A Single-Molecule Bioelectronic Portable Array for Early Diagnosis of Pancreatic Cancer Precursors

A cohort of 47 patients is screened for pancreatic cancer precursors with a portable 96-well bioelectronic sensing-array for single-molecule assay in cysts fluid and blood plasma, deployable at point-of-care (POC). Pancreatic cancer precursors are mucinous cysts diagnosed with a sensitivity of at most 80% by state-of-the-art cytopathological molecular analyses (e.g., KRASmut DNA). Adding the simultaneous assay of proteins related to malignant transformation (e.g., MUC1 and CD55) is deemed essential to enhance diagnostic accuracy. The bioelectronic array proposed here, based on single-molecule-with-a-large-transistor (SiMoT) technology, can assay both nucleic acids and proteins at the single-molecule limit-of-identification (LOI) (1% of false-positives and false-negatives). It comprises an enzyme-linked immunosorbent assay (ELISA)-like 8 × 12-array organic-electronics disposable cartridge with an electrolyte-gated organic transistor sensor array, and a reusable reader, integrating a custom Si-IC chip, operating via software installed on a USB-connected smart device. The cartridge is complemented by a 3D-printed sensing gate cover plate. KRASmut, MUC1, and CD55 biomarkers either in plasma or cysts-fluid from 5 to 6 patients at a time, are multiplexed at single-molecule LOI in 1.5 h. The pancreatic cancer precursors are classified via a machine-learning analysis resulting in at least 96% diagnostic-sensitivity and 100% diagnostic-specificity. This preliminary study opens the way to POC liquid-biopsy-based early diagnosis of pancreatic-cancer precursors in plasma.</p

A Single-Molecule Bioelectronic Portable Array for Early Diagnosis of Pancreatic Cancer Precursors

A cohort of 47 patients is screened for pancreatic cancer precursors with a portable 96-well bioelectronic sensing-array for single-molecule assay in cysts fluid and blood plasma, deployable at point-of-care (POC). Pancreatic cancer precursors are mucinous cysts diagnosed with a sensitivity of at most 80% by state-of-the-art cytopathological molecular analyses (e.g., KRASmut DNA). Adding the simultaneous assay of proteins related to malignant transformation (e.g., MUC1 and CD55) is deemed essential to enhance diagnostic accuracy. The bioelectronic array proposed here, based on single-molecule-with-a-large-transistor (SiMoT) technology, can assay both nucleic acids and proteins at the single-molecule limit-of-identification (LOI) (1% of false-positives and false-negatives). It comprises an enzyme-linked immunosorbent assay (ELISA)-like 8 × 12-array organic-electronics disposable cartridge with an electrolyte-gated organic transistor sensor array, and a reusable reader, integrating a custom Si-IC chip, operating via software installed on a USB-connected smart device. The cartridge is complemented by a 3D-printed sensing gate cover plate. KRASmut, MUC1, and CD55 biomarkers either in plasma or cysts-fluid from 5 to 6 patients at a time, are multiplexed at single-molecule LOI in 1.5 h. The pancreatic cancer precursors are classified via a machine-learning analysis resulting in at least 96% diagnostic-sensitivity and 100% diagnostic-specificity. This preliminary study opens the way to POC liquid-biopsy-based early diagnosis of pancreatic-cancer precursors in plasma.</p

Long Non-Coding RNA Landscape in Prostate Cancer Molecular Subtypes: A Feature Selection Approach

Prostate cancer is one of the most common malignancies in men. It is characterized by a high molecular genomic heterogeneity and, thus, molecular subtypes, that, to date, have not been used in clinical practice. In the present paper, we aimed to better stratify prostate cancer patients through the selection of robust long non-coding RNAs. To fulfill the purpose of the study, a bioinformatic approach focused on feature selection applied to a TCGA dataset was used. In such a way, LINC00668 and long non-coding(lnc)-SAYSD1-1, able to discriminate ERG/not-ERG subtypes, were demonstrated to be positive prognostic biomarkers in ERG-positive patients. Furthermore, we performed a comparison between mutated prostate cancer, identified as “classified”, and a group of patients with no peculiar genomic alteration, named “not-classified”. Moreover, LINC00920 lncRNA overexpression has been linked to a better outcome of the hormone regimen. Through the feature selection approach, it was found that the overexpression of lnc-ZMAT3-3 is related to low-grade patients, and three lncRNAs: lnc-SNX10-87, lnc-AP1S2-2, and ADPGK-AS1 showed, through a co-expression analysis, significant correlation values with potentially druggable pathways. In conclusion, the data mining of publicly available data and robust bioinformatic analyses are able to explore the unknown biology of malignancies

uPAR+ extracellular vesicles: a robust biomarker of resistance to checkpoint inhibitor immunotherapy in metastatic melanoma patients

