Metabolomic analysis of exosomal-markers in esophageal squamous cell carcinoma

Rapid screening of esophageal squamous cell carcinoma by near-infrared spectroscopy combined with aquaphotomics

Esophageal cancer (EC), the fifth most common cause of cancer-related mortality in China, poses a significant threat to public health. Among the pathological types, esophageal squamous cell carcinoma (ESCC) is predominant, comprising approximately 90 % of cases. Screening is crucial for early detection, diagnosis and treatment, thereby reducing ESCC mortality. This study aimed to develop a rapid, accurate, and cost-effective method based on near-infrared (NIR) spectroscopy combined with aquaphotomics for ESCC screening. NIR spectra were obtained from plasma samples of both healthy controls and ESCC patients. Subsequently, principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) were utilized to identify the water matrix coordinates (WAMACS), thereby delineating the water absorption spectrum pattern (WASP) and constructing an aquagram. The results showed that the PLS-DA screening test model demonstrated high accuracy and precision rates of 95.12 % and 97.10 %, respectively, along with sensitivity and specificity rates of 97.10 % and 84.62 %. The area under the curve (AUC) achieved 0.9064. Aquaphotomic analysis revealed that the WASP of the healthy group predominantly exhibited strong absorption in regions indicative of strong hydrogen bonds (1460 nm, 1480 nm, 1494 nm), while the WASP of the ESCC group showed strong absorption in regions associated with strong hydrogen bonds, weak hydrogen bonds and free water, especially the regions of weak hydrogen bonds (1434 nm) and free water (1390 nm) were significantly different from those of the healthy group. The findings indicated that the rapid screening model for ESCC, integrating NIR spectroscopy with aquaphotomics, is both effective and feasible, with the WASP presenting as a potentially valuable biomarker for ESCC screening.

Machine Learning-Based Identification of Novel Exosome-Derived Metabolic Biomarkers for the Diagnosis of Systemic Lupus Erythematosus and Differentiation of Renal Involvement

OBJECTIVE

This study aims to investigate the exosome-derived metabolomics profiles in systemic lupus erythematosus (SLE), identify differential metabolites, and analyze their potential as diagnostic markers for SLE and lupus nephritis (LN).

METHODS

Totally, 91 participants were enrolled between February 2023 and January 2024 including 58 SLE patients [30 with nonrenal-SLE and 28 with Lupus nephritis (LN)] and 33 healthy controls (HC). Ultracentrifugation was used to isolate serum exosomes, which were analyzed for their metabolic profiles using liquid chromatography-tandem mass spectrometry (LC-MS/MS). Endogenous metabolites were identified via public metabolite databases. Random Forest, Lasso regression and Support Vector Machine Recursive Feature Elimination (SVM-RFE) algorithms were employed to screen key metabolites, and a prediction model was constructed for SLE diagnosis and LN discrimination. ROC curves were constructed to determine the potential of these differential exosome-derived metabolites for the diagnosis of SLE. Furthermore, Spearman's correlation was employed to evaluate the potential links between exosome-derived metabolites and the clinical parameters which reflect disease progression.

RESULTS

A total of 586 endogenous serum exosome-derived metabolites showed differential expression, with 225 exosome-derived metabolites significantly upregulated, 88 downregulated and 273 exhibiting no notable changes in the HC and SLE groups. Machine learning algorithms revealed three differential metabolites: Pro-Asn-Gln-Met-Ser, C24:1 sphingolipid, and protoporphyrin IX, which exhibited AUC values of 0.998, 0.992 and 0.969 respectively, for distinguishing between the SLE and HC groups, with a combined AUC of 1.0. In distinguishing between the LN and SLE groups, the AUC values for these metabolites were 0.920, 0.893 and 0.865, respectively, with a combined AUC of 0.931, demonstrating excellent diagnostic performance. Spearman correlation analysis revealed that Pro-Asn-Gln-Met-Ser and protoporphyrin IX were positively correlated with the SLE Disease Activity Index (SLEDAI) scores, urinary protein/creatinine ratio (ACR) and urinary protein levels, while C24:1 sphingolipid exhibited a negative correlation.

CONCLUSIONS

This study provides the first comprehensive characterization of the exosome-derived metabolites in SLE and established a promising prediction model for SLE and LN discrimination. The correlation between exosome-derived metabolites and key clinical parameters strongly indicated their potential role in SLE pathological progression.

Ultrasensitive Detection of Extracellular Vesicles Based on Metal-Organic Framework DNA Biobarcodes Triggered G-Quadruplex Coupled with Rolling Circle Amplification Assay

Extracellular vesicles (EVs), as liquid biopsy markers for accurate tumor diagnosis, are considered to hold great promise. However, effectively isolating and sensitively detecting EVs with convenience still face challenges. Herein, we propose a highly sensitive and specific platform for EV detection by integrating a metal-organic framework (MOF)-based DNA biobarcodes strategy with a rolling circle amplification (RCA)/G-quadruplex system. In this study, first, Zr-MOFs act as signal converters by comodification with DNA barcodes and antibodies, converting and amplifying the abundance of EVs into DNA barcodes. Second, the released DNA can trigger RCA, followed by G-quadruplex formation to further amplify the signal. Consequently, this approach significantly enhances the sensitivity for EV biomarker detection, achieving a low limit of detection of 100 EVs mL-1. Furthermore, the strategy offers high sensitivity, specificity, accuracy, and simplicity, highlighting its potential for clinical applications in noninvasive EV detection.

Spermine accumulation via spermine synthase promotes tumor cell proliferation in head and neck squamous cell carcinoma

BACKGROUND

Head and neck squamous cell carcinoma (HNSCC) is among the most aggressive malignancies, underscoring the need for early diagnosis to improve patient outcomes. Tumor-derived exosomes, which can be non-invasively obtained and reflect the metabolic state of tumors in real-time, are under increasing investigation for their diagnostic potential. Herein we analyzed metabolite differences in exosomes, serum, and tissues from patients with HNSCC to identify potential diagnostic biomarkers of clinical relevance.

METHODS

Non-targeted metabolomics based on liquid chromatography-mass spectrometry was employed to quantify metabolites in exosome, serum, and tissue samples from 11 patients with HNSCC and six patients without cancer. The metabolic profiles of HNSCC were analyzed through univariate and multivariate statistical methods, differential metabolite analysis, and pathway enrichment analysis.

