Trends in biomarker research for cancer detection

Photoelectrochemical biosensors: Prospects of graphite carbon nitride-based sensors in prostate-specific antigen diagnosis

Prostate cancer (PCs) is very common in old age and causes many deaths. Early diagnosis and monitoring of the progress of the disease and the effectiveness of cancer treatment are critical. On the other hand, choosing a specific biomarker for PCs is essential. Prostate-specific antigen (PSA) is a specific biomarker secreted in the prostate epithelial cells, which increases in cancer cells. Between all employed sensing mechanism, electrochemical sensors based on nanomaterials have created many hopes. Meanwhile, graphite carbon nitride (g-C3N4) is interested in developing photoelectrochemical sensors due to its large surface area, stability, easy modification, and good photoelectronic properties. In this review, electrochemical sensors based on nanocomposites containing g-C3N4 have been investigated in PSA detection. After providing an overview of the characteristics of g-C3N4 and cancer biomarkers, it reviews the strategies and mechanisms involved in identifying PSA. Different approaches to photoelectrochemistry, impedimetric immunosensors, photocatalysis, and luminescence have been used in diagnostic mechanisms. Then, challenges and prospects for electrochemical sensors based on nanocomposites containing g-C3N4 in PSA detection have been analyzed. The recent review generally opens an efficient view in PSA diagnosis and the application of g-C3N4-based electrochemical sensors in personalized medicine diagnosis and treatment.

Review of single-molecule immunoassays: Non-chip and on-chip Assays

Enhancing the sensitivity of immunoassays is an important requirement in the field of immunology, especially in light of rapid developments in genetic testing, making the detection of low-abundance protein biomarkers crucial. Therefore, innovations in highly sensitive immunoassays are imperative. This demand has led to the emergence of single-molecule immunoassays (SMIs), driving advancements in early diagnostic techniques, and ushering in a new era of immunoassays. This review begins by tracing the development of immunoassays and offers a detailed discussion of SMI technology across two distinct pathways: non-chip (SMI without microfluidic chips) and on-chip (SMI with microfluidic chips). Furthermore, we evaluated and compared these methods using two pathways. In addition, this review discusses the significance of SMI techniques in the diagnosis of various diseases and their current applications in laboratory and clinical settings. The progress of SMI in commercial applications and suggestions for innovative directions are also summarized. Despite the considerable potential of SMI, these technologies face challenges in practical application, particularly in developing countries and economically disadvantaged regions. The final section of this review addresses the challenges and prospects of these technologies.

Sensors Based on Molecularly Imprinted Polymers in the Field of Cancer Biomarker Detection: A Review

Biomarkers play a pivotal role in the screening, diagnosis, prevention, and post-treatment follow-up of various malignant tumors. In certain instances, identifying these markers necessitates prior treatment due to the complex nature of the tumor microenvironment. Consequently, advancing techniques that exhibit selectivity, specificity, and enable streamlined analysis hold significant importance. Molecularly imprinted polymers (MIPs) are considered synthetic antibodies because they possess the property of molecular recognition with high selectivity and sensitivity. In recent years, there has been a notable surge in the investigation of these materials, primarily driven by their remarkable adaptability in terms of tailoring them for specific target molecules and integrating them into diverse analytical technologies. This review presents a comprehensive analysis of molecular imprinting techniques, highlighting their application in developing sensors and analytical methods for cancer detection, diagnosis, and monitoring. Therefore, MIPs offer great potential in oncology and show promise for improving the accuracy of cancer screening and diagnosis procedures.

CRISPR-Cas Systems: Programmable Nuclease Revolutionizing the Molecular Diagnosis

CRISPR-Cas system has evolved as a highly preferred genetic engineering tool to perform target gene manipulation via alteration of the guide RNA (gRNA) sequence. The ability to recognize and cleave a specific target with high precision has led to its applicability in multiple frontiers pertaining to human health and medicine. From basic research focused on understanding the molecular basis of disease to translational approach leading to early and precise disease diagnosis as well as developing effective therapeutics, the CRISPR-Cas system has proved to be a quite versatile tool. The coupling of CRISPR-Cas mediated cleavage with isothermal amplification (ISA) of target DNA, followed by a read-out using fluorescent or colorimetric reporters appears quite promising in providing a solution to the urgent need for nucleic acid-based point-of-care diagnostic. Hence, it has been recognized as a highly sophisticated molecular diagnostic tool for the detection of disease-specific biomarkers not limited to nucleic acids-based detection but also of non-nucleic acid targets such as proteins, exosomes, and other small molecules. In this review, we have presented salient features and principles of class 2 type II, V, and VI CRISPR-Cas systems represented by Cas9, Cas12, and Cas13 endonucleases which are frequently used in molecular diagnosis. The article then highlights different medical diagnostic applications of CRISPR-Cas systems focusing on the diagnosis of SARS-CoV-2, Dengue, Mycobacterium tuberculosis, and Listeria monocytogenes. Lastly, we discuss existing obstacles and potential future pathways concerning this subject in a concise manner.

A nanoparticle-assisted signal-enhancement technique for lateral flow immunoassays

Lateral flow immunoassay (LFIA), an affordable and rapid paper-based detection technology, is employed extensively in clinical diagnosis, environmental monitoring, and food safety analysis. The COVID-19 pandemic underscored the validity and adoption of LFIA in performing large-scale clinical and public health testing. The unprecedented demand for prompt diagnostic responses and advances in nanotechnology have fueled the rise of next-generation LFIA technologies. The utilization of nanoparticles to amplify signals represents an innovative approach aimed at augmenting LFIA sensitivity. This review probes the nanoparticle-assisted amplification strategies in LFIA applications to secure low detection limits and expedited response rates. Emphasis is placed on comprehending the correlation between the physicochemical properties of nanoparticles and LFIA performance. Lastly, we shed light on the challenges and opportunities in this prolific field.

Recent Advances in Electrochemiluminescence Biosensors for MicroRNA Detection

Electrochemiluminescence (ECL) as an analytical technology with a perfect combination of electrochemistry and spectroscopy has received considerable attention in bioanalysis due to its high sensitivity and broad dynamic range. Given the selectivity of bio-recognition elements and the high sensitivity of the ECL analysis technique, ECL biosensors are powerful platforms for the sensitive detection of biomarkers, achieving the accurate prognosis and diagnosis of diseases. MicroRNAs (miRNAs) are crucial biomarkers involved in a variety of physiological and pathological processes, whose aberrant expression is often related to serious diseases, especially cancers. ECL biosensors can fulfill the highly sensitive and selective requirements for accurate miRNA detection, prompting this review. The ECL mechanisms are initially introduced and subsequently categorize the ECL biosensors for miRNA detection in terms of the quenching agents. Furthermore, the work highlights the signal amplification strategies for enhancing ECL signal to improve the sensitivity of miRNA detection and finally concludes by looking at the challenges and opportunities in ECL biosensors for miRNA detection.

