Self-Normalized Detection of ANXA3 from Untreated Urine of Prostate Cancer Patients without Digital Rectal Examination

Integrated machine learning identifies epithelial cell marker genes for improving outcomes and immunotherapy in prostate cancer

BACKGROUND

Prostate cancer (PCa), a globally prevalent malignancy, displays intricate heterogeneity within its epithelial cells, closely linked with disease progression and immune modulation. However, the clinical significance of genes and biomarkers associated with these cells remains inadequately explored. To address this gap, this study aimed to comprehensively investigate the roles and clinical value of epithelial cell-related genes in PCa.

METHODS

Leveraging single-cell sequencing data from GSE176031, we conducted an extensive analysis to identify epithelial cell marker genes (ECMGs). Employing consensus clustering analysis, we evaluated the correlations between ECMGs, prognosis, and immune responses in PCa. Subsequently, we developed and validated an optimal prognostic signature, termed the epithelial cell marker gene prognostic signature (ECMGPS), through synergistic analysis from 101 models employing 10 machine learning algorithms across five independent cohorts. Additionally, we collected clinical features and previously published signatures from the literature for comparative analysis. Furthermore, we explored the clinical utility of ECMGPS in immunotherapy and drug selection using multi-omics analysis and the IMvigor cohort. Finally, we investigated the biological functions of the hub gene, transmembrane p24 trafficking protein 3 (TMED3), in PCa using public databases and experiments.

RESULTS

We identified a comprehensive set of 543 ECMGs and established a strong correlation between ECMGs and both the prognostic evaluation and immune classification in PCa. Notably, ECMGPS exhibited robust predictive capability, surpassing traditional clinical features and 80 published signatures in terms of both independence and accuracy across five cohorts. Significantly, ECMGPS demonstrated significant promise in identifying potential PCa patients who might benefit from immunotherapy and personalized medicine, thereby moving us nearer to tailored therapeutic approaches for individuals. Moreover, the role of TMED3 in promoting malignant proliferation of PCa cells was validated.

CONCLUSIONS

Our findings highlight ECMGPS as a powerful tool for improving PCa patient outcomes and supply a robust conceptual framework for in-depth examination of PCa complexities. Simultaneously, our study has the potential to develop a novel alternative for PCa diagnosis and prognostication.

Comprehensive analysis the diagnosis, malignant progression and immune infiltrate of ANXA6 in prostate cancer

BACKGROUND

Annexins (ANXAs) play a crucial role in the development and progression of tumors. However, their specific involvement in prostate cancer (PCa) remains unclear.

OBJECTIVE

To investigate the function and clinical significance of key ANXAs in PCa.

METHODS

Multiple databases were used to analyze the expression levels, genetic variations, potential prognostic value and clinical significance of ANXAs in PCa. Then, the co-expressed genes of ANXA6 were identified, and the correlation between ANXA6 and immune cell infiltration was validated using the Tumor Immune Estimation Resource (TIMER) database. Additionally, in vitro assays such as Cell Counting Kit-8 (CCK-8), Colony Formation, Transwell and T-cell Chemotaxis assays were conducted to validate the functions of ANXA6. Moreover, multiple types of in vivo assays were performed to further validate the identified ANXA6 functions.

RESULTS

The results demonstrated that ANXA2, ANXA6 and ANXA8 were significantly downregulated in PCa. ANXA6 upregulation was significantly associated with improved PCa patients' overall survival. Enrichment analysis revealed that ANXA6 and its co-expressed genes were involved in tumor progression, and ANXA6 overexpression could effectively inhibit the proliferation, migration and invasion of PC-3 cells. In vivo studies also demonstrated that ANXA6 overexpression suppressed tumor growth. Importantly, ANXA6 was found to promote the chemotaxis of CD4+ T cells and CD8+ T cells towards PC-3 cells, and the overexpression of ANXA6 in PC-3 cells promoted the polarization of macrophages into M1 macrophages in the supernatant of PCa cells.

CONCLUSIONS

ANXA6 demonstrated promising potential for consideration as a prognostic biomarker in PCa as it was found to play key roles in regulating immune cell infiltration and the malignant progression to PCa.

