Stem Cell-Derived Extracellular Vesicle-Bearing Injectable Hydrogel for Collagen Generation in Dermis.

Despite the remarkable advances of dermal fillers that reduce wrinkles caused by dermis thickness reduction, they still lack effective hydrogel systems that stimulate collagen generation along with injection convenience. Here, we develop a stem cell-derived extracellular vesicle (EV)-bearing thermosensitive hydrogel (EVTS-Gel) for effective in vivo collagen generation. The TS-Gel undergoes sol-gel transition at 32.6 °C, as demonstrated by the storage and loss moduli crossover. Moreover, the TS-Gel and the EVTS-Gel have comparable rheological properties. Both hydrogels are injected in a sol state; hence, they require lower injection forces than conventional hydrogel-based dermal fillers. When locally administered to mouse skin, the TS-Gel extends the retention time of EVs by 2.23 times. Based on the nature of the controlled EV release, the EVTS-Gel significantly inhibits the dermis thickness reduction caused by aging compared to the bare EV treatment for 24 weeks. After a single treatment, the collagen layer thickness of the EVTS-Gel-treated dermis becomes 2.64-fold thicker than that of the bare EV-treated dermis. Notably, the collagen generation efficacy of the bare EV is poorer than that of the EVTS-Gel of a 10× lesser dose. Overall, the EVTS-Gel shows potential as an antiaging dermal filler for in vivo collagen generation.

Upconverting Nanoparticle-based Enhanced Luminescence Lateral-Flow Assay for Urinary Biomarker Monitoring.

Development of efficient portable sensors for accurately detecting biomarkers is crucial for early disease diagnosis, yet remains a significant challenge. To address this need, we introduce the enhanced luminescence lateral-flow assay, which leverages highly luminescent upconverting nanoparticles (UCNPs) alongside a portable reader and a smartphone app. The sensor's efficiency and versatility were shown for kidney health monitoring as a proof of concept. We engineered Er3+- and Tm3+-doped UCNPs coated with multiple layers, including an undoped inert matrix shell, a mesoporous silica shell, and an outer layer of gold (UCNP@mSiO2@Au). These coatings synergistically enhance emission by over 40-fold and facilitate biomolecule conjugation, rendering UCNP@mSiO2@Au easy to use and suitable for a broad range of bioapplications. Employing these optimized nanoparticles in lateral-flow assays, we successfully detected two acute kidney injury-related biomarkers─kidney injury molecule-1 (KIM-1) and neutrophil gelatinase-associated lipocalin (NGAL)─in urine samples. Using our sensor platform, KIM-1 and NGAL can be accurately detected and quantified within the range of 0.1 to 20 ng/mL, boasting impressively low limits of detection at 0.28 and 0.23 ng/mL, respectively. Validating our approach, we analyzed clinical urine samples, achieving biomarker concentrations that closely correlated with results obtained via ELISA. Importantly, our system enables biomarker quantification in less than 15 min, underscoring the performance of our novel UCNP-based approach and its potential as reliable, rapid, and user-friendly diagnostics.

Extracellular vesicle isolation and counting system (EVics) based on simultaneous tandem tangential flow filtration and large field-of-view light scattering.

Although the isolation and counting of small extracellular vesicles (sEVs) are essential steps in sEV research, an integrated method with scalability and efficiency has not been developed. Here, we present a scalable and ready-to-use extracellular vesicle (EV) isolation and counting system (EVics) that simultaneously allows isolation and counting in one system. This novel system consists of (i) EVi, a simultaneous tandem tangential flow filtration (TFF)-based EV isolation component by applying two different pore-size TFF filters, and (ii) EVc, an EV counting component using light scattering that captures a large field-of-view (FOV). EVi efficiently isolated 50-200 nm-size sEVs from 15 µL to 2 L samples, outperforming the current state-of-the-art devices in purity and speed. EVc with a large FOV efficiently counted isolated sEVs. EVics enabled early observations of sEV secretion in various cell lines and reduced the cost of evaluating the inhibitory effect of sEV inhibitors by 20-fold. Using EVics, sEVs concentrations and sEV PD-L1 were monitored in a 23-day cancer mouse model, and 160 clinical samples were prepared and successfully applied to diagnosis. These results demonstrate that EVics could become an innovative system for novel findings in basic and applied studies in sEV research.