RESULTS

We identified three differential metabolites in exosomes, 45 in serum, and 33 in tissues. Notably, patients with HNSCC exhibited significant disruptions in protein and amino acid metabolism. Spermine was exclusively detected in exosomes and tissues from patients with HNSCC. We hypothesize that spermine is extracellularly secreted by malignant cells via exosomes and subsequently enters the bloodstream. Moreover, spermine synthase was highly expressed in HNSCC tissues. Knocking down spermine synthase markedly impaired HNSCC cell proliferation and migration.

CONCLUSIONS

This study provides a preliminarily characterization of the metabolic profile of HNSCC and highlights spermine and its synthetic pathways as potential diagnostic and therapeutic targets. Future studies are warranted to elucidate the mechanism of action of spermine in HNSCC and explore its utility in early diagnosis and therapeutic development.

Current status and perspectives of esophageal cancer: a comprehensive review

Esophageal cancer (EC) continues to be a significant global health concern, with two main subtypes: esophageal squamous cell carcinoma and esophageal adenocarcinoma. Prevention and changes in etiology, improvements in early detection, and refinements in the treatment have led to remarkable progress in the outcomes of EC patients in the past two decades. This seminar provides an in-depth analysis of advances in the epidemiology, disease biology, screening, diagnosis, and treatment landscape of esophageal cancer, focusing on the ongoing debate surrounding multimodality therapy. Despite significant advancements, EC remains a deadly disease, underscoring the need for continued research into early detection methods, understanding the molecular mechanisms, and developing effective treatments.

Exosome-Derived Cargos in Immune Microenvironment in Esophageal Carcinoma: A Mini-Review

Esophageal carcinoma, a lethal malignancy with limited treatment options and poor prognosis, necessitates understanding its underlying mechanisms and identifying novel therapeutic targets. Recent studies have highlighted the critical role of the immune microenvironment in esophageal carcinoma, particularly the interplay between tumor cells and immune cells mediated by exosomes and their cargos. Exosomes, small extracellular vesicles secreted by various cells, including tumor cells, facilitate intercellular communication by transferring bioactive molecules such as proteins, nucleic acids, and lipids to recipient cells. In the context of esophageal carcinoma, tumor-derived exosomes have been shown to play a significant role in shaping the immune microenvironment. In esophageal carcinoma, exosomal cargos have been found to modulate immune cell function and impact tumor progression. These cargos can carry immune inhibitory molecules, such as programmed death-ligand 1 (PD-L1), to suppress T-cell activity and promote immune evasion by tumor cells. Furthermore, exosomal cargos can activate antigen- presenting cells, enhancing their ability to present tumor-specific antigens to T cells and thereby promoting anti-tumor immune responses. Additionally, the cargos of exosomes have been implicated in the induction of immune regulatory T cells (Tregs) and myeloid-derived suppressor cells (MDSCs) within the esophageal carcinoma microenvironment. These immunosuppressive effectors inhibit the activity of T cells, contributing to tumor immune evasion and resistance to immune therapies. In summary, exosomes and their cargo play a crucial role in the immune microenvironment of esophageal carcinoma. Understanding the mechanisms by which exosomal cargos regulate immune cell function and tumor progression may reveal novel therapeutic targets for this devastating disease.

Metabolic landscaping of extracellular vesicles from body fluids by phosphatidylserine imprinted polymer enrichment and mass spectrometry analysis

Extracellular vesicles (EVs) are emerging as new source of biomarkers discovery in liquid biopsy due to their stabilization in body fluids, protected by phospholipid bilayers. However, the metabolomics study of EVs is very little reported due to the lack of efficient and high-throughput isolation methods for clinical samples. In this study, phosphatidylserine imprinted polymers were employed for rapid and efficient EVs isolation from five human body fluids, including plasma, urine, amniotic fluid, cerebrospinal fluid, and saliva. The isolated EVs were subsequently analyzed for metabolomic studies by high-resolution mass spectrometry. Metabolic landscaping was conducted between the body fluids and their EVs, indicating EVs contain a large number of metabolites that are completely specific to the body fluid source. Finally, quantitative metabolomic analysis of EVs was carried out with plasma samples of hepatocellular carcinoma. Several differentially expressed exosomal metabolites were revealed including the upregulation of sphingosine (d18:1), taurochenodeoxycholic acid (TCDCA), pipecolic acid (PA), and 4-hydroxynonenal (4-HNE) and down-regulation of piperine, caffeine, and indole. We believe the proposed methodology will provide a deeper understanding of the molecular composition and functions of EVs as an alternative source for biomarker discovery.

The role of macrophage-derived exosomes in noncancer liver diseases: From intercellular crosstalk to clinical potential

Chronic liver disease has a substantial global prevalence and mortality rate. Macrophages, pivotal cells in innate immunity, exhibit remarkable heterogeneity and plasticity and play a considerable role in maintaining organ homeostasis, modulating inflammatory responses, and influencing disease progression in the liver. Exosomes, which can serve as conduits for intercellular communication, biomarkers, and therapeutic targets for a spectrum of diseases, have recently garnered increasing attention recently. Given that the liver is the organ with the highest macrophage content, a thorough understanding of the influence of macrophage-derived exosomes (MDEs) on noncancer liver disease pathogenesis and their potential therapeutic applications is paramount. Interactions among MDEs, hepatocytes, hepatic stellate cells (HSCs), and other nonparenchymal cells constitute a complex network regulates liver immune homeostasis. In this review, we summarize the latest progress in the current understanding of MDE heterogeneity and cellular crosstalk in noncancer liver diseases, as well as their potential clinical applications. Additionally, challenges and future directions are underscored.

