Browsing by Subject "Expression profiling"

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    Anticachectic regulator analysis reveals Perp-dependent antitumorigenic properties of 3-methyladenine in pancreatic cancer
    (American Society for Clinical Investigation, 2022-01-25) Dasgupta, Aneesha; Arneson-Wissink, Paige C.; Schmitt, Rebecca E.; Cho, Dong Seong; Ducharme, Alexandra M.; Hogenson, Tara L.; Krueger, Eugene W.; Bamlet, William R.; Zhang, Lizhi; Razidlo, Gina L.; Fernandez-Zapico, Martin E.; Doles, Jason D.; Anatomy, Cell Biology and Physiology, School of Medicine
    Approximately 80% of pancreatic cancer patients suffer from cachexia, and one-third die due to cachexia-related complications such as respiratory failure and cardiac arrest. Although there has been considerable research into cachexia mechanisms and interventions, there are, to date, no FDA-approved therapies. A major contributing factor for the lack of therapy options could be the failure of animal models to accurately recapitulate the human condition. In this study, we generated an aged model of pancreatic cancer cachexia to compare cachexia progression in young versus aged tumor-bearing mice. Comparative skeletal muscle transcriptome analyses identified 3-methyladenine (3-MA) as a candidate antiwasting compound. In vitro analyses confirmed antiwasting capacity, while in vivo analysis revealed potent antitumor effects. Transcriptome analyses of 3-MA-treated tumor cells implicated Perp as a 3-MA target gene. We subsequently (a) observed significantly higher expression of Perp in cancer cell lines compared with control cells, (b) noted a survival disadvantage associated with elevated Perp, and (c) found that 3-MA-associated Perp reduction inhibited tumor cell growth. Finally, we have provided in vivo evidence that survival benefits conferred by 3-MA administration are independent of its effect on tumor progression. Taken together, we report a mechanism linking 3-MA to Perp inhibition, and we further implicate Perp as a tumor-promoting factor in pancreatic cancer.
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    Integration of spatial and single-cell transcriptomics localizes epithelial cell–immune cross-talk in kidney injury
    (American Society for Clinical Investigation, 2021-06-22) Ferreira, Ricardo Melo; Sabo, Angela R.; Winfree, Seth; Collins, Kimberly S.; Janosevic, Danielle; Gulbronson, Connor J.; Cheng, Ying-Hua; Casbon, Lauren; Barwinska, Daria; Ferkowicz, Michael J.; Xuei, Xiaoling; Zhang, Chi; Dunn, Kenneth W.; Kelly, Katherine J.; Sutton, Timothy A.; Hato, Takashi; Dagher, Pierre C.; El-Achkar, Tarek M.; Eadon, Michael T.; Medicine, School of Medicine
    Single-cell sequencing studies have characterized the transcriptomic signature of cell types within the kidney. However, the spatial distribution of acute kidney injury (AKI) is regional and affects cells heterogeneously. We first optimized coordination of spatial transcriptomics and single-nuclear sequencing data sets, mapping 30 dominant cell types to a human nephrectomy. The predicted cell-type spots corresponded with the underlying histopathology. To study the implications of AKI on transcript expression, we then characterized the spatial transcriptomic signature of 2 murine AKI models: ischemia/reperfusion injury (IRI) and cecal ligation puncture (CLP). Localized regions of reduced overall expression were associated with injury pathways. Using single-cell sequencing, we deconvoluted the signature of each spatial transcriptomic spot, identifying patterns of colocalization between immune and epithelial cells. Neutrophils infiltrated the renal medulla in the ischemia model. Atf3 was identified as a chemotactic factor in S3 proximal tubules. In the CLP model, infiltrating macrophages dominated the outer cortical signature, and Mdk was identified as a corresponding chemotactic factor. The regional distribution of these immune cells was validated with multiplexed CO-Detection by indEXing (CODEX) immunofluorescence. Spatial transcriptomic sequencing complemented single-cell sequencing by uncovering mechanisms driving immune cell infiltration and detection of relevant cell subpopulations.