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Scribble Deficiency Promotes Pancreatic Ductal Adenocarcinoma Development and Metastasis
Camino Bermejo-Rodriguez1, Joaquín Araos Henríquez2, Giuseppina Caligiuri3,4
1Department of Molecular and Clinical Cancer Medicine, University of Liverpool, Liverpool, United Kingdom.
Abstract:
Perturbation of cell polarity is a hallmark of pancreatic ductal adenocarcinoma (PDAC) progression. Scribble (SCRIB) is a well-characterized polarity regulator that has diverse roles in the pathogenesis of human neoplasms. To investigate the impact of SCRIB deficiency in PDAC development and progression, Scrib expression was genetically ablated in well-established mouse models of PDAC. Scrib loss in combination with KrasG12D did not influence development of pancreatic intraepithelial neoplasms in mice. However, Scrib deletion cooperated with KrasG12D and concomitant Trp53 heterozygous deletion to promote invasive PDAC and metastatic dissemination, leading to reduced overall survival. Immunohistochemical and transcriptome analyses revealed that Scrib-null tumors display a pronounced reduction of collagen content and an abundance of cancer-associated fibroblasts (CAF). Mechanistically, IL1α levels were reduced in Scrib-deficient tumors, and Scrib knockdown downregulated IL1α in mouse PDAC organoids (mPDO), which impaired CAF activation. Furthermore, Scrib loss increased YAP activation in mPDOs and established PDAC cell lines, enhancing cell survival. Clinically, SCRIB expression was decreased in human PDAC, and SCRIB mislocalization was associated with poorer patient outcome. These results indicate that SCRIB deficiency enhances cancer cell survival and remodels the tumor microenvironment to accelerate PDAC development and progression, establishing the tumor suppressor function of SCRIB in advanced pancreatic cancer. Significance: SCRIB loss promotes invasive pancreatic cancer development via both cell-autonomous and non-cell-autonomous processes and is associated with poorer outcomes, denoting SCRIB as a tumor suppressor and potential biomarker for the prediction of recurrence.
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