MoS2-Based Sensor Array for Accurate Identification of Cancer Cells with Ensemble-Modified Aptamers

In this work, we present an array-based chemical nose sensor that utilizes a set of ensemble-modified aptamer (EMAmer) probes to sense subtle physicochemical changes on the cell surface for cancer cell identification. The EMAmer probes are engineered by domain-selective incorporation of different types and/or copies of positively charged functional groups into DNA scaffolds, and their differential interactions with cancer cells can be transduced through competitive adsorption of fluorophore-labeled EMAmer probes loaded on MoS2 nanosheets. We demonstrate that this MoS2-EMAmer-based sensor array enables rapid and effective discrimination among six types of cancer cells and their mixtures with a concentration of 104 cells within 60 min, achieving a 94.4% accuracy in identifying blinded unknown cell samples. The established MoS2-EMAmer sensing platform is anticipated to show significant promise in the advancement of cancer diagnostics.

An AgPd NP-based lateral flow immunoassay for simultaneous detection of glycocholic acid and alpha-fetoprotein

Hepatocellular carcinoma (HCC) remains a leading cause of cancer-related mortality globally, ranking third in cancer deaths. Early diagnosis of HCC markers is imperative for effective prognosis and treatment. This study explores the utility of glycocholic acid (GCA) and alpha-fetoprotein (AFP) as biomarkers for liver diseases, with a specific focus on their simultaneous detection for enhanced diagnostic and prognostic capabilities. Harnessing the benefits of lateral flow immunoassay (LFIA), such as operational simplicity, speed, and accuracy, we engineered AgPd nanocomposites with antibodies targeting GCA and AFP. Under the optimized conditions, the visual detection limit for GCA was established at 50 ng mL-1 and the cut-off value at 104 ng mL-1. And for AFP, the visual detection limit was 0.1 ng mL-1 and the cut-off value was 500 ng mL-1. The accuracy and feasibility of the strips were validated through the detection of 39 actual serum samples. The results highlight the potential of LFIA as a rapid and effective tool for clinical diagnosis. The developed LFIA method not only demonstrates accuracy and feasibility but also presents a promising avenue for the early diagnosis of hepatocellular carcinoma.

Point-Of-Care Ultra-Portable Single-Molecule Bioassays for One-Health

Screening asymptomatic organisms (humans, animals, plants) with a high-diagnostic accuracy using point-of-care-testing (POCT) technologies, though still visionary holds great potential. Convenient surveillance requires easy-to-use, cost-effective, ultra-portable but highly reliable, in-vitro-diagnostic devices that are ready for use wherever they are needed. Currently, there are not yet such devices available on the market, but there are a couple more promising technologies developed at readiness-level 5: the Clustered-Regularly-Interspaced-Short-Palindromic-Repeats (CRISPR) lateral-flow-strip tests and the Single-Molecule-with-a-large-Transistor (SiMoT) bioelectronic palmar devices. They both hold key features delineated by the World-Health-Organization for POCT systems and an occurrence of false-positive and false-negative errors <1-5% resulting in diagnostic-selectivity and sensitivity >95-99%, while limit-of-detections are of few markers. CRISPR-strip is a molecular assay that, can detect down to few copies of DNA/RNA markers in blood while SiMoT immunometric and molecular test can detect down to a single oligonucleotide, protein marker, or pathogens in 0.1mL of blood, saliva, and olive-sap. These technologies can prospectively enable the systematic and reliable surveillance of asymptomatic ones prior to worsening/proliferation of illnesses allowing for timely diagnosis and swift prognosis. This could establish a proactive healthcare ecosystem that results in effective treatments for all living organisms generating diffuse and well-being at efficient costs.

Localization of multiple DNAzymes as a branchedzyme-powered nanodevice for the immunoassay of tumor biomarkers

Traditional immunoassay methods often face challenges due to the labeling procedure of protein enzymes, the use of multiple antibodies, and severe conditions. To address these limitations, we propose the concept of incorporating branchedzyme-powered nanodevices into immunoassays. In this strategy, multiple DNAzymes are localized onto gold nanoparticles (AuNPs) along with substrates. The localization format facilitates intramolecular reactions between DNAzymes and substrates, leading to accelerated kinetics of the nanodevice. Upon the formation of an immunocomplex with an antibody on a 96-well plate, the branchedzyme-powered nanodevice catalytically releases multiple fluorescent signals under ambient temperature, eliminating the need for secondary antibodies. The branched DNAzymes exhibit catalytic properties similar to those of protein enzymes, thus simplifying the assay procedure and achieving isothermal detection. Furthermore, the detection process can be controlled by the addition or deletion of cofactors. Additionally, the affinity ligand can be easily modified to construct nanodevices specific to different targets without requiring extensive redesign. This strategy has demonstrated successful quantification of tumor biomarkers such as alpha-fetoprotein (AFP) and prostate-specific antigen (PSA) at subpicomolar concentrations, showcasing its suitability for clinical applications. Consequently, the branchedzyme-powered nanodevice represents a valuable addition to the immunoassay toolbox, opening new possibilities for clinical diagnostics.

Aptamer-functionalized quantum dots as theranostic nanotools against cancer and bacterial infections: A comprehensive overview of recent trends

Aptamers (Apts) are synthetic nucleic acid ligands that can be engineered to target various molecules, including amino acids, proteins, and pharmaceuticals. Through a series of adsorption, recovery, and amplification steps, Apts are extracted from combinatorial libraries of synthesized nucleic acids. Using aptasensors in bioanalysis and biomedicine can be improved by combining them with nanomaterials. Moreover, Apt-associated nanomaterials, including liposomes, polymeric, dendrimers, carbon nanomaterials, silica, nanorods, magnetic NPs, and quantum dots (QDs), have been widely used as promising nanotools in biomedicine. Following surface modifications and conjugation with appropriate functional groups, these nanomaterials can be successfully used in aptasensing. Advanced biological assays can use Apts immobilized on QD surfaces through physical interaction and chemical bonding. Accordingly, modern QD aptasensing platforms rely on interactions between QDs, Apts, and targets to detect them. QD-Apt conjugates can be used to directly detect prostate, ovarian, colorectal, and lung cancers or simultaneously detect biomarkers associated with these malignancies. Tenascin-C, mucin 1, prostate-specific antigen, prostate-specific membrane antigen, nucleolin, growth factors, and exosomes are among the cancer biomarkers that can be sensitively detected using such bioconjugates. Furthermore, Apt-conjugated QDs have shown great potential for controlling bacterial infections such as Bacillus thuringiensis, Pseudomonas aeruginosa, Escherichia coli, Acinetobacter baumannii, Campylobacter jejuni, Staphylococcus aureus, and Salmonella typhimurium. This comprehensive review discusses recent advancements in the design of QD-Apt bioconjugates and their applications in cancer and bacterial theranostics.