The diagnostic accuracy of serum and plasma microRNAs in detection of cervical intraepithelial neoplasia and cervical cancer: A systematic review and meta-analysis.

Studies suggest a need for new diagnostic approaches for cervical cancer including microRNA technology. In this review, we assessed the diagnostic accuracy of microRNAs in detecting cervical cancer and Cervical Intraepithelial Neoplasia (CIN). We performed a systematic review following the Preferred Reporting Items for Systematic Review and Meta-Analysis guideline for protocols (PRISMA-P). We searched for all articles in online databases and grey literature from 01st January 2012 to 16th August 2022. We used the quality assessment of diagnostic accuracy studies tool (QUADAS-2) to assess the risk of bias of included studies and then conducted a Random Effects Meta-analysis. We identified 297 articles and eventually extracted data from 24 studies. Serum/plasma concentration miR-205, miR-21, miR-192, and miR-9 showed highest diagnostic accuracy (AUC of 0.750, 0.689, 0.980, and 0.900, respectively) for detecting CIN from healthy controls. MicroRNA panels (miR-21, miR-125b and miR-370) and (miR-9, miR-10a, miR-20a and miR-196a and miR-16-2) had AUC values of 0.897 and 0.886 respectively for detecting CIN from healthy controls. For detection of cervical cancer from healthy controls, the most promising microRNAs were miR-21, miR-205, miR-192 and miR-9 (AUC values of 0.723, 0.960, 1.00, and 0.99 respectively). We report higher diagnostic accuracy of upregulated microRNAs, especially miR-205, miR-9, miR-192, and miR-21. This highlights their potential as stand-alone screening or diagnostic tests, either with others, in a new algorithm, or together with other biomarkers for purposes of detecting cervical lesions. Future studies could standardize quantification methods, and also study microRNAs in higher prevalence populations like in sub-Saharan Africa and South Asia. Our review protocol was registered in PROSPERO (CRD42022313275).

Prevalence of cervical intraepithelial lesions and associated factors among women attending a cervical cancer clinic in Western Uganda; results based on Pap smear cytology.

Introduction: There are high incidence and mortality rates of cervical cancer among females in East Africa. This is exacerbated by limited up-to-date data on premalignant lesions and associated factors in this setting. In this study, we determined the prevalence of cervical intraepithelial lesions and associated factors among women attending the Mbarara Regional Referral Hospital cervical cancer clinic in Southwestern Uganda. Methods: In this cross-sectional study, 364 participants were recruited from among women attending the Mbarara Regional Referral Hospital cervical cancer clinic from 1 April to 30 June 2023. On consent, the study nurse collected demographic data and Pap smears, which were microscopically examined and reported by a laboratory scientist and a pathologist following the Bethesda grading system (2014). Statistical analyses were done in STATA version 17, using proportions, Chi-square, bivariate, and multivariate logistic regression analysis to determine associated factors at ⩽0.05 significance level. Results: The mean age of participants was 41.9 years. A third of all study participants (37.6%, 132/351) were contraceptive users, mostly hormonal contraceptives (87.1%, 115/132). Almost 88% (307/351) had an unknown Human Papilloma Virus status. The prevalence of cervical intraepithelial lesions among our study participants was 6.6% (23/351), of which 73.9% (17/23) were low-grade squamous intraepithelial lesions. More than half (9/17, 52.9%) of low-grade squamous intraepithelial lesions were active hormonal contraceptive users. Use of hormonal contraceptives (OR: 3.032, p: 0.0253), use of intrauterine devices (OR: 6.284, p: 0.039), and any family history of cervical cancer (OR: 4.144, p: 0.049) were significantly associated with cervical intraepithelial lesions. Conclusion: The prevalence of cervical intraepithelial lesions was 6.6%, lower than global estimates. Use of hormonal and intrauterine device contraceptives, as well as family history of cervical cancer, were significantly associated with cervical intraepithelial lesions among our study population. Prospective studies are recommended to further understand associations between different types of intrauterine devices and hormonal contraceptives, and cervical lesions.

