Dataset Information

Fibroblast growth factor inhibition by molecular-targeted agents mitigates immunosuppressive tissue microenvironment in hepatocellular carcinoma.

ABSTRACT:

Background & aims

Combination immunotherapy refers to the use of immune checkpoint inhibitors (ICI) and molecular-targeted agents (MTA), which have recently been approved for the treatment of advanced hepatocellular carcinoma (HCC). Owing to its relatively low antitumor effect (up to 30%), sequential therapy following ICIs treatment is required in patients with HCC. This study aimed to determine the impact of MTAs on the tumor immune microenvironment (TIME).

Methods

We established immune syngeneic orthotopic HCC mouse models using Hep-55.1C and Hep-53.4, and treated them with MTAs (lenvatinib, sorafenib, regorafenib, cabozantinib, and DC101 as anti-vascular endothelial growth factor receptor-2 antibodies, and AZD4547 as a fibroblast growth factor receptor (FGFR)-1/2/3/4 inhibitor) for 2 weeks. Subsequently, alterations in the TIME caused by MTAs were evaluated using immunohistochemistry (antibodies for CD3, CD8, Foxp3, Granzyme B, Arginase-1, NK1.1, F4/80, CD11c, PD-1, and PD-L1). We conducted RNA-seq analysis using lenvatinib- and AZD4547-treated tumors. To confirm the clinical relevance of these findings, we analyzed the transcriptome data of human HCC cells (MHCC-97H) treated with various concentrations of lenvatinib for 24 h using RNA-seq data from the Gene Expression Omnibus database.

Results

The number of Foxp3- and F4/80-positive cells in the TIME was decreased in many MTAs. Cabozantinib increased the numbers in NK1.1-, Granzyme B, and CD11c-positive cells. Lenvatinib and AZD4547 increased the number of CD8, Granzyme B, and PD-L1-positive cells. Gene ontology enrichment analysis revealed that lipid metabolism-related genes were downregulated by lenvatinib and AZD4547. In total, 161 genes downregulated by FGFR inhibition in rodent models overlapped with those downregulated by lenvatinib in human HCC cells.

Conclusions

In this study, we showed that cabozantinib activated the innate immune system, and lenvatinib and AZD4547, which commonly inhibit FGFR signaling, altered TIME to a hot immune state by downregulating lipid metabolism-related genes. These findings support the therapeutic use of combination immunotherapies.

SUBMITTER: Suzuki H

PROVIDER: S-EPMC11014819 | biostudies-literature | 2024 Apr

REPOSITORIES: biostudies-literature

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Publications

Fibroblast growth factor inhibition by molecular-targeted agents mitigates immunosuppressive tissue microenvironment in hepatocellular carcinoma.

Suzuki Hiroyuki H Iwamoto Hideki H Tanaka Toshimitsu T Sakaue Takahiko T Imamura Yasuko Y Masuda Atsutaka A Nakamura Toru T Koga Hironori H Hoshida Yujin Y Kawaguchi Takumi T

Hepatology international 20231021 2

<h4>Background & aims</h4>Combination immunotherapy refers to the use of immune checkpoint inhibitors (ICI) and molecular-targeted agents (MTA), which have recently been approved for the treatment of advanced hepatocellular carcinoma (HCC). Owing to its relatively low antitumor effect (up to 30%), sequential therapy following ICIs treatment is required in patients with HCC. This study aimed to determine the impact of MTAs on the tumor immune microenvironment (TIME).<h4>Methods</h4>We established ...[more]

PMID: 37864726

Similar Datasets

Project description:Background: Generally, hepatocellular carcinoma (HCC) exists in an immunosuppressive microenvironment that promotes tumor evasion. Hypoxia can impact intercellular crosstalk in the tumor microenvironment. This study aimed to explore and elucidate the underlying relationship between hypoxia and immunotherapy in patients with HCC. Methods: HCC genomic and clinicopathological datasets were obtained from The Cancer Genome Atlas (TCGA-LIHC), Gene Expression Omnibus databases (GSE14520) and International Cancer Genome Consortium (ICGC-LIRI). The TCGA-LIHC cases were divided into clusters based on single sample gene set enrichment analysis and hierarchical clustering. After identifying patients with immunosuppressive microenvironment with different hypoxic conditions, correlations between immunological characteristics and hypoxia clusters were investigated. Subsequently, a hypoxia-associated score was established by differential expression, univariable Cox regression, and lasso regression analyses. The score was verified by survival and receiver operating characteristic curve analyses. The GSE14520 cohort was used to validate the findings of immune cell infiltration and immune checkpoints expression, while the ICGC-LIRI cohort was employed to verify the hypoxia-associated score. Results: We identified hypoxic patients with immunosuppressive HCC. This cluster exhibited higher immune cell infiltration and immune checkpoint expression in the TCGA cohort, while similar significant differences were observed in the GEO cohort. The hypoxia-associated score was composed of five genes (ephrin A3, dihydropyrimidinase like 4, solute carrier family 2 member 5, stanniocalcin 2, and lysyl oxidase). In both two cohorts, survival analysis revealed significant differences between the high-risk and low-risk groups. In addition, compared to other clinical parameters, the established score had the highest predictive performance at both 3 and 5 years in two cohorts. Conclusion: This study provides further evidence of the link between hypoxic signals in patients and immunosuppression in HCC. Defining hypoxia-associated HCC subtypes may help reveal potential regulatory mechanisms between hypoxia and the immunosuppressive microenvironment, and our hypoxia-associated score could exhibit potential implications for future predictive models.

Dataset Information

Fibroblast growth factor inhibition by molecular-targeted agents mitigates immunosuppressive tissue microenvironment in hepatocellular carcinoma.

Background & aims

Methods

Results

Conclusions

Publications

Fibroblast growth factor inhibition by molecular-targeted agents mitigates immunosuppressive tissue microenvironment in hepatocellular carcinoma.

Similar Datasets

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