Exosomes in esophageal cancer: a promising frontier for liquid biopsy in diagnosis and therapeutic monitoring

Esophageal cancer is a common and lethal digestive system malignancy, and both treatment efficacy and patient survival rates face significant challenges. In recent years, exosomes have emerged as crucial mediators of intercellular communication, demonstrating tremendous clinical potential, particularly in the diagnosis, treatment, and prognostic evaluation of esophageal cancer. These exosomes not only serve as biomarkers for early diagnosis and prognosis but also modulate tumor growth, metastasis, and drug resistance by delivering bioactive molecules. Importantly, exosomes can act as carriers for esophageal cancer-related therapeutic agents, optimizing gene therapy strategies to enhance efficacy while reducing toxicity and side effects. Despite facing challenges in clinical applications such as purification, enrichment, and standardization of analytical methods, exosomes maintain broad prospects for application in esophageal cancer treatment, with the potential to significantly improve patient outcomes and quality of life. This review focuses on the innovative role of exosomes in the early diagnosis of esophageal cancer, exploring their application value and safety in disease monitoring and assessment of treatment response. Furthermore, this study outlines the challenges and limitations of transitioning exosome research from basic studies to clinical applications, as well as potential solutions and future research directions to address these obstacles.

Extracellular vesicles in cancers: mechanisms, biomarkers, and therapeutic strategies

Extracellular vesicles (EVs) composed of various biologically active constituents, such as proteins, nucleic acids, lipids, and metabolites, have emerged as a noteworthy mode of intercellular communication. There are several categories of EVs, including exosomes, microvesicles, and apoptotic bodies, which largely differ in their mechanisms of formation and secretion. The amount of evidence indicated that changes in the EV quantity and composition play a role in multiple aspects of cancer development, such as the transfer of oncogenic signals, angiogenesis, metabolism remodeling, and immunosuppressive effects. As EV isolation technology and characteristics recognition improve, EVs are becoming more commonly used in the early diagnosis and evaluation of treatment effectiveness for cancers. Actually, EVs have sparked clinical interest in their potential use as delivery vehicles or vaccines for innovative antitumor techniques. This review will focus on the function of biological molecules contained in EVs linked to cancer progression and their participation in the intricate interrelationship within the tumor microenvironment. Furthermore, the potential efficacy of an EV-based liquid biopsy and delivery cargo for treatment will be explored. Finally, we explicitly delineate the limitations of EV-based anticancer therapies and provide an overview of the clinical trials aimed at improving EV development.

Exosomes in esophageal cancer: function and therapeutic prospects

Esophageal cancer (EC) is one of the most common malignant tumors worldwide. Exosomes are a type of extracellular vesicles produced by eukaryotic cells and present in all body fluids. Recent studies have revealed that exosomes can be used as a tool for cell signaling and have great potential in cancer diagnosis and treatment strategies. This article reviews the research progress of exosomes in EC in recent years, mainly including the mechanism of action, diagnostic markers, therapeutic targets, and drug carriers. The challenges faced are discussed to provide guidelines for further research in future.

The Role of Fatty Acid Metabolism, the Related Potential Biomarkers, and Targeted Therapeutic Strategies in Gastrointestinal Cancers

Gastrointestinal cancer has emerged as a significant global health concern due to its high incidence and mortality, limited effectiveness of early detection, suboptimal treatment outcomes, and poor prognosis. Metabolic reprogramming is a prominent feature of cancer, and fatty acid metabolism assumes a pivotal role in bridging glucose metabolism and lipid metabolism. Fatty acids play important roles in cellular structural composition, energy supply, signal transduction, and other lipid-related processes. Changes in the levels of fatty acid metabolite may indicate the malignant transformation of gastrointestinal cells, which have an impact on the prognosis of patients and can be used as a marker to monitor the efficacy of anticancer therapy. Therefore, targeting key enzymes involved in fatty acid metabolism, either as monotherapy or in combination with other agents, is a promising strategy for anticancer treatment. This article reviews the potential mechanisms of fatty acid metabolism disorders in the occurrence and development of gastrointestinal tumors, and summarizes the related potential biomarkers and anticancer strategies.

Artificial intelligence enhances the management of esophageal squamous cell carcinoma in the precision oncology era

Esophageal squamous cell carcinoma (ESCC) is the most common histological type of esophageal cancer with a poor prognosis. Early diagnosis and prognosis assessment are crucial for improving the survival rate of ESCC patients. With the advancement of artificial intelligence (AI) technology and the proliferation of medical digital information, AI has demonstrated promising sensitivity and accuracy in assisting precise detection, treatment decision-making, and prognosis assessment of ESCC. It has become a unique opportunity to enhance comprehensive clinical management of ESCC in the era of precision oncology. This review examines how AI is applied to the diagnosis, treatment, and prognosis assessment of ESCC in the era of precision oncology, and analyzes the challenges and potential opportunities that AI faces in clinical translation. Through insights into future prospects, it is hoped that this review will contribute to the real-world application of AI in future clinical settings, ultimately alleviating the disease burden caused by ESCC.

The signature of extracellular vesicles in hypoxic breast cancer and their therapeutic engineering

Breast cancer (BC) currently ranks second in the global cancer incidence rate. Hypoxia is a common phenomenon in BC. Under hypoxic conditions, cells in the tumor microenvironment (TME) secrete numerous extracellular vesicles (EVs) to achieve intercellular communication and alter the metabolism of primary and metastatic tumors that shape the TME. In addition, emerging studies have indicated that hypoxia can promote resistance to tumor treatment. Engineered EVs are expected to become carriers for cancer treatment due to their high biocompatibility, low immunogenicity, high drug delivery efficiency, and ease of modification. In this review, we summarize the mechanisms of EVs in the primary TME and distant metastasis of BC under hypoxic conditions. Additionally, we highlight the potential applications of engineered EVs in mitigating the malignant phenotypes of BC cells under hypoxia.

Sensors and Devices Guided by Artificial Intelligence for Personalized Pain Medicine

Personalized pain medicine aims to tailor pain treatment strategies for the specific needs and characteristics of an individual patient, holding the potential for improving treatment outcomes, reducing side effects, and enhancing patient satisfaction. Despite existing pain markers and treatments, challenges remain in understanding, detecting, and treating complex pain conditions. Here, we review recent engineering efforts in developing various sensors and devices for addressing challenges in the personalized treatment of pain. We summarize the basics of pain pathology and introduce various sensors and devices for pain monitoring, assessment, and relief. We also discuss advancements taking advantage of rapidly developing medical artificial intelligence (AI), such as AI-based analgesia devices, wearable sensors, and healthcare systems. We believe that these innovative technologies may lead to more precise and responsive personalized medicine, greatly improved patient quality of life, increased efficiency of medical systems, and reducing the incidence of addiction and substance use disorders.

