Label-Free Nanosensing Platform for Breast Cancer Exosome Profiling

Surface-enhanced Raman scattering-based strategies for tumor markers detection: A review

The presence of malignant tumors poses a significant threat to people's life and well-being. As biochemical parameters indicate the occurrence and development of tumors, tumor markers play a pivotal role in early cancer detection, treatment, prognosis, efficient monitoring, and other aspects. Surface-enhanced Raman scattering (SERS) is considered a potent tool for the detection of tumor markers owing to its exceptional advantages encompassing high sensitivity, superior selectivity, rapid analysis speed, and photobleaching resistance nature. This review aims to provide a comprehensive understanding of SERS applications in the detection of tumor markers. Firstly, we introduce the SERS enhancement mechanism, classification of active substrates, and SERS detection techniques. Secondly, the latest research progress of in vitro SERS detection of different types of tumor markers in body fluids and the application of SERS imaging in biomedical imaging are highlighted in sections of the review. Finally, according to the current status of SERS detection of tumor markers, the challenges and problems of SERS in biomedical detection are discussed, and insights into future developments in SERS are offered.

Label-Free Exosome Analysis by Surface-Enhanced Raman Scattering Spectroscopy with Laser-Ablated Silver Nanoparticle Substrate

Early diagnostics of breast cancer is crucial to reduce the risk of cancer metastasis and late relapse. Exosome, which contains distinct information of its origin, can be the target object as a liquid biopsy. However, its low sensitivity and inadequate diagnostic tools interfere with the point-of-care testing (POCT) of the exosome. Recently, Surface-enhanced Raman Scattering (SERS) spectroscopy, which amplifies the Raman scattering, has been proved as a promising tool for exosome detection. However, the fabrication process of SERS probe or substrate is still inefficient and far from large-scale production. This study proposes rapid and label-free detection of breast cancer-derived exosomes by statistical analysis of SERS spectra using silver-nanoparticle-based SERS substrate fabricated by selective laser ablation and melting (SLAM). Employing silver nanowires and optimizing laser process parameters enable rapid and low-energy fabrication of SERS substrate. The functionalities including sensitivity, reproducibility, stability, and renewability are evaluated using rhodamine 6G as a probe molecule. Then, the feasibility of POCT is examined by the statistical analysis of SERS spectra of exosomes from malignant breast cancer cells and non-tumorigenic breast epithelial cells. The presented framework is anticipated to be utilized in other biomedical applications, facilitating cost-effective and large-scale production performance.

Recent progress in Surface-Enhanced Raman Spectroscopy detection of biomarkers in liquid biopsy for breast cancer

Breast cancer is the most commonly diagnosed cancer in women globally and a leading cause of cancer-related mortality. However, current detection methods, such as X-rays, ultrasound, CT scans, MRI, and mammography, have their limitations. Recently, with the advancements in precision medicine and technologies like artificial intelligence, liquid biopsy, specifically utilizing Surface-Enhanced Raman Spectroscopy (SERS), has emerged as a promising approach to detect breast cancer. Liquid biopsy, as a minimally invasive technique, can provide a temporal reflection of breast cancer occurrence and progression, along with a spatial representation of overall tumor information. SERS has been extensively employed for biomarker detection, owing to its numerous advantages such as high sensitivity, minimal sample requirements, strong multi-detection ability, and controllable background interference. This paper presents a comprehensive review of the latest research on the application of SERS in the detection of breast cancer biomarkers, including exosomes, circulating tumor cells (CTCs), miRNA, proteins and others. The aim of this review is to provide valuable insights into the potential of SERS technology for early breast cancer diagnosis.

Effective enrichment of trace exosomes for the label-free SERS detection via low-cost thermophoretic profiling

Exosome-based liquid biopsies possess great potential in monitoring cancer development However, current exosome detection biosensors require large exosome volumes, showing the weak detection sensitivity. Besides, these methods pay little attention to in situ analysis of exosomes, hence limiting the provision of more accurate clinically-relevant information. Herein, we develop an innovative label-free biosensor combining the low-cost thermophoretic enrichment method with the surface-enhanced Raman spectroscopy (SERS) detection. Based on the thermophoretic enrichment strategy, exosomes and gold nanoparticles can be enriched together into a small area with a scale of 500 μm within 10 min. The Raman signals of various exosomes derived from normal, cancerous cell lines and human serum are dynamically monitored in situ, with the limit of detection of 102-103 particles per microliter, presenting higher sensitivity compared with the similar label-free SERS detection. The spectral data set of different exosomes is applied to train for multivariate classification of cell types and to estimate how the normal exosome data resemble cancer cell exosome. The reliable classification and identification of different exosomes can be realized. The current biosensor is convenient, low-cost and requires small exosome volumes (∼3 μL), and if validated in larger cohorts may contribute to the tumor prediction and diagnosis.