Molecular fingerprinting of biological nanoparticles with a label-free optofluidic platform.

Label-free detection of multiple analytes in a high-throughput fashion has been one of the long-sought goals in biosensing applications. Yet, for all-optical approaches, interfacing state-of-the-art label-free techniques with microfluidics tools that can process small volumes of sample with high throughput, and with surface chemistry that grants analyte specificity, poses a critical challenge to date. Here, we introduce an optofluidic platform that brings together state-of-the-art digital holography with PDMS microfluidics by using supported lipid bilayers as a surface chemistry building block to integrate both technologies. Specifically, this platform fingerprints heterogeneous biological nanoparticle populations via a multiplexed label-free immunoaffinity assay with single particle sensitivity. First, we characterise the robustness and performance of the platform, and then apply it to profile four distinct ovarian cell-derived extracellular vesicle populations over a panel of surface protein biomarkers, thus developing a unique biomarker fingerprint for each cell line. We foresee that our approach will find many applications where routine and multiplexed characterisation of biological nanoparticles are required.

Phase-driven progress in nanophotonic biosensing.

In the continuous pursuit of enhancing the sensitivity of nanophotonic biosensors by leveraging phase phenomena, a recent development involved the engineering of an atomically thin Ge2Sb2Te5 layer on a silver nanofilm to generate large Goos-Hänchen-shifts associated with phase singularities. The resulting detection limit reached ~7 × 10-7 RIU.

Rigorous Comparison of Extracellular Vesicle Processing to Enhance Downstream Analysis for Glioblastoma Characterization.

Extracellular vesicles (EVs) are highly sought after as a source of biomarkers for disease detection and monitoring. Tumor EV isolation, processing, and evaluation from biofluids is convoluted by EV heterogeneity and biological contaminants and is limited by technical processing efficacy. This study rigorously compares common bulk EV isolation workflows (size exclusion chromatography, SEC; membrane affinity, MA) alongside downstream RNA extraction protocols to investigate molecular analyte recovery. EV integrity and recovery is evaluated using a variety of technologies to quantify total intact EVs, total and surface proteins, and RNA purity and recovery. A comprehensive evaluation of each analyte is performed, with a specific emphasis on maintaining user (n = 2), biological (n = 3), and technical replicates (n≥3) under in vitro conditions. Subsequent study of tumor EV spike-in into healthy donor plasma samples is performed to further validate biofluid-derived EV purity and isolation for clinical application. Results show that EV surface integrity is considerably preserved in eluates from SEC-derived EVs, but RNA recovery and purity, as well as bulk protein isolation, is significantly improved in MA-isolated EVs. This study concludes that EV isolation and RNA extraction pipelines govern recovered analyte integrity, necessitating careful selection of processing modality to enhance recovery of the analyte of interest.

Molecular fingerprinting of biological nanoparticles with a label-free optofluidic platform.

Label-free detecting multiple analytes in a high-throughput fashion has been one of the long-sought goals in biosensing applications. Yet, for all-optical approaches, interfacing state-of-the-art label-free techniques with microfluidics tools that can process small volumes of sample with high throughput, and with surface chemistry that grants analyte specificity, poses a critical challenge to date. Here, we introduce an optofluidic platform that brings together state-of-the-art digital holography with PDMS microfluidics by using supported lipid bilayers as a surface chemistry building block to integrate both technologies. Specifically, this platform fingerprints heterogeneous biological nanoparticle populations via a multiplexed label-free immunoaffinity assay with single particle sensitivity. Herein, we first thoroughly characterise the robustness and performance of the platform, and then apply it to profile four distinct ovarian cell-derived extracellular vesicle populations over a panel of surface protein biomarkers, thus developing a unique biomarker fingerprint for each cell line. We foresee that our approach will find many applications where routine and multiplexed characterisation of biological nanoparticles is required.

Longitudinal analysis of serum-derived extracellular vesicle RNA to monitor dacomitinib treatment response in EGFR-amplified recurrent glioblastoma patients.