Metabolic features of tumor-derived extracellular vesicles: challenges and opportunities

Tumor-derived extracellular vesicles (TDEVs) play crucial roles in intercellular communication both in the local tumor microenvironment and systemically, facilitating tumor progression and metastatic spread. They carry a variety of molecules with bioactive properties, such as nucleic acids, proteins and metabolites, that trigger different signaling processes in receptor cells and induce, among other downstream effects, metabolic reprogramming. Interestingly, the cargo of TDEVs also reflects the metabolic status of the producing cells in a time- and context-dependent manner, providing information on the functionality and state of those cells. For these reasons, together with their ability to be detected in diverse biofluids, there is increasing interest in the study of TDEVs, particularly their metabolic cargo, as diagnostic and prognostic tools in cancer management. This review presents a compilation of metabolism-related molecules (enzymes and metabolites) described in cancer extracellular vesicles (EVs) with potential use as cancer biomarkers, and discusses the challenges arising in this rapidly evolving field.

Application of machine learning for high-throughput tumor marker screening

High-throughput sequencing and multiomics technologies have allowed increasing numbers of biomarkers to be mined and used for disease diagnosis, risk stratification, efficacy assessment, and prognosis prediction. However, the large number and complexity of tumor markers make screening them a substantial challenge. Machine learning (ML) offers new and effective ways to solve the screening problem. ML goes beyond mere data processing and is instrumental in recognizing intricate patterns within data. ML also has a crucial role in modeling dynamic changes associated with diseases. Used together, ML techniques have been included in automatic pipelines for tumor marker screening, thereby enhancing the efficiency and accuracy of the screening process. In this review, we discuss the general processes and common ML algorithms, and highlight recent applications of ML in tumor marker screening of genomic, transcriptomic, proteomic, and metabolomic data of patients with various types of cancers. Finally, the challenges and future prospects of the application of ML in tumor therapy are discussed.

Liquid biopsy of oesophageal squamous cell carcinoma: implications in diagnosis, prognosis, and treatment monitoring

Oesophageal squamous cell carcinoma (ESCC) is a common malignant tumour of the gastrointestinal tract. Early detection and access to appropriate treatment are crucial for the long-term survival of patients. However, limited diagnostic and monitoring methods are available for identifying early stage ESCC. Endoscopic screening and surgical resection are commonly used to diagnose and treat early ESCC. However, these methods have disadvantages, such as high recurrence, lethality, and mortality rates. Therefore, methods to improve early diagnosis of ESCC and reduce its mortality rate are urgently required. In 1961, Gary et al. proposed a novel liquid biopsy approach for clinical diagnosis. This involved examining exosomes, circulating tumour cells, circulating free DNA, and circulating free RNA in body fluids. The ability of liquid biopsy to obtain samples repeatedly, wide detection range, and fast detection speed make it a feasible option for non-invasive tumour detection. In clinical practice, liquid biopsy technology has gained popularity for early screening, diagnosis, treatment efficacy monitoring, and prognosis assessment. Thus, this is a highly promising examination method. However, there have been no comprehensive reviews on the four factors of liquid biopsy in the context of ESCC. This review aimed to analyse the progress of liquid biopsy research for ESCC, including its classification, components, and potential future applications.

Combining fecal microbiome and metabolomics reveals diagnostic biomarkers for esophageal squamous cell carcinoma

Esophageal squamous cell carcinoma (ESCC) is one of the most predominant subtypes of esophageal cancer. The characteristics of the gut microbiome and its metabolites from patients with ESCC have not been adequately studied and discussed. In this study, 40 fecal samples (20 from ESCC patients and 20 from healthy controls) were analyzed by 16S rRNA gene sequencing and untargeted metabolomics. The data sets were analyzed individually and synthesized using various bioinformatics methods. Alpha and beta diversity indicated significant differences in microbial diversity and abundance between ESCC and healthy control feces. At the genus level, the abundance of Phascolarctobacterium, Sutterella, and Streptococcus was significantly increased in ESCC. At the genus level, linear discriminant analysis effect size identified two biomarkers: Bacteroides_stercoris and Prevotella_copri. Untargeted metabolomics analysis revealed 307 differential metabolites between ESCC and healthy control feces, with indoles and derivatives, tropane alkaloids, lipids, and lipid-like molecules in higher relative abundance in ESCC feces than in healthy control feces. Kyoto Encyclopedia of Genes and Genomes enrichment analysis revealed that unsaturated fatty acids (FAs), ascorbate and aldarate metabolism, and hypoxia-inducible factor 1 signaling pathway were significantly associated with differential metabolite. Phenylethanolamine and despropionyl p-fluoro fentanyl could be used as reliable biomarkers to differentiate ESCC from healthy control. The correlation analysis showed that Prevotella may be involved in the synthesis of fatty acyl, carboxylic acids and derivatives, benzenes and substituted derivatives, organic oxygenates, and indoles and derivatives as metabolites. Fusicatenibacter and Lachnospira may be involved in the degradation of indoles and derivatives. Alistipes, Agathobacter, and Parabacteroides may be involved in the synthesis of indoles and derivatives with strong contributions. There is an intricate relationship between the gut microbiome and the levels of several metabolites (e.g., fatty acyls, carboxylic acids and derivatives, indoles, and derivatives). Microbial-associated metabolites can be used as diagnostic biomarkers in therapeutic exploration. Further analysis revealed that Prevotella, Alistipes, Agathobacter, and Parabacteroides might promote ESCC by regulating the synthesis of indoles and their derivatives. The results of this study provide favorable evidence for the early diagnosis of ESCC and subsequent individualized treatment and targeted interventions.IMPORTANCEWe describe for the first time the differences in fecal microbiome composition and metabolites between patients with esophageal squamous cell carcinoma (ESCC) and healthy controls by 16S rRNA gene sequencing and untargeted metabolomics. The results of this study provide a favorable basis for the early diagnosis of ESCC and subsequent targeted interventional therapy.

