Isolation and characterization of cancer-associated fibroblasts in the tumor microenvironment of hepatocellular carcinoma

Intrahepatic IgA complex induces polarization of cancer-associated fibroblasts to matrix phenotypes in the tumor microenvironment of HCC

BACKGROUND AND AIMS

Cancer-associated fibroblasts (CAFs) play key roles in the tumor microenvironment. IgA contributes to inflammation and dismantling antitumor immunity in the human liver. In this study, we aimed to elucidate the effects of the IgA complex on CAFs in Pil Soo Sung the tumor microenvironment of HCC.

APPROACH AND RESULTS

CAF dynamics in HCC tumor microenvironment were analyzed through single-cell RNA sequencing of HCC samples. CAFs isolated from 50 HCC samples were treated with mock or serum-derived IgA dimers in vitro. Progression-free survival of patients with advanced HCC treated with atezolizumab and bevacizumab was significantly longer in those with low serum IgA levels ( p <0.05). Single-cell analysis showed that subcluster proportions in the CAF-fibroblast activation protein-α matrix were significantly increased in patients with high serum IgA levels. Flow cytometry revealed a significant increase in the mean fluorescence intensity of fibroblast activation protein in the CD68 + cells from patients with high serum IgA levels ( p <0.001). We confirmed CD71 (IgA receptor) expression in CAFs, and IgA-treated CAFs exhibited higher programmed death-ligand 1 expression levels than those in mock-treated CAFs ( p <0.05). Coculture with CAFs attenuated the cytotoxic function of activated CD8 + T cells. Interestingly, activated CD8 + T cells cocultured with IgA-treated CAFs exhibited increased programmed death-1 expression levels than those cocultured with mock-treated CAFs ( p <0.05).

CONCLUSIONS

Intrahepatic IgA induced polarization of HCC-CAFs into more malignant matrix phenotypes and attenuates cytotoxic T-cell function. Our study highlighted their potential roles in tumor progression and immune suppression.

Machine learning model reveals roles of interferon‑stimulated genes in sorafenib‑resistant liver cancer

HCC (Hepatocellular carcinoma) is the most common malignant tumor; however, the molecular pathogenesis of these tumors is not well understood. Sorafenib, an approved treatment for HCC, inhibits angiogenesis and tumor cell proliferation. However, only ~30% of patients are sensitive to sorafenib and most show disease progression, indicating resistance to sorafenib. The present study used machine learning to investigate several mechanisms related to sorafenib resistance in liver cancer cells. This revealed that unphosphorylated interferon-stimulated genes (U-ISGs) were upregulated in sorafenib-resistant liver cancer cells, and the unphosphorylated ISGF3 (U-ISGF3; unphosphorylated STAT1, unphosphorylated STAT2 and IRF9) complex was increased in sorafenib-resistant liver cancer cells. Further study revealed that the knockdown of the U-ISGF3 complex downregulated U-ISGs. In addition, inhibition of the U-ISGF3 complex downregulated cell viability in sorafenib-resistant liver cancer cells. These results suggest that U-ISGF3 induced sorafenib resistance in liver cancer cells. Also, this mechanism may also be relevant to patients with sorafenib resistance.

Rebuilding the microenvironment of primary tumors in humans: a focus on stroma

Conventional tumor models have critical shortcomings in that they lack the complexity of the human stroma. The heterogeneous stroma is a central compartment of the tumor microenvironment (TME) that must be addressed in cancer research and precision medicine. To fully model the human tumor stroma, the deconstruction and reconstruction of tumor tissues have been suggested as new approaches for in vitro tumor modeling. In this review, we summarize the heterogeneity of tumor-associated stromal cells and general deconstruction approaches used to isolate patient-specific stromal cells from tumor tissue; we also address the effect of the deconstruction procedure on the characteristics of primary cells. Finally, perspectives on the future of reconstructed tumor models are discussed, with an emphasis on the essential prerequisites for developing authentic humanized tumor models.