Correlative Histopathology and Systems Biology Approach in Product Risk Assessment
Presented at Society of Toxicology (SOT) 2011
* This author is not affiliated with PMI.
With a view to developing a systems biology-based product risk assessment approach, classical toxicology was combined with analysis of gene expression and protein abundance to investigate disease-relevant molecular perturbations at the sites of histopathological changes in an OECD 28-d rat inhalation study. Rats were exposed for 28 d to filtered air (SHAM), or to a low, medium, or high concentration of cigarette mainstream smoke (MS). Histopathology of respiratory tract sections revealed typical dose-dependent adaptive changes in the airway epithelia and inflammatory responses in the lung. For each rat, respiratory nasal epithelium (RNE) was dissected bilaterally and split for RNA and protein samples. Whole lung cryosections were used for protein samples; respiratory epithelium of the main bronchus and lung parenchyma were separated by laser capture microscopy for RNA samples. Systems profiles of gene expression (affymetrix microarrays) and principal component analysis (PCA) showed MS dose-dependent numbers of significantly up- or down-regulated genes in all 3 tissues. The differentially regulated genes were related mainly to the expected pathways, e.g., inflammation, oxidative and ER stress, etc. Correlating with histological changes, stress-related responses were more pronounced in RNE, while inflammatory responses were more pronounced in lung parenchyma. Reverse protein arrays (RPA) analysis generated systems response profiles for 46 (RNE) and 47 (lung) proteins / protein modifications. PCA showed clear separation of all MS groups from sham for RNE, and of the high MS group from sham for the lung. RNE from the medium and high MS groups differed significantly from sham in the abundance of proteins related to pathways, including the MAPK-stress signaling pathway. Responses were less pronounced in the lung. In conclusion, a correlative evaluation of classical histopathology with molecular patterns (gene expression and RPA) may facilitate a systems biology-based product risk assessment approach.