Pivotal role of exosomes in diagnosis and treatment of esophageal cancer in a new era of precision medicine

In this editorial we comment on the article published by Ning et al, "Role of exosomes in metastasis and therapeutic resistance in esophageal cancer". Esophageal cancer (EC) represents a significant global health concern, being the seventh most common and sixth in terms of mortality worldwide. Despite the advances in therapeutic modalities, the management of patients with EC remains challenging, with a 5-year survival rate of only 25% and a limited eligibility for curative surgery due to its late diagnosis. Conventional screening methods are impractical for the early detection of EC, given their either invasive or insensitive nature. The advent of liquid biopsy, with a focus on circulating tumor cells, circulating tumor DNA, and exosomes, heralds a non-invasive avenue for cancer detection. Exosomes, small vesicles involved in intercellular communication, are highlighted as potential biomarkers for EC diagnosis and prognosis. Along with a diverse cargo encompassing various types of RNA, DNA molecules, proteins, and metabolites, exosomes emerge as key players in tumorigenesis, tumor development, and metastasis. Their significance extends to carrying distinctive biomarkers, including microRNAs (miRNAs), long non-coding RNAs, and circular RNAs, underscoring their potential diagnostic and prognostic value. Furthermore, exosomes may be utilized for therapeutic purposes in the context of EC treatment, serving as efficient delivery vehicles for therapeutic agents such as chemotherapeutic medicines and miRNAs. In this editorial we delve into the applications of exosomes for the early detection and treatment of EC, as well as the future perspectives.

Non-endoscopic Screening for Esophageal Squamous Cell Carcinoma: Recent Advances

BACKGROUND

Esophageal squamous cell carcinoma (ESCC) is one of the most common tumors in the gastrointestinal tract, and China has a high incidence area with a high burden on the disease. As early symptoms of ESCC are not obvious, the mortality rate is high, and it is often diagnosed in the intermediate and advanced stages. However, early screening and treatment may reduce morbidity and mortality.

METHODS

Screening methods are divided into endoscopic and non-endoscopic screening.

RESULTS

Endoscopic screening cannot be widely used because of its invasive nature and high cost. Currently, non-endoscopic screening consists primarily of tumor biomarkers and cytology, and tumor biomarkers including autoantibodies, circulating tumor cells, circulating tumor DNA, exosomes and serum metabolomics are more likely to be effective. But the efficiency of early diagnosis of esophageal cancer is low and the accuracy of screening needs to be improved. The aim of this study is to summarize advances in non-endoscopic esophageal cancer screening and strategies to provide a scientific basis and research idea for esophageal cancer prevention and control.

CONCLUSIONS

Non-endoscopic screening is better than endoscopic screening. And the application of tumor biomarkers is much better than other non-endoscopic screening methods.

Efficient preparation of high-purity and intact mesenchymal stem cell-derived extracellular vesicles

Mesenchymal stem cell-derived extracellular vesicles (MSC-EVs) have shown great promise for regeneration and immunomodulation. However, efficient and scalable methods for their preparation are still lacking. In this study, we present the adoption of a label-free technique known as "EXODUS" to isolate and purify MSC-EVs from the conditioned medium. Our findings indicate that EXODUS can rapidly isolate EVs from 10 mL of conditioned medium with a 5-fold higher yield compared to conventional approaches, including ultracentrifugation (UC) and polyethylene glycol precipitation (PEG) methods. Additionally, pre-storing the conditioned medium at 4°C for 1 week resulted in a ~2-fold higher yield of MSC-EVs compared to the freshly prepared medium. However, storing the purified EV particles at 4°C for 1 month led to a 2-fold reduction in particle concentration. Furthermore, we found that MSC-EVs isolated using EXODUS exhibit higher expression levels of EV markers such as Alix, Flotillin1, CD81, and TSG101 in comparison to PEG and UC methods. We also discovered that MSC-EVs isolated using EXODUS are enriched in response to cytokine, collagen-containing extracellular matrix, and calcium ion binding compared to PEG method and enriched in extracellular structure organization, extracellular matrix, and extracellular matrix structure constituents compared to UC. Finally, we demonstrated that MSC-EVs isolated using EXODUS exhibit greater potential in animal organ development, tissue development, and anatomical structure morphogenesis compared to the UC. These findings suggest that EXODUS is a suitable method for the large-scale preparation of high-quality MSC-EVs for various clinical applications.

Exploiting Sound for Emerging Applications of Extracellular Vesicles

Extracellular vesicles are nano- to microscale, membrane-bound particles released by cells into extracellular space, and act as carriers of biomarkers and therapeutics, holding promising potential in translational medicine. However, the challenges remain in handling and detecting extracellular vesicles for disease diagnosis as well as exploring their therapeutic capability for disease treatment. Here, we review the recent engineering and technology advances by leveraging the power of sound waves to address the challenges in diagnostic and therapeutic applications of extracellular vesicles and biomimetic nanovesicles. We first introduce the fundamental principles of sound waves for understanding different acoustic-assisted extracellular vesicle technologies. We discuss the acoustic-assisted diagnostic methods including the purification, manipulation, biosensing, and bioimaging of extracellular vesicles. Then, we summarize the recent advances in acoustically enhanced therapeutics using extracellular vesicles and biomimetic nanovesicles. Finally, we provide perspectives into current challenges and future clinical applications of the promising extracellular vesicles and biomimetic nanovesicles powered by sound.

Lipid metabolism analysis in esophageal cancer and associated drug discovery

Esophageal cancer is an upper gastrointestinal malignancy with a bleak prognosis. It is still being explored in depth due to its complex molecular mechanisms of occurrence and development. Lipids play a crucial role in cells by participating in energy supply, biofilm formation, and signal transduction processes, and lipid metabolic reprogramming also constitutes a significant characteristic of malignant tumors. More and more studies have found esophageal cancer has obvious lipid metabolism abnormalities throughout its beginning, progress, and treatment resistance. The inhibition of tumor growth and the enhancement of antitumor therapy efficacy can be achieved through the regulation of lipid metabolism. Therefore, we reviewed and analyzed the research results and latest findings for lipid metabolism and associated analysis techniques in esophageal cancer, and comprehensively proved the value of lipid metabolic reprogramming in the evolution and treatment resistance of esophageal cancer, as well as its significance in exploring potential therapeutic targets and biomarkers.

