Probing Field Cancerization in the Gastrointestinal Tract Using a Hybrid Raman and Partial Wave Spectroscopy Microscope Articles uri icon

authors

  • KRIUKOVA, ELENA
  • MAZURENKA, MIKHAIL
  • MARCAZZAN, SABRINA
  • TSCHURTSCHENTHALER, MARKUS
  • PUPPELS, GERWIN
  • GLASL, SARAH
  • SAUR, DIETER
  • JESINGHAUS, MORITZ
  • POULIOU, MARIALENA
  • AGELOPOULOS, MARIOS
  • KLINAKIS, APOSTOLOS
  • QUANTE, MICHAEL
  • RIPOLL LORENZO, JORGE
  • Ntziachristos, Vasilis
  • GORPAS, DIMITRIS

publication date

  • June 2025

start page

  • 12642

end page

  • 12653

issue

  • 24

volume

  • 97

International Standard Serial Number (ISSN)

  • 0003-2700

Electronic International Standard Serial Number (EISSN)

  • 1520-6882

abstract

  • Field cancerization (FC) refers to spatially distributed premalignant tissue changes that lead to the appearance of local malignancy, and its detection can improve cancer screening. In this work, we employ combined Raman and partial wave spectroscopy (RS-PWS) to detect FC in gastroesophageal (L2-IL1B) and intestinal (Villin-Cre, Apcfl/wt) tumor mouse models. Using a hybrid RS-PWS microscope, we acquire both molecular and morphological information from macroscopically normal tumor-adjacent tissue and investigate the individual and combined performance of each modality. For data analysis, we use partial least-squares discriminant analysis (PLS-DA). In the normal tissue of L2-IL1B mice, we demonstrate a statistically significant increase (p less than 0.001) in Raman band intensities associated with free amino acids and a decrease in bands associated with lipids (p less than 0.005) and carotenoids (p less than 0.001) compared to healthy controls. Similarly, in the normal mucosa of Villin-Cre, Apcfl/wt mice, the intensities of RS bands associated with amino acids increase significantly (p less than 0.05) compared to controls, while the intensities of lipid-associated bands decrease significantly (p less than 0.05). Transcriptomic profiling using RNA-sequencing analysis on these samples identified a significant correlation between gene expression and optical findings. Moreover, we demonstrate that combining RS and PWS data further improves the significance of our classification results. When macroscopically normal tumor-adjacent tissue is compared with tissue from healthy controls, we observe that PWS increases the R2 of RS results by ~9% in L2-IL1B mice and ~5% in Villin-Cre, Apcfl/wt mice. Combining molecular RS with structural PWS information enhances the ability to detect precancerous changes and provides insights into tissue alterations during cancer development.

subjects

  • Biology and Biomedicine