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Plasmonic Biosensors for the Detection of Lung Cancer Biomarkers: A Review

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TLDR
In this paper, a review of plasmonic sensors for lung cancer biomarkers is presented, where the challenges and prospects of the plasmoric biosensors are highlighted.
Abstract
Lung cancer is the most common and deadliest cancer type globally. Its early diagnosis can guarantee a five-year survival rate. Unfortunately, application of the available diagnosis methods such as computed tomography, chest radiograph, magnetic resonance imaging (MRI), ultrasound, low-dose CT scan, bone scans, positron emission tomography (PET), and biopsy is hindered due to one or more problems, such as phenotypic properties of tumours that prevent early detection, invasiveness, expensiveness, and time consumption. Detection of lung cancer biomarkers using a biosensor is reported to solve the problems. Among biosensors, optical biosensors attract greater attention due to being ultra-sensitive, free from electromagnetic interference, capable of wide dynamic range detection, free from the requirement of a reference electrode, free from electrical hazards, highly stable, capable of multiplexing detection, and having the potential for more information content than electrical transducers. Inspired by promising features of plasmonic sensors, including surface plasmon resonance (SPR), localised surface plasmon resonance (LSPR), and surface enhanced Raman scattering (SERS) such as ultra-sensitivity, single particle/molecular level detection capability, multiplexing capability, photostability, real-time measurement, label-free measurement, room temperature operation, naked-eye readability, and the ease of miniaturisation without sophisticated sensor chip fabrication and instrumentation, numerous plasmonic sensors for the detection of lung cancer biomarkers have been investigated. In this review, the principle plasmonic sensor is explained. In addition, novel strategies and modifications adopted for the detection of lung cancer biomarkers such as miRNA, carcinoembryonic antigen (CEA), cytokeratins, and volatile organic compounds (VOCs) using plasmonic sensors are also reported. Furthermore, the challenges and prospects of the plasmonic biosensors for the detection of lung cancer biomarkers are highlighted.

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Citations
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Recent Trends in SERS-Based Plasmonic Sensors for Disease Diagnostics, Biomolecules Detection, and Machine Learning Techniques

TL;DR: A brief review on the recent developments in the surface-enhanced Raman spectroscopy/scattering (SERS) technique for biosensing applications, with a particular focus on machine learning techniques used for the same can be found in this paper .
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One-Step and Real-Time Detection of microRNA-21 in Human Samples for Lung Cancer Biosensing Diagnosis

TL;DR: A nanophotonic biosensor for the direct and real-time detection in human plasma of the microRNA-21-5p biomarker related to lung cancer and can identify and quantify the levels of microRNA in a one-step assay, without the need for DNA extraction or amplification steps.
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Biosensing through surface enhanced Raman spectroscopy: A review on the role of plasmonic nanoparticle-polymer composites

TL;DR: In this paper , the progress made in the SERS biosensors based on polymer-plasmonic nanoparticles (P-PNPs) composites towards their practical applications is reviewed.
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Au Nanoparticle-Based Integrated Microfluidic Plasmonic Chips for the Detection of Carcinoembryonic Antigen in Human Serum

TL;DR: In this article , a localized surface plasmon resonance (LSPR) biosensor integrated with microfluidics, which has multiple sensing units, was developed by nanomaterial fabrication technology.
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Trending Questions (1)
What is the challanges of Plasmonic sensors for detection cancer cell?

The challenges of plasmonic sensors for detecting cancer cells are not mentioned in the provided paper.