Ultrasensitive Electrochemical Immunosensors Using Nanobodies as Biocompatible Sniffer Tools of Agricultural Contaminants and Human Disease Biomarkers

Nanobodies (Nbs) are known as camelid single-domain fragments or variable heavy chain antibodies (VHH) that in vitro recognize the antigens (Ag) similar to full-size antibodies (Abs) and in vivo allow immunoreactions with biomolecule cavities inaccessible to conventional Abs. Currently, Nbs are widely used for clinical treatments due to their remarkably improved performance, ease of production, thermal robustness, superior physical and chemical properties. Interestingly, Nbs are also very promising bioreceptors for future rapid and portable immunoassays, compared to those using unstable full-size antibodies. For all these reasons, Nbs are excellent candidates in ecological risk assessments and advanced medicine, enabling the development of ultrasensitive biosensing platforms. In this review, immobilization strategies of Nbs on conductive supports for enhanced electrochemical immune detection of food contaminants (Fcont) and human biomarkers (Hbio) are discussed. In the case of Fcont, the direct competitive immunoassay detection using coating antigen solid surface is the most commonly used approach for efficient Nbs capture which was characterized with cyclic voltammetry (CV) and differential pulse voltammetry (DPV) when the signal decays for increasing concentrations of free antigen prepared in aqueous solutions. In contrast, for the Hbio investigations on thiolated gold electrodes, increases in amperometric and electrochemical impedance spectroscopy (EIS) signals were recorded, with increases in the antigen concentrations prepared in PBS or spiked real human samples.

Prostate cancer detection: a systematic review of urinary biosensors

BACKGROUND

Current diagnostic methods for prostate cancer are invasive and lack specificity towards aggressive forms of the disease, which can lead to overtreatment. A new class of non-invasive alternatives is under development, in which urinary biomarkers are detected using biosensing devices to offer rapid and accurate prostate cancer diagnosis. These different approaches are systematically reviewed and their potential for translation to clinical practice is evaluated.

METHODS

A systematic review of the literature was performed in May 2021 using PubMed Medline database, Embase, and Web of Science. The objective was to review the structural designs and performance of biosensors tested on urine samples from patients with prostate cancer.

RESULTS

A total of 76 records were identified. After screening and eligibility, 14 articles were included and are discussed in this paper. The biosensors were discussed based on the target biomarkers and detection technologies used, as well as the results of the clinical studies. Most of the works reported good discrimination between patients with prostate cancer and controls.

CONCLUSIONS

This review highlights the potential of urinary biosensors for non-invasive prostate cancer detection. However, clinical studies have so far only been conducted on small cohorts of patient, with large scale trials still needed to validate the proposed approaches. Overall, the consensus arising from the proof of concepts studies reviewed here, is that an adequate combination of biomarkers into multiplex biosensor platforms is required to achieve accurate diagnostic tests. Furthermore, whether such devices can discriminate between aggressive and indolent cancer has not yet been addressed, because it entails optimized biomarkers panels and long-term clinical trials.

Large-Area Interfaces for Single-Molecule Label-free Bioelectronic Detection

Bioelectronic transducing surfaces that are nanometric in size have been the main route to detect single molecules. Though enabling the study of rarer events, such methodologies are not suited to assay at concentrations below the nanomolar level. Bioelectronic field-effect-transistors with a wide (μm²-mm²) transducing interface are also assumed to be not suited, because the molecule to be detected is orders of magnitude smaller than the transducing surface. Indeed, it is like seeing changes on the surface of a one-kilometer-wide pond when a droplet of water falls on it. However, it is a fact that a number of large-area transistors have been shown to detect at a limit of detection lower than femtomolar; they are also fast and hence innately suitable for point-of-care applications. This review critically discusses key elements, such as sensing materials, FET-structures, and target molecules that can be selectively assayed. The amplification effects enabling extremely sensitive large-area bioelectronic sensing are also addressed.

