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Waveguiding and SERS Simplified Raman Spectroscopy on Biological Samples.

ABSTRACT: Biomarkers detection at an ultra-low concentration in biofluids (blood, serum, saliva, etc.) is a key point for the early diagnosis success and the development of personalized therapies. However, it remains a challenge due to limiting factors like (i) the complexity of analyzed media, and (ii) the aspecificity detection and the poor sensitivity of the conventional methods. In addition, several applications require the integration of the primary sensors with other devices (microfluidic devices, capillaries, flasks, vials, etc.) where transducing the signal might be difficult, reducing performances and applicability. In the present work, we demonstrate a new class of optical biosensor we have developed integrating an optical waveguide (OWG) with specific plasmonic surfaces. Exploiting the plasmonic resonance, the devices give consistent results in surface enhanced Raman spectroscopy (SERS) for continuous and label-free detection of biological compounds. The OWG allows driving optical signals in the proximity of SERS surfaces (detection area) overcoming spatial constraints, in order to reach places previously optically inaccessible. A rutile prism couples the remote laser source to the OWG, while a Raman spectrometer collects the SERS far field scattering. The present biosensors were implemented by a simple fabrication process, which includes photolithography and nanofabrication. By using such devices, it was possible to detect cell metabolites like Phenylalanine (Phe), Adenosine 5-triphosphate sodium hydrate (ATP), Sodium Lactate, Human Interleukin 6 (IL6), and relate them to possible metabolic pathway variation.

SUBMITTER: Valpapuram I

PROVIDER: S-EPMC6468818 | biostudies-literature | 2019 Mar

REPOSITORIES: biostudies-literature

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Waveguiding and SERS Simplified Raman Spectroscopy on Biological Samples.

Valpapuram Immanuel I Candeloro Patrizio P Coluccio Maria Laura ML Parrotta Elvira Immacolata EI Giugni Andrea A Das Gobind G Cuda Gianni G Di Fabrizio Enzo E Perozziello Gerardo G

Biosensors 20190303 1

Biomarkers detection at an ultra-low concentration in biofluids (blood, serum, saliva, etc.) is a key point for the early diagnosis success and the development of personalized therapies. However, it remains a challenge due to limiting factors like (<i>i</i>) the complexity of analyzed media, and (<i>ii</i>) the aspecificity detection and the poor sensitivity of the conventional methods. In addition, several applications require the integration of the primary sensors with other devices (microflui ...[more]

PMID: 30832416

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Project description:Gene promoter hypermethylation is a vital step in tumorigenesis. This paper set out to explore the use of polymerase chain reaction - surface-enhanced Raman spectroscopy (PCR-SERS) for the detection of gene methylation levels, with a focus on cancer diagnosis. Methods: PCR with methylation independent primers were used on DNA samples to amplify target genes regardless of their methylation states. SERS was used on the obtained PCR products to generate spectra that contained peak changes belonging to CG and AT base pairs. Multiple linear regression (MLR) was then used to deconvolute the SERS spectra so that the CG/AT ratios of the sample could be obtained. These MLR results were used to calculate methylation levels of the target genes. For protocol verification, three sets of seven reference DNA solutions with known methylation levels (0%, 1%, 5%, 25%, 50%, 75%, and 100%) were analysed. Clinically, blood plasma samples were taken from 48 non-small-cell lung cancer (NSCLC) patients and 51 healthy controls. The methylation levels of the genes p16, MGMT, and RASSF1 were determined for each patient using this method. Results: Verification experiment on the mixtures with known methylation levels resulted in an error of less than 6% from the actual levels. When applied to our clinical samples, the frequency of methylation in at least one of the three target genes among the NSCLC patients was 87.5%, but this percentage decreased to 11.8% for the control group. The methylation levels of p16 were found to be significantly higher in NSCLC patients with more pack-years smoked (p=0.04), later cancer stages (p=0.03), and cancer types of squamous cell and large cell versus adenocarcinoma (p=0.03). Prediction accuracy of 88% was achieved from classification and regression trees (CART) based on methylation levels and states, respectively. Conclusion: This research showed that the PCR-SERS protocol could quantitatively measure the methylation levels of genes in plasma. The methylation levels of the genes p16, MGMT, and RASSF1 were higher in NSCLC patients than in controls.

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Waveguiding and SERS Simplified Raman Spectroscopy on Biological Samples.

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Waveguiding and SERS Simplified Raman Spectroscopy on Biological Samples.

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