Construction of Exosome SORL1 Detection Platform Based on 3D Porous Microfluidic Chip and its Application in Early Diagnosis of Colorectal Cancer

Mass Spectrometry-Based Proteomics for Next-Generation Precision Oncology

Cancer is the leading cause of death worldwide characterized by patient heterogeneity and complex tumor microenvironment. While the genomics-based testing has transformed modern medicine, the challenge of diverse clinical outcomes highlights unmet needs for precision oncology. As functional molecules regulating cellular processes, proteins hold great promise as biomarkers and drug targets. Mass spectrometry (MS)-based clinical proteomics has illuminated the molecular features of cancers and facilitated discovery of biomarkers or therapeutic targets, paving the way for innovative strategies that enhance the precision of personalized treatment. In this article, we introduced the tools and current achievements of MS-based proteomics, choice of discovery and targeted MS from discovery to validation phases, profiling sensitivity from bulk samples to single-cell level and tissue to liquid biopsy specimens, current regulatory landscape of MS-based protein laboratory-developed tests (LDTs). The challenges, success and future perspectives in translating research MS assay into clinical applications are also discussed. With well-designed validation studies to demonstrate clinical benefits and meet the regulatory requirements for both analytical and clinical performance, the future of MS-based assays is promising with numerous opportunities to improve cancer diagnosis, treatment, and monitoring.

Enhancing Analysis of Extracellular Vesicles by Microfluidics

Extracellular vesicles (EVs) play crucial roles in intercellular communication and hold great promise as biomarkers for noninvasive disease diagnosis. Intensive research efforts have been devoted to discovering the EV subpopulations responsible for specific functions or with enhanced effectiveness as disease markers, through extensive EV purification and content analysis. However, their high heterogeneity in size and cargo composition poses significant challenges for reaching such goals. Isolation methods like ultracentrifugation and size-exclusion chromatography, as well as content analysis approaches like polymerase chain reaction and enzyme-linked immunosorbent assay, have made significant contributions to improving our understanding of EV biology. Nonetheless, these methods face limitations in isolation efficiency, EV purity, and detection sensitivity and specificity due to issues like large sample consumption, unsatisfactory purity, and insufficient resolution in EV subtyping. Microfluidic technology presents promising solutions to these challenges, leveraging their intrinsic capabilities in precise flow and external energy field manipulation, sample compartmentalization, and signal enhancement at the micro- and nanoscale. Hence, this review summarizes the recent developments in microfluidics-enabled EV analysis, paying special attention to the unique microfluidic features exploited. Strategies such as viscoelastic and inertial flow, fluid mixing, and external-field-assisted approaches in improving EV purification, as well as compartmentalization and micro/nanostructures for enhancing EV detection, are examined. Furthermore, the current limitations and potential future directions are discussed to inspire advancements in this rapidly developing field.

Advances in electrochemical biosensors for the detection of tumor-derived exosomes

Exosomes, released from diverse cells as nanoscale lipid bilayer vesicles, mediate intercellular communication and participate in various physiological and pathological processes. Thereinto, tumor-derived exosomes (T-EXOs) with molecular cargoes of parent tumor cells act as attractive biomarkers for tumor liquid biopsy. The amount of T-EXOs and their levels of contained specific proteins and nucleic acids are closely associated with cancer burden and classification. Nevertheless, the nanoscale size and relatively low abundance of exosomes, as well as complex body liquid matrix pose daunting challenges for efficient isolation and sensitive detection of T-EXOs. Biosensing as fast, convenient and accurate method, has been widely employed for the detection of biomarkers over the past decades. Among them, electrochemical sensors can sensitively detect biomarkers by measuring of the change of electrical signal caused by oxidation or reduction at the working electrode surface. This review aims to summarize the recent advance in electrochemical biosensors for quantification, and protein and RNA analysis of exosomes. Further, challenges and future perspectives for exosome-based liquid biopsy have been discussed.

