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Background: Hepatocellular carcinoma (HCC) is closely associatedwith chronic liver diseases, particularly liver cirrhosis, which has an altered extracellular matrix (ECM) composition. The influence and its mechanism of the cirrhotic-ECM on the response of HCC to immune checkpoint inhibitor (ICI) remains less clarified. Methods: In silico, proteomic and pathological assessment of alteration of cirrhotic-ECM were applied in clinical cohort. Multiple pre-clinical models with ECM manipulation were used to evaluate cirrhotic-ECM's effect on ICI treatment. In silico, flow cytometry and IHC were applied to explore how cirrhotic-ECM affect HCC microenvironment. In vitro and in vivo experiments were carried out to identify the mechanism of how cirrhotic-ECM undermined ICI treatment. Results: We defined "a pro-tumor cirrhotic-ECM" which was featured as the up-regulation of collagen type 1 (Col1). Cirrhotic-ECM/Col1 was closely related to impaired T cell function and limited anti PD-1 (aPD-1) response of HCC patients from the TCGA pan cancer cohort and the authors' institution, as well as in multiple pre-clinical models. Mechanically, cirrhotic-ECM/Col1 orchestrated an immunosuppressive microenvironment (TME) by triggering Col1-DDR1-NFκB-CXCL8 axis, which initiated neutrophil extracellular traps (NETs) formation to shield HCC cells from attacking T cells and impede approaching T cells. Nilotinib, an inhibitor of DDR1, reversed the neutrophils/NETs dominant TME and efficiently enhanced the response of HCC to aPD-1. Conclusions: Cirrhotic-ECM modulated a NETs enriched TME in HCC, produced an immune suppressive TME and weakened ICI efficiency. Col1 receptor DDR1 could be a potential target synergically used with ICI to overcome ECM mediated ICI resistance. These provide a mechanical insight and novel strategy to overcome the ICI resistance of HCC. [ABSTRACT FROM AUTHOR]

Background: Neutrophils form extracellular net-like structures called neutrophil extracellular traps (NETs). Emerging evidence has shown that cancer can induce NET formation; however, it is not fully understood how NETs influence cancer biology, and no consensus has been reached on their pro- or antitumor effects. A comprehensive analysis of the global NET-associated gene regulatory network is currently unavailable and is urgently needed. Methods: We systematically explored and discussed NET enrichment, NET-associated gene regulatory patterns, and the prognostic implications of NETs in approximately 8,000 patients across 22 major human cancer types. We identified NET-associated regulatory gene sets that we then screened for NET-associated regulatory patterns that might affect patient survival. We functionally annotated the NET-associated regulatory patterns to compare the biological differences between NET-related survival subgroups. Results: A gene set variation analysis (GSVA) based on 23 major component genes was used to calculate a metric called the NET score. We found that the NET score was closely associated with many important cancer hallmarks, particularly inflammatory responses and epithelial-to-mesenchymal transition (EMT)-induced metastasis. Higher NET scores were related to poor immunotherapy response. Survival analysis revealed that NETs had diverse prognostic impacts among various cancer types. The NET-associated regulatory patterns linked to shorter or longer cancer patient survival were distinct from each other. Functional analysis revealed that more of the NET-associated regulatory genes linked to poor cancer survival were associated with extracellular matrix (ECM) remodeling and pan-cancerous risk factors. SPP1 was found to be highly expressed and correlated with NET formation in cancers with poor survival. We also found that the co-upregulation of NET formation and SPP1 expression was closely linked to increased EMT and poor survival, that SPP1 influenced NET-induced malignant capacity, and that SPP1 overproduction induced a robust formation of metastatic-promoting NETs. Conclusion: NETs were common across cancers but displayed a diverse regulatory pattern and outcome readouts in different cancer types. SPP1 is potentially the key to NET-related poor outcomes. [ABSTRACT FROM AUTHOR]