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The aim of this study was to investigate whether the lack of signal transducer and activator of transcription 5 (STAT5) in mature adipocytes of obese mice (Stat5Adipoq mice) improves glucose and lipid metabolism as previously observed in lean mice. Male Stat5Adipoq mice and their wild type (WT) littermates were fed high-fat diet (HFD). Effects of adipocyte STAT5 deficiency on adiposity as well as on glucose and lipid metabolism were determined under ad libitum feeding and after weight loss induced by calorie restriction. Compared to WT mice, obese Stat5Adipoq mice showed modestly accelerated weight gain and blunted depletion of fat stores under calorie restriction (reduction in % body fat after 3 weeks: WT, -9.3±1.1, vs Stat5Adipoq, -5.9±0.8, p = 0.04). No differences were observed between Stat5Adipoq and WT mice with regard to parameters of glucose and lipid metabolism including basal glycaemia, glucose tolerance, and plasma triglycerides. In conclusion, STAT5 deficiency in the adipocyte of HFD-fed obese mice was associated with increased fat accumulation. In contrast to previous findings in lean mice, however, lipid accumulation was not associated with any improvement in glucose and lipid metabolism. Our results do not support adipocyte STAT5 as a promising target for the treatment of obesity-associated metabolic derangements. [ABSTRACT FROM AUTHOR]

In targeted therapy, patient tumors are analyzed for aberrant activations of core cancer pathways, monitored based on biomarker expression, to ensure efficient treatment. Thus, diagnosis and therapeutic decisions are often based on the status of biomarkers determined by immunohistochemistry in combination with other clinical parameters. Standard evaluation of cancer specimen by immunohistochemistry is frequently impeded by its dependence on subjective interpretation, showing considerable intra- and inter-observer variability. To make treatment decisions more reliable, automated image analysis is an attractive possibility to reproducibly quantify biomarker expression in patient tissue samples. We tested whether image analysis could detect subtle differences in protein expression levels. Gene dosage effects generate well-graded expression patterns for most gene-products, which vary by a factor of two between wildtype and haploinsufficient cells lacking one allele. We used conditional mouse models with deletion of the transcription factors Stat5ab in the liver as well Junb deletion in a T-cell lymphoma model. We quantified the expression of total or activated STAT5AB or JUNB protein in normal (Stat5ab+/+ or JunB+/+), hemizygous (Stat5ab+/Δ or JunB+/Δ) or knockout (Stat5abΔ/Δ or JunBΔ/Δ) settings. Image analysis was able to accurately detect hemizygosity at the protein level. Moreover, nuclear signals were distinguished from cytoplasmic expression and translocation of the transcription factors from the cytoplasm to the nucleus was reliably detected and quantified using image analysis. We demonstrate that image analysis supported pathologists to score nuclear STAT5AB expression levels in immunohistologically stained human hepatocellular patient samples and decreased inter-observer variability. [ABSTRACT FROM AUTHOR]