Evidence map›Paper›PMID 37470391›Full record

ArticleACS nano2023

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

Tianyi Yin, Lizhou Xu, Bruno Gil, Nabeel Merali, Maria S Sokolikova, David C A Gaboriau, Daniel S K Liu, Ahmad Nizamuddin Muhammad Mustafa, Sarah Alodan, Michael Chen and 12 more

Open access · hybridAbstract read
In one paragraph

Article in ACS nano, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed
7.4field-weighted citation impact, top 2% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

24 citing papers in PubMed, 77 citations in OpenAlex.

  1. Review
  2. From Sensing Mechanisms to System Co-Design: Graphene-Based Sensors and Readout Circuits.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Review
  3. Ultrasensitive Detection of Neurofilament Light in Plasma Using F(Ab')Small (Weinheim an der Bergstrasse, Germany) · 2026
    Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

22 authors at 8 institutions in 4 countries.

Tianyi YinDepartment of Materials, Imperial College London, London SW7 2AZ, U.K.ORCID 0000-0003-2206-0218
Lizhou XuDepartment of Materials, Imperial College London, London SW7 2AZ, U.K.
Bruno GilHamlyn Centre, Imperial College London, London SW7 2AZ, U.K.ORCID 0000-0001-8054-059X
Nabeel MeraliOncology 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.
Maria S SokolikovaDepartment of Materials, Imperial College London, London SW7 2AZ, U.K.ORCID 0000-0001-7717-3768
David C A GaboriauFacility for Imaging By Light Microscopy, Imperial College London, London SW7 2AZ, U.K.ORCID 0000-0003-4047-6487
Daniel S K LiuDepartment of Surgery & Cancer, Imperial College London, Hammersmith Hospital Campus, London W12 0NN, U.K.
Ahmad Nizamuddin Muhammad MustafaDepartment of Materials, Imperial College London, London SW7 2AZ, U.K.ORCID 0000-0002-7797-4968
Sarah AlodanDepartment of Materials, Imperial College London, London SW7 2AZ, U.K.
Michael ChenDepartment of Materials, Imperial College London, London SW7 2AZ, U.K.
Oihana TxoperenaGraphenea Semiconductor, Paseo Mikeletegi 83, San Sebastián ES 20009, Spain.
María ArrastuaGraphenea Semiconductor, Paseo Mikeletegi 83, San Sebastián ES 20009, Spain.
Juan Manuel GomezGraphenea Semiconductor, Paseo Mikeletegi 83, San Sebastián ES 20009, Spain.
Nerea OntosoGraphenea Semiconductor, Paseo Mikeletegi 83, San Sebastián ES 20009, Spain.
Marta EliceguiGraphenea Semiconductor, Paseo Mikeletegi 83, San Sebastián ES 20009, Spain.
Elias TorresGraphenea Semiconductor, Paseo Mikeletegi 83, San Sebastián ES 20009, Spain.
Danyang LiResearch Center, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen 518107, China.
Cecilia MatteviDepartment of Materials, Imperial College London, London SW7 2AZ, U.K.ORCID 0000-0003-0005-0633
Adam E FramptonOncology 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.
Long R JiaoDepartment of Surgery & Cancer, Imperial College London, Hammersmith Hospital Campus, London W12 0NN, U.K.
Sami RamadanDepartment of Materials, Imperial College London, London SW7 2AZ, U.K.
Norbert KleinDepartment of Materials, Imperial College London, London SW7 2AZ, U.K.
Imperial College London · GBGraphenea (Spain) · ESHammersmith Hospital · GBImperial College Healthcare NHS Trust · GBSun Yat-sen University · CNTechnical University of Malaysia Malacca · MYUniversity of Surrey · GBZhejiang University of Science and Technology · CN

Funding

Biotechnology and Biological Sciences Research Council BB/L015129/1Cancer Research UK EDDCPT\100016Wellcome TrustWellcome Trust 104931/Z/14/Z
6 · The paper itself

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.

Indexed as

Biosensing TechniquesCarcinoma, Pancreatic DuctalExosomesGraphitePancreatic NeoplasmsHumansReproducibility of ResultsTransistors, ElectronicGraphitebiosensorexosomesGPC-1graphene field-effect transistorsPDAC cancer

Identifiers

PMID37470391
PMCPMC10416564
OpenAlexW4384819501

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.