Rapid and Quantitative Detection of Lung Cancer Biomarker ENOX2 Using a Novel Aptamer in an Electrochemical DNA-Based (E-DNA) Biosensor

To overcome early cancer detection challenges, diagnostic tools enabling more sensitive, rapid, and noninvasive detection are necessary. An attractive cancer target for diagnostic blood tests is human Ecto-NOX disulfide-thiol exchanger 2 (ENOX2), expressed in most human cancer types and regularly shed into blood sera. Here, we developed an electrochemical DNA-based (E-DNA) biosensor that rapidly detects physiologically relevant levels of ENOX2. To identify ENOX2-binding aptamers that could potentially be used in a biosensor, recombinantly expressed ENOX2 was used as a binding target in an oligonucleotide library pull-down that generated a highly enriched ENOX2-binding aptamer. This candidate aptamer sensitively bound ENOX2 via gel mobility shift assays. To enable this aptamer to function in an ENOX2 E-DNA biosensor, the aptamer sequence was modified to adopt two conformations, one capable of ENOX2 binding, and one with disrupted ENOX2 binding. Upon ENOX2 introduction, a conformational shift to the ENOX2 binding state resulted in changed dynamics of a redox reporter molecule, which generated a rapid, significant, and target-specific electrical current readout change. ENOX2 biosensor sensitivity was at or below the diagnostic range. The ENOX2 E-DNA biosensor design presented here may enable the development of more sensitive, rapid, diagnostic tools for early cancer detection.

Biomarkers as Biomedical Bioindicators: Approaches and Techniques for the Detection, Analysis, and Validation of Novel Biomarkers of Diseases

A biomarker is any measurable biological moiety that can be assessed and measured as a potential index of either normal or abnormal pathophysiology or pharmacological responses to some treatment regimen. Every tissue in the body has a distinct biomolecular make-up, which is known as its biomarkers, which possess particular features, viz., the levels or activities (the ability of a gene or protein to carry out a particular body function) of a gene, protein, or other biomolecules. A biomarker refers to some feature that can be objectively quantified by various biochemical samples and evaluates the exposure of an organism to normal or pathological procedures or their response to some drug interventions. An in-depth and comprehensive realization of the significance of these biomarkers becomes quite important for the efficient diagnosis of diseases and for providing the appropriate directions in case of multiple drug choices being presently available, which can benefit any patient. Presently, advancements in omics technologies have opened up new possibilities to obtain novel biomarkers of different types, employing genomic strategies, epigenetics, metabolomics, transcriptomics, lipid-based analysis, protein studies, etc. Particular biomarkers for specific diseases, their prognostic capabilities, and responses to therapeutic paradigms have been applied for screening of various normal healthy, as well as diseased, tissue or serum samples, and act as appreciable tools in pharmacology and therapeutics, etc. In this review, we have summarized various biomarker types, their classification, and monitoring and detection methods and strategies. Various analytical techniques and approaches of biomarkers have also been described along with various clinically applicable biomarker sensing techniques which have been developed in the recent past. A section has also been dedicated to the latest trends in the formulation and designing of nanotechnology-based biomarker sensing and detection developments in this field.

Exploring the immunological role and prognostic potential of PPM1M in pan-cancer

BACKGROUND

PPM1M is a member of the metal-dependent protein phosphatase family, and its role in the immunization process has not been studied in depth. In this study, we investigated the role of PPM1M in pan-cancer.

METHODS

Samples of cancer and normal tissues were obtained from the cancer genome atlas and genotype-tissue expression. Kaplan-Meier survival curves and Cox regression were used to analyze the effect of PPM1M on prognosis. Functional and pathway enrichment analyses were performed using the R package "clusterProfiler" to explore the role of PPM1M. The Sanger Box database was used to analyze the relationship between PPM1M and tumor immune checkpoint, tumor mutational burden, and microsatellite instability. The Tumor Immune Estimation Resource 2 database and CIBERSORT method were used to analyze the relationship between PPM1M and tumor-infiltrating immune cells. Finally, the cBioPortal database was used to analyze the genomic variation in PPM1M.

RESULTS

Among the variety of tumors, the expression of PPM1M was higher in normal tissues than in cancerous tissues. The expression of PPM1M is closely associated with patient prognosis, tumor immune checkpoint, tumor mutational burden, and microsatellite instability. PPM1M is closely associated with the infiltration of immune cells into the tumor microenvironment. In addition, PPM1M is involved in the regulation of several immune-related pathways.

CONCLUSION

In pan-cancer, PPM1M affects patient prognosis and may be a potential immunological biomarker. Furthermore, PPM1M may be a potential therapeutic target in tumor immunology.

Inexpensive High-Throughput Multiplexed Biomarker Detection Using Enzymatic Metallization with Cellphone-Based Computer Vision

Multiplexed biomarker detection can play a critical role in reliable and comprehensive disease diagnosis and prediction of outcome. Enzyme-linked immunosorbent assay (ELISA) is the gold standard method for immunobinding-based biomarker detection. However, this is currently expensive, limited to centralized laboratories, and usually limited to the detection of a single biomarker at a time. We present a low-cost, smartphone-based portable biosensing platform for high-throughput, multiplexed, sensitive, and quantitative detection of biomarkers from single, low-volume drops (<1 μL) of clinical samples. Biomarker binding to spotted capture antigens is converted, via enzymatic metallization, to the localized surface deposition of amplified, dry-stable, silver metal spots whose darkness is proportional to biomarker concentration. A custom smartphone application is developed, which uses real-time computer vision to enable easy optical detection of the deposited metal spots and sensitive and reproducible quantification of the biomarkers. We demonstrate the use of this platform for high-throughput, multiplexed detection of multiple viral antigen-specific antibodies from convalescent COVID-19 patient serum as well as vaccine-elicited antibody responses from uninfected vaccine-recipient serum and show that distinct multiplexed antibody fingerprints are observed among them.

