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https://www.selleckchem.com/products/blu-667.html Combined predictive models comprising the protein expression status of the validated CCC, EC and MC biomarkers together with established clinical markers (age, stage, CA125, ploidy) improved the predictive power in comparison with models containing established clinical markers alone, further strengthening the importance of the biomarkers in ovarian carcinoma. Further, even improved predictive powers were demonstrated when combining these models with our previously identified prognostic biomarkers PITHD1 (CCC) and GPR158 (MC). Moreover, the proteins demonstrated improved risk prediction of CCC-, EC-, and MC-associated ovarian carcinoma survival. The novel histotype-specific prognostic biomarkers may not only improve prognostication and patient stratification of early-stage ovarian carcinomas, but may also guide future clinical therapy decisions. Copyright © 2020 Engqvist, Parris, Kovács, Rönnerman, Sundfeldt, Karlsson and Helou.Altered metabolism is considered a core hallmark of cancer. By monitoring in vivo metabolites changes or characterizing the tumor microenvironment, non-invasive imaging approaches play a fundamental role in elucidating several aspects of tumor biology. Within the magnetic resonance imaging (MRI) modality, the chemical exchange saturation transfer (CEST) approach has emerged as a new technique that provides high spatial resolution and sensitivity for in vivo imaging of tumor metabolism and acidosis. This mini-review describes CEST-based methods to non-invasively investigate tumor metabolism and important metabolites involved, such as glucose and lactate, as well as measurement of tumor acidosis. Approaches that have been exploited to assess response to anticancer therapies will also be reported for each specific technique. Copyright © 2020 Consolino, Anemone, Capozza, Carella, Irrera, Corrado, Dhakan, Bracesco and Longo.Background The close proximity of adipose tissue and mammary epithelium pred

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