Exosome, a Rising Biomarkers in Liquid Biopsy: Advances of Label-Free and Label Strategy for Diagnosis of Cancer

Cancer is commonly considered as one of the most severe diseases, posing a significant threat to human health and society due to various serious challenges. These challenges include difficulties in accurate diagnosis and a high propensity to form metastasis. Tissue biopsy remains the gold standard for diagnosing and subtyping cancer. However, concerns arise from its invasive nature and the potential risk of metastasis during these complex diagnostic procedures. Meanwhile, liquid biopsy has recently witnessed the rapid advancements with the emergence of three prominent detection biomarkers: circulating tumor cells (CTCs), circulating tumor DNA (ctDNA), and exosomes. Whereas, the very low abundance of CTCs combined with the instability of ctDNA intensify the challenges and decrease the accuracy of these two biomarkers for cancer diagnosis. While exosomes have gained widespread recognition as a promising biomarker in liquid biopsy due to their relatively low-invasive detection method, excellent biostability, rich resources, high abundance, and ability to provide valuable information about cancer. Therefore, it is crucial to systematically summarize recent advancements mainly in exosome-based detection methods for early cancer diagnosis. Specifically, this review will primarily focus on label-based and label-free strategies for detecting cancer using exosomes. We anticipate that this comprehensive analysis will enhance readers' understanding of the significance and value of exosomes in the fields of cancer diagnosis and therapy.

Nanoplasmonic Detection of EGFR Mutations Based on Extracellular Vesicle-Derived EGFR-Drug Interaction

Analysis of membrane proteins from extracellular vesicles (EVs) has emerged as an important strategy for molecular cancer diagnosis. The epidermal growth factor receptor (EGFR) is one of the most well-known oncogenic membrane proteins, particularly in non-small cell lung cancer (NSCLC), where targeted therapies using tyrosine kinase inhibitors (TKIs) are often addressed based on EGFR mutation status. Consequently, several studies aimed at analyzing oncogenic membrane proteins have been proposed for cancer diagnosis. However, conventional protein analysis still faces limitations due to the requirement for large sample quantities and extensive post-labeling processes. Here, we develop a nanoplasmonic detection method for EGFR mutations in the diagnosis of NSCLC based on interactions between EGFR loaded in EVs and TKI. Gefitinib is selected as a model TKI due to its strong signals in the surface-enhanced Raman spectroscopy (SERS) and mutation-dependent binding affinity to EGFR. We demonstrate an SERS signal attributed to gefitinib at a higher value in the EGFR exon 19 deletion, both in cells and EVs, compared to wild-type and exon 19 deletion/T790M variants. Furthermore, we observe a significantly higher gefitinib SERS signal in EGFR obtained from exon 19 deletion NSCLC patient plasma-derived EVs compared with those from wild-type and exon 19 deletion/T790M EVs. Since our approach utilizes an analysis of the SERS signal generated by the interaction between oncogenic membrane proteins within EVs and targeted drugs, its diagnostic applicability could potentially extend to other liquid biopsy methods based on EVs.

Exosomes as Novel Diagnostic Biomarkers and Therapeutic Tools in Gliomas

Exosomes constitute small extracellular vesicles that contain lipids, proteins, nucleic acids, and glycoconjugates from the secreted cells and are capable of transmitting signals between cells and coordinating cellular communication. By this means, they are ultimately involved in physiology and disease, including development, homeostasis, and immune system regulation, as well as contributing to tumor progression and neurodegenerative diseases pathology. Recent studies have shown that gliomas secrete a panel of exosomes which have been associated with cell invasion and migration, tumor immune tolerance, potential for malignant transformation, neovascularization, and resistance to treatment. Exosomes have therefore emerged as intercellular communicators, which mediate the tumor-microenvironment interactions and exosome-regulated glioma cell stemness and angiogenesis. They may induce tumor proliferation and malignancy in normal cells by carrying pro-migratory modulators from cancer cells as well as many different molecular cancer modifiers, such as oncogenic transcripts, miRNAs, mutant oncoproteins, etc., which promote the communication of cancer cells with the surrounding stromal cells and provide valuable information on the molecular profile of the existing tumor. Moreover, engineered exosomes can provide an alternative system for drug delivery and enable efficient treatment. In the present review, we discuss the latest findings regarding the role of exosomes in glioma pathogenesis, their utility in non-invasive diagnosis, and potential applications to treatment.

