Highly sensitive and portable mRNA detection platform for early cancer detection

Recent Advances in Microfluidics for Nucleic Acid Analysis of Small Extracellular Vesicles in Cancer

Small extracellular vesicles (sEVs) are membranous vesicles released from cellular structures through plasma membrane budding. These vesicles contain cellular components such as proteins, lipids, mRNAs, microRNAs, long-noncoding RNA, circular RNA, and double-stranded DNA, originating from the cells they are shed from. Ranging in size from ≈25 to 300 nm and play critical roles in facilitating cell-to-cell communication by transporting signaling molecules. The discovery of sEVs in bodily fluids and their involvement in intercellular communication has revolutionized the fields of diagnosis, prognosis, and treatment, particularly in diseases like cancer. Conventional methods for isolating and analyzing sEVs, particularly their nucleic acid content face challenges including high costs, low purity, time-consuming processes, limited standardization, and inconsistent yield. The development of microfluidic devices, enables improved precision in sorting, isolating, and molecular-level separation using small sample volumes, and offers significant potential for the enhanced detection and monitoring of sEVs associated with cancer. These advanced techniques hold great promise for creating next-generation diagnostic and prognostic tools given their possibility of being cost-effective, simple to operate, etc. This comprehensive review explores the current state of research on microfluidic devices for the detection of sEV-derived nucleic acids as biomarkers and their translation into practical point-of-care and clinical applications.

Innovative strategies for enhancing AuNP-based point-of-care diagnostics: Focus on coronavirus detection

Highly pathogenic coronaviruses have consistently threatened humanity, encompassing SARS-CoV, MERS-CoV, SARS-CoV-2 and others. Swift detection and accurate diagnosis play a crucial role in promptly identifying high-risk populations, enabling timely intervention, and effectively breaking the transmission chain to reduce casualties. However, the diagnostic "gold standard" reverse transcription-polymerase chain reaction (RT-PCR) failed to meet the overwhelming demand during the pandemic due to insufficient equipment and trained personnel, impeding the effective control of viral spread. Undoubtedly, there is an urgent need for the development of convenient, rapid, and sensitive point-of-care (POC) diagnostic technology. Gold nanoparticles (AuNPs) satisfy the substantial market demand for biosensors owing to their exceptional optical properties and stability. In this comprehensive review, we summarize the potential advantages of AuNPs in visual solution colorimetry and lateral flow assays (LFAs) for the diagnosis of COVID-19. We delve into the techniques for enhancing LFA signals, with the goal of increasing both detection sensitivity and specificity. Furthermore, we include the application of smartphones for unbiased and objective interpretation of results. The examples presented in this review are anticipated to inspire researchers in designing AuNPs biosensors to address current and potential outbreaks of infectious diseases in the future.

Sensitive electrochemical biosensor for rapid detection of sEV-miRNA based turbo-like localized catalytic hairpin assembly

Small extracellular vesicle-associated microRNAs (sEV-miRNAs) have emerged as critical biomarkers for cancer diagnosis, yet the rapid detection of these low-abundance molecules in clinical samples remains a formidable challenge. Herein, a simple turbo-like localized catalytic hairpin assembly (TL-CHA) was proposed for sEV-miR-1246 measurement. This electrochemical sensor achieves dual localization through the ingeniously use of AuNPs and DNA nanowires, which provides rich sites for CHA cascade amplification, significantly enhancing the effective reaction and amplify the detection response. Leveraging this innovative design, this biosensor demonstrated the ability to detect sEV-miRNA at concentrations as low as 5.24 aM in a time frame of 30 min. The precision of the measurements was validated through reverse transcription quantitative polymerase chain reaction. Furthermore, the sensor was used for analyzing plasma samples from gastric cancer patients yielded AUC values of 0.973 for all stages and 0.945 for early stages. This demonstrates the sensor's robust performance in both the staging diagnosis and early screening of gastric cancer. Therefore, this platform has great potential for the clinical cancer diagnosis.

Prospect of Gold Nanoparticles in Pancreatic Cancer

Pancreatic cancer (PC) is characterized by its notably poor prognosis and high mortality rate, underscoring the critical need for advancements in its diagnosis and therapy. Gold nanoparticles (AuNPs), with their distinctive physicochemical characteristics, demonstrate significant application potential in cancer therapy. For example, upon exposure to lasers of certain wavelengths, they facilitate localized heating, rendering them extremely effective in photothermal therapy. Additionally, their extensive surface area enables the conjugation of therapeutic agents or targeting molecules, increasing the accuracy of drug delivery systems. Moreover, AuNPs can serve as radiosensitizers, enhancing the efficacy of radiotherapy by boosting the radiation absorption in tumor cells. Here, we systematically reviewed the application and future directions of AuNPs in the diagnosis and treatment of PC. Although AuNPs have advantages in improving diagnostic and therapeutic efficacy, as well as minimizing damage to normal tissues, concerns about their potential toxicity and safety need to be comprehensively evaluated.

Knowledge mapping and research trends of exosomes in pancreatic cancer: a bibliometric analysis and review (2013-2023)

Objective

This review aims to provide a quantitative and qualitative bibliometric analysis of literature from 2013 to 2023 on the role of exosomes in PC, with the goal of identifying current trends and predicting future hotspots.

