CD168+ macrophages promote hepatocellular carcinoma tumor stemness and progression through TOP2A/β-catenin/YAP1 axis

Cancer stem cells: advances in knowledge and implications for cancer therapy

Cancer stem cells (CSCs), a small subset of cells in tumors that are characterized by self-renewal and continuous proliferation, lead to tumorigenesis, metastasis, and maintain tumor heterogeneity. Cancer continues to be a significant global disease burden. In the past, surgery, radiotherapy, and chemotherapy were the main cancer treatments. The technology of cancer treatments continues to develop and advance, and the emergence of targeted therapy, and immunotherapy provides more options for patients to a certain extent. However, the limitations of efficacy and treatment resistance are still inevitable. Our review begins with a brief introduction of the historical discoveries, original hypotheses, and pathways that regulate CSCs, such as WNT/β-Catenin, hedgehog, Notch, NF-κB, JAK/STAT, TGF-β, PI3K/AKT, PPAR pathway, and their crosstalk. We focus on the role of CSCs in various therapeutic outcomes and resistance, including how the treatments affect the content of CSCs and the alteration of related molecules, CSCs-mediated therapeutic resistance, and the clinical value of targeting CSCs in patients with refractory, progressed or advanced tumors. In summary, CSCs affect therapeutic efficacy, and the treatment method of targeting CSCs is still difficult to determine. Clarifying regulatory mechanisms and targeting biomarkers of CSCs is currently the mainstream idea.

Proteo-genomic characterization of cirrhosis-associated liver cancers reveals potential subtypes and therapeutic targets

BACKGROUND

This study aimed to identify potential subtypes of hepatocellular carcinoma (HCC) associated with cirrhosis and to investigate key markers using bioinformatic analysis of gene expression datasets-0.

METHODS

Three data sets (GSE17548, GSE56140, and GSE87630) were extracted from the Gene Expression Omnibus (GEO) database and normalized using the Limma package in R. Principal component analysis (PCA) and cluster analysis was performed to examine data distribution and identify subtypes. Differential gene expression analysis was performed using the Limma software package. Protein-protein interaction analysis and functional annotation were performed using the STRING database and Cytoscape software. Important signaling pathways and processes were identified using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) Pathway Analysis.

RESULTS

The analysis revealed different subtypes of HCC associated with cirrhosis and identified several key genes, including CCNB2, MCM4, and CDC20, with strong binding power and prognostic value. Functional annotation indicated involvement in cell cycle regulation and metabolic pathways. ROC analysis showed high sensitivity and specificity of these genes in predicting HCC prognosis.

CONCLUSION

These results suggest that CCNB2, MCM4, and CDC20 may serve as potential biomarkers for predicting HCC prognosis in patients with cirrhosis and provide insights into the molecular mechanisms of HCC progression.

Characterizing ligand-receptor interactions and unveiling the pro-tumorigenic role of CCL16-CCR1 axis in the microenvironment of hepatocellular carcinoma

Background

The heterogeneity of the tumor microenvironment significantly influences the prognosis of hepatocellular carcinoma (HCC) patients, with cell communication through ligand-receptor complexes playing a central role.

Methods

We conducted single-cell transcriptomic analysis on ten HCC tissues to identify ligand-receptor genes involved in malignant HCC cell communication using CellChat. Leveraging RNA-Seq data from the TCGA Liver Cancer (TCGA-LIHC) and Liver Cancer - RIKEN, JP (LIRI-JP) cohorts, we employed Cox regression analysis to screen for prognosis-related genes. Prognostic risk models were constructed through unsupervised clustering and differential gene expression analysis. Subsequently, a co-culture system involving tumor cells and macrophages was established. A series of experiments, including Transwell assays, immunofluorescence staining, immunoprecipitation, flow cytometry, and immunohistochemistry, were conducted to elucidate the mechanism through which HCC cells recruit macrophages via the CCL16-CCR1 axis.

Results

Single-cell analysis unveiled significant interactions between malignant HCC cells and macrophages, identifying 76 related ligand-receptor genes. Patients were classified into three subtypes based on the expression patterns of eight prognosis-related ligand-receptor genes. The subtype with the worst prognosis exhibited reduced infiltration of T cell-related immune cells, downregulation of immune checkpoint genes, and increased M2-like tumor-associated macrophage scores. In vitro experiments confirmed the pivotal role of the CCL16-CCR1 axis in the recruitment and M2 polarization of tumor-associated macrophages. Clinical samples demonstrated a significant association between CCL16 protein expression levels and advanced stage, lymph node metastasis, and distant metastasis. Immunohistochemistry and immunofluorescence staining further confirmed the correlation between CCL16 and CCR1, CD68, and CD206, as well as CD68+CCR1+ macrophage infiltration.

Conclusions

Our study identified molecular subtypes, a prognostic model, and immune microenvironment features based on ligand-receptor interactions in malignant HCC cell communication. Moreover, we revealed the pro-tumorigenic role of HCC cells in recruiting M2-like tumor-associated macrophages through the CCL16-CCR1 axis.

Perspective from single-cell sequencing: Is inflammation in acute ischemic stroke beneficial or detrimental?

BACKGROUND

Acute ischemic stroke (AIS) is a common cerebrovascular event associated with high incidence, disability, and poor prognosis. Studies have shown that various cell types, including microglia, astrocytes, oligodendrocytes, neurons, and neutrophils, play complex roles in the early stages of AIS and significantly affect its prognosis. Thus, a comprehensive understanding of the mechanisms of action of these cells will be beneficial for improving stroke prognosis. With the rapid development of single-cell sequencing technology, researchers have explored the pathophysiological mechanisms underlying AIS at the single-cell level.

METHOD

We systematically summarize the latest research on single-cell sequencing in AIS.

RESULT

In this review, we summarize the phenotypes and functions of microglia, astrocytes, oligodendrocytes, neurons, neutrophils, monocytes, and lymphocytes, as well as their respective subtypes, at different time points following AIS. In particular, we focused on the crosstalk between microglia and astrocytes, oligodendrocytes, and neurons. Our findings reveal diverse and sometimes opposing roles within the same cell type, with the possibility of interconversion between different subclusters.

CONCLUSION

This review offers a pioneering exploration of the functions of various glial cells and cell subclusters after AIS, shedding light on their regulatory mechanisms that facilitate the transformation of detrimental cell subclusters towards those that are beneficial for improving the prognosis of AIS. This approach has the potential to advance the discovery of new specific targets and the development of drugs, thus representing a significant breakthrough in addressing the challenges in AIS treatment.