Machine Learning-Based Label-Free SERS Profiling of Exosomes for Accurate Fuzzy Diagnosis of Cancer and Dynamic Monitoring of Drug Therapeutic Processes

Exosomes are a class of extracellular vesicles secreted by cells, which can be used as promising noninvasive biomarkers for the early diagnosis and treatment of diseases, especially cancer. However, due to the heterogeneity of exosomes, it remains a grand challenge to distinguish accurately and reliably exosomes from clinical samples. Herein, we achieve accurate fuzzy discrimination of exosomes from human serum samples for accurate diagnosis of breast cancer and cervical cancer through machine learning-based label-free surface-enhanced Raman spectroscopy (SERS), by using "hot spot" rich 3D plasmonic AuNPs nanomembranes as substrates. Due to the existence of some weak distinguishable SERS fingerprint signals and the high sensitivity of the method, the machine learning-based SERS analysis can precisely identify three (normal and cancerous) cell lines, two of which are different types of cancer cells, without specific labeling of biomarkers. The prediction accuracy based on the machine learning algorithm was up to 91.1% for the discrimination of different cell lines (H8, HeLa, and MCF-7 cell)-derived exosomes. Our model trained with SERS spectra of cell-derived exosomes could reach 93.3% prediction accuracy for clinical samples. Furthermore, the action mechanism of the chemotherapeutic process of MCF-7 cells can be revealed by dynamic monitoring of SERS profiling of the exosomes secreted. The method would be useful for noninvasive and accurate diagnosis and postoperative assessment of cancer or other diseases in the future.

Induced ultrasensitive electrochemical biosensor for target MDA-MB-231 cell cytoplasmic protein detection based on RNA-cleavage DNAzyme catalytic reaction

Herein, we implemented RNA-cleaving DNAzymes specific for the endogenous protein of breast cancer cells (MDA-MB -231) and programmed for electrochemical detection. Thionine-modified gold nanoparticles and modified magnetic nanoparticles are attached to the two ends of the DNAzyme molecule. The prepared probe is pulled to the surface of the electrode with the help of a magnetic field, and the signal caused by the electrochemical activity of thionine is observed on the surface of the electrode. The presence of a covalent gold nanoparticle-thionine hybrid as a highly electroactive/enhanced electrochemical label ensures a strong detection signal. After addition of the enzyme activator cofactor (MDA-MB -231 cytoplasmic cell protein), it reacts with the catalytic core of the enzyme sequence in the DNAzyme molecule and triggers the cleavage reaction in the substrate sequence of the DNAzyme molecule. During this process, the gold nanoparticle-thionine labels are detached from the probe and released into the solution. Inductive removal of gold nanoparticles leads to a decrease in the current related to the reduction of thionine on the electrode surface. The results show that this biosensor can detect this protein marker in the linear range of (1.0E-06 to 1.0E+01) pg/ml, with a detection limit (1.0129E-07 pg/ml), using differential pulse voltammetry as a measuring technique. As well as, electrochemical impedance spectroscopy (EIS).

Nanomaterials for Molecular Detection and Analysis of Extracellular Vesicles

Extracellular vesicles (EVs) have emerged as a novel resource of biomarkers for cancer and certain other diseases. Probing EVs in body fluids has become of major interest in the past decade in the development of a new-generation liquid biopsy for cancer diagnosis and monitoring. However, sensitive and specific molecular detection and analysis are challenging, due to the small size of EVs, low amount of antigens on individual EVs, and the complex biofluid matrix. Nanomaterials have been widely used in the technological development of protein and nucleic acid-based EV detection and analysis, owing to the unique structure and functional properties of materials at the nanometer scale. In this review, we summarize various nanomaterial-based analytical technologies for molecular EV detection and analysis. We discuss these technologies based on the major types of nanomaterials, including plasmonic, fluorescent, magnetic, organic, carbon-based, and certain other nanostructures. For each type of nanomaterial, functional properties are briefly described, followed by the applications of the nanomaterials for EV biomarker detection, profiling, and analysis in terms of detection mechanisms.

Recent progress in surface-enhanced Raman spectroscopy-based biosensors for the detection of extracellular vesicles

Extracellular vesicles (EVs) are a type of mediator that enables intercellular communication. Moreover, EVs carry critical molecular information from parental cells, making them ideal biomarkers for clinical screening and diagnosis. Currently, several sensing technologies have been established to sensitively detect EVs. Among them, surface-enhanced Raman spectroscopy (SERS) has become a powerful analytical tool with high sensitivity and low detection limits. In this review, we first cover the biological characteristics of EVs and the principle of SERS amplification. Then, we describe the recent progress in SERS technology applied to detect EVs, including direct label-free methods and indirect labeling strategies, in which substrate fabrication and nanoprobe assembly were emphasized. Furthermore, SERS technology could also be used to characterize or monitor the behavior of programmable EVs. Finally, we discuss the prospects and issues to be addressed for the development of SERS technology for EV analysis.

Artificial Intelligent Label-Free SERS Profiling of Serum Exosomes for Breast Cancer Diagnosis and Postoperative Assessment

Breast cancer subtypes have important implications of treatment responses and clinical outcomes. Exosomes have been considered as promising biomarkers for liquid biopsies, but the utility of exosomes for accurate diagnosis of distinct breast cancer subtypes is a grand challenge due to the difficulty in uncovering the subtle compositional difference in complex clinical settings. Herein, we report an artificial intelligent surface-enhanced Raman spectroscopy (SERS) strategy for label-free spectroscopic analysis of serum exosomes, allowing for accurate diagnosis of breast cancer and assessment of surgical outcomes. Our deep learning algorithm trained with SERS spectra of cancer cell-derived exosomes is demonstrated with a 100% prediction accuracy for human patients with different breast cancer subtypes who do not undergo surgery using SERS spectra of serum exosomes. Furthermore, when combined with similarity analysis by principal component analysis, our approach is able to evaluate the surgical outcomes of breast cancer of distinct molecular subtypes.

