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      Graphene Sensor Arrays for Rapid and Accurate Detection of Pancreatic Cancer Exosomes in Patients’ Blood Plasma Samples

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          Abstract

          Biosensors based on graphene field effect transistors (GFETs) have the potential to enable the development of point-of-care diagnostic tools for early stage disease detection. However, issues with reproducibility and manufacturing yields of graphene sensors, but also with Debye screening and unwanted detection of nonspecific species, have prevented the wider clinical use of graphene technology. Here, we demonstrate that our wafer-scalable GFETs array platform enables meaningful clinical results. As a case study of high clinical relevance, we demonstrate an accurate and robust portable GFET array biosensor platform for the detection of pancreatic ductal adenocarcinoma (PDAC) in patients’ plasma through specific exosomes (GPC-1 expression) within 45 min. In order to facilitate reproducible detection in blood plasma, we optimized the analytical performance of GFET biosensors via the application of an internal control channel and the development of an optimized test protocol. Based on samples from 18 PDAC patients and 8 healthy controls, the GFET biosensor arrays could accurately discriminate between the two groups while being able to detect early cancer stages including stages 1 and 2. Furthermore, we confirmed the higher expression of GPC-1 and found that the concentration in PDAC plasma was on average more than 1 order of magnitude higher than in healthy samples. We found that these characteristics of GPC-1 cancerous exosomes are responsible for an increase in the number of target exosomes on the surface of graphene, leading to an improved signal response of the GFET biosensors. This GFET biosensor platform holds great promise for the development of an accurate tool for the rapid diagnosis of pancreatic cancer.

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          Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries

          This article provides an update on the global cancer burden using the GLOBOCAN 2020 estimates of cancer incidence and mortality produced by the International Agency for Research on Cancer. Worldwide, an estimated 19.3 million new cancer cases (18.1 million excluding nonmelanoma skin cancer) and almost 10.0 million cancer deaths (9.9 million excluding nonmelanoma skin cancer) occurred in 2020. Female breast cancer has surpassed lung cancer as the most commonly diagnosed cancer, with an estimated 2.3 million new cases (11.7%), followed by lung (11.4%), colorectal (10.0 %), prostate (7.3%), and stomach (5.6%) cancers. Lung cancer remained the leading cause of cancer death, with an estimated 1.8 million deaths (18%), followed by colorectal (9.4%), liver (8.3%), stomach (7.7%), and female breast (6.9%) cancers. Overall incidence was from 2-fold to 3-fold higher in transitioned versus transitioning countries for both sexes, whereas mortality varied <2-fold for men and little for women. Death rates for female breast and cervical cancers, however, were considerably higher in transitioning versus transitioned countries (15.0 vs 12.8 per 100,000 and 12.4 vs 5.2 per 100,000, respectively). The global cancer burden is expected to be 28.4 million cases in 2040, a 47% rise from 2020, with a larger increase in transitioning (64% to 95%) versus transitioned (32% to 56%) countries due to demographic changes, although this may be further exacerbated by increasing risk factors associated with globalization and a growing economy. Efforts to build a sustainable infrastructure for the dissemination of cancer prevention measures and provision of cancer care in transitioning countries is critical for global cancer control.
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            NIH Image to ImageJ: 25 years of image analysis

            For the past twenty five years the NIH family of imaging software, NIH Image and ImageJ have been pioneers as open tools for scientific image analysis. We discuss the origins, challenges and solutions of these two programs, and how their history can serve to advise and inform other software projects.
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              Rapid Detection of COVID-19 Causative Virus (SARS-CoV-2) in Human Nasopharyngeal Swab Specimens Using Field-Effect Transistor-Based Biosensor

              Coronavirus disease 2019 (COVID-19) is a newly emerging human infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2, previously called 2019-nCoV). Based on the rapid increase in the rate of human infection, the World Health Organization (WHO) has classified the COVID-19 outbreak as a pandemic. Because no specific drugs or vaccines for COVID-19 are yet available, early diagnosis and management are crucial for containing the outbreak. Here, we report a field-effect transistor (FET)-based biosensing device for detecting SARS-CoV-2 in clinical samples. The sensor was produced by coating graphene sheets of the FET with a specific antibody against SARS-CoV-2 spike protein. The performance of the sensor was determined using antigen protein, cultured virus, and nasopharyngeal swab specimens from COVID-19 patients. Our FET device could detect the SARS-CoV-2 spike protein at concentrations of 1 fg/mL in phosphate-buffered saline and 100 fg/mL clinical transport medium. In addition, the FET sensor successfully detected SARS-CoV-2 in culture medium (limit of detection [LOD]: 1.6 × 101 pfu/mL) and clinical samples (LOD: 2.42 × 102 copies/mL). Thus, we have successfully fabricated a promising FET biosensor for SARS-CoV-2; our device is a highly sensitive immunological diagnostic method for COVID-19 that requires no sample pretreatment or labeling.
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                Author and article information

