Shamara S Lawrence, Hironobu Yamashita, Lauren Shuman, Jay D Raman, Monika Joshi, Gregory S Yochum, Xue-Ru Wu, Hikmat A Al-Ahmadie, Joshua I Warrick, Vonn Walter, David J DeGraff
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引用次数: 0
Abstract
During progression, luminal muscle-invasive bladder cancer (MIBC) can transition to the aggressive basal-squamous (Ba/Sq) subtype. Reduced expression of forkhead box A1 (FOXA1) in the urothelium is a hallmark and driver of the Ba/Sq transcriptional state and squamous differentiation. Ba/Sq tumors are highly inflamed; however, the specific inflammatory pathways contributing to the Ba/Sq state are unknown. In this study, transcriptomic analyses of The Cancer Genome Atlas MIBC cohort were performed to determine whether immune response gene signatures were associated with MIBC molecular states. Results showed that Ba/Sq MIBCs were enriched for the interferon-γ (IFN-γ)-dominant signature. Ba/Sq MIBCs exhibited increased IFN-γ/Janus kinase (JAK)/STAT pathway activity, corresponding to reduced FOXA1 regulon activity. Immunohistochemistry of MIBC specimens demonstrated that JAK1 expression was significantly increased in tumor areas with squamous differentiation. IFN-γ treatment of luminal MIBC cell lines significantly decreased the expression of luminal transcriptional drivers, including FOXA1, and increased the expression of Ba/Sq markers in a STAT1-dependent manner. RNA-sequencing analyses identified IFN-γ as a driver of the Ba/Sq state. The ability of IFN-γ to repress FOXA1 in luminal cells was abrogated by ruxolitinib inhibition of JAK1/2 activity. Additionally, pharmacologic inhibition or genetic ablation of JAK1 restored FOXA1 expression in Ba/Sq MIBC cells. These findings are the first to identify IFN-γ as an epithelial cell-extrinsic mechanism to repress FOXA1 and drive the Ba/Sq state in MIBC.
期刊介绍:
The American Journal of Pathology, official journal of the American Society for Investigative Pathology, published by Elsevier, Inc., seeks high-quality original research reports, reviews, and commentaries related to the molecular and cellular basis of disease. The editors will consider basic, translational, and clinical investigations that directly address mechanisms of pathogenesis or provide a foundation for future mechanistic inquiries. Examples of such foundational investigations include data mining, identification of biomarkers, molecular pathology, and discovery research. Foundational studies that incorporate deep learning and artificial intelligence are also welcome. High priority is given to studies of human disease and relevant experimental models using molecular, cellular, and organismal approaches.