Pancreatic cancer (PC) is an aggressive and lethal neoplasm, ranking seventh in the world for cancer deaths, with an overall 5-year survival rate of below 10%. The knowledge about PC pathogenesis is rapidly expanding. New aspects of tumor biology, including its molecular and morphological heterogeneity, have been reported to explain the complicated "cross-talk" that occurs between the cancer cells and the tumor stroma or the nature of pancreatic ductal adenocarcinoma-associated neural remodeling. Nevertheless, currently, there are no specific and sensitive diagnosis options for PC. Vibrational spectroscopy (VS) shows a promising role in the development of early diagnosis technology. In this review, we summarize recent reports about improvements in spectroscopic methodologies, briefly explain and highlight the drawbacks of each of them, and discuss available solutions. The important aspects of spectroscopic data evaluation with multivariate analysis and a convolutional neural network methodology are depicted. We conclude by presenting a study design for systemic verification of the VS-based methods in the diagnosis of PC.
Keywords: Convolutional neural networks; DNA methylation; Liquid biopsy biomarkers; Pancreatic cancer diagnosis; Raman spectroscopy; Spectroscopic cancer diagnosis.
©The Author(s) 2023. Published by Baishideng Publishing Group Inc. All rights reserved.