Recent Advances in Detection for Breast-Cancer-Derived Exosomes

Breast cancer is the most common malignant tumor in women, its incidence is secret, and more than half of the patients are diagnosed in the middle and advanced stages, so it is necessary to develop simple and efficient detection methods for breast cancer diagnosis to improve the survival rate and quality of life of breast cancer patients. Exosomes are extracellular vesicles secreted by all kinds of living cells, and play an important role in the occurrence and development of breast cancer and the formation of the tumor microenvironment. Exosomes, as biomarkers, are an important part of breast cancer fluid biopsy and have become ideal targets for the early diagnosis, curative effect evaluation, and clinical treatment of breast cancer. In this paper, several traditional exosome detection methods, including differential centrifugation and immunoaffinity capture, were summarized, focusing on the latest research progress in breast cancer exosome detection. It was summarized from the aspects of optics, electrochemistry, electrochemiluminescence and other aspects. This review is expected to provide valuable guidance for exosome detection of clinical breast cancer and the establishment of more reliable, efficient, simple and innovative methods for exosome detection of breast cancer in the future.

Exosome-based strategies for diagnosis and therapy of glioma cancer

Glioblastoma belongs to the most aggressive type of cancer with a low survival rate that is characterized by the ability in forming a highly immunosuppressive tumor microenvironment. Intercellular communication are created via exosomes in the tumor microenvironment through the transport of various biomolecules. They are primarily involved in tumor growth, differentiation, metastasis, and chemotherapy or radiation resistance. Recently several studies have highlighted the critical role of tumor-derived exosomes against immune cells. According to the structural and functional properties, exosomes could be essential instruments to gain a better molecular mechanism for tumor understanding. Additionally, they are qualified as diagnostic/prognostic markers and therapeutic tools for specific targeting of invasive tumor cells such as glioblastomas. Due to the strong dependency of exosome features on the original cells and their developmental status, it is essential to review their critical modulating molecules, clinical relevance to glioma, and associated signaling pathways. This review is a non-clinical study, as the possible role of exosomes and exosomal microRNAs in glioma cancer are reported. In addition, their content to overcome cancer resistance and their potential as diagnostic biomarkers are analyzed.

Nano-Based Theranostic Platforms for Breast Cancer: A Review of Latest Advancements

Breast cancer (BC) is a highly metastatic multifactorial disease with various histological and molecular subtypes. Due to recent advancements, the mortality rate in BC has improved over the past five decades. Detection and treatment of many cancers are now possible due to the application of nanomedicine in clinical practice. Nanomedicine products such as Doxil^® and Abraxane^® have already been extensively used for BC adjuvant therapy with favorable clinical outcomes. However, these products were designed initially for generic anticancer purposes and not specifically for BC treatment. With a better understanding of the molecular biology of BC, several novel and promising nanotherapeutic strategies and devices have been developed in recent years. In this context, multi-functionalized nanostructures are becoming potential carriers for enhanced chemotherapy in BC patients. To design these nanostructures, a wide range of materials, such as proteins, lipids, polymers, and hybrid materials, can be used and tailored for specific purposes against BC. Selective targeting of BC cells results in the activation of programmed cell death in BC cells and can be considered a promising strategy for managing triple-negative BC. Currently, conventional BC screening methods such as mammography, digital breast tomosynthesis (DBT), ultrasonography, and magnetic resonance imaging (MRI) are either costly or expose the user to hazardous radiation that could harm them. Therefore, there is a need for such analytical techniques for detecting BC that are highly selective and sensitive, have a very low detection limit, are durable, biocompatible, and reproducible. In detecting BC biomarkers, nanostructures are used alone or in conjunction with numerous molecules. This review intends to highlight the recent advances in nanomedicine in BC treatment and diagnosis, emphasizing the targeting of BC cells that overexpress receptors of epidermal growth factors. Researchers may gain insight from these strategies to design and develop more tailored nanomedicine for BC to achieve further improvements in cancer specificity, antitumorigenic effects, anti-metastasis effects, and drug resistance reversal effects.

Defining Optimal Conditions for Tumor Extracellular Vesicle DNA Extraction for Mutation Profiling

(1) Background: Extracellular vesicles (EVs) have emerged as crucial players in the communication between cells in both physiological and pathological scenarios. The functions of EVs are strongly determined by their molecular content, which includes all bioactive molecules, such as proteins, lipids, RNA, and, as more recently described, double-stranded DNA. It has been shown that in oncological settings DNA associated with EVs (EV-DNA) is representative of the genome of parental cells and that it reflects the mutational status of the tumor, gaining much attention as a promising source of biomarker mutant DNA. However, one of the challenges in studies of EV-DNA is the lack of standardization of protocols for the DNA extraction from EVs, as well as ways to assess quality control, which hinders its future implementation in clinics. (2) Methods: We performed a comprehensive comparison of commonly used approaches for EV-DNA extraction by assessing DNA quantity, quality, and suitability for downstream analyses. (3) Results: We here established strategic points to consider for EV-DNA preparation for mutational analyses, including qPCR and NGS. (4) Conclusions: We put in place a workflow that can be applied for the detection of clinically relevant mutations in the EV-DNA of cancer patients.