Background Emerging evidence has highlighted the importance of extracellular vesicle (EV)-based biomarkers of resistance to immunotherapy with checkpoint inhibitors in metastatic melanoma. Considering the tumor-promoting implications of urokinase-type plasminogen activator receptor (uPAR) signaling, this study aimed to assess uPAR expression in the plasma-derived EVs of patients with metastatic melanoma to determine its potential correlation with clinical outcomes.Methods Blood samples from 71 patients with metastatic melanoma were collected before initiating immunotherapy. Tumor-derived and immune cell-derived EVs were isolated and analyzed to assess the relative percentage of uPAR+ EVs. The associations between uPAR and clinical outcomes, sex, BRAF status, baseline lactate dehydrogenase levels and number of metastatic sites were assessed.Results Responders had a significantly lower percentage of tumor-derived, dendritic cell (DC)-derived and CD8+ T cell-derived uPAR +EVs at baseline than non-responders. The Kaplan-Meier survival curves for the uPAR+EV quartiles indicated that higher levels of melanoma-derived uPAR+ EVs were strongly correlated with poorer progression-free survival (p&lt;0.0001) and overall survival (p&lt;0.0001). We also found a statistically significant correlation between lower levels of uPAR+ EVs from both CD8+ T cells and DCs and better survival.Conclusions Our results indicate that higher levels of tumor-derived, DC-derived and CD8+ T cell-derived uPAR+ EVs in non-responders may represent a new biomarker of innate resistance to immunotherapy with checkpoint inhibitors. Moreover, uPAR+ EVs represent a new potential target for future therapeutic approaches

Label-free electronic detection of peptide post-translational modification with functional enzyme-driven assay at the physical limit

High-performance, ultra-sensitive, and universal protein post-translational modification (PTM) and protein-protein interaction (PPI) technologies are eagerly pursued in the pharmaceutical industry and bioanalytical research. Novel PTM and PPI detection methods outperform traditional assays in scope and scalability, enabling the collection of information on multiple biochemical targets. Detecting peptides and proteins at the single-molecule level is done by utilizing nanosized transducing elements and assaying solutions at very high analyte concentrations, in the nanomolar range or higher. Here, a proof of principle of a biosensing platform for single-molecule PTM detection is demonstrated. This platform is based on the single molecule with a large transistor (SiMoT) technology, encompassing a millimeter-sized electrolyte-gated organic field-effect transistor, for label-free PTM detection with a zeptomolar limit of detection. Sensitivity is improved 106- to 1012-fold compared with mass-spectrometry and luminescence-based assay methods. A functional assay for detecting enzyme-driven peptide PTMs in the zeptomolar concentration range is demonstrated using multivariate data processing, opening the way for future applications to monitor PTMs

Spectrum of Germline Pathogenic Variants in BRCA1/2 Genes in the Apulian Southern Italy Population: Geographic Distribution and Evidence for Targeted Genetic Testing

BRCA1/2-associated hereditary breast and ovarian cancer is the most common form of hereditary breast and ovarian cancer and occurs in all ethnicities and racial populations. Different BRCA1/BRCA2 pathogenic variants (PVs) have been reported with a wide variety among populations. In this study, we retrospectively analyzed prevalence and geographic distribution of pathogenic germline BRCA1/2 variants in families from Apulia in southern Italy and evaluated the genotype–phenotype correlations. Data were collected from Oncogenetic Services present in Apulian hospitals and a shared database was built containing Apulian native probands (n = 2026) that had undergone genetic testing from 2004 to 2019. PVs were detected in 499 of 2026 (24.6%) probands and 68.5% of them (342 of 499) were in the BRCA1 gene. We found 65 different PVs in BRCA1 and 46 in BRCA2. There were 10 most recurrent PVs and their geographical distribution appears to be significantly specific for each province. We have assumed that these PVs are related to the historical and geopolitical changes that occurred in Apulia over time and/or to a “founder effect”. Broader knowledge of BRCA1/2 prevalence and recurring PVs in specific geographic areas could help establish more flexible genetic testing strategies that may enhance our ability to detect high-risk subjects

Analysis of Clinical Samples of Pancreatic Cyst's Lesions with A Multi‐Analyte Bioelectronic Simot Array Benchmarked Against Ultrasensitive Chemiluminescent Immunoassay

Abstract Pancreatic cancer, ranking as the third factor in cancer‐related deaths, necessitates enhanced diagnostic measures through early detection. In response, SiMoT‐Single‐molecule with a large Transistor multiplexing array, achieving a Technology Readiness Level of 5, is proposed for a timely identification of pancreatic cancer precursor cysts and is benchmarked against the commercially available chemiluminescent immunoassay SIMOA (Single molecule array) SP‐X System. A cohort of 39 samples, comprising 33 cyst fluids and 6 blood plasma specimens, undergoes detailed examination with both technologies. The SiMoT array targets oncoproteins MUC1 and CD55, and oncogene KRAS, while the SIMOA SP‐X planar technology exclusively focuses on MUC1 and CD55. Employing Principal Component Analysis (PCA) for multivariate data processing, the SiMoT array demonstrates effective discrimination of malignant/pre‐invasive high‐grade or potentially malignant low‐grade pancreatic cysts from benign non‐mucinous cysts. Conversely, PCA analysis applied to SIMOA assay reveals less effective differentiation ability among the three cyst classes. Notably, SiMoT unique capability of concurrently analyzing protein and genetic markers with the threshold of one single molecule in 0.1 mL positions it as a comprehensive and reliable diagnostic tool. The electronic response generated by the SiMoT array facilitates direct digital data communication, suggesting potential applications in the development of field‐deployable liquid biopsy

