title: Raman microspectroscopic mapping studies of human bronchial tissue.
abstract: Characterization of the biochemical composition of normal bronchial tissue is a prerequisite for understanding the biochemical changes that accompany histological changes during lung cancer development. In this study, 12 Raman microspectroscopic mapping experiments are performed on frozen sections of normal bronchial tissue. Pseudocolor Raman images are constructed using principal component analysis and K-means cluster analysis. Subsequent comparison of Raman images with histologic evaluation of stained sections enables the identification of the morphologic origin (e.g., bronchial mucus, epithelium, fibrocollagenous stroma, smooth muscle, glandular tissue, and cartilage) of the spectral features. Raman spectra collected from the basal side of epithelium consistently show higher DNA contributions and lower lipid contributions when compared with superficial epithelium spectra. Spectra of bronchial mucus reveal a strong signal contribution of lipids, predominantly triolein. These spectra are almost identical to the spectra obtained from submucosal glands, which suggests that the bronchial mucus is mainly composed of gland secretions. Different parts of fibrocollagenous tissue are distinguished by differences in spectral contributions from collagen and actin/myosin. Cartilage is identified by spectral contributions of glycosaminoglycans and collagen. As demonstrated here, in situ analysis of the molecular composition of histologic structures by Raman microspectroscopic mapping creates powerful opportunities for increasing our fundamental understanding of tissue organization and function. Moreover, it provides a firm basis for further in vitro and in vivo investigations of the biochemical changes that accompany pathologic transformation of tissue.
authors.affiliation: Erasmus Medical Center Rotterdam, Department of General Surgery, Laboratory of Intensive Care Research and Optical Spectroscopy, Rotterdam, The Netherlands.
authors.forename: Senada
authors.initials: S
authors.lastname: Koljenović
authors.forename: Tom C
authors.initials: TC
authors.lastname: Bakker Schut
authors.forename: Jan P
authors.initials: JP
authors.lastname: van Meerbeeck
authors.forename: Alexander P W M
authors.initials: AP
authors.lastname: Maat
authors.forename: Sjaak A
authors.initials: SA
authors.lastname: Burgers
authors.forename: Pieter E
authors.initials: PE
authors.lastname: Zondervan
authors.forename: Johan M
authors.initials: JM
authors.lastname: Kros
authors.forename: Gerwin J
authors.initials: GJ
authors.lastname: Puppels
mesh_terms: D000465:Algorithms; D015415:Biomarkers / Q000378:metabolism; D001980:Bronchi / Q000737:chemistry / Q000166:cytology* / Q000378:metabolism*; D018920:Coculture Techniques / Q000379:methods; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D050356:Lipid Metabolism; D008055:Lipids / Q000032:analysis; D018613:Microscopy, Confocal / Q000379:methods*; D020545:Respiratory Mucosa / Q000737:chemistry / Q000166:cytology / Q000378:metabolism; D013059:Spectrum Analysis, Raman / Q000379:methods*; D014018:Tissue Distribution
chemical_list: D015415:Biomarkers; D008055:Lipids