Fusion of Raman and FTIR Spectroscopy Data Uncovers Physiological Changes Associated with Lung Cancer

Hano, Harun; Suarez, Beatriz; Lawrie, Charles H.; Seifert, Andreas

doi:10.3390/ijms252010936

Open AccessArticle

Fusion of Raman and FTIR Spectroscopy Data Uncovers Physiological Changes Associated with Lung Cancer

¹

CIC nanoGUNE BRTA, 20018 San Sebastián, Spain

²

Department of Physics, University of the Basque Country (UPV/EHU), 20018 San Sebastián, Spain

³

Faculty of Nursing and Medicine, University of the Basque Country (UPV/EHU), 48940 Leioa, Spain

⁴

Biogipuzkoa Health Research Institute, 20014 San Sebastián, Spain

⁵

IKERBASQUE—Basque Foundation for Science, 48009 Bilbao, Spain

⁶

Sino-Swiss Institute of Advanced Technology (SSIAT), University of Shanghai, Shanghai 201800, China

⁷

Radcliffe Department of Medicine, University of Oxford, Oxford OX3 9DU, UK

^*

Authors to whom correspondence should be addressed.

Int. J. Mol. Sci. 2024, 25(20), 10936; https://doi.org/10.3390/ijms252010936

Submission received: 6 September 2024 / Revised: 1 October 2024 / Accepted: 8 October 2024 / Published: 11 October 2024

(This article belongs to the Special Issue Infrared and Raman Spectroscopy of Human Diseases: 2nd Edition)

Download

Browse Figures

Versions Notes

Abstract

Due to the high mortality rate, more effective non-invasive diagnostic methods are still needed for lung cancer, the most common cause of cancer-related death worldwide. In this study, the integration of Raman and Fourier-transform infrared spectroscopy with advanced data-fusion techniques is investigated to improve the detection of lung cancer from human blood plasma samples. A high statistical significance was found for important protein-related oscillations, which are crucial for differentiating between lung cancer patients and healthy controls. The use of low-level data fusion and feature selection significantly improved model accuracy and emphasizes the importance of structural protein changes in cancer detection. Although other biomolecules such as carbohydrates and nucleic acids also contributed, proteins proved to be the decisive markers found using this technique. This research highlights the power of these combined spectroscopic methods to develop a non-invasive diagnostic tool for discriminating lung cancer from healthy state, with the potential to extend such studies to a variety of other diseases.

Keywords: data fusion; vibrational spectroscopy; chemometrics; feature selection; photonic diagnostics

Share and Cite

MDPI and ACS Style

Hano, H.; Suarez, B.; Lawrie, C.H.; Seifert, A. Fusion of Raman and FTIR Spectroscopy Data Uncovers Physiological Changes Associated with Lung Cancer. Int. J. Mol. Sci. 2024, 25, 10936. https://doi.org/10.3390/ijms252010936

AMA Style

Hano H, Suarez B, Lawrie CH, Seifert A. Fusion of Raman and FTIR Spectroscopy Data Uncovers Physiological Changes Associated with Lung Cancer. International Journal of Molecular Sciences. 2024; 25(20):10936. https://doi.org/10.3390/ijms252010936

Chicago/Turabian Style

Hano, Harun, Beatriz Suarez, Charles H. Lawrie, and Andreas Seifert. 2024. "Fusion of Raman and FTIR Spectroscopy Data Uncovers Physiological Changes Associated with Lung Cancer" International Journal of Molecular Sciences 25, no. 20: 10936. https://doi.org/10.3390/ijms252010936

APA Style

Hano, H., Suarez, B., Lawrie, C. H., & Seifert, A. (2024). Fusion of Raman and FTIR Spectroscopy Data Uncovers Physiological Changes Associated with Lung Cancer. International Journal of Molecular Sciences, 25(20), 10936. https://doi.org/10.3390/ijms252010936

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Menu

Fusion of Raman and FTIR Spectroscopy Data Uncovers Physiological Changes Associated with Lung Cancer

Abstract

Share and Cite

Article Metrics

Article Access Statistics

Further Information

Guidelines

MDPI Initiatives

Follow MDPI