Integrated Microfluidic Chip for Neutrophil Extracellular Vesicle Analysis and Gastric Cancer Diagnosis

Neutrophil-derived extracellular vesicles (NEVs) are critically involved in disease progression and are considered potential biomarkers. However, the tedious processes of NEV separation and detection restrain their use. Herein, we presented an integrated microfluidic chip for NEV (IMCN) analysis, which achieved immune-separation of CD66b+ NEVs and multiplexed detection of their contained miRNAs (termed NEV signatures) by using 10 μL serum samples. The optimized microchannel and flow rate of the IMCN chip enabled efficient capture of NEVs (>90%). After recognition of the captured NEVs by a specific CD63 aptamer, on-chip rolling circle amplification (RCA) reaction was triggered by the released aptamers and miRNAs from heat-lysed NEVs. Then, the RCA products bound to molecular beacons (MBs), initiating allosteric hairpin structures and amplified "turn on" fluorescence signals (RCA-MB assay). Clinical sample analysis showed that NEV signatures had a high area under curve (AUC) in distinguishing between healthy control (HC) and gastric cancer (GC) (0.891), benign gastric diseases (BGD) and GC (0.857). Notably, the AUC reached 0.912 with a combination of five biomarkers (NEV signatures, CEA, and CA199) to differentiate GC from HC, and the diagnostic accuracy was further increased by using a machine learning (ML)-based ensemble classification system. Therefore, the developed IMCN chip is a valuable platform for NEV analysis and may have potential use in GC diagnosis.

Surface Components and Biological Interactions of Extracellular Vesicles

Extracellular vesicles (EVs) are critical mediators of intercellular communication, carrying bioactive cargo and displaying diverse surface components that reflect their cellular origins and functions. The EV surface, composed of proteins, lipids, and glycocalyx elements, plays a pivotal role in targeting recipient cells, mediating biological interactions, and enabling selective cargo delivery. This review comprehensively examined the molecular architecture of EV surfaces, linking their biogenesis to functional diversity, and highlights their therapeutic and diagnostic potential in diseases such as cancer and cardiovascular disorders. Additionally, we explore emerging applications of EVs, including machine-learning-assisted analysis, chemical integration, and cross-system combinations. The review also discusses some key challenges in the clinical translation of EV-related technologies.

Time-Lapse Acquisition of Both Freely Secreted Proteome and Exosome Encapsulated Proteome in Live Organoids' Microenvironment

Proteomic communications in neighboring microenvironments during early organ development is a dynamic process that continuously reshapes human embryonic stem cells (hESCs) developmental fate. Such dynamic proteomic alteration in the microenvironment consists of both freely secreted proteome and exosome-encapsulated proteome. Simultaneous monitoring of the time-lapse shift of both proteomes with live organoids remains technically challenging. Here, a continuous organoid secretion/encapsulation proteome tandem LC-MS/MS (COSEP-LCM) is introduced, which permits time-lapse monitoring of proteomic alterations both in free secretion form and in exosome encapsulated form at live organoids' microenvironment. Continuous growth of human cerebral organoids (COs) and free-secretion/exosome-encapsulation proteomics acquisition with COSEP-LCM for 60 days is demonstrated. SERPINF1, F5, and EFNB1 are initially enriched inside exosomes as encapsulated excretion and then gradually enriched outside exosomes as freely secreted excretion, while C3 is initially enriched outside exosomes as freely secreted excretion and gradually enriched inside exosomes as encapsulated excretion. Such dynamic excretion pattern paradigm shift may imply critical developmental strategy evolution during early human cerebral development. COSEP-LCM offers a platform technique for continuous inside/outside exosome proteomics co-analysis in live organoids' microenvironment.

A microfluidic-based chemiluminescence biosensor for sensitive multiplex detection of exosomal microRNAs based on hybridization chain reaction

The analysis of microRNAs (miRNAs) in exosomes is of great importance for noninvasive early disease diagnosis. However, current techniques to detect exosomal miRNAs is hampered either by laborious exosome isolation or low abundance of miRNAs in exosomes. Here, we developed a microfluidic chemiluminescence (CL) analysis method for the multiplexed detection of exosomal miR-21 and miR-155. The microfluidic device contained three parts: a snake-shaped channel for fully mixing chemiluminescent reagents, a ship-shaped channel modified with CD63 protein aptamer for capturing exosomes, and another two parallel ship-shaped channels for hybridization chain reaction (HCR) amplification and CL detection. The multiple signal amplification was realized by Y-shaped arrays, HCR amplification, and poly-HRP catalyzed CL reaction. Using this multiple signal amplification method, our microfluidic CL biosensor achieves a limit of detection of miRNAs of 0.49 fM, with a linear range of 1 fM-10 pM, which is better or comparable to previously reported biosensors. What's more, the proposed microfluidic biosensor exhibits great specificity and selectivity to the target miRNA. Moreover, the microfluidic CL strategy exhibited excellent accuracy and could significantly distinguish different cancer subtypes as well as cancer patients and healthy people. These results suggest that this simple, high sensitive, and more accurate analytical strategy by analyzing different types of exosomal miRNAs has the potential applications in cancer diagnosis and stage monitoring.