Classification of Preeclamptic Placental Extracellular Vesicles Using Femtosecond Laser Fabricated Nanoplasmonic Sensors

Placental extracellular vesicles (EVs) play an essential role in pregnancy by protecting and transporting diverse biomolecules that aid in fetomaternal communication. However, in preeclampsia, they have also been implicated in contributing to disease progression. Despite their potential clinical value, current technologies cannot provide a rapid and effective means of differentiating between healthy and diseased placental EVs. To address this, a fabrication process called laser-induced nanostructuring of SERS-active thin films (LINST) was developed to produce scalable nanoplasmonic substrates that provide exceptional Raman signal enhancement and allow the biochemical fingerprinting of EVs. After validating the performance of LINST substrates with chemical standards, placental EVs from tissue explant cultures were characterized, demonstrating that preeclamptic and normotensive placental EVs have classifiably distinct Raman spectra following the application of advanced machine learning algorithms. Given the abundance of placental EVs in maternal circulation, these findings encourage immediate exploration of surface-enhanced Raman spectroscopy (SERS) of EVs as a promising method for preeclampsia liquid biopsies, while this novel fabrication process will provide a versatile and scalable substrate for many other SERS applications.

Exosome detection via surface-enhanced Raman spectroscopy for cancer diagnosis

As nanoscale extracellular vesicles, exosomes are secreted by various cell types, and they are widely distributed in multiple biological fluids. Studies have shown that tumor-derived exosomes can carry a variety of primary tumor-specific molecules, which may represent a novel tool for the early detection of cancer. However, the clinical translation of exosomes remains a challenge due to the requirement of large quantities of samples when enriching the cancer-related exosomes in biological fluids, the insufficiency of traditional techniques for exosome subpopulations, and the complex exosome isolation of the current commercially available exosome phenotype profiling approaches. The evolving surface-enhanced Raman scattering (SERS) technology, with properties of unique optoelectronics, easy functionalization, and the particular interaction between light and nanoscale metallic materials, can achieve sensitive detection of exosomes without large quantities of samples and multiplexed phenotype profiling, providing a new mode of real-time and noninvasive analysis for cancer patients. In the present review, we mainly discussed exosome detection based on SERS, especially SERS immunoassay. The basic structure and function of exosomes were firstly introduced. Then, recent studies using the SERS technique for cancer detection were critically reviewed, which mainly included various SERS substrates, biological modification of SERS substrates, SERS-based exosome detection, and the combination of SERS and other technologies for cancer diagnosis. This review systematically discussed the essential aspects, limitations, and considerations of applying SERS technology in the detection and analysis of cancer-derived exosomes, which could provide a valuable reference for the early diagnosis of cancer through SERS technology. STATEMENT OF SIGNIFICANCE: Surface-enhanced Raman scattering (SERS) has been applied to exosomes detection to obtain better diagnostic results. In past three years, several reviews have been published in exosome detection, which were narrowly focus on methods of exosome detection. Selection and surface functionalization of the substrate and the combination detection with different methods based on SERS will provide new strategies for the detection of exosomes. This review will focus on the above aspects. This emerging detection method is constantly evolving and contributing to the early discovery of diseases in the future.

Surface enhanced Raman scattering for probing cellular biochemistry

Surface enhanced Raman scattering (SERS) from biomolecules in living cells enables the sensitive, but also very selective, probing of their biochemical composition. This minireview discusses the developments of SERS probing in cells over the past years from the proof-of-principle to observe a biochemical status to the characterization of molecule-nanostructure and molecule-molecule interactions and cellular processes that involve a wide variety of biomolecules and cellular compartments. Progress in applying SERS as a bioanalytical tool in living cells, to gain a better understanding of cellular physiology and to harness the selectivity of SERS, has been achieved by a combination of live cell SERS with several different approaches. They range from organelle targeting, spectroscopy of relevant molecular models, and the optimization of plasmonic nanostructures to the application of machine learning and help us to unify the information from defined biomolecules and from the cell as an extremely complex system.

Single Particle Automated Raman Trapping Analysis of Breast Cancer Cell-Derived Extracellular Vesicles as Cancer Biomarkers

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.

