A pilot multimodal study of cervical cancer: Raman spectroscopy as a molecular fingerprint tool

Abstract

Cervical cancer remains a significant global health burden, highlighting the need for more effective tools for early detection and tissue characterization. In this study, we propose a multimodal strategy that combines Raman spectroscopy, Atomic Force Microscopy (AFM), and Scanning Electron Microscopy (SEM) to investigate the molecular and morphological features of cervical squamous cell carcinoma (SCC). Raman spectroscopy was used to analyze biochemical signatures across different tissue regions tumor, necrotic, stromal, and glandular within the 813–1668 cm -1 range, identifying distinct molecular profiles between malignant and healthy areas. Specific vibrational peaks associated with DNA, proteins, and lipids were examined to track molecular changes related to tumor progression. AFM enabled nanoscale mapping of surface morphology, revealing structural irregularities associated with malignancy, while SEM provided detailed imaging of cellular and extracellular architecture, enhancing the visualization of cancer-induced morphological alterations. Although Raman spectroscopy has been studied for decades in cancer research, it has not yet replaced Pap smears and biopsies in clinical practice due to challenges in standardization, reproducibility, and clinical validation. This pilot study aims to serve as a stepping stone toward that goal, providing proof-of-concept data that may support the gradual translation of Raman spectroscopy into clinically relevant diagnostic workflows and underscores the potential of the technique, supported by complementary high-resolution imaging techniques, in the characterization of cervical cancer tissues. The integration of Raman, AFM, and SEM was used here as a pilot approach on paraffin-embedded samples, with AFM and SEM providing supportive morphological information while the long-term aim is to transfer Raman spectroscopy to fresh, untreated tissues, where its non-destructive and label-free nature could enable minimally invasive diagnostic applications.