Advances of New Extracellular Vesicle Isolation and Detection Technologies in Cancer Diagnosis

Cancer is a global health issue threatening people's lives. Currently, cancer detection methods still have a lot of room for improvement in both efficiency and accuracy. The development and application of new technologies are urgently required for early cancer diagnosis and prognosis. Extracellular vesicles (EVs) are a type of phospholipid bilayer vesicle secreted by cells and play an important role in cancer development and metastasis. These small vesicles participate in cancer information transmission, antigen presentation, angiogenesis, immune response, tumor invasion, and mediate signaling pathways in the tumor microenvironment. Liquid biopsy of EV cargo contents is a fast-developing research area, holding promise for early cancer diagnosis and monitoring cancer progression in real-time. However, current EV detection technologies for clinical translation are still facing many challenges. Recent advancements in developing techniques for EV isolation and detection have made significant progress and are paving the way toward clinical application. Here, the advantages and limitations of traditional EV detection and isolation technologies in cancer diagnosis and prognosis are reviewed. The review also focuses on emerging EV detection and isolation technologies in cancer, discusses the challenges faced by current methods, and explores the perspective of new EV detection techniques for future cancer diagnosis.

Implications of Artificial Intelligence for Colorectal Cancer in Young Populations

A considerable amount of recent research has focused on the role of artificial intelligence (AI) in colorectal cancer (CRC), aiming to improve outcomes in CRC. However, AI for young onset colorectal cancer (yoCRC)-defined as colorectal cancer in patients less than 50 years old-is not nearly as explored, and its role in the prevention, detection, and management of yoCRC remains largely unknown. To address this gap, we performed an integrative review on AI in yoCRC. We conducted a comprehensive literature search of PubMed, Medline (Ovid), and Embase for articles published from 2020 to 2024, adhering to specific inclusion and exclusion criteria. This integrative review involved gathering information from diverse research designs and literature sources. After removing duplicates and applying inclusion criteria, a total of 11 articles were included in the review. Our analysis identified one review discussing the importance of AI in yoCRC, three articles presenting research studies mentioning applications for yoCRC, and seven comprehensive investigations utilizing AI with a specific focus on yoCRC. The findings indicate that while AI in CRC is an evolving research field, there are few plans or implementations reported on how to incorporate AI specifically in yoCRC. Potential limitations of this review include the limited number of databases searched and the scope of search queries used. Nonetheless, this review highlights the need for more targeted research on AI applications in yoCRC. Future research can build upon the foundation of AI in CRC with adjustments to account for the increasing incidence of yoCRC.

Exploration of the Key Pathways and Genes Involved in Osteoarthritis Genesis: Evidence from Multiple Platforms and Real-World Validation

Background

Osteoarthritis (OA), a degenerative and chronic joint disease, is essential for identifying novel biomarkers for the clinical diagnosis of OA.

Methods

We collected 35 OA patients and 32 healthy controls from four clinical cohorts and 8 real-world samples from our institute. The activation status of 7530 signalling pathways was calculated via the gene set enrichment analysis (GSEA) algorithm. Ten machine learning algorithms and 101 algorithm combinations were further applied to recognize the most diagnostic genes. KDELR3 was chosen for further validation via immunohistochemical staining to determine its diagnostic value in real-world samples.