Biological impact and therapeutic perspective of targeting PI3K/Akt signaling in hepatocellular carcinoma: Promises and Challenges

Cancer progression results from activation of various signaling networks. Among these, PI3K/Akt signaling contributes to proliferation, invasion, and inhibition of apoptosis. Hepatocellular carcinoma (HCC) is a primary liver cancer with high incidence rate, especially in regions with high prevalence of viral hepatitis infection. Autoimmune disorders, diabetes mellitus, obesity, alcohol consumption, and inflammation can also lead to initiation and development of HCC. The treatment of HCC depends on the identification of oncogenic factors that lead tumor cells to develop resistance to therapy. The present review article focuses on the role of PI3K/Akt signaling in HCC progression. Activation of PI3K/Akt signaling promotes glucose uptake, favors glycolysis and increases tumor cell proliferation. It inhibits both apoptosis and autophagy while promoting HCC cell survival. PI3K/Akt stimulates epithelial-to-mesenchymal transition (EMT) and increases matrix-metalloproteinase (MMP) expression during HCC metastasis. In addition to increasing colony formation capacity and facilitating the spread of tumor cells, PI3K/Akt signaling stimulates angiogenesis. Therefore, silencing PI3K/Akt signaling prevents aggressive HCC cell behavior. Activation of PI3K/Akt signaling can confer drug resistance, particularly to sorafenib, and decreases the radio-sensitivity of HCC cells. Anti-cancer agents, like phytochemicals and small molecules can suppress PI3K/Akt signaling by limiting HCC progression. Being upregulated in tumor tissues and clinical samples, PI3K/Akt can also be used as a biomarker to predict patients' response to therapy.

Two-Dimensional Graphitic Carbon Nitride (g-C3N4) Nanosheets and Their Derivatives for Diagnosis and Detection Applications

The early diagnosis of certain fatal diseases is vital for preventing severe consequences and contributes to a more effective treatment. Despite numerous conventional methods to realize this goal, employing nanobiosensors is a novel approach that provides a fast and precise detection. Recently, nanomaterials have been widely applied as biosensors with distinctive features. Graphite phase carbon nitride (g-C3N4) is a two-dimensional (2D) carbon-based nanostructure that has received attention in biosensing. Biocompatibility, biodegradability, semiconductivity, high photoluminescence yield, low-cost synthesis, easy production process, antimicrobial activity, and high stability are prominent properties that have rendered g-C3N4 a promising candidate to be used in electrochemical, optical, and other kinds of biosensors. This review presents the g-C3N4 unique features, synthesis methods, and g-C3N4-based nanomaterials. In addition, recent relevant studies on using g-C3N4 in biosensors in regard to improving treatment pathways are reviewed.

Electrochemical α-fetoprotein immunosensor based on Fe3O4NPs@covalent organic framework decorated gold nanoparticles and magnetic nanoparticles including SiO2@TiO2

The early diagnosis of major diseases such as cancer is typically a major issue for humanity. Human α-fetoprotein (AFP) as a sialylated glycoprotein is of approximately 68 kD molecular weight and is considered to be a key biomarker, and an increase in its level indicates the presence of liver, testicular, or gastric cancer. In this study, an electrochemical AFP immunosensor based on Fe₃O₄NPs@covalent organic framework decorated gold nanoparticles (Fe₃O₄ NPs@COF/AuNPs) for the electrode platform and double-coated magnetic nanoparticles (MNPs) based on SiO₂@TiO₂ (MNPs@SiO₂@TiO₂) nanocomposites for the signal amplification was fabricated. The immobilization of anti-AFP capture antibody was successfully performed on Fe₃O₄ NPs@COF/AuNPs modified electrode surface by amino-gold affinity, while the conjugation of anti-AFP secondary antibody on MNPs@SiO₂@TiO₂ was achieved by the electrostatic/ionic interactions. Transmission electron microscopy (TEM), X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR) analysis, cyclic voltammetry (CV), square wave voltammetry (SWV), and electrochemical impedance spectroscopy (EIS) techniques were used to characterize the nanostructures in terms of physical and electrochemical features. The limit of detection (LOD) was 3.30 fg mL^-1. The findings revealed that the proposed electrochemical AFP immunosensor can be effectively used to diagnose cancer.

Next-Generation Intelligent MXene-Based Electrochemical Aptasensors for Point-of-Care Cancer Diagnostics

Delayed diagnosis of cancer using conventional diagnostic modalities needs to be addressed to reduce the mortality rate of cancer. Recently, 2D nanomaterial-enabled advanced biosensors have shown potential towards the early diagnosis of cancer. The high surface area, surface functional groups availability, and excellent electrical conductivity of MXene make it the 2D material of choice for the fabrication of advanced electrochemical biosensors for disease diagnostics. MXene-enabled electrochemical aptasensors have shown great promise for the detection of cancer biomarkers with a femtomolar limit of detection. Additionally, the stability, ease of synthesis, good reproducibility, and high specificity offered by MXene-enabled aptasensors hold promise to be the mainstream diagnostic approach. In this review, the design and fabrication of MXene-based electrochemical aptasensors for the detection of cancer biomarkers have been discussed. Besides, various synthetic processes and useful properties of MXenes which can be tuned and optimized easily and efficiently to fabricate sensitive biosensors have been elucidated. Further, futuristic sensing applications along with challenges will be deliberated herein.

All on size-coded single bead set: a modular enrich-amplify-amplify strategy for attomolar level multi-immunoassay

Ultrasensitive protein analysis is of great significance for early diagnosis and biological studies. The core challenge is that many critical protein markers at extremely low aM to fM levels are difficult to accurately quantify because the target-induced weak signal may be easily masked by the surrounding background. Hence, we propose herein an ultrasensitive immunoassay based on a modular Single Bead Enrich-Amplify-Amplify (SBEAA) strategy. The highly efficient enrichment of targets on only a single bead (enrich) could confine the target-responsive signal output within a limited tiny space. Furthermore, a cascade tyramide signal amplification design enables remarkable in situ signal enhancement just affixed to the target. As a result, the efficient but space-confined fluorescence deposition on a single bead will significantly exceed the background and provide a wide dynamic range. Importantly, the SBEAA system can be modularly combined to meet different levels of clinical need regarding the detection sensitivity from aM to nM. Finally, a size-coded SBEAA set (SC-SBEAA) is also designed that allows ultrasensitive multi-immunoassay for rare samples in a single tube.

FAM46C as a Potential Marker for Pan-Cancer Prognosis and Predicting Immunotherapeutic Efficacy

Background:FAM46C is a common mutated gene in tumours. A comprehensive understanding of the relationship between FAM46C expression and pan-cancer can guide clinical prognosis and broaden the immunotherapeutic targets.

Methods: Data from The Cancer Genome Atlas and Genotype-Tissue Expression (GTEx) databases were obtained, and gene expression of different tumour types and stages was analysed. Immunohistochemical analysis was performed to detect differences in the FAM46C protein levels in normal and cancerous tissues. The genetic variation of FAM46C was characterised using cBioPortal. The clinical prognostic value of FAM46C and the impact of FAM46C expression levels on the prognosis of patients with different types of cancer were assessed based on Kaplan–Meier and Cox regression analyses. Gene set enrichment analysis (GSEA) was used to analyse the pathways associated with FAM46C. Correlations between FAM46C expression levels and immune infiltration were assessed using the TIMER2 database and CIBERSORT algorithm, and correlations between FAM46C expression and the ESTIMATE, immune and stromal scores were analysed using the ESTIMATE algorithm. In addition, we also analysed the correlation between FAM46C expression and immune activation, suppression genes and immune chemokines.

