Precise diagnosis of small cell and non-small cell lung cancer based on Raman spectroscopy

Lung cancer has been the second most prevalent cancer globally and the leading cause of cancer-related mortality. Due to the similar clinical symptoms but different treatment protocols for different subtypes of lung cancer, precise diagnosis between small cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC) is of paramount importance for guiding treatment and improving outcomes. In this study, we explored an innovative diagnostic approach that combines Raman spectroscopy with partial least squares analysis and linear discriminant analysis (PLS-LDA) to identify the presence of lung cancer and differentiate its specific subtype. Based on biochemical analysis results, statistically significant differences between SCLC and NSCLC groups were observed in levels of amino acids, nucleic acids, and collagen. In addition, high diagnostic accuracy rates of up to 100 % for in vitro cultured cell samples and 93.75 % for ex-vivo tissue samples were achieved to differentiate SCLC and NSCLC. The proposed method offers great potential in the precise diagnosis of lung cancer with different histologic subtypes, benefiting timely and rational treatment for lung cancer patients.