Annexin A3 and cancer

Annexin A3 (ANXA3), an annexin family member, contains 36 kDa and 33 kDa isoforms. Similar to other annexin members, ANXA3 plays an important role in the development of human diseases. Recent studies have reported that abnormal ANXA3 expression is closely associated with the development, progression, metastasis, drug resistance and prognosis of several malignant tumours, such as breast cancer, lung cancer and hepatocellular carcinoma. ANXA3 exerts its role by regulating cell proliferation, migration and apoptosis via the phosphatidylinositol-3 kinase/Akt, nuclear factor-κB (NF-κB), c-JUN N-terminal kinase, extracellular signal-regulated kinase and hypoxia-inducible factor-1 signalling pathways. ANXA3 may act as a novel target for the early diagnosis and treatment of tumours. The present review summarises the recent progress in the role of ANXA3 and its regulatory pathways in tumours.

Non-invasive Urine Test for Molecular Classification of Clinical Significance in Newly Diagnosed Prostate Cancer Patients

Objective: To avoid over-treatment of low-risk prostate cancer patients, it is important to identify clinically significant and insignificant cancer for treatment decision-making. However, no accurate test is currently available.

Methods: To address this unmet medical need, we developed a novel gene classifier to distinguish clinically significant and insignificant cancer, which were classified based on the National Comprehensive Cancer Network risk stratification guidelines. A non-invasive urine test was developed using quantitative mRNA expression data of 24 genes in the classifier with an algorithm to stratify the clinical significance of the cancer. Two independent, multicenter, retrospective and prospective studies were conducted to assess the diagnostic performance of the 24-Gene Classifier and the current clinicopathological measures by univariate and multivariate logistic regression and discriminant analysis. In addition, assessments were performed in various Gleason grades/ISUP Grade Groups.

Results: The results showed high diagnostic accuracy of the 24-Gene Classifier with an AUC of 0.917 (95% CI 0.892–0.942) in the retrospective cohort (n = 520), AUC of 0.959 (95% CI 0.935–0.983) in the prospective cohort (n = 207), and AUC of 0.930 (95% 0.912-CI 0.947) in the combination cohort (n = 727). Univariate and multivariate analysis showed that the 24-Gene Classifier was more accurate than cancer stage, Gleason score, and PSA, especially in the low/intermediate-grade/ISUP Grade Group 1–3 cancer subgroups.

Conclusions: The 24-Gene Classifier urine test is an accurate and non-invasive liquid biopsy method for identifying clinically significant prostate cancer in newly diagnosed cancer patients. It has the potential to improve prostate cancer treatment decisions and active surveillance.

Electrical Cartridge Sensor Enables Reliable and Direct Identification of MicroRNAs in Urine of Patients

Urinary miRNAs are biomarkers that demonstrate considerable promise for the noninvasive diagnosis and prognosis of diseases. However, because of background noise resulting from complex physiological features of urine, instability of miRNAs, and their low concentration, accurate monitoring of miRNAs in urine is challenging. To address these limitations, we developed a urine-based disposable and switchable electrical sensor that enables reliable and direct identification of miRNAs in patient urine. The proposed sensing platform combining disposable sensor chips composed of a reduced graphene oxide nanosheet and peptide nucleic acid facilitates the label-free detection of urinary miRNAs with high specificity and sensitivity. Using real-time detection of miRNAs in patient urine without pretreatment or signal amplification, this sensor allows rapid, direct detection of target miRNAs in a broad dynamic range with a detection limit down to 10 fM in human urine specimens within 20 min and enables simultaneous quantification of multiple miRNAs. As confirmed using a blind comparison with the results of pathological examination of patients with prostate cancer, the sensor offers the potential to improve the accuracy of early diagnosis before a biopsy is taken. This study holds the usefulness of the practical sensor for the clinical diagnosis of urological diseases.

Noninvasive Precision Screening of Prostate Cancer by Urinary Multimarker Sensor and Artificial Intelligence Analysis

Screening for prostate cancer relies on the serum prostate-specific antigen test, which provides a high rate of false positives (80%). This results in a large number of unnecessary biopsies and subsequent overtreatment. Considering the frequency of the test, there is a critical unmet need of precision screening for prostate cancer. Here, we introduced a urinary multimarker biosensor with a capacity to learn to achieve this goal. The correlation of clinical state with the sensing signals from urinary multimarkers was analyzed by two common machine learning algorithms. As the number of biomarkers was increased, both algorithms provided a monotonic increase in screening performance. Under the best combination of biomarkers, the machine learning algorithms screened prostate cancer patients with more than 99% accuracy using 76 urine specimens. Urinary multimarker biosensor leveraged by machine learning analysis can be an important strategy of precision screening for cancers using a drop of bodily fluid.