Characterization of ovarian cancer-derived extracellular vesicles by surface-enhanced Raman spectroscopy

Ovarian cancer is the most lethal gynecological malignancy, owing to the fact that most cases are diagnosed at a late stage. To improve prognosis and reduce mortality, we must develop methods for the early diagnosis of ovarian cancer. A step towards early and non-invasive cancer diagnosis is through the utilization of extracellular vesicles (EVs), which are nanoscale, membrane-bound vesicles that contain proteins and genetic material reflective of their parent cell. Thus, EVs secreted by cancer cells can be thought of as cancer biomarkers. In this paper, we present gold nanohole arrays for the capture of ovarian cancer (OvCa)-derived EVs and their characterization by surface-enhanced Raman spectroscopy (SERS). For the first time, we have characterized EVs isolated from two established OvCa cell lines (OV-90, OVCAR3), two primary OvCa cell lines (EOC6, EOC18), and one human immortalized ovarian surface epithelial cell line (hIOSE) by SERS. We subsequently determined their main compositional differences by principal component analysis and were able to discriminate the groups by a logistic regression-based machine learning method with ∼99% accuracy, sensitivity, and specificity. The results presented here are a great step towards quick, facile, and non-invasive cancer diagnosis.

Paper-Based Biosensors for COVID-19: A Review of Innovative Tools for Controlling the Pandemic

The appearance and quick spread of the new severe acute respiratory syndrome coronavirus disease, COVID-19, brought major societal challenges. Importantly, suitable medical diagnosis procedures and smooth clinical management of the disease are an emergent need, which must be anchored on novel diagnostic methods and devices. Novel molecular diagnostic tools relying on nucleic acid amplification testing have emerged globally and are the current gold standard in COVID-19 diagnosis. However, the need for widespread testing methodologies for fast, effective testing in multiple epidemiological scenarios remains a crucial step in the fight against the COVID-19 pandemic. Biosensors have previously shown the potential for cost-effective and accessible diagnostics, finding applications in settings where conventional, laboratorial techniques may not be readily employed. Paper- and cellulose-based biosensors can be particularly relevant in pandemic times, for the renewability, possibility of mass production with sustainable methodologies, and safe environmental disposal. In this review, paper-based devices and platforms targeting SARS-CoV-2 are showcased and discussed, as a means to achieve quick and low-cost PoC diagnosis, including detection methodologies for viral genomic material, viral antigen detection, and serological antibody testing. Devices targeting inflammatory markers relevant for COVID-19 are also discussed, as fast, reliable bedside diagnostic tools for patient treatment and follow-up.

Advanced Nanotechnologies for Extracellular Vesicle-Based Liquid Biopsy

Extracellular vesicles (EVs) are emerging as a new source of biomarkers in liquid biopsy because of their wide presence in most body fluids and their ability to load cargoes from disease-related cells. Owing to the crucial role of EVs in disease diagnosis and treatment, significant efforts have been made to isolate, detect, and analyze EVs with high efficiency. A recent overview of advanced EV detection nanotechnologies is discussed here. First, several key challenges in EV-based liquid biopsies are introduced. Then, the related pivotal advances in nanotechnologies for EV isolation based on physical features, chemical affinity, and the combination of nanostructures and chemical affinity are summarized. Next, a summary of high-sensitivity sensors for EV detection and advanced approaches for single EV detection are provided. Later, EV analysis is introduced in practical clinical scenarios, and the application of machine learning in this field is highlighted. Finally, future opportunities for the development of next-generation nanotechnologies for EV detection are presented.

Recent Progress in Detection and Profiling of Cancer Cell-Derived Exosomes

Exosomes, known as nanometer-sized vesicles (30-200 nm), are secreted by many types of cells. Cancer-derived exosomes have great potential to be biomarkers for early clinical diagnosis and evaluation of cancer therapeutic efficacy. Conventional detection methods are limited to low sensitivity and reproducibility. There are hundreds of papers published with different detection methods in recent years to address these challenges. Therefore, in this review, pioneering researches about various detection strategies are comprehensively summarized and the analytical performance of these tests is evaluated. Furthermore, the exosome molecular composition (protein and nucleic acid) profiling, a single exosome profiling, and their application in clinical cancer diagnosis are reviewed. Finally, the principles and applications of machine learning method in exosomes researches are presented.

Thermoconformational Behavior of Cellulose Nanofiber Films as a Device Substrate and Their Superior Flexibility and Durability to Glass

The design and high-throughput manufacturing of thin renewable energy devices with high structural and atomic configurational stability are crucial for the fabrication of green electronics. Yet, this concept is still in its infancy. In this work, we report the extraordinary durability of thin molecular interlayered organic flexible energy devices based on chemically tuned cellulose nanofiber transparent films that outperform glass by decreasing the substrate weight by 50%. The nanofabricated flexible thin film has an exceptionally low thermal coefficient of expansion of 1.8 ppm/K and a stable atomic configuration under a harsh fabrication condition (over 190 °C for an extended period of 5 h). A flexible optoelectronic device using the same renewable cellulose nanofiber film substrate was found to be functionally operational over a life span of 5 years under an intermittent operating condition. The success of this device's stability opens up an entirely new frontier of applications of flexible electronics.