Background: Glioblastoma (GBM) is a highly aggressive and invasive brain tumor associated with high patient mortality. A large fraction of GBM tumors have been identified as epidermal growth factor receptor (EGFR) amplified and ~50% also are EGFRvIII mutant positive. In a previously reported multicenter phase II study, we have described the response of recurrent GBM (rGBM) patients to dacomitinib, an EGFR tyrosine kinase inhibitor (TKI). As a continuation of that report, we leverage the tumor cargo-encapsulating extracellular vesicles (EVs) and explore their genetic composition as carriers of tumor biomarker. Methods: Serum samples were longitudinally collected from EGFR-amplified rGBM patients who clinically benefitted from dacomitinib therapy (responders) and those who did not (nonresponders), as well as from a healthy cohort of individuals. The serum EV transcriptome was evaluated to map the RNA biotype distribution and distinguish GBM disease. Results: Using long RNA sequencing, we show enriched detection of over 10 000 coding RNAs from serum EVs. The EV transcriptome yielded a unique signature that facilitates differentiation of GBM patients from healthy donors. Further analysis revealed genetic enrichment that enables stratification of responders from nonresponders prior to dacomitinib treatment as well as following administration. Conclusion: This study demonstrates that genetic composition analysis of serum EVs may aid in therapeutic stratification to identify patients with dacomitinib-responsive GBM.

The Liquid Biopsy Consortium: Challenges and opportunities for early cancer detection and monitoring.

The emerging field of liquid biopsy stands at the forefront of novel diagnostic strategies for cancer and other diseases. Liquid biopsy allows minimally invasive molecular characterization of cancers for diagnosis, patient stratification to therapy, and longitudinal monitoring. Liquid biopsy strategies include detection and monitoring of circulating tumor cells, cell-free DNA, and extracellular vesicles. In this review, we address the current understanding and the role of existing liquid-biopsy-based modalities in cancer diagnostics and monitoring. We specifically focus on the technical and clinical challenges associated with liquid biopsy and biomarker development being addressed by the Liquid Biopsy Consortium, established through the National Cancer Institute. The Liquid Biopsy Consortium has developed new methods/assays and validated existing methods/technologies to capture and characterize tumor-derived circulating cargo, as well as addressed existing challenges and provided recommendations for advancing biomarker assays.

Extrinsic and intrinsic preanalytical variables affecting liquid biopsy in cancer.

Liquid biopsy, through isolation and analysis of disease-specific analytes, has evolved as a promising tool for safe and minimally invasive diagnosis and monitoring of tumors. It also has tremendous utility as a companion diagnostic allowing detection of biomarkers in a range of cancers (lung, breast, colon, ovarian, brain). However, clinical implementation and validation remains a challenge. Among other stages of development, preanalytical variables are critical in influencing the downstream cellular and molecular analysis of different analytes. Although considerable progress has been made to address these challenges, a comprehensive assessment of the impact on diagnostic parameters and consensus on standardized and optimized protocols is still lacking. Here, we summarize and critically evaluate key variables in the preanalytical stage, including study population selection, choice of biofluid, sample handling and collection, processing, and storage. There is an unmet need to develop and implement comprehensive preanalytical guidelines on the optimal practices and methodologies.

Molecular fingerprinting of biological nanoparticles with a label-free optofluidic platform.

Label-free detecting multiple analytes in a high-throughput fashion has been one of the long-sought goals in biosensing applications. Yet, for all-optical approaches, interfacing state-of-the-art label-free techniques with microfluidics tools that can process small volumes of sample with high throughput, and with surface chemistry that grants analyte specificity, poses a critical challenge to date. Here, we introduce an optofluidic platform that brings together state-of-the-art digital holography with PDMS microfluidics by using supported lipid bilayers as a surface chemistry building block to integrate both technologies. Specifically, this platform fingerprints heterogeneous biological nanoparticle populations via a multiplexed label-free immunoaffinity assay with single particle sensitivity. Herein, we first thoroughly characterise the robustness and performance of the platform, and then apply it to profile four distinct ovarian cell-derived extracellular vesicle populations over a panel of surface protein biomarkers, thus developing a unique biomarker fingerprint for each cell line. We foresee that our approach will find many applications where routine and multiplexed characterisation of biological nanoparticles is required.