Methods

We retrieved relevant publications concerning exosomes in PC, published between 2013 and 2023, from the Web of Science Core Collection. Bibliometric analyses were conducted using VOSviewer(1.6.19), CiteSpace(6.2.R4), and Microsoft Excel (2019).

Results

A total of 624 papers were analyzed, authored by 4017 researchers from 55 countries/regions and 855 institutions, published in 258 academic journals. China (n=285, 34.42%) and the United States (n=183, 24.87%) were the most frequent contributors and collaborated closely. However, publications from China had a relatively low average number of citations (41.45 times per paper). The output of Shanghai Jiao Tong University ranked first, with 28 papers (accounting for 4.5% of the total publications). Cancers (n=31, 4.9%); published the most papers in this field. Researcher Margot Zoeller published the most papers (n=12) on this topic. Research hotspots mainly focused on the mechanisms of exosomes in PC onset and progression, the role of exosomes in PC early diagnosis and prognosis, exosomes promote the development of PC chemoresistance, and potential applications of exosomes as drug carriers for PC therapies. We observed a shift in research trends, from mechanistic studies toward clinical trials, suggesting that clinical applications will be the focus of future attention. Emerging topics were pancreatic stellate cells, diagnostic biomarkers, mesenchymal stem cells, extracellular vesicles.

Conclusion

Our scientometric and visual analysis provides a comprehensive overview of the literature on the role of exosomes in PC published during 2013-2023. This review identifies the frontiers and future directions in this area over the past decade, and is expected to provide a useful reference for researchers in this field.

Improving the prognosis of pancreatic cancer: insights from epidemiology, genomic alterations, and therapeutic challenges

Pancreatic cancer, notorious for its late diagnosis and aggressive progression, poses a substantial challenge owing to scarce treatment alternatives. This review endeavors to furnish a holistic insight into pancreatic cancer, encompassing its epidemiology, genomic characterization, risk factors, diagnosis, therapeutic strategies, and treatment resistance mechanisms. We delve into identifying risk factors, including genetic predisposition and environmental exposures, and explore recent research advancements in precursor lesions and molecular subtypes of pancreatic cancer. Additionally, we highlight the development and application of multi-omics approaches in pancreatic cancer research and discuss the latest combinations of pancreatic cancer biomarkers and their efficacy. We also dissect the primary mechanisms underlying treatment resistance in this malignancy, illustrating the latest therapeutic options and advancements in the field. Conclusively, we accentuate the urgent demand for more extensive research to enhance the prognosis for pancreatic cancer patients.

Toward Personalized Nanomedicine: The Critical Evaluation of Micro and Nanodevices for Cancer Biomarker Analysis in Liquid Biopsy

Liquid biopsy for the analysis of circulating cancer biomarkers (CBs) is a major advancement toward the early detection of cancer. In comparison to tissue biopsy techniques, liquid biopsy is relatively painless, offering multiple sampling opportunities across easily accessible bodily fluids such as blood, urine, and saliva. Liquid biopsy is also relatively inexpensive and simple, avoiding the requirement for specialized laboratory equipment or trained medical staff. Major advances in the field of liquid biopsy are attributed largely to developments in nanotechnology and microfabrication that enables the creation of highly precise chip-based platforms. These devices can overcome detection limitations of an individual biomarker by detecting multiple markers simultaneously on the same chip, or by featuring integrated and combined target separation techniques. In this review, the major advances in the field of portable and semi-portable micro, nano, and multiplexed platforms for CB detection for the early diagnosis of cancer are highlighted. A comparative discussion is also provided, noting merits and drawbacks of the platforms, especially in terms of portability. Finally, key challenges toward device portability and possible solutions, as well as discussing the future direction of the field are highlighted.

Biorecognition Engineering Technologies for Cancer Diagnosis: A Systematic Literature Review of Non-Conventional and Plausible Sensor Development Methods

Cancer is the second cause of mortality worldwide. Early diagnosis of this multifactorial disease is challenging, especially in populations with limited access to healthcare services. A vast repertoire of cancer biomarkers has been studied to facilitate early diagnosis; particularly, the use of antibodies against these biomarkers has been of interest to detect them through biorecognition. However, there are certain limitations to this approach. Emerging biorecognition engineering technologies are alternative methods to generate molecules and molecule-based scaffolds with similar properties to those presented by antibodies. Molecularly imprinted polymers, recombinant antibodies, and antibody mimetic molecules are three novel technologies commonly used in scientific studies. This review aimed to present the fundamentals of these technologies and address questions about how they are implemented for cancer detection in recent scientific studies. A systematic analysis of the scientific peer-reviewed literature regarding the use of these technologies on cancer detection was carried out starting from the year 2000 up to 2021 to answer these questions. In total, 131 scientific articles indexed in the Web of Science from the last three years were included in this analysis. The results showed that antibody mimetic molecules technology was the biorecognition technology with the highest number of reports. The most studied cancer types were: multiple, breast, leukemia, colorectal, and lung. Electrochemical and optical detection methods were the most frequently used. Finally, the most analyzed biomarkers and cancer entities in the studies were carcinoembryonic antigen, MCF-7 cells, and exosomes. These technologies are emerging tools with adequate performance for developing biosensors useful in cancer detection, which can be used to improve cancer diagnosis in developing countries.