Space curvature-inspired nanoplasmonic sensor for breast cancer extracellular vesicle fingerprinting and machine learning classification

Extracellular vesicles (EVs) are micro and nanoscale lipid-enclosed packages that have shown potential as liquid biopsy targets for cancer because their structure and contents reflect their cell of origin. However, progress towards the clinical applications of EVs has been hindered due to the low abundance of disease-specific EVs compared to EVs from healthy cells; such applications thus require highly sensitive and adaptable characterization tools. To address this obstacle, we designed and fabricated a novel space curvature-inspired surfaced-enhanced Raman spectroscopy (SERS) substrate and tested its capabilities using bioreactor-produced and size exclusion chromatography-purified breast cancer EVs of three different subtypes. Our findings demonstrate the platform's ability to effectively fingerprint and efficiently classify, for the first time, three distinct subtypes of breast cancer EVs following the application of machine learning algorithms on the acquired spectra. This platform and characterization approach will enhance the viability of EVs and nanoplasmonic sensors towards clinical utility for breast cancer and many other applications to improve human health.

Emerging Diagnostic Potential of Tumor-derived Exosomes

Exosomes carry genetic information originating from their parental cells, raising their possibility as novel noninvasive biomarkers for cancer. Tumor-derived exosomes (TEXs) have a variety of endogenous cargos that reflect the pathophysiology status and information of tumor cells. TEXs are increasingly being recognized as potential biomarkers for cancer diagnosis prognosis, and monitoring. It is important to develop a variety of sensitive methods, including probes and biomaterials to isolate exosomes. A variety of approaches for detecting exosomes have been established. By combining exosome DNA and RNA sequencing tools, exosome proteomics analysis and immunoassay technology, it is expected that exosomes will gain widespread use in the diagnosis and treatment of cancer.

Surface-Enhanced Raman Scattering (SERS) Spectroscopy for Sensing and Characterization of Exosomes in Cancer Diagnosis

Simple Summary

The distinct molecular and biological properties of exosomes, together with their abundance and stability, make them an ideal target in liquid biopsies for early diagnosis and disease monitoring. On the other hand, in recent years, nanomaterial-based optical biosensors have been extensively investigated as novel, rapid and sensitive tools for exosome detection and discrimination. The scope of this review is to summarize and coherently discussed the diverse applications, challenges and limitations of nanosensors based on surface-enhanced Raman spectroscopy (SERS) as the optosensing technique.

Abstract

Exosomes are emerging as one of the most intriguing cancer biomarkers in modern oncology for early cancer diagnosis, prognosis and treatment monitoring. Concurrently, several nanoplasmonic methods have been applied and developed to tackle the challenging task of enabling the rapid, sensitive, affordable analysis of exosomes. In this review, we specifically focus our attention on the application of plasmonic devices exploiting surface-enhanced Raman spectroscopy (SERS) as the optosensing technique for the structural interrogation and characterization of the heterogeneous nature of exosomes. We summarized the current state-of-art of this field while illustrating the main strategic approaches and discuss their advantages and limitations.

Microbubbles versus Extracellular Vesicles as Therapeutic Cargo for Targeting Drug Delivery

Extracellular vesicles (EVs) and microbubbles are nanoparticles in drug-delivery systems that are both considered important for clinical translation. Current research has found that both microbubbles and EVs have the potential to be utilized as drug-delivery agents for therapeutic targets in various diseases. In combination with EVs, microbubbles are capable of delivering chemotherapeutic drugs to tumor sites and neighboring sites of damaged tissues. However, there are no standards to evaluate or to compare the benefits of EVs (natural carrier) versus microbubbles (synthetic carrier) as drug carriers. Both drug carriers are being investigated for release patterns and for pharmacokinetics; however, few researchers have focused on their targeted delivery or efficacy. In this Perspective, we compare EVs and microbubbles for a better understanding of their utility in terms of delivering drugs to their site of action and future clinical translation.

Positively charged gold-silver nanostar enabled molecular characterization of cancer associated extracellular vesicles

Direct surface-enhanced Raman scattering (SERS) has contributed to characterizing extracellular vesicles (EVs) by providing molecular signatures. However, little work has been carried out to understand the heterogeneity of EVs created by different methods or from different biological sources. Herein, we pioneered the use of positively charged gold-silver nanostars to explore the SERS profiles of different EVs. The physical features of EVs from cancer cells including the size, concentration, morphology and surface potential have been characterized via nanoparticle tracking analysis, transmission electron microscopy and zeta potential analysis. The results show that negatively charged EVs are attracted to positively charged gold-silver nanostar surfaces via electrostatic forces resulting in SERS spectra showing characteristic vibrational modes of the different components of EVs (i.e. proteins, lipids and nucleic acids). SERS data were complemented by other spectroscopic techniques including atomic force microscopy-infrared spectroscopy, UV-visible absorbance spectroscopy and fluorescence spectroscopy providing a more complete molecular picture of EVs. SERS signatures of EVs from different origins, batches, and isolation approaches were compared and analyzed. A statistical method (principal component analysis-linear discriminant analysis) was utilized to differentiate EV subtypes. Consequently, a desirable discrimination outcome for blind samples was obtained. This study provides novel insights to deepen our understanding of EV heterogeneity.