Results

Sixteen pathways, namely, the cellular respiration chain, protein transport, lysosomal and endocytosis pathways, were activated in OA patients. A total of 101 types of algorithm combinations were considered for the diagnostic model, and 58 were successfully output. The two-step model of glmBoost plus RF had the highest average AUC value of 0.95 and was composed of LY86, SORL1, KDELR3, CSK, PTGS1, and PTGS2. Preferable consistency of the diagnostic mole and real conditions was observed in all four cohorts (GSE55235: Kappa=1.000, P<0.001; GSE55457: Kappa=0.700, P<0.001; GSE82107: Kappa=0.643, P=0.004; GSE1919: Kappa=1.000, P<0.001). KDELR3 was expressed at higher levels in OA patients than were the other genes, and with the help of immunohistochemistry (IHC), we confirmed that OA patients presented high levels of KDELR3 in synovial tissues. The infiltration of immunocytes, macrophages, and natural killer T cells was high in OA patients. KDELR3 might be involved in the activation and infiltration of effector memory CD4 T cells (Rpearson = 0.58, P < 0.001) and natural killer T cells (Rpearson = 0.53, P < 0.001).

Conclusion

We constructed and validated a six-gene diagnostic model for OA patients via machine learning, and KDELR3 emerged as a novel biomarker for OA.

Exosomes: intriguing mediators of intercellular communication in the organism's response to noxious agents

Exosomes are small extracellular vesicles that range from 30 to 150 nm in size and are formed through cellular endocytosis. They consist of proteins, lipids, and nucleic acids at varying ratios and quantities. The composition and spatiotemporal dynamics of exosomes suggest that they play a crucial role in intercellular communication. The information conveyed by exosomes significantly impacts the regulation of health and disease states in the organism. The term "noxious" refers to all harmful environmental agents and conditions that can disrupt the physiological equilibrium and induce pathological states, regardless whether of radiological, biological, or chemical origin. This review comprehensively examines the presence of such noxious agents within the organism in relation to exosome formation and function. Furthermore, it explores the cause-effect relationship between noxious agents and exosomes, aiming to restore physiological homeostasis and prepare the organism for defence against harmful agents. Regardless of the specific bioinformatic content associated with each noxious agent, synthesis of data on the interactions between various types of noxious agents and exosomes reveals that an organized defence against these agents is unachievable without the support of exosomes. Consequently, exosomes are identified as the primary communication and information system within an organism, with their content being pivotal in maintaining the health-disease balance.

Revolutionary Point-of-Care Wearable Diagnostics for Early Disease Detection and Biomarker Discovery through Intelligent Technologies

Early-stage disease detection, particularly in Point-Of-Care (POC) wearable formats, assumes pivotal role in advancing healthcare services and precision-medicine. Public benefits of early detection extend beyond cost-effectively promoting healthcare outcomes, to also include reducing the risk of comorbid diseases. Technological advancements enabling POC biomarker recognition empower discovery of new markers for various health conditions. Integration of POC wearables for biomarker detection with intelligent frameworks represents ground-breaking innovations enabling automation of operations, conducting advanced large-scale data analysis, generating predictive models, and facilitating remote and guided clinical decision-making. These advancements substantially alleviate socioeconomic burdens, creating a paradigm shift in diagnostics, and revolutionizing medical assessments and technology development. This review explores critical topics and recent progress in development of 1) POC systems and wearable solutions for early disease detection and physiological monitoring, as well as 2) discussing current trends in adoption of smart technologies within clinical settings and in developing biological assays, and ultimately 3) exploring utilities of POC systems and smart platforms for biomarker discovery. Additionally, the review explores technology translation from research labs to broader applications. It also addresses associated risks, biases, and challenges of widespread Artificial Intelligence (AI) integration in diagnostics systems, while systematically outlining potential prospects, current challenges, and opportunities.

Microfluidic systems for modeling digestive cancer: a review of recent progress

Purpose. This review aims to highlight current improvements in microfluidic devices designed for digestive cancer simulation. The review emphasizes the use of multicellular 3D tissue engineering models to understand the complicated biology of the tumor microenvironment (TME) and cancer progression. The purpose is to develop oncology research and improve digestive cancer patients' lives.Methods. This review analyzes recent research on microfluidic devices for mimicking digestive cancer. It uses tissue-engineered microfluidic devices, notably organs on a chip (OOC), to simulate human organ function in the lab. Cell cultivation on modern three-dimensional hydrogel platforms allows precise geometry, biological components, and physiological qualities. The review analyzes novel methodologies, key findings, and technical progress to explain this field's advances.Results. This study discusses current advances in microfluidic devices for mimicking digestive cancer. Micro physiological systems with multicellular 3D tissue engineering models are emphasized. These systems capture complex biochemical gradients, niche variables, and dynamic cell-cell interactions in the tumor microenvironment (TME). These models reveal stomach cancer biology and progression by duplicating the TME. Recent discoveries and technology advances have improved our understanding of gut cancer biology, as shown in the review.Conclusion. Microfluidic systems play a crucial role in modeling digestive cancer and furthering oncology research. These platforms could transform drug development and treatment by revealing the complex biology of the tumor microenvironment and cancer progression. The review provides a complete summary of recent advances and suggests future research for field professionals. The review's major goal is to further medical research and improve digestive cancer patients' lives.