Identification of a Prognostic Gene Signature Based on Lipid Metabolism-Related Genes in Esophageal Squamous Cell Carcinoma

Background

Dysregulation of lipid metabolism is common in cancer. However, the molecular mechanism underlying lipid metabolism in esophageal squamous cell carcinoma (ESCC) and its effect on patient prognosis are not well understood. The objective of our study was to construct a lipid metabolism-related prognostic model to improve prognosis prediction in ESCC.

Methods

We downloaded the mRNA expression profiles and corresponding survival data of patients with ESCC from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. We performed differential expression analysis to identify differentially expressed lipid metabolism-related genes (DELMGs). We used Univariate Cox regression and least absolute shrinkage and selection operator (LASSO) analyses to establish a risk model in the GEO cohort and used data of patients with ESCC from the TCGA cohort for validation. We also explored the relationship between the risk model and the immune microenvironment via infiltrated immune cells and immune checkpoints.

Results

The result showed that 132 unique DELMGs distinguished patients with ESCC from the controls. We identified four genes (ACAA1, ACOT11, B4GALNT1, and DDHD1) as prognostic gene expression signatures to construct a risk model. Patients were classified into high- and low-risk groups as per the signature-based risk score. We used the receiver operating characteristic (ROC) curve and the Kaplan-Meier (KM) survival analysis to validate the predictive performance of the 4-gene signature in both the training and validation sets. Infiltrated immune cells and immune checkpoints indicated a difference in the immune status between the two risk groups.

Conclusion

The results of our study indicated that a prognostic model based on the 4-gene signature related to lipid metabolism was useful for the prediction of prognosis in patients with ESCC.

Exosome-mediated metabolic reprogramming: Implications in esophageal carcinoma progression and tumor microenvironment remodeling

Esophageal carcinoma is among the most fatal malignancies with increasing incidence globally. Tumor onset and progression can be driven by metabolic reprogramming, especially during esophageal carcinoma development. Exosomes, a subset of extracellular vesicles, display an average size of ∼100 nanometers, containing multifarious components (nucleic acids, proteins, lipids, etc.). An increasing number of studies have shown that exosomes are capable of transferring molecules with biological functions into recipient cells, which play crucial roles in esophageal carcinoma progression and tumor microenvironment that is a highly heterogeneous ecosystem through rewriting the metabolic processes in tumor cells and environmental stromal cells. The review introduces the reprogramming of glucose, lipid, amino acid, mitochondrial metabolism in esophageal carcinoma, and summarize current pharmaceutical agents targeting such aberrant metabolism rewiring. We also comprehensively overview the biogenesis and release of exosomes, and recent advances of exosomal cargoes and functions in esophageal carcinoma and their promising clinical application. Moreover, we discuss how exosomes trigger tumor growth, metastasis, drug resistance, and immunosuppression as well as tumor microenvironment remodeling through focusing on their capacity to transfer materials between cells or between cells and tissues and modulate metabolic reprogramming, thus providing a theoretical reference for the design potential pharmaceutical agents targeting these mechanisms. Altogether, our review attempts to fully understand the significance of exosome-based metabolic rewriting in esophageal carcinoma progression and remodeling of the tumor microenvironment, bringing novel insights into the prevention and treatment of esophageal carcinoma in the future.

Statistical methods and resources for biomarker discovery using metabolomics

Metabolomics is a dynamic tool for elucidating biochemical changes in human health and disease. Metabolic profiles provide a close insight into physiological states and are highly volatile to genetic and environmental perturbations. Variation in metabolic profiles can inform mechanisms of pathology, providing potential biomarkers for diagnosis and assessment of the risk of contracting a disease. With the advancement of high-throughput technologies, large-scale metabolomics data sources have become abundant. As such, careful statistical analysis of intricate metabolomics data is essential for deriving relevant and robust results that can be deployed in real-life clinical settings. Multiple tools have been developed for both data analysis and interpretations. In this review, we survey statistical approaches and corresponding statistical tools that are available for discovery of biomarkers using metabolomics.

Metabolomic investigation of urinary extracellular vesicles for early detection and screening of lung cancer

Lung cancer is a prevalent cancer type worldwide that often remains asymptomatic in its early stages and is frequently diagnosed at an advanced stage with a poor prognosis due to the lack of effective diagnostic techniques and molecular biomarkers. However, emerging evidence suggests that extracellular vesicles (EVs) may promote lung cancer cell proliferation and metastasis, and modulate the anti-tumor immune response in lung cancer carcinogenesis, making them potential biomarkers for early cancer detection. To investigate the potential of urinary EVs for non-invasive detection and screening of patients at early stages, we studied metabolomic signatures of lung cancer. Specifically, we conducted metabolomic analysis of 102 EV samples and identified metabolome profiles of urinary EVs, including organic acids and derivatives, lipids and lipid-like molecules, organheterocyclic compounds, and benzenoids. Using machine learning with a random forest model, we screened for potential markers of lung cancer and identified a marker panel consisting of Kanzonol Z, Xanthosine, Nervonyl carnitine, and 3,4-Dihydroxybenzaldehyde, which exhibited a diagnostic potency of 96% for the testing cohort (AUC value). Importantly, this marker panel also demonstrated effective prediction for the validation set, with an AUC value of 84%, indicating the reliability of the marker screening process. Our findings suggest that the metabolomic analysis of urinary EVs provides a promising source of non-invasive markers for lung cancer diagnostics. We believe that the EV metabolic signatures could be used to develop clinical applications for the early detection and screening of lung cancer, potentially improving patient outcomes.

Proteomic Research of Extracellular Vesicles in Clinical Biofluid

Extracellular vesicles (EVs), the lipid bilayer membranous structures of particles, are produced and released from almost all cells, including eukaryotes and prokaryotes. The versatility of EVs has been investigated in various pathologies, including development, coagulation, inflammation, immune response modulation, and cell-cell communication. Proteomics technologies have revolutionized EV studies by enabling high-throughput analysis of their biomolecules to deliver comprehensive identification and quantification with rich structural information (PTMs, proteoforms). Extensive research has highlighted variations in EV cargo depending on vesicle size, origin, disease, and other features. This fact has sparked activities to use EVs for diagnosis and treatment to ultimately achieve clinical translation with recent endeavors summarized and critically reviewed in this publication. Notably, successful application and translation require a constant improvement of methods for sample preparation and analysis and their standardization, both of which are areas of active research. This review summarizes the characteristics, isolation, and identification approaches for EVs and the recent advances in EVs for clinical biofluid analysis to gain novel knowledge by employing proteomics. In addition, the current and predicted future challenges and technical barriers are also reviewed and discussed.