A Single-Molecule Bioelectronic Portable Array for Early Diagnosis of Pancreatic Cancer Precursors

A cohort of 47 patients is screened for pancreatic cancer precursors with a portable 96-well bioelectronic sensing-array for single-molecule assay in cysts fluid and blood plasma, deployable at point-of-care (POC). Pancreatic cancer precursors are mucinous cysts diagnosed with a sensitivity of at most 80% by state-of-the-art cytopathological molecular analyses (e.g., KRAS(mut) DNA). Adding the simultaneous assay of proteins related to malignant transformation (e.g., MUC1 and CD55) is deemed essential to enhance diagnostic accuracy. The bioelectronic array proposed here, based on single-molecule-with-a-large-transistor (SiMoT) technology, can assay both nucleic acids and proteins at the single-molecule limit-of-identification (LOI) (1% of false-positives and false-negatives). It comprises an enzyme-linked immunosorbent assay (ELISA)-like 8 x 12-array organic-electronics disposable cartridge with an electrolyte-gated organic transistor sensor array, and a reusable reader, integrating a custom Si-IC chip, operating via software installed on a USB-connected smart device. The cartridge is complemented by a 3D-printed sensing gate cover plate. KRAS(mut), MUC1, and CD55 biomarkers either in plasma or cysts-fluid from 5 to 6 patients at a time, are multiplexed at single-molecule LOI in 1.5 h. The pancreatic cancer precursors are classified via a machine-learning analysis resulting in at least 96% diagnostic-sensitivity and 100% diagnostic-specificity. This preliminary study opens the way to POC liquid-biopsy-based early diagnosis of pancreatic-cancer precursors in plasma

Analysis of Clinical Samples of Pancreatic Cyst's Lesions with A Multi‐Analyte Bioelectronic Simot Array Benchmarked Against Ultrasensitive Chemiluminescent Immunoassay

Pancreatic cancer, ranking as the third factor in cancer-related deaths, necessitates enhanced diagnostic measures through early detection. In response, SiMoT-Single-molecule with a large Transistor multiplexing array, achieving a Technology Readiness Level of 5, is proposed for a timely identification of pancreatic cancer precursor cysts and is benchmarked against the commercially available chemiluminescent immunoassay SIMOA (Single molecule array) SP-X System. A cohort of 39 samples, comprising 33 cyst fluids and 6 blood plasma specimens, undergoes detailed examination with both technologies. The SiMoT array targets oncoproteins MUC1 and CD55, and oncogene KRAS, while the SIMOA SP-X planar technology exclusively focuses on MUC1 and CD55. Employing Principal Component Analysis (PCA) for multivariate data processing, the SiMoT array demonstrates effective discrimination of malignant/pre-invasive high-grade or potentially malignant low-grade pancreatic cysts from benign non-mucinous cysts. Conversely, PCA analysis applied to SIMOA assay reveals less effective differentiation ability among the three cyst classes. Notably, SiMoT unique capability of concurrently analyzing protein and genetic markers with the threshold of one single molecule in 0.1 mL positions it as a comprehensive and reliable diagnostic tool. The electronic response generated by the SiMoT array facilitates direct digital data communication, suggesting potential applications in the development of field-deployable liquid biopsy.SiMoT-Single-Molecule with Large Transistor technology simultaneously analyzes protein and genetic markers, achieving a one-molecule threshold in 0.1 mL. Benchmarking against SIMOA chemiluminescent ultrasensitive assay, SiMoT outperforms SIMOA in speed and overall performance. Moreover, SiMoT provides an electronic response, enhancing its suitability for direct digital data communication.imag

The Improvement of Durability of Reinforced Concretes for Sustainable Structures: A Review on Different Approaches

The topic of sustainability of reinforced concrete structures is strictly related with their durability in aggressive environments. In particular, at equal environmental impact, the higher the durability of construction materials, the higher the sustainability. The present review deals with the possible strategies aimed at producing sustainable and durable reinforced concrete structures in different environments. It focuses on the design methodologies as well as the use of unconventional corrosion-resistant reinforcements, alternative binders to Portland cement, and innovative or traditional solutions for reinforced concrete protection and prevention against rebars corrosion such as corrosion inhibitors, coatings, self-healing techniques, and waterproofing aggregates. Analysis of the scientific literature highlights that there is no preferential way for the production of “green” concrete but that the sustainability of the building materials can only be achieved by implementing simulta-neous multiple strategies aimed at reducing environmental impact and improving both durability and performances