Lectin microarray based glycan profiling of exosomes for dynamic monitoring of colorectal cancer progression

BACKGROUND

Exosomes, as emerging biomarkers in liquid biopsies in recent years, offer profound insights into cancer diagnostics due to their unique molecular signatures. The glycosylation profiles of exosomes have emerged as potential biomarkers, offering a novel and less invasive method for cancer diagnosis and monitoring. Colorectal cancer (CRC) represents a substantial global health challenge and burden. Thus there is a great need for the aberrant glycosylation patterns on the surface of CRC cell-derived exosomes, proposing them as potential biomarkers for tumor characterization.

RESULTS

The interactions of 27 lectins with exosomes from three CRC cell lines (SW480, SW620, HCT116) and one normal colon epithelial cell line (NCM460) have been analyzed by the lectin microarray. The result indicates that Ulex Europaeus Agglutinin I (UEA-I) exhibits high affinity and specificity towards exosomes derived from SW480 cells. The expression of glycosylation related genes within cells has been analyzed by high-throughput quantitative polymerase chain reaction (HT-qPCR). The experimental result of HT-qPCR is consistent with that of lectin microarray. Moreover, the limit of detection (LOD) of UEA-I microarray is calculated to be as low as 2.7 × 105 extracellular vehicles (EVs) mL-1 (three times standard deviation (3σ) of blank sample). The UEA-I microarray has been successfully utilized to dynamically monitor the progression of tumors in mice-bearing SW480 CRC subtype, applicable in tumor sizes ranging from 2 mm to 20 mm in diameter.

SIGNIFICANCE

The results reveal that glycan expression pattern of exosome is linked to specific CRC subtypes, and regulated by glycosyltransferase and glycosidase genes of mother cells. Our findings illuminate the potential of glycosylation molecules on the surface of exosomes as reliable biomarkers for diagnosis of tumor at early stage and monitoring of cancer progression.

Advancements in 3D In Vitro Models for Colorectal Cancer

The process of drug discovery and pre-clinical testing is currently inefficient, expensive, and time-consuming. Most importantly, the success rate is unsatisfactory, as only a small percentage of tested drugs are made available to oncological patients. This is largely due to the lack of reliable models that accurately predict drug efficacy and safety. Even animal models often fail to replicate human-specific pathologies and human body's complexity. These factors, along with ethical concerns regarding animal use, urge the development of suitable human-relevant, translational in vitro models.

Extracellular Vesicle Preparation and Analysis: A State-of-the-Art Review

In recent decades, research on Extracellular Vesicles (EVs) has gained prominence in the life sciences due to their critical roles in both health and disease states, offering promising applications in disease diagnosis, drug delivery, and therapy. However, their inherent heterogeneity and complex origins pose significant challenges to their preparation, analysis, and subsequent clinical application. This review is structured to provide an overview of the biogenesis, composition, and various sources of EVs, thereby laying the groundwork for a detailed discussion of contemporary techniques for their preparation and analysis. Particular focus is given to state-of-the-art technologies that employ both microfluidic and non-microfluidic platforms for EV processing. Furthermore, this discourse extends into innovative approaches that incorporate artificial intelligence and cutting-edge electrochemical sensors, with a particular emphasis on single EV analysis. This review proposes current challenges and outlines prospective avenues for future research. The objective is to motivate researchers to innovate and expand methods for the preparation and analysis of EVs, fully unlocking their biomedical potential.