Transcriptome Reprogramming of CD11b+ Bone Marrow Cells by Pancreatic Cancer Extracellular Vesicles

Pancreatic cancers (PC) are highly metastatic with poor prognosis, mainly due to delayed detection. We previously showed that PC-derived extracellular vesicles (EVs) act on macrophages residing in the liver, eliciting extracellular matrix remodeling in this organ and marked hepatic accumulation of CD11b+ bone marrow (BM) cells, which support PC liver metastasis. We here show that PC-EVs also bind to CD11b+ BM cells and induce the expansion of this cell population. Transcriptomic characterization of these cells shows that PC-EVs upregulate IgG and IgA genes, which have been linked to the presence of monocytes/macrophages in tumor microenvironments. We also report here the transcriptional downregulation of genes linked to monocyte/macrophage activation, trafficking, and expression of inflammatory molecules. Together, these results show for the first time the existence of a PC-BM communication axis mediated by EVs with a potential role in PC tumor microenvironments.

Plasmonic Sensors for Extracellular Vesicle Analysis: From Scientific Development to Translational Research

Extracellular vesicles (EVs), actively shed from a variety of neoplastic and host cells, are abundant in blood and carry molecular markers from parental cells. For these reasons, EVs have gained much interest as biomarkers of disease. Among a number of different analytical methods that have been developed, surface plasmon resonance (SPR) stands out as one of the ideal techniques given its sensitivity, robustness, and ability to miniaturize. In this Review, we compare different SPR platforms for EV analysis, including conventional SPR, nanoplasmonic sensors, surface-enhanced Raman spectroscopy, and plasmonic-enhanced fluorescence. We discuss different surface chemistries used to capture targeted EVs and molecularly profile their proteins and RNAs. We also highlight these plasmonic platforms' clinical applications, including cancers, neurodegenerative diseases, and cardiovascular diseases. Finally, we discuss the future perspective of plasmonic sensing for EVs and their potentials for commercialization and clinical translation.

Extracellular Vesicle Identification Using Label-Free Surface-Enhanced Raman Spectroscopy: Detection and Signal Analysis Strategies

Extracellular vesicles (EVs) have been widely investigated as promising biomarkers for the liquid biopsy of diseases, owing to their countless roles in biological systems. Furthermore, with the notable progress of exosome research, the use of label-free surface-enhanced Raman spectroscopy (SERS) to identify and distinguish disease-related EVs has emerged. Even in the absence of specific markers for disease-related EVs, label-free SERS enables the identification of unique patterns of disease-related EVs through their molecular fingerprints. In this review, we describe label-free SERS approaches for disease-related EV pattern identification in terms of substrate design and signal analysis strategies. We first describe the general characteristics of EVs and their SERS signals. We then present recent works on applied plasmonic nanostructures to sensitively detect EVs and notable methods to interpret complex spectral data. This review also discusses current challenges and future prospects of label-free SERS-based disease-related EV pattern identification.

Applications of surface-enhanced Raman spectroscopy in detection fields

Surface-enhanced Raman spectroscopy (SERS) is a Raman spectroscopy technique that has been widely used in food safety, environmental monitoring, medical diagnosis and treatment and drug monitoring because of its high selectivity, sensitivity, rapidness, simplicity and specificity in identifying molecular structures. This review introduces the detection mechanism of SERS and summarizes the most recent progress concerning the use of SERS for the detection and characterization of molecules, providing references for the later research of SERS in detection fields.

Molecular-Imprinting-Based Surface-Enhanced Raman Scattering Sensors

Molecularly imprinted polymers (MIPs) receive extensive interest, owing to their structure predictability, recognition specificity, and application universality as well as robustness, simplicity, and inexpensiveness. Surface-enhanced Raman scattering (SERS) is regarded as an ideal optical detection candidate for its unique features of fingerprint recognition, nondestructive property, high sensitivity, and rapidity. Accordingly, MIP based SERS (MIP-SERS) sensors have attracted significant research interest for versatile applications especially in the field of chemo- and bioanalysis, showing excellent identification and detection performances. Herein, we comprehensively review the recent advances in MIP-SERS sensors construction and applications, including sensing principles and signal enhancement mechanisms, focusing on novel construction strategies and representative applications. First, the basic structure of the MIP-SERS sensors is briefly outlined. Second, novel imprinting strategies are highlighted, mainly including multifunctional monomer imprinting, dummy template imprinting, living/controlled radical polymerization, and stimuli-responsive imprinting. Third, typical application of MIP-SERS sensors in chemo/bioanalysis is summarized from both small and macromolecular aspects. Lastly, the challenges and perspectives of the MIP-SERS sensors are proposed, orienting sensitivity improvement and application expanding.