Establishing a Urine-Based Biomarker Assay for Prostate Cancer Risk Stratification

One of the major features of prostate cancer (PCa) is its heterogeneity, which often leads to uncertainty in cancer diagnostics and unnecessary biopsies as well as overtreatment of the disease. Novel non-invasive tests using multiple biomarkers that can identify clinically high-risk cancer patients for immediate treatment and monitor patients with low-risk cancer for active surveillance are urgently needed to improve treatment decision and cancer management. In this study, we identified 14 promising biomarkers associated with PCa and tested the performance of these biomarkers on tissue specimens and pre-biopsy urinary sediments. These biomarkers showed differential gene expression in higher- and lower-risk PCa. The 14-Gene Panel urine test (PMP22, GOLM1, LMTK2, EZH2, GSTP1, PCA3, VEGFA, CST3, PTEN, PIP5K1A, CDK1, TMPRSS2, ANXA3, and CCND1) was assessed in two independent prospective and retrospective urine study cohorts and showed high diagnostic accuracy to identify higher-risk PCa patients with the need for treatment and lower-risk patients for surveillance. The AUC was 0.897 (95% CI 0.939–0.855) in the prospective cohort (n = 202), and AUC was 0.899 (95% CI 0.964–0.834) in the retrospective cohort (n = 97). In contrast, serum PSA and Gleason score had much lower accuracy in the same 202 patient cohorts [AUC was 0.821 (95% CI 0.879–0.763) for PSA and 0.860 (95% CI 0.910–0.810) for Gleason score]. In addition, the 14-Gene Panel was more accurate at risk stratification in a subgroup of patients with Gleason scores 6 and 7 in the prospective cohort (n = 132) with AUC of 0.923 (95% CI 0.968–0.878) than PSA [AUC of 0.773 (95% CI 0.852–0.794)] and Gleason score [AUC of 0.776 (95% CI 0.854–0.698)]. Furthermore, the 14-Gene Panel was found to be able to accurately distinguish PCa from benign prostate with AUC of 0.854 (95% CI 0.892–0.816) in a prospective urine study cohort (n = 393), while PSA had lower accuracy with AUC of 0.652 (95% CI 0.706–0.598). Taken together, the 14-Gene Panel urine test represents a promising non-invasive tool for detection of higher-risk PCa to aid treatment decision and lower-risk PCa for active surveillance.

Design and Implementation of a pH Sensor for Micro Solution Based on Nanostructured Ion-Sensitive Field-Effect Transistor

pH sensors based on a nanostructured ion-sensitive field-effect transistor have characteristics such as fast response, high sensitivity and miniaturization, and they have been widely used in biomedicine, food detection and disease monitoring. However, their performance is affected by many factors, such as gate dielectric material, channel material and channel thickness. In order to obtain a pH sensor with high sensitivity and fast response, it is necessary to determine the appropriate equipment parameters, which have high processing cost and long production time. In this study, a nanostructured ion-sensitive field-effect transistor was developed based on the SILVACO technology computer-aided design (TCAD) simulator. Through experiments, we analyzed the effects of the gate dielectric material, channel material and channel thickness on the electrical characteristics of the nanostructured field-effect transistor. Based on simulation results, silicon nitride was selected as the gate dielectric layer, while indium oxide was chosen as the channel layer. The structure and parameters of the dual channel ion-sensitive field-effect transistor were determined and discussed in detail. Finally, according to the simulation results, a pH sensor based on the nanostructured ion-sensitive field-effect transistor was fabricated. The accuracy of simulation results was verified by measuring the output, transfer and pH characteristics of the device. The fabricated pH sensor had a subthreshold swing as low as 143.19 mV/dec and obtained an actual sensitivity of 88.125 mV/pH. In addition, we also tested the oxidation reaction of hydrogen peroxide catalyzed by horseradish peroxidase, and the sensitivity was up to 144.26 pA mol⁻¹ L⁻¹, verifying that the ion-sensitive field-effect transistor (ISFET) can be used to detect the pH of micro solution, and then combine the enzyme-linked assay to detect the concentration of protein, DNA, biochemical substances, biomarkers, etc.