Results: The expression level of FAM46C was correlated with the prognosis of most tumours, and low expression levels often suggested a poor prognosis. FAM46C was positively correlated with the abundance of CD4+ T cells, CD8+ T cells and plasma B lymphocytes in the tumour microenvironment. FAM46C exhibited a strong correlation with immunomodulatory pathways, immunomodulatory factors and immune markers. In addition, high FAM46C expression correlated with tumour mutational burden in acute myeloid leukaemia and microsatellite instability in endometrial cancer.

Conclusion: Our study suggests that FAM46C can be a potential prognostic marker for pan-cancer, is closely associated with immune regulation and may be an immune checkpoint to guide future clinical immunotherapy.

Development of the DNA-based biosensors for high performance in detection of molecular biomarkers: More rapid, sensitive, and universal

The molecular biomarkers are molecules that are closely related to specific physiological states. Numerous molecular biomarkers have been identified as targets for disease diagnosis and biological research. To date, developing highly efficient probes for the precise detection of biomarkers has become an attractive research field which is very important for biological and biochemical studies. During the past decades, not only the small chemical probe molecules but also the biomacromolecules such as enzymes, antibodies, and nucleic acids have been introduced to construct of biosensor platform to achieve the detection of biomarkers in a highly specific and highly efficient way. Nevertheless, improving the performance of the biosensors, especially in clinical applications, is still in urgent demand in this field. A noteworthy example is the Corona Virus Disease 2019 (COVID-19) that breaks out globally in a short time in 2020. The COVID-19 was caused by the virus called SARS-CoV-2. Early diagnosis is very important to block the infection of the virus. Therefore, during these months scientists have developed dozens of methods to achieve rapid and sensitive detection of the virus. Nowadays some of these new methods have been applied for producing the commercial detection kit and help people against the disease worldwide. DNA-based biosensors are useful tools that have been widely applied in the detection of molecular biomarkers. The good stability, high specificity, and excellent biocompatibility make the DNA-based biosensors versatile in application both in vitro and in vivo. In this paper, we will review the major methods that emerged in recent years on the design of DNA-based biosensors and their applications. Moreover, we will also briefly discuss the possible future direction of DNA-based biosensors design. We believe this is helpful for people interested in not only the biosensor field but also in the field of analytical chemistry, DNA nanotechnology, biology, and disease diagnosis.

Human disease biomarker panels through systems biology

As more uses for biomarkers are sought after for an increasing number of disease targets, single-target biomarkers are slowly giving way for biomarker panels. These panels incorporate various sources of biomolecular and clinical data to guarantee a higher robustness and power of separation for a clinical test. Multifactorial diseases such as psychiatric disorders show great potential for clinical use, assisting medical professionals during the analysis of risk and predisposition, disease diagnosis and prognosis, and treatment applicability and efficacy. More specific tests are also being developed to assist in ruling out, distinguishing between, and confirming suspicions of multifactorial diseases, as well as to predict which therapy option may be the best option for a given patient's biochemical profile. As more complex datasets are entering the field, involving multi-omic approaches, systems biology has stepped in to facilitate the discovery and validation steps during biomarker panel generation. Filtering biomolecules and clinical data, pre-validating and cross-validating potential biomarkers, generating final biomarker panels, and testing the robustness and applicability of those panels are all beginning to rely on machine learning and systems biology and research in this area will only benefit from advances in these approaches.

Tumor-associated autoantibodies in ESCC screening: Detecting prevalent early-stage malignancy or predicting future cancer risk?

BACKGROUND

To assess potential roles for tumor-associated autoantibodies (TAAs) in esophageal squamous cell carcinoma (ESCC) screening: detecting early-stage malignancy, and predicting future cancer risk.

METHOD

Thirteen candidate autoantibodies identified in previous literatures were measured using multiplex serological assays in sera from cases and matched controls nested in two population-level screening cohorts in China. To evaluate the role of TAAs in detecting prevalent esophageal malignant lesions, an identification set (150 cases vs. 560 controls) and an external validation set (34 cases vs. 121 controls) were established with pre-screening sera collected ≤ 12 months prior to screening-related diagnosis. To explore the role of TAAs in predicting future ESCC risk, an exploration set (105 cases vs. 416 controls) with pre-diagnostic sera collected > 12 months before clinical diagnosis was established. Two models, the questionnaire-based model and full model additionally incorporating TAA markers, were constructed. Area under the receiver operating characteristic curve (AUC) and net reclassification improvement (NRI) were calculated to compare the performance of the two models.

FINDINGS

In the identification set, NY-ESO-1 (OR=2·12, 95% CI=1·02-4·40) and STIP1 (OR=1·83, 95% CI=1·10-3·05) were positively associated with higher risk of esophageal malignancy. Elevated MMP-7 was associated with higher risk of malignancy in females (ORfemale=5·07, 95% CI=1·30-19·71). The estimates in validation set were consistent with these results, but were close to null in exploration set. Integration of selected TAAs improved the performance of questionnaire-based models in detecting prevalent esophageal malignancy (female: AUCfull model=0·745, 95% CI=0·675-0·814, AUCquestionnaire-based model=0·658, 95% CI=0·585-0·732, NRI=0·604, P<0·0001; male: AUCfull model=0·662, 95% CI=0·596-0·728, AUCquestionnaire-based model=0·619, 95% CI=0·548-0·690, NRI=0·357, P=0·0028). This improvement was also seen in validation set, but was not similarly effective in distinguishing long-term incident cases from healthy controls.

INTERPRETATION

Serological autoantibodies against NY-ESO-1, STIP1, and MMP-7 perform well in detecting early-stage esophageal malignancy, but are less effective in predicting future ESCC risks.

FUNDING

This work was supported by the National Science & Technology Fundamental Resources Investigation Program of China (2019FY101102), the National Natural Science Foundation of China (82073626), the National Key R&D Program of China (2016YFC0901404), the Beijing-Tianjin-Hebei Basic Research Cooperation Project (J200016), the Digestive Medical Coordinated Development Center of Beijing Hospitals Authority (XXZ0204), and the Natural Science Foundation of Beijing Municipality (7182033).

The role of miRNA125b in the progression of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is one of the most common tumours worldwide, and identifying markers related to HCC is an important area of research. As a microRNA (miRNA), miRNA125b (miR-125b) plays an important role in the prediction and prognosis of HCC. In the past 10 years, with increasing research on miR-125b and HCC, the molecular mechanism of its relationship with the development of HCC has been elucidated. MiR-125b inhibits the development of HCC and is highly accurate in predicting HCC and is therefore a valuable predictive marker of HCC. This article summarizes the clinical application of miR-125b in HCC and the potential mechanism of its involvement in the progression of HCC.

