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Characterization of the inflammatory microenvironment and hepatic macrophage subsets in experimental hepatocellular carcinoma models.

ABSTRACT: Hepatocellular carcinoma (HCC) is one of the leading causes of cancer-related death worldwide. HCC typically develops on a background of chronic inflammation and fibrosis with tumor associated macrophages (TAMs) playing an important role in chronic inflammation-induced HCC and progression. However, the liver harbors unique macrophages, resident liver Kupffer cells (KCs) and monocyte-derived macrophages (Mo-Mφ), and their contribution to HCC and to the population of TAMs is incompletely known. Here, we characterized the tumor microenvironment and the proportion and transcriptional profile of hepatic macrophages (Mφ) in two commonly used HCC mouse models. A gradually increased expression of inflammatory, immune regulatory, fibrotic and cell proliferation pathways and markers was observed during diethylnitrosamine (DEN)- and non-alcoholic steatohepatitis (NASH)-induced HCC development. The transcriptional phenotypes of isolated hepatic Mφ subsets were clearly distinct and shifted during HCC development, with mixed pro-inflammatory and tumor-promoting expression profiles. There were marked differences between the models as well, with Mφ in NASH-HCC exhibiting a more immunomodulatory phenotype, in conjunction with an upregulation of lipid metabolism genes. Our data show that at least some infiltrated macrophages display expression of pro-tumoral markers, and that Kupffer cells are part of the population of TAMs and enhance tumor progression. These insights are useful to further unravel sequential pathogenic events during hepatocarcinogenesis and direct future development of new treatment strategies for HCC.

SUBMITTER: Degroote H

PROVIDER: S-EPMC7984829 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Macrophage activity is a major component of the healthy response to infection and injury that consists of tightly regulated early pro-inflammatory activation followed by anti-inflammatory and regenerative activity. In numerous diseases, however, macrophage polarization becomes dysregulated and can not only impair recovery, but can promote further injury and pathogenesis, e.g., after trauma or in diabetic ulcers. Dysregulated macrophages may either fail to polarize or become chronically polarized, resulting in increased production of cytotoxic factors, diminished capacity to clear pathogens, or failure to promote tissue regeneration. In these cases, a method of predicting and dynamically controlling macrophage polarization will enable a new strategy for treating diverse inflammatory diseases. In this work, we developed a model-predictive control framework to temporally regulate macrophage polarization. Using RAW 264.7 macrophages as a model system, we enabled temporal control by identifying transfer function models relating the polarization marker iNOS to exogenous pro- and anti-inflammatory stimuli. These stimuli-to-iNOS response models were identified using linear autoregressive with exogenous input terms (ARX) equations and were coupled with non-linear elements to account for experimentally identified supra-additive and hysteretic effects. Using this model architecture, we were able to reproduce experimentally observed temporal iNOS dynamics induced by lipopolysaccharides (LPS) and interferon gamma (IFN-γ). Moreover, the identified model enabled the design of time-varying input trajectories to experimentally sustain the duration and magnitude of iNOS expression. By designing transfer function models with the intent to predict cell behavior, we were able to predict and experimentally obtain temporal regulation of iNOS expression using LPS and IFN-γ from both naïve and non-naïve initial states. Moreover, our data driven models revealed decaying magnitude of iNOS response to LPS stimulation over time that could be recovered using combined treatment with both LPS and IFN-γ. Given the importance of dynamic tissue macrophage polarization and overall inflammatory regulation to a broad number of diseases, the temporal control methodology presented here will have numerous applications for regulating immune activity dynamics in chronic inflammatory diseases.

Project description:PurposeHepatocellular carcinoma (HCC) is characterized by a poor prognosis and a high recurrence rate. The tumor immune microenvironment in HCC has been characterized as shifted toward immunosuppression. We conducted a genomic data-driven classification of immune microenvironment HCC subtypes. In addition, we demonstrated their prognostic value and suggested a potential therapeutic targeting strategy.MethodsRNA sequencing data from The Cancer Genome Atlas-Liver Hepatocellular Carcinoma was used (n = 366). Abundance of immune cells was imputed using CIBERSORT and visualized using unsupervised hierarchic clustering. Overall survival (OS) was analyzed using Kaplan-Meier estimates and Cox regression. Differential expression and gene set enrichment analyses were conducted on immune clusters with poor OS and high programmed death-1 (PD-1)/programmed death-ligand 1 (PD-L1) coexpression. A scoring metric combining differentially expressed genes and immune cell content was created, and its prognostic value and immune checkpoint blockade response prediction was evaluated.ResultsTwo clusters were characterized by macrophage enrichment, with distinct M0Hi and M2Hi subtypes. M2Hi (P = .038) and M0Hi (P = .018) were independently prognostic for OS on multivariable analysis. Kaplan-Meier estimates demonstrated that patients in M0Hi and M2Hi treated with sorafenib had decreased OS (P = .041), and angiogenesis hallmark genes were enriched in the M0Hi group. CXCL6 and POSTN were overexpressed in both the M0Hi and the PD-1Hi/PD-L1Hi groups. A score consisting of CXCL6 and POSTN expression and absolute M0 macrophage content was discriminatory for OS (intermediate: hazard ratio [HR], 1.59; P ≤ .001; unfavorable: HR, 2.08; P = .04).ConclusionDistinct immune cell clusters with macrophage predominance characterize an aggressive HCC phenotype, defined molecularly by angiogenic gene enrichment and clinically by poor prognosis and sorafenib response. This novel immunogenomic signature may aid in stratification of unresectable patients to receive checkpoint inhibitor and antiangiogenic therapy combinations.

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Characterization of the inflammatory microenvironment and hepatic macrophage subsets in experimental hepatocellular carcinoma models.

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