic peptide ligands, LLY12 and LLY13 were previously identified. These ligands are capable of specific binding to the oral cancer cell lines (MOK-101, HSC-3, SCC-4 and SCC-10a) but not non-cancerous keratinocytes, leukocytes, fibroblast, and endothelial cells. These two peptides were synthesized and evaluated for their binding property, cytotoxicity and cell permeability. In vitro studies indicate that both LLY12 and LLY13 were able to bind to oral cancer cells with high specificity but did not show any cytotoxicity against human keratinocytes. Biotinylated LLY13, in complex with streptavidin-alexa488 was taken up by live oral cancer cells, thus rendering it as an excellent candidate vehicle for efficient delivery of drug loaded-nanoparticles. In vivo and ex vivo near infra-red fluorescence imaging studies confirmed the in vivo targeting efficiency and specificity of LLY13 in oral cancer orthotopic murine xenograft model. In vivo studies also showed that LLY13 was able to accumulate in the OSC tumors and demarcate the tumor margins in orthotopic xenograft model. Together, our data supports LLY13 as a promising theranostic agent against OSC.

Oligomerization Alters Binding Affinity Between Amyloid Beta and a Modulator of Peptide Aggregation.

The soluble oligomeric form of the amyloid beta (Aß) peptide is the major causative agent in the molecular pathogenesis of Alzheimer's disease (AD). We have previously developed a pyrroline-nitroxyl fluorene compound (SLF) that blocks the toxicity of Aß. Here we introduce the multi-parametric surface plasmon resonance (MP-SPR) approach to quantify SLF binding and effect on the self-association of the peptide via a label-free, real-time approach. Kinetic analysis of SLF binding to Aß and measurements of layer thickness alterations inform on the mechanism underlying the ability of SLF to inhibit Aß toxicity and its progression towards larger oligomeric assemblies. Depending on the oligomeric state of Aß, distinct binding affinities for SLF are revealed. The Aß monomer and dimer uniquely possess sub-nanomolar affinity for SLF via a non-specific mode of binding. SLF binding is weaker in oligomeric Aß, which displays an affinity for SLF on the order of 100 µM. To complement these experiments we carried out molecular docking and molecular dynamics simulations to explore how SLF interacts with the Aß peptide. The MP-SPR results together with in silico modeling provide affinity data for the SLF-Aß interaction and allow us to develop a new general method for examining protein aggregation.

Targeting Tumor-Associated Exosomes with Integrin-Binding Peptides.

All cells expel a variety of nano-sized extracellular vesicles (EVs), including exosomes, with composition reflecting the cells' biological state. Cancer pathology is dramatically mediated by EV trafficking via key proteins, lipids, metabolites, and microRNAs. Recent proteomics evidence suggests that tumor-associated exosomes exhibit distinct expression of certain membrane proteins, rendering those proteins as attractive targets for diagnostic or therapeutic application. Yet, it is not currently feasible to distinguish circulating EVs in complex biofluids according to their tissue of origin or state of disease. Here we demonstrate peptide binding to tumor-associated EVs via overexpressed membrane protein. We find that SKOV-3 ovarian tumor cells and their released EVs express α3ß1 integrin, which can be targeted by our in-house cyclic nonapeptide, LXY30. After measuring bulk SKOV-3 EV association with LXY30 by flow cytometry, Raman spectral analysis of laser-trapped single exosomes with LXY30-dialkyne conjugate enabled us to differentiate cancer-associated exosomes from non-cancer exosomes. Furthermore, we introduce the foundation for a highly specific detection platform for tumor-EVs in solution with biosensor surface-immobilized LXY30. LXY30 not only exhibits high specificity and affinity to α3ß1 integrin-expressing EVs, but also reduces EV uptake into SKOV-3 parent cells, demonstrating the possibility for therapeutic application.

Multi-parametric surface plasmon resonance platform for studying liposome-serum interactions and protein corona formation.

When nanocarriers are administered into the blood circulation, a complex biomolecular layer known as the "protein corona" associates with their surface. Although the drivers of corona formation are not known, it is widely accepted that this layer mediates biological interactions of the nanocarrier with its surroundings. Label-free optical methods can be used to study protein corona formation without interfering with its dynamics. We demonstrate the proof-of-concept for a multi-parametric surface plasmon resonance (MP-SPR) technique in monitoring the formation of a protein corona on surface-immobilized liposomes subjected to flowing 100 % human serum. We observed the formation of formulation-dependent "hard" and "soft" coronas with distinct refractive indices, layer thicknesses, and surface mass densities. MP-SPR was also employed to determine the affinity (K D ) of a complement system molecule (C3b) with cationic liposomes with and without polyethylene glycol. Tendency to create a thick corona correlated with a higher affinity of opsonin C3b for the surface. The label-free platform provides a fast and robust preclinical tool for tuning nanocarrier surface architecture and composition to control protein corona formation.