Rafia S Al-Lamki, Jun Wang, Thomas Willingham, Jordan S Pober, Aviva M Tolkovsky, John R Bradley
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引用次数: 0
Abstract
Clear-cell renal cell carcinoma (ccRCC), the most prevalent form of kidney cancer, is associated with an increased risk of local and systemic thromboembolism and a worse prognosis. The mechanisms that drive the coagulation program in tumours are not known. Combining RNAscope with immunofluorescence, local transcription of the key coagulation factors X and V, as well as prothrombin and fibrinogen chains (α, β, γ), across tumour cells, vascular endothelial cells and T cells is significantly enhanced in ccRCC tumours compared to adjacent normal kidney tissue. Elevated intratumoural protein expression of factors X and V is accompanied by local thrombin generation, fibrin deposition, and the presence of intravascular microthrombi, which themselves harbour coagulation transcripts. Mechanistic analysis using ccRCC organ cultures reveal that selective engagement of tumour necrosis factor receptor-2 (TNFR2) by a R2TNF mutein is sufficient to significantly enhance the transcription and protein expression of the same coagulation program in tumour cells, endothelial cells, and T cells compared to adjacent normal kidney cultures, whereas TNFR2 knockdown attenuates this response. In addition, TNFR2 appears to link inflammatory signalling with activation of the local coagulation system through the PI3K/Akt/MEK/NFκB signalling axes. These data provide evidence that locally produced coagulation factors driven by TNFR2 signalling may contribute to intratumoural pro-thrombotic outcomes in ccRCC, highlighting a novel pathway with potential therapeutic relevance.
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.