A simple urine test by 3D-plus-3D immunoassay guides precise in vitro cancer diagnosis

Although a variety of urinary cancer markers are available for in vitro diagnosis, inherent problems of urine environment-containing various inorganic/organic ions/molecules that vary in concentration over a 20-fold range or more and significantly attenuate antibody avidity for markers-render conventional immunoassays unsuitable, remaining unresolved and a major challenge. Here we developed a 3D-plus-3D (3p3) immunoassay method, based on a single-step urinary marker detection by 3D-antibody probes, which are free of steric hindrance and capable of omnidirectional capture of markers in a 3D solution. The 3p3 immunoassay showed an excellent performance in the diagnosis of prostate cancer (PCa) through detecting PCa-specific urinary engrailed-2 protein, demonstrating 100% sensitivity and 100% specificity with the urine specimens of PCa-related and other related disease patients and healthy individuals. This innovative approach holds a great potential in opening up a novel clinical route for precise in vitro cancer diagnosis and also pushing urine immunoassay closer to more widespread adoption.

Identification and detection of plasma extracellular vesicles-derived biomarkers for esophageal squamous cell carcinoma diagnosis

Esophageal cancer is a malignant tumor with two-thirds of patients having a local recurrence or distant metastasis. To date, diagnostic biomarkers with high sensitivity and specificity are lacking. Extracellular vesicles (EVs) have shown their potential values as disease biomarkers as they carry specific proteins and RNAs derived from cancer cells. In this study, we investigate ESCC precision diagnostics from the insights of circulating EVs, and integrate the ultrafast EV isolation approach (EXODUS) and ELISA for fast detection and screening of ESCC patients. First, we isolate and characterize the high-purity plasma EVs with EXODUS and identify 401 proteins and 372 proteins from ESCC patient and healthy individuals, respectively. Further looking into the differentially expressed proteins (DEPs) of ESCC patients and enriched KEGG pathways, we discover EV-CD14 as a potential diagnostic biomarker for ESCC, which has been further validated as a significantly differentially expressed protein by Western Blot and immunogold labelling TEM. For fast screening and detection of ESCC towards clinical applications, we apply ELISA method to diagnose ESCC from 60 clinical samples based on circulating EV-CD14, which shows a high AUC value up to 96.0% for detection of ESCC in a test set (30 samples), and displays a high accuracy rate up to 90% for prediction of ESCC in a screening test (30 samples). Our results suggest that the circulating EV-CD14 may highly be related to the initiation and progression of ESCC, providing a novel method for the diagnosis and prognosis of ESCC towards clinical translations.

Metabolites as extracellular vesicle cargo in health, cancer, pleural effusion, and cardiovascular diseases: An emerging field of study to diagnostic and therapeutic purposes

Extracellular vesicles (EVs) are highly diverse nanoscale membrane-bound structures released from different cell types into the extracellular environment. They play essential functions in cell signaling by transporting their cargo, such as proteins, RNA, DNA, lipids, metabolites, and small molecules, to recipient cells. It has recently been shown that EVs might modulate carcinogenesis by delivering cargo to recipient cells. Furthermore, recent discoveries revealed that changes in plasma-derived EV levels and cargo in subjects with metabolic diseases were documented by many researchers, suggesting that EVs might be a promising source of disease biomarkers. One of the cargos of EVs that has recently attracted the most attention is metabolites. The metabolome of these vesicles introduces a plethora of disease indicators; hence, examining the metabolomics of EVs detected in human biofluids would be an effective approach. On the other hand, metabolites have various roles in biological systems, including the production of energies, synthesizing macromolecules, and serving as signaling molecules and hormones. Metabolome rewiring in cancer and stromal cells is a characteristic of malignancy, but the current understanding of how this affects the metabolite composition and activity of tumor-derived EVs remains in its infancy. Since new findings and studies in the field of exosome biology and metabolism are constantly being published, it is likely that diagnostic and treatment techniques, including the use of exosome metabolites, will be launched in the coming years. Recent years have seen increased interest in the EV metabolome as a possible source for biomarker development. However, our understanding of the role of these molecules in health and disease is still immature. In this work, we have provided the latest findings regarding the role of metabolites as EV cargoes in the pathophysiology of diseases, including cancer, pleural effusion (PE), and cardiovascular disease (CVD). We also discussed the significance of metabolites as EV cargoes of microbiota and their role in host-microbe interaction. In addition, the latest findings on metabolites in the form of EV cargoes as biomarkers for disease diagnosis and treatment are presented in this study.

Contamination of bacterial extracellular vesicles (bEVs) in human urinary extracellular vesicles (uEVs) samples and their effects on uEVs study

Bacterial overgrowth is common for improperly stored urine. However, its effects on human urinary extracellular vesicles (uEVs) study had not been previously examined nor documented. This study investigated the presence of bacterial EVs (bEVs) contaminated in uEVs samples and their effects on uEVs study. Nanoscale uEVs were isolated from normal human urine immediately after collection (0-h) or after 25°C-storage with/without preservative (10 mM NaN3) for up to 24-h. Turbidity, bacterial count and total uEVs proteins abnormally increased in the 8-h and 24-h-stored urine without NaN3. NanoLC-ESI-LTQ-Orbitrap MS/MS identified 6-13 bacterial proteins in these contaminated uEVs samples. PCR also detected bacterial DNAs in these contaminated uEVs samples. Besides, uEVs derived from 8-h and 24-h urine without NaN3 induced macrophage activation (CD11b and phagocytosis) and secretion of cytokines (IFN-α, IL-8, and TGF-β) from macrophages and renal cells (HEK-293, HK-2, and MDCK). All of these effects induced by bacterial contamination were partially/completely prevented by NaN3. Interestingly, macrophage activation and cytokine secretion were also induced by bEVs purified from Escherichia coli. This study clearly shows evidence of bEVs contamination and their effects on human uEVs study when the urine samples were inappropriately stored, whereas NaN3 can partially/completely prevent such effects from the contaminated bEVs.