Annexin A3 in sepsis: novel perspectives from an exploration of public transcriptome data

According to publicly available transcriptome datasets, the abundance of Annexin A3 (ANXA3) is robustly increased during the course of sepsis; however, no studies have examined the biological significance or clinical relevance of ANXA3 in this pathology. Here we explored this interpretation gap and identified possible directions for future research. Based on reference transcriptome datasets, we found that ANXA3 expression is restricted to neutrophils, is upregulated in vitro after exposure to plasma obtained from septic patients, and is associated with adverse clinical outcomes. Secondly, an increase in ANXA3 transcript abundance was also observed in vivo, in the blood of septic patients in multiple independent studies. ANXA3 is known to mediate calcium-dependent granules-phagosome fusion in support of microbicidal activity in neutrophils. More recent work has also shown that ANXA3 enhances proliferation and survival of tumour cells via a Caspase-3-dependent mechanism. And this same molecule is also known to play a critical role in regulation of apoptotic events in neutrophils. Thus, we posit that during sepsis ANXA3 might either play a beneficial role, by facilitating microbial clearance and resolution of the infection; or a detrimental role, by prolonging neutrophil survival, which is known to contribute to sepsis-mediated organ damage.

Fluorescent Lipo-Beads for the Sensitive Detection of Phospholipase A2 and Its Inhibitors

Phospholipase A₂ (PLA₂) is a membrane lytic enzyme that is present in many organisms. Human PLA₂ has emerged as a potential biomarker as well as a therapeutic target for several diseases including cancer, cardiovascular diseases, and some inflammatory diseases. The current study focuses on the development of lipo-beads that are very reactive and highly sensitive to PLA₂. To develop the best supported lipid bilayer formulation, several lipid combinations were investigated using 10 μm porous silica beads. The reactivity of PLA₂ was monitored via the decrease in particle fluorescence because of the release of entrapped fluorescent dye from the particle pores or the disintegration of a fluorescent lipid constituted on the bilayer upon lipid hydrolysis using flow cytometry. The enzyme binding studies indicate that lipo-beads with bulky fluorescent tags in the lipid head group and anionic lipids produce a more pronounced response. The kinetic studies suggest that these lipo-beads are very reactive with PLA₂ and can generate a detectable signal in less than 5 min. The enzyme inhibition studies were also conducted with two known PLA₂ inhibitors, varespladib and quercetin. We find that quercetin can hydrolyze the supported membrane, and thus inhibition of PLA₂ is not observed; however, varespladib has shown significant PLA₂ inhibition on lipo-beads. We have demonstrated that our lipo-bead-based approach can detect annexin-3, a known disease biomarker, as low as 10 nM within 5 min after incubation.

Expression and significance of Annexin A3 in the osteosarcoma cell lines HOS and U2OS

Annexin A3 (ANXA3) is highly expressed in different types of cancers, but the impact of ANXA3 in bone tumors is still not clear. In the present study, the expression of ANXA3 in osteosarcoma cells was first confirmed by cellular immunofluorescence. Reverse transcription‑quantitative polymerase chain reaction (RT‑qPCR) and western blot analysis were used to detect the expression of ANXA3 in osteoblasts in the osteosarcoma cell lines U2OS and HOS. Furthermore, small interfering (si)‑RNA were transfected into U2OS and HOS cells via a liposome‑mediated method. Then once ANXA3 had been successfully downregulated in U2OS and HOS cells, the cells were collected and total protein was extracted after 48 h of transfection. Western blot analysis was used to confirm successful ANXA3 transfection into osteosarcoma cells and the apoptotic rate of HOS and U2OS was detected by flow cytometry. The expression of ANXA3 in the osteosarcoma cell lines HOS and U2OS were first observed by confocal laser scanning microscopy, and was then detected by RT‑qPCR and western blotting. The mRNA and protein levels of ANXA3 in the osteosarcoma cell lines HOS and U2OS were significantly increased compared with osteoblasts, particularly in HOS cells. When siRNA was transfected into HOS and U2OS cells, the protein expression level of ANXA3 was measured via western blotting. The results indicated that the expression of ANXA3 was significantly decreased. In addition, to determine whether ANXA3 knockdown induced cell apoptosis, the present study analyzed the apoptotic rate by flow cytometry. The results revealed that ANXA3 knockdown markedly increased HOS and U2OS cell apoptosis. To the best of our knowledge, the present study is the first to confirm that ANXA3 is highly expressed in the osteosarcoma cell lines HOS and U2OS. In addition, downregulation of ANXA3 expression in HOS and U2OS cells could increase apoptotic ability.