CRISPR as a Diagnostic Tool

Clustered regularly interspaced short palindromic repeats (CRISPR)-Cas system has recently gained growing attention as a diagnostic tool due to its capability of specific gene targeting. It consists of Cas enzymes and a guide RNA (gRNA) that can cleave the target DNA or RNA based on the sequence of the gRNA, making it an attractive genetic engineering technique. In addition to the target-specific binding and cleavage, the trans-cleavage activity was reported for some Cas proteins, including Cas12a and Cas13a, which is to cleave the surrounding single-stranded DNA or RNA upon the target binding of Cas-gRNA complex. All these activities of the CRISPR-Cas system are based on its target-specific binding, making it applied to develop diagnostic methods by detecting the disease-related gene as well as microRNAs and the genetic variations such as single nucleotide polymorphism and DNA methylation. Moreover, it can be applied to detect the non-nucleic acids target such as proteins. In this review, we cover the various CRISPR-based diagnostic methods by focusing on the activity of the CRISPR-Cas system and the form of the target. The CRISPR-based diagnostic methods without target amplification are also introduced briefly.

Protein detection in blood with single-molecule imaging

The ability to characterize individual biomarker protein molecules in patient blood samples could enable diagnosis of diseases at an earlier stage, when treatment is typically more effective. Single-molecule imaging offers a promising approach to accomplish this goal. However, thus far, single-molecule imaging methods have not been translated into the clinical setting. The detection limit of these methods has been confined to the picomolar (10^-12 M) range, several orders of magnitude higher than the circulating concentrations of biomarker proteins present in many diseases. Here, we describe single-molecule augmented capture (SMAC), a single-molecule imaging technique to quantify and characterize individual protein molecules of interest down to the subfemtomolar (<10^-15 M) range. We demonstrate SMAC in a variety of applications with human blood samples, including the analysis of disease-associated secreted proteins, membrane proteins, and rare intracellular proteins. SMAC opens the door to the application of single-molecule imaging in noninvasive disease profiling.

Expression and Diagnostic Value of tRNA-Derived Fragments Secreted by Extracellular Vesicles in Hypopharyngeal Carcinoma

OBJECTIVE

To detect the expression level of tRNA-derived fragments secreted by extracellular vesicles in hypopharyngeal cancer and explore the influence of tRNA-derived fragments on the occurrence of hypopharyngeal cancer and lung metastasis.

METHODS

After high-speed centrifugation, tRNA, which was extracted from the extracellular vesicles of patients with hypopharyngeal cancer and healthy subjects, was sequenced using microarrays. The expression of three differentially expressed tRNAs in hypopharyngeal cancer, healthy subjects, human normal laryngeal epithelial cells and hypopharyngeal cancer line was detected by qRT-PCR. The correlation between the upregulated tRNA, as identified by qRT-PCR, and the clinicopathological features of the non-lung metastatic patients was further analyzed. Finally, the expressions of upregulated tRNA were compared between the non-lung metastatic and lung metastatic patients. The risk factors of hypopharyngeal cancer with lung metastatic were identified by the Cox regression analysis.

RESULTS

By high-speed centrifugation, extracellular vesicles were extracted successfully. It was found that a variety of tRNAs in the extracellular vesicles from patients with hypopharyngeal cancer by sequencing. qRT-PCR validation indicated that tRF-1:30-Lys-CTT-1-M2 was significantly overexpressed in hypopharyngeal cancer patients and tumor cells, especially in lung metastatic patients. It was indicated that tRF-1:30-Lys-CTT-1-M2 overexpression was closely related to such pathological features as tumor staging, differentiation grade, smoking history and drinking history. According to the Cox regression analysis, stage III-IV, smoking history, drinking history and tRF-1:30-Lys-CTT-1-M2 overexpression were independent risk factors for metastasis of hypopharyngeal cancer.

CONCLUSION

tRF-1:30-Lys-CTT-1-M2 was overexpressed in patients with hypopharyngeal cancer and was identified as an independent risk factor for lung metastasis. It can be used as a novel biomarker for the diagnosis and lung metastasis monitoring of hypopharyngeal cancer.

Solid-state nanopore analysis of human genomic DNA shows unaltered global 5-hydroxymethylcytosine content associated with early-stage breast cancer

5-Hydroxymethylcytosine (5hmC), the first oxidized form of the well-known epigenetic modification 5-methylcytosine, is an independent regulator of gene expression and therefore a potential marker for disease. Here, we report on methods developed for a selective solid-state nanopore assay that enable direct analysis of global 5hmC content in human tissue. We first describe protocols for preparing genomic DNA derived from both healthy breast tissue and stage 1 breast tumor tissue and then use our approach to probe the net abundance of the modified base in each cohort. Then, we employ empirical data to adjust for the impact of nanopore diameter on the quantification. Correcting for variations in nanopore diameter among the devices used for analysis reveals no detectable difference in global 5hmC content between healthy and tumor tissue. These results suggest that 5hmC changes may not be associated with early-stage breast cancer and instead are a downstream consequence of the disease.

A dual-signal self-checking photoelectrochemical immunosensor based on the sole composite of MIL-101(Cr) and CdSe quantum dots for the detection of α-fetoprotein

Designing a photoelectrochemical (PEC) immunosensor that can produce dual photocurrent signals which can refer to each other is a great importance but a big challenge. In this manuscript, a novel dual photocurrent signals immunosensor was constructed for the detection of α-fetoprotein (AFP). Unlike the usual method of using two composite materials to provide cathode and anode photocurrent respectively, this work applies only one compound of MIL-101 (Cr) and CdSe quantum dots (QDs). Thereinto, we found that the photocurrent polarity of MIL-101(Cr) would switch by adjusting applied voltage. And then CdSe QDs was introduced by simple ultrasound mixing to boost the dual photocurrent signals. Furthermore, in the composite of M&C, the electron transfer path between MIL-101(Cr) and CdSe QDs may switch between "Z-type" and "Ⅱ-type" by adjusting voltage. Benefiting by the dual signals, the proposed sensor can not only perform sensitively quantitative detection of α-fetoprotein (AFP), but also can intuitively estimate the accuracy and reliability of the test result by determining whether the corresponding relationship of "cathode photocurrent-analyte concentration-anode photocurrent" is established. The linear ranges of the sensing electrodes as cathode and anode are the same, both from 0.1 to 300 ng mL^-1. The limit of detection (LOD) is 0.082 ng mL^-1 (S/N = 3) when it used as an anode, and the LOD is 0.054 ng mL^-1 (S/N = 3) when it served as cathode. Furthermore, this sensor showed acceptable stability, reproducibility, specificity, and feasibility of detecting AFP in human serum, which has broad development prospects in the early clinical diagnosis.

Prognostic and Immunological Role of mRNA ac4C Regulator NAT10 in Pan-Cancer: New Territory for Cancer Research?