                Journal
                ACS Nano
                ACS Nano
                nn
                ancac3
                ACS Nano
                American Chemical Society
                1936-0851
                1936-086X
                20 July 2023
                08 August 2023
                : 17
                : 15
                : 14619-14631
                Affiliations
                []Department of Materials, Imperial College London , London SW7 2AZ, U.K.
                []ZJU-Hangzhou Global Scientific and Technological Innovation Center, Zhejiang University , Hangzhou 311200, China
                [§ ]Hamlyn Centre, Imperial College London , London SW7 2AZ, U.K.
                []Oncology Section, Surrey Cancer Research Institute, Department of Clinical and Experimental Medicine, FHMS, University of Surrey , The Leggett Building, Daphne Jackson Road, Guildford GU2 7WG, U.K.
                []HPB Surgical Unit, Royal Surrey NHS Foundation Trust , Guildford, Surrey GU2 7XX, U.K.
                [# ]Minimal Access Therapy Training Unit (MATTU), University of Surrey , The Leggett Building, Daphne Jackson Road, Guildford GU2 7WG, U.K.
                []Facility for Imaging By Light Microscopy, Imperial College London , London SW7 2AZ, U.K.
                []Department of Surgery & Cancer, Imperial College London , Hammersmith Hospital Campus, London W12 0NN, U.K.
                []HPB Surgical Unit, Imperial College Healthcare NHS Trust, Hammersmith Hospital , London W12 0HS, U.K.
                []FTKEE, Universiti Teknikal Malaysia Melaka , 76100 Durian Tunggal, Melaka, Malaysia
                []Graphenea Semiconductor , Paseo Mikeletegi 83, San Sebastián ES 20009, Spain
                []Research Center, The Seventh Affiliated Hospital, Sun Yat-sen University , Shenzhen 518107, China
                Author notes
                Author information
                https://orcid.org/0000-0003-2206-0218
                https://orcid.org/0000-0001-8054-059X
                https://orcid.org/0000-0001-7717-3768
                https://orcid.org/0000-0003-4047-6487
                https://orcid.org/0000-0002-7797-4968
                https://orcid.org/0000-0003-0005-0633
                Article
                10.1021/acsnano.3c01812
                10416564
                37470391
                32179d00-3e07-45be-b000-a64b06efd0d2
                © 2023 The Authors. Published by American Chemical Society

                Permits the broadest form of re-use including for commercial purposes, provided that author attribution and integrity are maintained ( https://creativecommons.org/licenses/by/4.0/).

                History
                : 24 February 2023
                : 17 July 2023
                Funding
                Funded by: Wellcome Trust, doi 10.13039/100010269;
                Award ID: 104931/Z/14/Z
                Funded by: Natural Science Foundation of Zhejiang Province, doi 10.13039/501100004731;
                Award ID: LR23C130001
                Funded by: Cancer Research UK, doi 10.13039/501100000289;
                Award ID: EDDCPT100016
                Funded by: Royal Society, doi 10.13039/501100000288;
                Award ID: UF160539
                Funded by: Biotechnology and Biological Sciences Research Council, doi 10.13039/501100000268;
                Award ID: BB/L015129/1
                Funded by: Engineering and Physical Sciences Research Council, doi 10.13039/501100000266;
                Award ID: EP/V062387/1
                Funded by: H2020 European Research Council, doi 10.13039/100010663;
                Award ID: 819069
                Categories
                Article
                Custom metadata
                nn3c01812
                nn3c01812

                Nanotechnology
                graphene field-effect transistors,pdac cancer,biosensor,gpc-1,exosomes
                Nanotechnology
                graphene field-effect transistors, pdac cancer, biosensor, gpc-1, exosomes

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