Development of an SPR-Raman biosensor for early lung cancer biomarker detection

In this study, we propose an integrated detection system that combines Surface Plasmon Resonance (SPR) and Raman spectroscopy for the rapid and quantitative detection of Small Cell Lung Cancer (SCLC). Neuron-Specific Enolase (NSE) is a reliable biomarker for Small Cell Lung Cancer (SCLC), making its accurate detection essential for the early diagnosis of lung cancer. SPR enables real-time detection of biomolecular interactions, providing critical information into molecular affinity and selectivity. Raman spectroscopy identifies chemical bonds and functional groups in proteins, allowing for detailed molecular structure analysis. By analyzing molecular fingerprints in Raman spectra, concentration changes can also be inferred. The results demonstrate that SPR exhibits exceptionally high detection sensitivity, with a Limit of Detection (LOD) of 0.1 pg/mL for NSE. The calibration curve, y = 2.64 + 0.1x with an R² value of 0.98, demonstrates a strong linear correlation. Raman spectroscopy reveals characteristic peaks corresponding to both MOA and NSE. Additionally, mass spectrometry analysis of antigen–antibody binding identifies distinct amide I (1654 cm⁻¹) and amide II (1546 cm⁻¹) peaks. Notably, the amide C–N bonds (1241 cm⁻¹ and 1115 cm⁻¹) were observed only after successful antigen–antibody binding, confirming the specificity of the interaction. The integrated SPR-Raman system demonstrates remarkable sensitivity and accuracy, effectively overcoming nonspecific binding issues associated with SPR and enhancing overall detection precision. This system holds significant potential for the early diagnosis of diseases such as SCLC, as well as broader applications in disease diagnostics and drug development.

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Publication Details

Published
2025-04-04
DOI
https://doi.org/10.1117/12.3056355
Citations
1
Primary Topic
Spectroscopy Techniques in Biomedical and Chemical Research
Type
article
Field-Weighted Citation Impact
1.63
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article

Development of an SPR-Raman biosensor for early lung cancer biomarker detection

Nan‐Fu Chiu, Jou-Chen Lin
1 citations
Spectroscopy Techniques in Biomedical and Chemical Research
1.63
article

Development of an SPR-Raman biosensor for early lung cancer biomarker detection

Nan‐Fu Chiu, Jou-Chen Lin
article en
1 citations

Abstract

In this study, we propose an integrated detection system that combines Surface Plasmon Resonance (SPR) and Raman spectroscopy for the rapid and quantitative detection of Small Cell Lung Cancer (SCLC). Neuron-Specific Enolase (NSE) is a reliable biomarker for Small Cell Lung Cancer (SCLC), making its accurate detection essential for the early diagnosis of lung cancer. SPR enables real-time detection of biomolecular interactions, providing critical information into molecular affinity and selectivity. Raman spectroscopy identifies chemical bonds and functional groups in proteins, allowing for detailed molecular structure analysis. By analyzing molecular fingerprints in Raman spectra, concentration changes can also be inferred. The results demonstrate that SPR exhibits exceptionally high detection sensitivity, with a Limit of Detection (LOD) of 0.1 pg/mL for NSE. The calibration curve, y = 2.64 + 0.1x with an R² value of 0.98, demonstrates a strong linear correlation. Raman spectroscopy reveals characteristic peaks corresponding to both MOA and NSE. Additionally, mass spectrometry analysis of antigen–antibody binding identifies distinct amide I (1654 cm⁻¹) and amide II (1546 cm⁻¹) peaks. Notably, the amide C–N bonds (1241 cm⁻¹ and 1115 cm⁻¹) were observed only after successful antigen–antibody binding, confirming the specificity of the interaction. The integrated SPR-Raman system demonstrates remarkable sensitivity and accuracy, effectively overcoming nonspecific binding issues associated with SPR and enhancing overall detection precision. This system holds significant potential for the early diagnosis of diseases such as SCLC, as well as broader applications in disease diagnostics and drug development.

National Taiwan Normal University (TW)
Good health and well-being
Openalex Percentile: Top 15%
Spectroscopy Techniques in Biomedical and Chemical Research
1.63
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