Background

NAT10 (also known as human N-acetyltransferase-like protein) is a critical gene that regulates N4-acetylcytidine formation in RNA, similar to the multiple regulators of N6-methyladenosine. However, the underlying functions and mechanisms of NAT10 in tumor progression and immunology are unclear.

Methods

In this study, we systematically analyzed the pan-cancer expression and correlations of NAT10, using databases including Oncomine, PrognoScan, GEPIA2, and Kaplan-Meier Plotter. The potential correlations of NAT10 with immune infiltration stages and gene marker sets were analyzed using the Tumor Immune Estimation Resource and GEPIA2.

Results

Compared with normal tissues, NAT10 showed higher expression in most cancers based on combined data from TCGA and GTEx. In different datasets, high NAT10 expression was significantly correlated with poor prognosis in adrenocortical carcinoma, head and neck squamous cell carcinoma, liver hepatocellular carcinoma, kidney renal papillary cell carcinoma, and pheochromocytoma and paraganglioma. Moreover, there were significant positive correlations between NAT10 expression and immune infiltrates, including B cells, CD8+ T cells, CD4+ T cells, neutrophils, macrophages, dendritic cells, endothelial cells, and fibroblasts in LIHC. NAT10 expression showed strong correlations with diverse immune marker gene sets in LIHC.

Conclusion

NAT10 expression affects the prognosis of pan-cancer patients and is significantly correlated with tumor immune infiltration. Furthermore, it represents a potential target for cancer therapy.

Rational Design of Dendritic Mesoporous Silica Nanoparticles' Surface Chemistry for Quantum Dot Enrichment and an Ultrasensitive Lateral Flow Immunoassay

Lateral flow immunoassays (LFIAs) have drawn much attention in point-of-care diagnostic applications, and the development of high-performance label materials is the key. In this study, the impact of the surface chemistry of dendritic mesoporous silica nanoparticles (DMSNs) on their enrichment performance toward quantum dots (QDs) and signal amplification of the resultant DMSNs-QDs as label materials have been investigated. A series of DMSNs with controllable amino/thiol group densities have been synthesized. It is demonstrated that the amino groups are beneficial for QD fluorescence preservation, owing to the amino-based surface passivation, while the thiol groups are responsible for increasing the loading capacity of QDs due to the thiol-metal coordination. The optimized DMSNs-QDs labels with an amino density of 153 μmol g^-1 and a thiol density of 218 μmol g^-1 displayed sufficient QD fluorescence preservation (89.4%) and high QD loading capacity (1.55 g g^-1). Ultrasensitive detection of serum amyloid A (SAA) with a detection limit of 10 pg mL^-1 with the naked eye was achieved, which is 1 order of magnitude higher than that reported in the literature. This study provides insights into the development of advanced label materials and an ultrasensitive LFIA for future bioassay applications.

Candidate Molecular Biomarkers for the Non- Invasive Detection of Colorectal Cancer using Gene Expression Profiling

Background & Objective:

olorectal Cancer (CRC) is the third most common cancer after prostate (breast in women) and lung cancer; it is also the third cause of cancer deaths reported in both men and women in 2020. Currently, the most commonly used diagnostic tools for CRC are colonoscopy, serological methods, and other imaging techniques. Despite the benefits and abilities of these methods, each of them has disadvantages that reduce its functionality and acceptance. The aim of this study was identifying specific and non-invasive genetic biomarkers to diagnose colorectal cancer.

Methods:

In this study, changes in the expression of HLTF and SEPT9 genes were evaluated by Real Time PCR in blood and tissue samples of CRC patients. A total of 100 samples (50 Blood and 50 Tissue samples) were evaluated with a definite diagnosis of CRC in Firoozgar Hspital, Tehran, Iran, in 2018. The QPCR method was used to compare the expression of candidate genes between the patients group and control group in both samples. Sensitivity and specificity of the test were examined using ROC curve analysis.

Results:

The results showed a significant down-regulation in the expression of both selected genes in tissue and peripheral blood in the various stages of the CRC. The sensitivity and specifity of both genes was about 80%.

Conclusion:

The findings showed that the two candidate genes can be suggested as specific biomarkers for diagnosis of CRC using the peripheral blood as a non-invasive method. For a definite conclusion, more research is needed.

The Role of Dendritic Mesoporous Silica Nanoparticles' Size for Quantum Dots Enrichment and Lateral Flow Immunoassay Performance

Using dendritic mesoporous silica nanoparticles (DMSNs) for quantum dots (QDs) enrichment and signal amplification is an emerging strategy for improving the detection sensitivity of lateral flow immunoassay (LFIA). In this study, a new and convenient approach is developed to prepare water-dispersible DMSNs-QDs. A series of DMSNs with various diameters (138, 251, 368, and 471 nm) are studied for loading QDs and LFIA applications. The resultant water-dispersible DMSNs-QDs exhibit a high fluorescence retention of 81.8%. The increase in particle size from 138 to 471 nm results in an increase in loading capacity of QDs and a decrease in binding quantity of the DMSNs-QDs in the test line of LFIA. This trade-off leads to an optimal DMSNs-QDs size of 368 nm with a limit of detection reaching 10 pg mL^-1 (equivalent to 9.0 × 10^-14 m) for the detection of C-reactive protein, which is nearly an order of magnitude more sensitive than the literature. To the best of the authors' knowledge, this study is the first to demonstrate the distinctive role of DMSN's size for QDs enrichment and LFIA. The strategy developed from this work is useful for the rational design of high-quality QDs-based nanoparticles for ultrasensitive detection.

Investigating Complex Samples with Molograms of Low-Affinity Binders

In vitro diagnostics relies on the quantification of minute amounts of a specific biomolecule, called biomarker, from a biological sample. The majority of clinically relevant biomarkers for conditions beyond infectious diseases are detected by means of binding assays, where target biomarkers bind to a solid phase and are detected by biochemical or physical means. Nonspecifically bound biomolecules, the main source of variation in such assays, need to be washed away in a laborious process, restricting the development of widespread point-of-care diagnostics. Here, we show that a diffractometric assay provides a new, label-free possibility to investigate complex samples, such as blood plasma. A coherently arranged sub-micron pattern, that is, a peptide mologram, is created to demonstrate the insensitivity of this diffractometric assay to the unwanted masking effect of nonspecific interactions. In addition, using an array of low-affinity binders, we also demonstrate the feasibility of molecular profiling of blood plasma in real time and show that individual patients can be differentiated based on the binding kinetics of circulating proteins.

Diagnostic model for pancreatic cancer using a multi-biomarker panel

Purpose

Diagnostic biomarkers of pancreatic ductal adenocarcinoma (PDAC) have been used for early detection to reduce its dismal survival rate. However, clinically feasible biomarkers are still rare. Therefore, in this study, we developed an automated multi-marker enzyme-linked immunosorbent assay (ELISA) kit using 3 biomarkers (leucine-rich alpha-2-glycoprotein [LRG1], transthyretin [TTR], and CA 19-9) that were previously discovered and proposed a diagnostic model for PDAC based on this kit for clinical usage.

