Simultaneous Multi-miRNA Detection in Urinary Small Extracellular Vesicles Using Target-Triggered Locked Hairpin DNA-Functionalized Au Nanoprobes for Systemic Lupus Erythematosus Diagnosis.

Systemic lupus erythematosus (SLE) is a chronic autoimmune disease characterized by multiorgan involvement and complex clinical manifestations, leading to cumbersome diagnostic processes. MicroRNAs (miRNAs) in small extracellular vesicles (sEVs) have emerged as promising biomarkers for liquid biopsy. Herein, we constructed a simple multi-miRNA detection platform based on target-triggered locked hairpin DNA-functionalized Au nanoprobes (AuNP@LH) as a simple and noninvasive tool for the diagnosis and classification of SLE. The nanoprobes were prepared by modifying locked hairpin DNA designed for target miRNAs on gold nanoparticles. In the presence of target miRNAs, target-triggered hairpin assembly amplification was induced, and then fluorophore-labeled bolt DNA was released, resulting in a fluorescence signal responsive to miRNA concentration. Benefiting from the enzyme-free amplification strategy, the limits of detection (LOD) of three miRNA biomarkers for SLE were 19 pM for microRNA-146a, 66 pM for microRNA-29c, and 19 pM for microRNA-150. The proposed probes have been successfully applied to simultaneously detect multiple miRNAs in urinary sEVs from patients diagnosed with SLE and healthy controls, which exhibited good practicability in SLE diagnosis with the area under curve (AUC) of the receiver characteristic curve reaching 1.00. Furthermore, SLE patients with different disease severity can be differentiated with 81.2% accuracy. Predictably, with the advantages of low cost, rapidity, high sensitivity, and noninvasiveness, our multi-miRNA detection platform is a potential tool for multiple miRNA analysis and related clinical applications.

Quantification of GPC1(+) Exosomes Based on MALDI-TOF MS In Situ Signal Amplification for Pancreatic Cancer Discrimination and Evaluation.

Pancreatic cancer (PC) has a high mortality, with a fairly low five-year survival rate, because of its delayed diagnosis. Recently, liquid biopsy, especially based on exosomes, has attracted vast attention, thanks to its low invasiveness. Herein, we constructed a protocol for pancreatic cancer related Glypican 1 (GPC1) exosome quantification, based on in situ mass spectrometry signal amplification, by utilizing mass tag molecules on gold nanoparticles (AuNPs). Exosomes were extracted and purified by size-exclusion chromatography (SEC), captured by TiO2 modified magnetic nanoparticles, and then targeted specifically by anti-GPC1 antibody modified on AuNPs. With matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS), the signal of PC biomarker, GPC1, was converted to a mass tag signal and amplified. With addition of a certain amount of internal standard molecules modified on AuNPs, the relative intensity ratio of mass tag to internal standard was proportional to the concentration of GPC1(+) exosomes derived from pancreatic cancer cell lines, PANC-1, with good linearity (R2 = 0.9945) in a wide dynamic range from 7.1 × 10 to 7.1 × 106 particles/µL. This method was further applied to plasma samples from healthy control (HC) and pancreatic cancer patients with different tumor load, and exhibited a great potential in discriminating diagnosed PC patients from HC, and has the monitoring potential in PC progression.

Metabolic profiling of urinary exosomes for systemic lupus erythematosus discrimination based on HPL-SEC/MALDI-TOF MS.

