Thermophoretically enriched detection

Tumor-derived extracellular vesicle proteins as new biomarkers and targets in precision oncology

Extracellular vesicles (EVs) are important carriers of signaling molecules, such as nucleic acids, proteins, and lipids, and have become a focus of increasing interest due to their numerous physiological and pathological functions. For a long time, most studies on EV components focused on noncoding RNAs; however, in recent years, extracellular vesicle proteins (EVPs) have been found to play important roles in diagnosis, treatment, and drug resistance and thus have been considered favorable biomarkers and therapeutic targets for various tumors. In this review, we describe the general protocols of research on EVPs and summarize their multifaceted roles in precision medicine applications, including cancer diagnosis, dynamic monitoring of therapeutic efficacy, drug resistance research, tumor microenvironment interaction research, and anticancer drug delivery.

Blood plasma derived extracellular vesicles (BEVs): particle purification liquid chromatography (PPLC) and proteomic analysis reveals BEVs as a potential minimally invasive tool for predicting response to breast cancer treatment

PURPOSE

Circulating blood plasma derived extracellular vesicles (BEVs) containing proteins hold promise for their use as minimally invasive biomarkers for predicting response to cancer therapy. The main goal of this study was to establish the efficiency and utility of the particle purification liquid chromatography (PPLC) BEV isolation method and evaluate the role of BEVs in predicting breast cancer (BC) patient response to neoadjuvant chemotherapy (NAC).

METHODS

PPLC isolation was used to separate BEVs from non-EV contaminants and characterize BEVs from 17 BC patients scheduled to receive NAC. Using LC-MS/MS, we compared the proteome of PPLC-isolated BEVs from patients (n = 7) that achieved a pathological complete response (pCR) after NAC (responders [R]) to patients (n = 10) who did not achieve pCR (non-responders [NR]). Luminal MCF7 and basaloid MDA-MB-231 BC cells were treated with isolated BEVs and evaluated for metabolic activity by MTT assay.

RESULTS

NR had elevated BEV concentrations and negative zeta potential (ζ-potential) prior to receipt of NAC. Eight proteins were enriched in BEVs of NR. GP1BA (CD42b), PECAM-1 (CD31), CAPN1, HSPB1 (HSP27), and ANXA5 were validated using western blot. MTT assay revealed BEVs from R and NR patients increased metabolic activity of MCF7 and MDA-MB-231 BC cells and the magnitude was highest in MCF7s treated with NR BEVs.

CONCLUSION

PPLC-based EV isolation provides a preanalytical separation process for BEVs devoid of most contaminants. Our findings suggest that PPLC-isolated BEVs and the five associated proteins may be established as predictors of chemoresistance, and thus serve to identify NR to spare them the toxic effects of NAC.

Magnetic-Nanowaxberry-Based Simultaneous Detection of Exosome and Exosomal Proteins for the Intelligent Diagnosis of Cancer

Exosome concentration and exosomal proteins are regarded as promising cancer biomarkers. Herein, a waxberry-like magnetic bead (magnetic-nanowaxberry) which has huge surface area and strong affinity was synthesized to couple with aptamer for exosome capture and recovery. Subsequently, we developed a fluorescent assay for the sensitive, accurate, and simultaneous quantification of exosome and cancer-related exosomal proteins [epidermal growth factor receptor (EGFR) and epithelial cell adhesion molecule (EpCAM)] by using triple-colored probes to recognize EGFR and EpCAM or spontaneously anchor to the lipid bilayer. In this design, the interference of soluble proteins can be avoided due to the dual recognition strategy. Moreover, the lipid-based quantification of exosome concentration can improve the accuracy. Besides, the simultaneous detection mode can save samples and simplify the operation steps. Consequently, the assay shows high sensitivity (the limits of detection are down to 0.96 pg/mL for EGFR, 0.19 pg/mL for EpCAM, and 2.4 × 10⁴ particles/μL for exosome), high specificity, and satisfactory accuracy. More importantly, this technique is successfully used to analyze exosomes in plasma to distinguish cancer patients from healthy individuals. To improve the diagnostic efficacy, the deep learning was used to exploit the potential pattern hidden in data obtained by the proposed method. Also, the accuracy for the intelligent diagnosis of cancer can achieve 96.0%. This study provides a new avenue for developing new biosensors for exosome analysis and intelligent disease diagnosis.