Methods

Individual LRG1, TTR, and CA 19-9 panels were combined into a single automated ELISA panel and tested on 728 plasma samples, including PDAC (n = 381) and normal samples (n = 347). The consistency between individual panels of 3 biomarkers and the automated multi-panel ELISA kit were accessed by correlation. The diagnostic model was developed using logistic regression according to the automated ELISA kit to predict the risk of pancreatic cancer (high-, intermediate-, and low-risk groups).

Results

The Pearson correlation coefficient of predicted values between the triple-marker automated ELISA panel and the former individual ELISA was 0.865. The proposed model provided reliable prediction results with a positive predictive value of 92.05%, negative predictive value of 90.69%, specificity of 90.69%, and sensitivity of 92.05%, which all simultaneously exceed 90% cutoff value.

Conclusion

This diagnostic model based on the triple ELISA kit showed better diagnostic performance than previous markers for PDAC. In the future, it needs external validation to be used in the clinic.

Aptamer-Linked CRISPR/Cas12a-Based Immunoassay

The clustered regularly interspaced short palindromic repeat (CRISPR)/Cas system has shown great promising applications in the area of nucleic acid biosensing. However, because of the dearth of versatile signal transduction strategies, this system is usually compromised to low versatility, moderate sensitivity, and complex operation for non-nucleic acid targets, limiting its clinical transition. Herein, we describe a direct method to establish the correlation between non-nucleic acid analytes and the CRISPR/Cas12a system using a series of rationally designed, aptamer-flanked activator DNA strands, which enable ultrasensitive detection of biomarkers from different species, greatly broadening the possibility of the CRISPR/Cas system in bioanalysis. Meanwhile, the signal output is highly optional and the sensing principle is akin to the traditional enzyme-linked immunosorbent assay (ELISA), so it can be directly imposed on the currently available ELISA platform, further facilitating its application in medical diagnostics.

MUC Glycoproteins: Potential Biomarkers and Molecular Targets for Cancer Therapy

MUC proteins have great significance as prognostic and diagnostic markers as well as a potential target for therapeutic interventions in most cancers of glandular epithelial origin. These are high molecular weight glycosylated proteins located in the epithelial lining of several tissues and ducts. Mucins belong to a heterogeneous group of large O-glycoproteins that can be either secreted or membrane-bound. Glycosylation, a post-translational modification affects the biophysical, functional and biochemical properties and provides structural complexity for these proteins. Aberrant expression and glycosylation of mucins contribute to tumour survival and proliferation in many cancers, which in turn activates numerous signalling pathways such as NF-kB, ERα, HIF, MAPK, p53, c-Src, Wnt and JAK-STAT, etc. This subsequently induces cancer cell growth, proliferation and metastasis. The present review mainly demonstrates the functional aspects of MUC glycoproteins along with its unique signalling mechanism and role of aberrant glycosylation in cancer progression and therapeutics. The importance of MUC proteins and its subtypes in a wide spectrum of cancers including but not limited to breast cancer, colorectal cancer, endometrial and cervical cancer, lung cancer, primary liver cancer, pancreatic cancer, prostate cancer and ovarian cancer has been exemplified with significance in targeting the same. Several patents associated with the MUC proteins in the field of cancer therapy are also emphasized in the current review.

Highly sensitive electrochemical detection of cancer biomarker based on anti-EpCAM conjugated molybdenum disulfide grafted reduced graphene oxide nanohybrid

An ultrasensitive, electrochemical biosensor has been fabricated by utilizing molybdenum disulfide (MoS₂) grafted reduced graphene oxide (MoS₂@rGO) nanohybrid as a sensing platform. Biomolecular-assisted synthetic method was adopted to synthesize MoS₂@rGO nanohybrid, where L-cys was used to reduce GO. The MoS₂@rGO nanohybrid exhibits improved electrochemical performance when it has been electrophoretically deposited onto the indium tin oxide (ITO) coated glass substrate. Further, epithelialcell adhesion moleculeantibodies (anti-EpCAM) specific to cancer biomarker has been covalently immobilized on the MoS₂@rGO/ITO electrodes for label-free detection of EpCAM. Electrochemical results confirm that anti-EpCAM/MoS₂@rGO/ITO based biosensor can detect EpCAM in the concentration range of 0.001-20 ng mL^-1 with a detection limit of 44.22 fg mL^-1 (S/N = 3). The biosensor's excellent analytical performance has been attributed to the efficient immobilization of EpCAM antibodies on the MoS₂@rGO surface, which results in high specificity for EpCAM antigen. The fabricated biosensor showed good selectivity, reproducibility, and stability. The successful detection of EpCAM antigen in spiked samples (human saliva, serum and urine) makes this platform an alternative method for early screening of cancer biomarker.

Differentiation of Cancer Stem Cells through Nanoparticle Surface Engineering

Cancer stem cells (CSCs) are a crucial therapeutic target because of their role in resistance to chemo- and radiation therapy, metastasis, and tumor recurrence. Differentiation therapy presents a potential strategy for "defanging" CSCs. To date, only a limited number of small-molecule and nanomaterial-based differentiating agents have been identified. We report here the integrated use of nanoparticle engineering and hypothesis-free sensing to identify nanoparticles capable of efficient differentiation of CSCs into non-CSC phenotypes. Using this strategy, we identified a nanoparticle that induces CSC differentiation by increasing intracellular reactive oxygen species levels. Importantly, this unreported phenotype is more susceptible to drug treatment than either CSCs or non-CSCs, demonstrating a potentially powerful strategy for anticancer therapeutics.

Mitochondria-Targeted Sensor Array with Aggregation-Induced Emission Luminogens for Identification of Various Cells

Accurate discrimination of cancerous cells is a good solution for early diagnosis of tumors. The mitochondrion plays an important role in cells. Herein, the five aggregation-induced emission luminogens (AIEgens) with various double positive charges are synthesized to image mitochondria. Tetraphenylethylene (TPE) molecules are modified by methoxy groups, conjugated donor-acceptor, and different positive charges to achieve multicolor emission. The five AIEgens form the PTx-Sa (positive mitochondria-target molecular sensor array) to perform cross-fluorescence response based on the mitochondria-targeted imaging to achieve the discrimination of various cells. Principal component analysis of the cross-response fluorescence data of PTx-Sa shows that 100% accurate identification of various cells, including cancer cells and normal cells, digestive tract cancer cells, gastric cancer cells, and mixed gastric cancer cells. By support vector machine to show the predictive ability of PTx-Sa to unknown cells by using blind samples. This is the first time to apply mitochondria-targeted sensor array to identification of various cells.