A Novel Blood-Based Colorectal Cancer Diagnostic Technology Using Electrical Detection of Colon Cancer Secreted Protein-2

Colorectal cancer (CRC) is the second-leading cause of cancer-related mortality worldwide, which may be effectively reduced by early screening. Colon cancer secreted protein-2 (CCSP-2) is a promising blood marker for CRC. An electric-field effect colorectal sensor (E-FECS), an ion-sensitive field-effect transistor under dual gate operation with nanostructure is developed, to quantify CCSP-2 directly from patient blood samples. The sensing performance of the E-FECS is verified in 7 controls and 7 CRC samples, and it is clinically validated on 30 controls, 30 advanced adenomas, and 81 CRC cases. The concentration of CCSP-2 is significantly higher in plasma samples from CRC and advanced adenoma compared with controls (both P < 0.001). Sensitivity and specificity for CRC versus controls are 44.4% and 86.7%, respectively (AUC of 0.67), and 43.3% and 86.7%, respectively, for advanced adenomas (AUC of 0.67). CCSP-2 detects a greater number of CRC cases than carcinoembryonic antigen does (45.6% vs 24.1%), and the combination of the two markers detects an even greater number of cases (53.2%). The E-FECS system successfully detects CCSP-2 in a wide range of samples including early stage cancers and advanced adenoma. CCSP-2 has potential for use as a blood-based biomarker for CRC.

Fully Packaged Portable Thin Film Biosensor for the Direct Detection of Highly Pathogenic Viruses from On-Site Samples

The thin film transistor (TFT) is a promising biosensor system with great sensitivity, label-free detection, and a quick response time. However, even though the TFT sensor has such advantageous characteristics, the disadvantages hamper the TFT sensor's application in the clinical field. The TFT is susceptible to light, noise, vibration, and limited usage, and this significantly limits its on-site potential as a practical biosensor. Herein, we developed a fully packaged, portable TFT electrochemical biosensor into a chip form, providing both portability through minimizing the laboratory equipment size and multiple safe usages by protecting the semiconductor sensor. Additionally, a safe environment that serves as a miniature probe station minimizes the previously mentioned disadvantages, while providing the means to properly link the TFT biosensor with a portable analyzer. The biosensor was taken into a biosafety level 3 (BSL-3) laboratory setting to analyze highly pathogenic avian influenza virus (HPAIV) samples. This virus quickly accumulates within a host, and therefore, early stage detection is critical to deterring the further spread of the deadly disease to other areas. However, current on-site methods have poor limits of detection (10⁵-10⁶ EID₅₀/mL), and because the virus has low concentration in its early stages, it cannot be detected easily. We have compared the sample measurements from our device with virus concentration data obtained from a RT-PCR (virus range: 10⁰-10⁴ EID₅₀/mL) and have identified an increasing voltage signal which corresponds to increasing virus concentration.

Field-Effect Biosensors for On-Site Detection: Recent Advances and Promising Targets

There is an explosive interest in the immediate and cost-effective analysis of field-collected biological samples, as many advanced biodetection tools are highly sensitive, yet immobile. On-site biosensors are portable and convenient sensors that provide detection results at the point of care. They are designed to secure precision in highly ionic and heterogeneous solutions with minimal hardware. Among various methods that are capable of such analysis, field-effect biosensors are promising candidates due to their unique sensitivity, manufacturing scalability, and integrability with computational circuitry. Recent developments in nanotechnological surface modification show promising results in sensing from blood, serum, and urine. This report gives a particular emphasis on the on-site efficacy of recently published field-effect biosensors, specifically, detection limits in physiological solutions, response times, and scalability. The survey of the properties and existing detection methods of four promising biotargets, exosomes, bacteria, viruses, and metabolites, aims at providing a roadmap for future field-effect and other on-site biosensors.