Exosomes: a review of biologic function, diagnostic and targeted therapy applications, and clinical trials

Exosomes are extracellular vesicles generated by all cells and they carry nucleic acids, proteins, lipids, and metabolites. They mediate the exchange of substances between cells,thereby affecting biological properties and activities of recipient cells. In this review, we briefly discuss the composition of exocomes and exosome isolation. We also review the clinical applications of exosomes in cancer biology as well as strategies in exosome-mediated targeted drug delivery systems. Finally, the application of exosomes in the context of cancer therapeutics both in practice and literature are discussed.

Exosomes target HBV-host interactions to remodel the hepatic immune microenvironment

Chronic hepatitis B poses a significant global burden, modulating immune cells, leading to chronic inflammation and long-term damage. Due to its hepatotropism, the hepatitis B virus (HBV) cannot infect other cells. The mechanisms underlying the intercellular communication among different liver cells in HBV-infected individuals and the immune microenvironment imbalance remain elusive. Exosomes, as important intercellular communication and cargo transportation tools between HBV-infected hepatocytes and immune cells, have been shown to assist in HBV cargo transportation and regulate the immune microenvironment. However, the role of exosomes in hepatitis B has only gradually received attention in recent years. Minimal literature has systematically elaborated on the role of exosomes in reshaping the immune microenvironment of the liver. This review unfolds sequentially based on the biological processes of exosomes: exosomes' biogenesis, release, transport, uptake by recipient cells, and their impact on recipient cells. We delineate how HBV influences the biogenesis of exosomes, utilizing exosomal covert transmission, and reshapes the hepatic immune microenvironment. And based on the characteristics and functions of exosomes, potential applications of exosomes in hepatitis B are summarized and predicted.

Recent Advances in Microfluidic-Based Extracellular Vesicle Analysis

Extracellular vesicles (EVs) serve as vital messengers, facilitating communication between cells, and exhibit tremendous potential in the diagnosis and treatment of diseases. However, conventional EV isolation methods are labor-intensive, and they harvest EVs with low purity and compromised recovery. In addition, the drawbacks, such as the limited sensitivity and specificity of traditional EV analysis methods, hinder the application of EVs in clinical use. Therefore, it is urgent to develop effective and standardized methods for isolating and detecting EVs. Microfluidics technology is a powerful and rapidly developing technology that has been introduced as a potential solution for the above bottlenecks. It holds the advantages of high integration, short analysis time, and low consumption of samples and reagents. In this review, we summarize the traditional techniques alongside microfluidic-based methodologies for the isolation and detection of EVs. We emphasize the distinct advantages of microfluidic technology in enhancing the capture efficiency and precise targeting of extracellular vesicles (EVs). We also explore its analytical role in targeted detection. Furthermore, this review highlights the transformative impact of microfluidic technology on EV analysis, with the potential to achieve automated and high-throughput EV detection in clinical samples.

Hsa_circ_0124554 may serve as a biomarker for the diagnosis of colorectal cancer: An observational study

Circular RNAs (circRNAs) play important roles in the occurrence and development of cancer, and have been shown with diagnostic values in various cancers. The latest research showed that hsa_circ_0124554 is closely related to liver metastasis and vascular invasion in colorectal cancer (CRC). This study aimed to investigate whether hsa_circ_0124554 can be used as a diagnostic marker for CRC. In this study, quantitative reverse transcriptase polymerase chain reaction (qRT-PCR) was used to detect hsa_circ_0124554 expression levels in 40 pairs of CRC tissues and adjacent non-tumor intestinal tissues derived from CRC patients and 32 paired plasma specimens. The relationship between the expression of hsa_circ_0124554 and the clinicopathological features of CRC patients was analyzed by t-test and chi-square test. Receiver operating characteristic (ROC) curve analysis was established to explore the diagnostic value of hsa_circ_0124554 in CRC. The results showed that hsa_circ_0124554 was substantially expressed in CRC tissues (P < .001) and that there were variations in pathological differentiation, perineural invasion and invasion. The expression of hsa_circ_0124554 in CRC patients was considerably higher than healthy controls (P < .001). The area under the receiver operating characteristic (ROC) curve (AUC) of tissue and plasma hsa_circ_0124554 was 0.703 and 0.742. The AUC of the expression combined hsa_circ_0124554, carcinoembryonic antigen (CEA) and carbohydrate antigen 19-9 (CA19-9) had the best diagnostic performance (AUC = 0.899) in the CRC groups, and the sensitivity and specificity were 0.844 and 0.844. The expression of hsa_circ_0124554 was up-regulated in the tissues and plasma in CRC patients, which may be a new biomarker for the diagnosis of CRC. The combination hsa_circ_0124554, CEA and CA199 has the best diagnostic efficacy in CRC.