Analytical analysis of anisotropic thermophoresis of a charged spheroidal colloid in aqueous media for extremely thin EDL cases

Thermophoresis of charged spheroids has been widely applied in biology and medical science. In this work, we report an analysis of the anisotropic thermophoresis of diluted spheroidal colloids in aqueous media for extremely thin EDL cases. Under the boundary layer approximation, we formulate the thermophoretic velocity, the thermophoretic force, and the thermodiffusion coefficient of a randomly dispersed spheroid. The parametric studies show that under the aforementioned conditions, the thermophoresis is anisotropic and its thermodiffusion coefficient should be considered as a vector, D_T . The thermodiffusion coefficient values and directions of D_T are strongly related to the aspect ratio and the angle θ between the externally applied temperature gradient and the particle's axis of revolution: The increasing aspect ratio enlarges the thermodiffusion coefficient value D_T of prolate (oblate) spheroids to a constant value when θ < 60° (θ > 45°), and it reduces D_T of prolate (oblate) spheroids to a constant value when θ > 60° (θ < 45°). The thermodiffusion coefficient direction of both prolate and oblate spheroids deviates slightly from -∇T_∞ for a small aspect ratio, and such deviation becomes serious for a large aspect ratio.

Protein analysis of extracellular vesicles to monitor and predict therapeutic response in metastatic breast cancer

Molecular profiling of circulating extracellular vesicles (EVs) provides a promising noninvasive means to diagnose, monitor, and predict the course of metastatic breast cancer (MBC). However, the analysis of EV protein markers has been confounded by the presence of soluble protein counterparts in peripheral blood. Here we use a rapid, sensitive, and low-cost thermophoretic aptasensor (TAS) to profile cancer-associated protein profiles of plasma EVs without the interference of soluble proteins. We show that the EV signature (a weighted sum of eight EV protein markers) has a high accuracy (91.1 %) for discrimination of MBC, non-metastatic breast cancer (NMBC), and healthy donors (HD). For MBC patients undergoing therapies, the EV signature can accurately monitor the treatment response across the training, validation, and prospective cohorts, and serve as an independent prognostic factor for progression free survival in MBC patients. Together, this work highlights the potential clinical utility of EVs in management of MBC.

A thermophoretic aptasensor can be used to profile cancer-associated proteins of extracellular vesicles (EVs) in patients’ plasma. Here, the authors use this technique to develop an EV-signature able to discriminate metastatic breast cancer, monitor treatment response, and predict patients’ progression-free survival.

Towards Microfluidic-Based Exosome Isolation and Detection for Tumor Therapy

Exosomes are a class of cell-secreted, nano-sized extracellular vesicles with a bilayer membrane structure of 30-150 nm in diameter. Their discovery and application have brought breakthroughs in numerous areas, such as liquid biopsies, cancer biology, drug delivery, immunotherapy, tissue repair, and cardiovascular diseases. Isolation of exosomes is the first step in exosome-related research and its applications. Standard benchtop exosome separation and sensing techniques are tedious and challenging, as they require large sample volumes, multi-step operations that are complex and time-consuming, requiring cumbersome and expensive instruments. In contrast, microfluidic platforms have the potential to overcome some of these limitations, owing to their high-precision processing, ability to handle liquids at a microscale, and integrability with various functional units, such as mixers, actuators, reactors, separators, and sensors. These platforms can optimize the detection process on a single device, representing a robust and versatile technique for exosome separation and sensing to attain high purity and high recovery rates with a short processing time. Herein, we overview microfluidic strategies for exosome isolation based on their hydrodynamic properties, size filtration, acoustic fields, immunoaffinity, and dielectrophoretic properties. We focus especially on advances in label-free isolation of exosomes with active biological properties and intact morphological structures. Further, we introduce microfluidic techniques for the detection of exosomal proteins and RNAs with high sensitivity, high specificity, and low detection limits. We summarize the biomedical applications of exosome-mediated therapeutic delivery targeting cancer cells. To highlight the advantages of microfluidic platforms, conventional techniques are included for comparison. Future challenges and prospects of microfluidics towards exosome isolation applications are also discussed. Although the use of exosomes in clinical applications still faces biological, technical, regulatory, and market challenges, in the foreseeable future, recent developments in microfluidic technologies are expected to pave the way for tailoring exosome-related applications in precision medicine.