Imaging heterogeneity in the mitochondrial redox state of premalignant pancreas in the pancreas-specific PTEN-null transgenic mouse model

Abstract

Abstract Background Metabolic alteration is one of the hallmarks of carcinogenesis. We aimed to identify certain metabolic biomarkers for the early detection of pancreatic cancer (PC) using the transgenic PTEN-null mouse model. Pancreas-specific deletion of PTEN in mouse caused progressive premalignant lesions such as highly proliferative ductal metaplasia. We imaged the mitochondrial redox state of the pancreases of the transgenic mice approximately eight months old using the redox scanner, i.e., the nicotinamide adenine dinucleotide/oxidized flavoproteins (NADH/Fp) fluorescence imager at low temperature. Two different approaches, the global averaging of the redox indices without considering tissue heterogeneity along tissue depth and the univariate analysis of multi-section data using tissue depth as a covariate were adopted for the statistical analysis of the multi-section imaging data. The standard deviations of the redox indices and the histogram analysis with Gaussian fit were used to determine the tissue heterogeneity. Results All methods show consistently that the PTEN deficient pancreases (Pdx1-Cre;PTENlox/lox) were significantly more heterogeneous in their mitochondrial redox state compared to the controls (PTENlox/lox). Statistical analysis taking into account the variations of the redox state with tissue depth further shows that PTEN deletion significantly shifted the pancreatic tissue to an overall more oxidized state. Oxidization of the PTEN-null group was not seen when the imaging data were analyzed by global averaging without considering the variation of the redox indices along tissue depth, indicating the importance of taking tissue heterogeneity into account for the statistical analysis of the multi-section imaging data. Conclusions This study reveals a possible link between the mitochondrial redox state alteration of the pancreas and its malignant transformation and may be further developed for establishing potential metabolic biomarkers for the early diagnosis of pancreatic cancer.