Bile liquid biopsy in biliary tract cancer

Biliary tract cancers are heterogeneous in etiology, morphology and molecular characteristics thus impacting disease management. Diagnosis is complex and prognosis poor. The advent of liquid biopsy has provided a unique approach to more thoroughly understand tumor biology in general and biliary tract cancers specifically. Due to their minimally invasive nature, liquid biopsy can be used to serially monitor disease progression and allow real-time monitoring of tumor genetic profiles as well as therapeutic response. Due to the unique anatomic location of biliary tract cancer, bile provides a promising biologic fluid for this purpose. This review focuses on the composition of bile and the use of these various components, ie, cells, extracellular vesicles, nucleic acids, proteins and metabolites as potential biomarkers. Based on the disease characteristics and research status of biliary tract cancer, considerable effort should be made to increase understanding of this disease, promote research and development into early diagnosis, develop efficient diagnostic, therapeutic and prognostic markers.

Current Status and Emerging Trends in Colorectal Cancer Screening and Diagnostics

Colorectal cancer (CRC) is a prevalent and potentially fatal disease categorized based on its high incidences and mortality rates, which raised the need for effective diagnostic strategies for the early detection and management of CRC. While there are several conventional cancer diagnostics available, they have certain limitations that hinder their effectiveness. Significant research efforts are currently being dedicated to elucidating novel methodologies that aim at comprehending the intricate molecular mechanism that underlies CRC. Recently, microfluidic diagnostics have emerged as a pivotal solution, offering non-invasive approaches to real-time monitoring of disease progression and treatment response. Microfluidic devices enable the integration of multiple sample preparation steps into a single platform, which speeds up processing and improves sensitivity. Such advancements in diagnostic technologies hold immense promise for revolutionizing the field of CRC diagnosis and enabling efficient detection and monitoring strategies. This article elucidates several of the latest developments in microfluidic technology for CRC diagnostics. In addition to the advancements in microfluidic technology for CRC diagnostics, the integration of artificial intelligence (AI) holds great promise for further enhancing diagnostic capabilities. Advancements in microfluidic systems and AI-driven approaches can revolutionize colorectal cancer diagnostics, offering accurate, efficient, and personalized strategies to improve patient outcomes and transform cancer management.

Advancing Healthcare: Synergizing Biosensors and Machine Learning for Early Cancer Diagnosis

Cancer is a fatal disease and a significant cause of millions of deaths. Traditional methods for cancer detection often have limitations in identifying the disease in its early stages, and they can be expensive and time-consuming. Since cancer typically lacks symptoms and is often only detected at advanced stages, it is crucial to use affordable technologies that can provide quick results at the point of care for early diagnosis. Biosensors that target specific biomarkers associated with different types of cancer offer an alternative diagnostic approach at the point of care. Recent advancements in manufacturing and design technologies have enabled the miniaturization and cost reduction of point-of-care devices, making them practical for diagnosing various cancer diseases. Furthermore, machine learning (ML) algorithms have been employed to analyze sensor data and extract valuable information through the use of statistical techniques. In this review paper, we provide details on how various machine learning algorithms contribute to the ongoing development of advanced data processing techniques for biosensors, which are continually emerging. We also provide information on the various technologies used in point-of-care cancer diagnostic biosensors, along with a comparison of the performance of different ML algorithms and sensing modalities in terms of classification accuracy.

Porous Structural Microfluidic Device for Biomedical Diagnosis: A Review

Microfluidics has recently received more and more attention in applications such as biomedical, chemical and medicine. With the development of microelectronics technology as well as material science in recent years, microfluidic devices have made great progress. Porous structures as a discontinuous medium in which the special flow phenomena of fluids lead to their potential and special applications in microfluidics offer a unique way to develop completely new microfluidic chips. In this article, we firstly introduce the fabrication methods for porous structures of different materials. Then, the physical effects of microfluid flow in porous media and their related physical models are discussed. Finally, the state-of-the-art porous microfluidic chips and their applications in biomedicine are summarized, and we present the current problems and future directions in this field.