Systematic Review of Photodynamic Therapy in Gliomas.

Over the last 20 years, gliomas have made up over 89% of malignant CNS tumor cases in the American population (NIH SEER). Within this, glioblastoma is the most common subtype, comprising 57% of all glioma cases. Being highly aggressive, this deadly disease is known for its high genetic and phenotypic heterogeneity, rendering a complicated disease course. The current standard of care consists of maximally safe tumor resection concurrent with chemoradiotherapy. However, despite advances in technology and therapeutic modalities, rates of disease recurrence are still high and survivability remains low. Given the delicate nature of the tumor location, remaining margins following resection often initiate disease recurrence. Photodynamic therapy (PDT) is a therapeutic modality that, following the administration of a non-toxic photosensitizer, induces tumor-specific anti-cancer effects after localized, wavelength-specific illumination. Its effect against malignant glioma has been studied extensively over the last 30 years, in pre-clinical and clinical trials. Here, we provide a comprehensive review of the three generations of photosensitizers alongside their mechanisms of action, limitations, and future directions.

Inaugurating High-Throughput Profiling of Extracellular Vesicles for Earlier Ovarian Cancer Detection.

Detecting early cancer through liquid biopsy is challenging due to the lack of specific biomarkers for early lesions and potentially low levels of these markers. The current study systematically develops an extracellular-vesicle (EV)-based test for early detection, specifically focusing on high-grade serous ovarian carcinoma (HGSOC). The marker selection is based on emerging insights into HGSOC pathogenesis, notably that it arises from precursor lesions within the fallopian tube. This work thus establishes murine fallopian tube (mFT) cells with oncogenic mutations and performs proteomic analyses on mFT-derived EVs. The identified markers are then evaluated with an orthotopic HGSOC animal model. In serially-drawn blood of tumor-bearing mice, mFT-EV markers increase with tumor initiation, supporting their potential use in early cancer detection. A pilot clinical study (n = 51) further narrows EV markers to five candidates, EpCAM, CD24, VCAN, HE4, and TNC. The combined expression of these markers distinguishes HGSOC from non-cancer with 89% sensitivity and 93% specificity. The same markers are also effective in classifying three groups (non-cancer, early-stage HGSOC, and late-stage HGSOC). The developed approach, for the first time inaugurated in fallopian tube-derived EVs, could be a minimally invasive tool to monitor women at high risk of ovarian cancer for timely intervention.

Electrokinetically enhanced label-free plasmonic sensing for rapid detection of tumor-derived extracellular vesicles.

ANALYSIS: of rare circulating extracellular vesicles (EV) from early cancers or different types of host cells requires extremely sensitive EV sensing technologies. Nanoplasmonic EV sensing technologies have demonstrated good analytical performances, but their sensitivity is often limited by EVs' diffusion to the active sensor surface for specific target EV capture. Here, we developed an advanced plasmonic EV platform with electrokinetically enhanced yields (KeyPLEX). The KeyPLEX system effectively overcomes diffusion-limited reactions with applied electroosmosis and dielectrophoresis forces. These forces bring EVs toward the sensor surface and concentrate them in specific areas. Using the keyPLEX, we showed significant improvements in detection sensitivity by ∼100-fold, leading to the sensitive detection of rare cancer EVs from human plasma samples in 10 min. The keyPLEX system could become a valuable tool for point-of-care rapid EV analysis.

CRISPR-Enhanced Hydrogel Microparticles for Multiplexed Detection of Nucleic Acids.

CRISPR/Cas systems offer a powerful sensing mechanism to transduce sequence-specific information into amplified analytical signals. However, performing multiplexed CRISPR/Cas assays remains challenging and often requires complex approaches for multiplexed assays. Here, a hydrogel-based CRISPR/Cas12 system termed CLAMP (Cas-Loaded Annotated Micro-Particles) is described. The approach compartmentalizes the CRISPR/Cas reaction in spatially-encoded hydrogel microparticles (HMPs). Each HMP is identifiable by its face code and becomes fluorescent when target DNA is present. The assay is further streamlined by capturing HMPs inside a microfluidic device; the captured particles are then automatically recognized by a machine-learning algorithm. The CLAMP assay is fast, highly sensitive (attomolar detection limits with preamplification), and capable of multiplexing in a single-pot assay. As a proof-of-concept clinical application, CLAMP is applied to detect nucleic acid targets of human papillomavirus in cervical brushing samples.