Systemic lupus erythematosus (SLE) is a chronic autoimmune disease which leads to the formation of immune complex deposits in multiple organs and has heterogeneous clinical manifestations. Currently, exosomes for liquid biopsy have been applied in diagnosis and monitoring of diseases, whereas SLE discrimination based on exosomes at the metabolic level is rarely reported. Herein, we constructed a protocol for metabolomic study of urinary exosomes from SLE patients and healthy controls (HCs) with high efficiency and throughput. Exosomes were first obtained by high-performance liquid size-exclusion chromatography (HPL-SEC), and then metabolic fingerprints of urinary exosomes were extracted by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) with high throughput and high efficency. With the statistical analysis by orthogonal partial least-squares discriminant analysis (OPLS-DA) model, SLE patients were efficiently distinguished from HCs, the area under the curve (AUC) of the receiver characteristic curve (ROC) was 1.00, and the accuracy of the unsupervised clustering heatmap was 90.32%. In addition, potential biomarkers and related metabolic pathways were analyzed. This method, with the characteristics of high throughput, high efficiency, and high accuracy, will provide the broad prospect of exosome-driven precision medicine and large-scale screening in clinical applications.

Integrated Pipeline of Rapid Isolation and Analysis of Human Plasma Exosomes for Cancer Discrimination Based on Deep Learning of MALDI-TOF MS Fingerprints.

Plasma exosomes have shown great potential for liquid biopsy in clinical cancer diagnosis. Herein, we present an integrated strategy for isolating and analyzing exosomes from human plasma rapidly and then discriminating different cancers excellently based on deep learning fingerprints of plasma exosomes. Sequential size-exclusion chromatography (SSEC) was developed efficiently for separating exosomes from human plasma. SSEC isolated plasma exosomes, taking as less as 2 h for a single sample with high purity such that the discard rates of high-density lipoproteins and low/very low-density lipoproteins were 93 and 85%, respectively. Benefitting from the rapid and high-purity isolation, the contents encapsulated in exosomes, covered by plasma proteins, were well profiled by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MS). We further analyzed 220 clinical samples, including 79 breast cancer patients, 57 pancreatic cancer patients, and 84 healthy controls. After MS data pre-processing and feature selection, the extracted MS feature peaks were utilized as inputs for constructing a multi-classifier artificial neural network (denoted as Exo-ANN) model. The optimized model avoided overfitting and performed well in both training cohorts and test cohorts. For the samples in the independent test cohort, it realized a diagnosed accuracy of 80.0% with an area under the curve of 0.91 for the whole group. These results suggest that our integrated pipeline may become a generic tool for liquid biopsy based on the analysis of plasma exosomes in clinics.

Tomatidine inhibits invasion of human lung adenocarcinoma cell A549 by reducing matrix metalloproteinases expression.

Tomatidine is an aglycone of glycoalkaloid tomatine in tomato. Tomatidine is found to possess anti-inflammatory properties and may serve as a chemosensitizer in multidrug-resistant tumor cells. However, the effect of tomatidine on cancer cell metastasis remains unclear. This study examines the effect of tomatidine on the migration and invasion of human lung adenocarcinoma A549 cell in vitro. The data demonstrates that tomatidine does not effectively inhibit the viability of A549 cells. When treated with non-toxic doses of tomatidine, cell invasion is markedly suppressed by Boyden chamber invasion assay, while cell migration is not affected. Tomatidine reduces the mRNA level of matrix metalloproteinase-2 (MMP-2), MMP-9 and increases the expression of reversion-inducing cysteine-rich protein with kazal motifs (RECK), as well as tissue inhibitor of metalloproteinase-1 (TIMP-1). The immunoblotting assays indicate that tomatidine is very effective in suppressing the phosphorylation of Akt and extracellular signal regulating kinase (ERK). In addition, tomatidine significantly decreases the nuclear level of nuclear factor kappa B (NF-κB), which suggests that tomatidine inhibits NF-κB activity. Furthermore, the treatment of inhibitors specific for PI3K/Akt (LY294002), ERK (U0126), or NF-κB (pyrrolidine dithiocarbamate) to A549 cells reduced cell invasion and MMP-2/9 expression. The results suggest that tomatidine inhibits the invasion of A549 cells by reducing the expression of MMPs. It also inhibits ERK and Akt signaling pathways and NF-κB activity. These findings demonstrate a new therapeutic potential for tomatidine in anti-metastatic therapy.