Raman Spectroscopy Combined with Principal Component Analysis for Screening Nasopharyngeal Cancer in Human Blood Sera

Khan, Saranjam; Ullah, Rahat; Javaid, Samina; Shahzad, Shaheen; Ali, Hina; Bilal, Muhammad; Saleem, Muhammad; Ahmed, Mushtaq

doi:10.1177/0003702817723928

Cited by 33 publications

(13 citation statements)

References 28 publications

(30 reference statements)

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“…Among these, Raman spectroscopy has been considered as the most sensitive method in providing information about the biochemical nature of tissue samples in real-time and in an automated manner. It has been widely used for the characterization of lung cancer from saliva, breast cancer, atherosclerosis and other types of cancer screening from sera samples [23,24]. Also in the context of asthma, Raman spectroscopy was applied at an early phase pilot study of disease diagnosis based on serum.…”

Section: Introductionmentioning

confidence: 99%

Demonstrating the application of Raman spectroscopy together with chemometric technique for screening of asthma disease

Ullah¹,

Khan

Farman

et al. 2019

Biomed. Opt. Express

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Medical biophotonic tools provide new sources of diagnostic information regarding the state of human health that are used in managing patient care. In our current study, Raman spectroscopy, together with the chemometric technique, has successfully been demonstrated for the screening of asthma disease. Raman spectra of sera samples from asthmatic patients as well as healthy (control) volunteers have been recorded at 532 nm excitation. In healthy sera, three highly reproducible Raman peaks assigned to β-carotene have been detected. Their sensitive detection is facilitated due to the resonance Raman effect. In contrast, in asthmatic patients sera, the peaks assigned to β-carotene are either diminished or suppressed accompanied by other new Raman peaks. These new peaks most probably arise due to an elevated level of proteins, which could be used to identify/differentiate between asthma and non-asthma samples. Furthermore, a partial least squares discrimination analysis (PLS-DA) model was developed and applied on the Raman spectra of diseased as well as healthy samples, which successfully classified them. The correlation coefficient (r2) of the model was determined as 0.965. Similarly, the root mean square errors in cross-validation (RMSECV) and in the prediction (RMSECP) are 0.09 and 0.25, respectively. PLS-DA has the potential to be incorporated in a microcontroller's code attached with a hand-held Raman spectrometer for screening purposes in asthma, which is a disease of great concern for the clinicians, especially in children.

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Section: Introductionmentioning

confidence: 99%

Demonstrating the application of Raman spectroscopy together with chemometric technique for screening of asthma disease

Ullah¹,

Khan

Farman

et al. 2019

Biomed. Opt. Express

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“…1. Spectral shifts due to analyte binding are easy to observe, particularly in regions where there is concurrent depletion of some bands and appearance of others Although principal component analysis has been widely used in analysing Raman spectra, it is usually applied to "blindly" categorise samples, [21][22][23] although the importance of separating out technical and sample variability has recently been recognised. 24,25 However, to the best of our knowledge, this work represents the first example of using differential principal component analysis in combination with a "probe recognition" experimental strategy to separate out technical and sample variability by design.…”

Section: Resultsmentioning

confidence: 99%

DeltaPCA: A Statistically Robust Method for Detecting Protein Analyte Binding to Aptamer-Functionalised Nanoparticles using Surface-Enhanced Raman Spectroscopy

Given

Stanborough

Waterland

et al. 2021

Preprint

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In this work, we introduce a novel joint experimental design and computational analysis procedure to reliably and reproducibly quantify protein analyte binding to DNA aptamer-functionalised silver nanoparticles using slippery surface-enhanced Raman spectroscopy. We employ an indirect detection approach, based upon monitoring spectral changes in the covalent bond-stretching region as intermolecular bonds are formed between the surface-immobilized probe biomolecule and its target analyte. Sample variability is minimized by preparing aptamer-only and aptamer-plus-analyte samples under the same conditions, and then analysing difference spectra. To account for technical variability, multiple spectra are recorded from the same sample. Our new DeltaPCA analysis procedure takes into account technical variability within each spectral data set while also extracting statistically robust difference spectra between data sets. Proof of principle experiments using thiolated aptamers to detect CoV-SARS-2 spike protein reveal that analyte binding is mediated through the formation of N-H...X and C-H...X hydrogen bonds between the aptamer (H-bond donor) and protein (H-bond acceptor). Our computational analysis code can be freely downloaded from https://github.com/dlc62/DeltaPCA.

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“…It can provide plentiful information on the chemical compounds in the blood samples [16]. More recently, Raman spectroscopy has been studied as a blood screening method in oral cancer [17], colorectal cancer [18], lung cancer [19], nasopharyngeal cancer [20,21], meningioma cancer [22], prostate cancer [23], breast cancer [24], cervical cancer [25] and gastric cancer [26]. For esophageal cancer, there were some studies using surface-enhanced Raman spectroscopy (SERS) of plasma or serum [27,28].…”

Section: Introductionmentioning

confidence: 99%

Blood plasma resonance Raman spectroscopy combined with multivariate analysis for esophageal cancer detection

Chen

Zhang

et al. 2021

Journal of Biophotonics

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We herein report a novel, reliable and inexpensive method for detecting esophageal cancer using blood plasma resonance Raman spectroscopy combined with multivariate analysis methods. The blood plasma samples were divided into late stage cancer group (n = 164), early stage cancer group (n = 35) and normal group (n = 135) based on clinical pathological diagnosis. Using a specially designed quartz capillary tube as sample holder, we obtained higher quality resonance Raman spectra of blood plasma than existing method. The study demonstrated that the carotenoids levels in blood plasma were reduced in esophageal cancer patients. The area under the receiver operating characteristic curve (and 95% confidence interval) calculated by wavenumber selection and principal component analysis combined with linear discriminant analysis (PC-LDA) algorithm were 0.894 (0.858-0.929), 0.901 (0.841-0.960) and 0.871 (0.799-0.942) for differentiating late cancer from normal, late cancer from early cancer, and early cancer from normal respectively. The contribution from the two carotenoids wavenumber regions of 1155 and 1515 cm À1 were more than 84.2%. The results show that the plasma carotenoids could be a potential biomarker for screening esophageal cancer using resonance Raman spectroscopy combined with wavenumber selection and PC-LDA algorithms.

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Raman Spectroscopy Combined with Principal Component Analysis for Screening Nasopharyngeal Cancer in Human Blood Sera

Cited by 33 publications

References 28 publications

Demonstrating the application of Raman spectroscopy together with chemometric technique for screening of asthma disease

Demonstrating the application of Raman spectroscopy together with chemometric technique for screening of asthma disease

DeltaPCA: A Statistically Robust Method for Detecting Protein Analyte Binding to Aptamer-Functionalised Nanoparticles using Surface-Enhanced Raman Spectroscopy

Blood plasma resonance Raman spectroscopy combined with multivariate analysis for esophageal cancer detection

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