Deep Learning Pipeline for Automated Cell Profiling from Cyclic Imaging.

Recent advances in microscopy allow scientists to generate vast amounts of biological data from a single biopsy sample. Cyclic fluorescence microscopy, in particular, enables multiple targets to be detected simultaneously. This, in turn, has deepened our understanding of tissue composition, cell-to-cell interactions, and cell signaling. Unfortunately, analysis of these datasets can be time-prohibitive due to the sheer volume of data. In this paper, we present CycloNET, a computational pipeline tailored for analyzing raw fluorescent images obtained through cyclic immunofluorescence. The automated pipeline pre-processes raw image files, quickly corrects for translation errors between imaging cycles, and leverages a pre-trained neural network to segment individual cells and generate single-cell molecular profiles. We applied CycloNET to a dataset of 22 human samples from head and neck squamous cell carcinoma patients and trained a neural network to segment immune cells. CycloNET efficiently processed a large-scale dataset (17 fields of view per cycle and 13 staining cycles per specimen) in 10 minutes, delivering insights at the single-cell resolution and facilitating the identification of rare immune cell clusters. We expect that this rapid pipeline will serve as a powerful tool to understand complex biological systems at the cellular level, with the potential to facilitate breakthroughs in areas such as developmental biology, disease pathology, and personalized medicine.

Glioblastoma-derived extracellular vesicle subpopulations following 5-aminolevulinic acid treatment bear diagnostic implications.

Liquid biopsy is a minimally invasive alternative to surgical biopsy, encompassing different analytes including extracellular vesicles (EVs), circulating tumour cells (CTCs), circulating tumour DNA (ctDNA), proteins, and metabolites. EVs are released by virtually all cells, but at a higher rate by faster cycling, malignant cells. They encapsulate cargo native to the originating cell and can thus provide a window into the tumour landscape. EVs are often analysed in bulk which hinders the analysis of rare, tumour-specific EV subpopulations from the large host EV background. Here, we fractionated EV subpopulations in vitro and in vivo and characterized their phenotype and generic cargo. We used 5-aminolevulinic acid (5-ALA) to induce release of endogenously fluorescent tumour-specific EVs (EVPpIX ). Analysis of five different subpopulations (EVPpIX , EVCD63 , EVCD9 , EVEGFR , EVCFDA ) from glioblastoma (GBM) cell lines revealed unique transcriptome profiles, with the EVPpIX transcriptome demonstrating closer alignment to tumorigenic processes over the other subpopulations. Similarly, isolation of tumour-specific EVs from GBM patient plasma showed enrichment in GBM-associated genes, when compared to bulk EVs from plasma. We propose that fractionation of EV populations facilitates detection and isolation of tumour-specific EVs for disease monitoring.

Electrochemiluminescence in paired signal electrode (ECLipse) enables modular and scalable biosensing.

Electrochemiluminescence (ECL) has an inherently low background and enables precise chemical reactions through electrical control. Here, we report an advanced ECL system, termed ECLipse (ECL in paired signal electrode). We physically separated ECL generation from target detection: These two processes were carried out in isolated chambers and coupled through an electrode. The strategy allowed us to minimize cross-chemical reactions, design electrodes for high ECL signals, and integrate multiple sensors in a chip. As a proof of concept, we implemented an eight-plex ECLipse and applied it to detect host factors in human plasma. ECLipse achieved higher signal-to-noise ratio than conventional ECL assays and was >7000-fold more sensitive than enzyme-linked immunosorbent assay. In a pilot clinical study, we could detect septic conditions by measuring host factors [i.e., interleukin-3 (IL-3), IL-6, and procalcitonin (PCT)]. ECLipse assay further revealed distinct IL-3 and IL-6 patterns in patients with severe acute respiratory syndrome coronavirus 2 infection.