Highly Selective Purification of Plasma Extracellular Vesicles Using Titanium Dioxide Microparticles for Depicting the Metabolic Signatures of Diabetic Retinopathy

Extracellular vesicle (EV) cargos with regular fluctuations hold the potential for providing chemical predictors toward clinical diagnosis and prognosis. A plasma sample is one of the most important sources of circulating EVs, yet the technical barrier and cost consumption in plasma-EV isolation still limit its application in disease diagnosis and biomarker discovery. Here, we introduced an easy-to-use strategy that allows selectively purifying small EVs (sEVs) from human plasma and detecting their metabolic alternations. Fe₃O₄@TiO₂ microbeads with a rough island-shaped surface have proven the capability of performing efficient and reversible sEV capture owing to the phospholipid affinity, enhanced binding sites, and size-exclusion-like effect of the rough TiO₂ shell. The proposed system can also shorten the separation procedure from hours to 20 min when compared with the ultracentrifugation method and yield approximately 10⁸ sEV particles from 100 μL of plasma. Metabolome variations of sEVs among progressive diabetic retinopathy subjects were finally studied, observing a cluster of metabolites with elevated levels and suggesting potential roles of these sEV chemicals in diabetic retinopathy onset and progression. Such a scalable and flexible EV capture system can be seen as an effective analytical tool for facilitating plasma-based liquid biopsies.

Targeting Strategies for Aberrant Lipid Metabolism Reprogramming and the Immune Microenvironment in Esophageal Cancer: A Review

Esophageal cancer is of high importance to occurrence, development, and treatment resistance. As evidenced by recent studies, pathways (e.g., Wnt/β-catenin, AMPK, and Hippo) are critical to the proliferation, differentiation, and self-renewal of esophageal cancer. In addition, the above pathways play a certain role in regulating esophageal cancer and act as potential therapeutic targets. Over the past few years, the function of lipid metabolism in controlling tumor cells and immune cells has aroused extensive attention. It has been reported that there are intricate interactions between lipid metabolism reprogramming between immune and esophageal cancer cells, whereas molecular mechanisms should be studied in depth. Immune cells have been commonly recognized as a vital player in the esophageal cancer microenvironment, having complex crosstalk with cancer cells. It is increasingly evidenced that the function of immune cells in the tumor microenvironment (TME) is significantly correlated with abnormal lipid metabolism. In this review, the latest findings in lipid metabolism reprogramming in TME are summarized, and the above findings are linked to esophageal cancer progression. Aberrant lipid metabolism and associated signaling pathways are likely to serve as a novel strategy to treat esophageal cancer through lipid metabolism reprogramming.

Challenges in Metabolomics-Based Tests, Biomarkers Revealed by Metabolomic Analysis, and the Promise of the Application of Metabolomics in Precision Medicine

Metabolomics helps identify metabolites to characterize/refine perturbations of biological pathways in living organisms. Pre-analytical, analytical, and post-analytical limitations that have hampered a wide implementation of metabolomics have been addressed. Several potential biomarkers originating from current targeted metabolomics-based approaches have been discovered. Precision medicine argues for algorithms to classify individuals based on susceptibility to disease, and/or by response to specific treatments. It also argues for a prevention-based health system. Because of its ability to explore gene-environment interactions, metabolomics is expected to be critical to personalize diagnosis and treatment. Stringent guidelines have been applied from the very beginning to design studies to acquire the information currently employed in precision medicine and precision prevention approaches. Large, prospective, expensive and time-consuming studies are now mandatory to validate old, and discover new, metabolomics-based biomarkers with high chances of translation into precision medicine. Metabolites from studies on saliva, sweat, breath, semen, feces, amniotic, cerebrospinal, and broncho-alveolar fluid are predicted to be needed to refine information from plasma and serum metabolome. In addition, a multi-omics data analysis system is predicted to be needed for omics-based precision medicine approaches. Omics-based approaches for the progress of precision medicine and prevention are expected to raise ethical issues.

The dysregulation of unsaturated fatty acid-based metabolomics in the MNNG-induced malignant transformation of Het-1A cells

Studies have shown that environmental carcinogens exerted an important function in the high incidence of esophageal cancer (EC). Nitrosamines have been identified as important environmental carcinogens for EC. This study aimed to investigate the metabolic disturbances and new key toxicological markers in the malignant transformation process of normal esophageal epithelial cells (Het-1A) induced by MNNG (N-methyl-N'-nitro-N-nitrosoguanidine). Untargeted metabolomic and lipidomic profiling analysis by using ultra-high-performance liquid chromatography coupled with mass spectrometry (UHPLC-MS) were applied to explore the metabolic network alterations of Het-1A cells. The metabolomic results showed that significant alterations were observed in metabolic signatures between different generations (P5, P15, P25, P35) and the control cell group (P0). A total of 48 differential endogenous metabolites were screened and identified, mainly containing fatty acids, amino acids, and nucleotides. The differential metabolites were predominantly linked to the pathway of biosynthesis of unsaturated fatty acids metabolism. The cell lipidomic profiling revealed that the most differential lipids contained fatty acids (FAs), phosphatidylcholines (PC), phosphatidylethanolamines (PE), and phosphatidylserines (PS). The enrichment of the lipidomic pathway also confirmed that the lipid metabolism of biosynthesis of unsaturated fatty acids was the significant variation during the cell malignant transformation. Furthermore, we detected the expression of the upstream regulatory enzymes related to the unsaturated fatty acids to explore the regulation mechanism. The expression of stearoyl-CoA desaturase (SCD), ELOVL fatty acid elongase 1 (ELOVL1) promoted, and fatty acid desaturase 1 (FADS1) inhibited the key fatty acids of unsaturated fatty acids metabolism compared to the control cell group. Overall, our results revealed that lipid fatty acid metabolism was involved in the malignant transformation of Het-1A cells induced by MNNG and deepened the awareness of the carcinogenic mechanism of environmental exposure pollutants.