Identification of the Different Gene Expression Characteristics from Liver Cirrhosis to Hepatocellular Carcinoma Using Single-Cell Sequencing Analyses

Prognostic risk model of LIHC T-cells based on scRNA-seq and RNA-seq and the regulation of the tumor immune microenvironment

BACKGROUND

T-cell-related genes play a crucial role in LIHC development. However, a reliable prognostic profile based on risk models of these genes has yet to be identified.

METHODS

Single-cell datasets from both tumor and normal tissue samples were obtained from the GEO database. We identified T-cell marker genes and developed a genetic risk model using the TCGA-LIHC dataset, which was subsequently validated with an independent GEO dataset. We also explored the relationship between risk model predictions and immune responses.

RESULTS

We constructed a prognostic risk model using eight gene features identified through screening 860 T-cell marker genes via scRNA-seq and RNA-seq, which was subsequently integrated with the TCGA dataset. Its validity was independently confirmed using GEO and ICGC datasets. The TCGA dataset was stratified into high-risk and low-risk groups based on the risk model. Multivariate Cox regression analysis confirmed the risk score as an independent prognostic factor. GSEA indicated ribosomal transporter metabolism enrichment in the high-risk group and significant transcriptional activation in the low-risk group. ESTIMATE analysis showed higher ESTIMATE, immune, and stromal scores in the low-risk group, which also exhibited lower tumor purity than the high-risk group. Immunophenotyping revealed distinct patterns of immune cell infiltration and an immunosuppressive environment in the high-risk group.

CONCLUSIONS

This study introduces a T-cell marker-based prognostic risk model for LIHC patients. This model effectively predicted survival outcomes and immunotherapy effectiveness in LIHC patients, aligning with diverse immune responses and the distinct immunological profiles observed in the high-risk group.

Understanding tumour endothelial cell heterogeneity and function from single-cell omics

Anti-angiogenic therapies (AATs) are used to treat different types of cancers. However, their success is limited owing to insufficient efficacy and resistance. Recently, single-cell omics studies of tumour endothelial cells (TECs) have provided new mechanistic insight. Here, we overview the heterogeneity of human TECs of all tumour types studied to date, at the single-cell level. Notably, most human tumour types contain varying numbers but only a small population of angiogenic TECs, the presumed targets of AATs, possibly contributing to the limited efficacy of and resistance to AATs. In general, TECs are heterogeneous within and across all tumour types, but comparing TEC phenotypes across tumours is currently challenging, owing to the lack of a uniform nomenclature for endothelial cells and consistent single-cell analysis protocols, urgently raising the need for a more consistent approach. Nonetheless, across most tumour types, universal TEC markers (ACKR1, PLVAP and IGFBP3) can be identified. Besides angiogenesis, biological processes such as immunomodulation and extracellular matrix organization are among the most commonly predicted enriched signatures of TECs across different tumour types. Although angiogenesis and extracellular matrix targets have been considered for AAT (without the hoped success), the immunomodulatory properties of TECs have not been fully considered as a novel anticancer therapeutic approach. Therefore, we also discuss progress, limitations, solutions and novel targets for AAT development.

Integrated Analysis of mRNA and lncRNA Expression Profiles Reveals Regulatory Networks Associated with Decompensated Cirrhosis

The stage of decompensation is termed end-stage liver cirrhosis. Patients with decompensated cirrhosis (DCC) often have a variety of comorbidities that contribute to exacerbation of the disease and its high mortality rate. By comparing differential gene expression, transcriptomic analysis is useful for exploring relevant functional changes during disease progression. The purpose of this study was to identify differentially expressed long noncoding RNAs (lncRNAs) and mRNAs in patients with decompensated cirrhosis and to further explore the functions as well as interactions between lncRNAs and mRNAs. Four patients with decompensated cirrhosis and four controls with liver cirrhosis were recruited in this study. RNA was isolated from peripheral blood mononuclear cells, and RNA-seq was used for transcriptome analysis. The functions of differentially expressed mRNAs were revealed by Gene Ontology (GO) functional annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses, and a regulatory network was also constructed. A total of 1046 differentially expressed mRNAs and 1175 lncRNAs were identified between the decompensated cirrhosis patients and cirrhosis controls. Functional enrichment analyses indicated enrichment of genes involved in pathways related to inflammation and cellular metabolic activities. In addition, the findings suggested that the phagosome/endosome/autophagy-lysosome pathway might play an important role in cirrhotic decompensation. In summary, this study identified differentially expressed mRNAs (DE-mRNAs) and DE-lncRNAs and predicted the biological processes and signaling pathways involved in cirrhotic decompensation, which might provide new ideas for further revealing the molecular mechanism of DCC pathogenesis.

The Role of Chronic Liver Diseases in the Emergence and Recurrence of Hepatocellular Carcinoma: An Omics Perspective

Hepatocellular carcinoma (HCC) typically develops from a background of cirrhosis resulting from chronic inflammation. This inflammation is frequently associated with chronic liver diseases (CLD). The advent of next generation sequencing has enabled extensive analyses of molecular aberrations in HCC. However, less attention has been directed to the chronically inflamed background of the liver, prior to HCC emergence and during recurrence following surgery. Hepatocytes within chronically inflamed liver tissues present highly activated inflammatory signaling pathways and accumulation of a complex mutational landscape. In this altered environment, cells may transform in a stepwise manner toward tumorigenesis. Similarly, the chronically inflamed environment which persists after resection may impact the timing of HCC recurrence. Advances in research are allowing an extensive epigenomic, transcriptomic and proteomic characterization of CLD which define the emergence of HCC or its recurrence. The amount of data generated will enable the understanding of oncogenic mechanisms in HCC from the CLD perspective and provide the possibility to identify robust biomarkers or novel therapeutic targets for the treatment of primary and recurrent HCC. Importantly, biomarkers defined by the analysis of CLD tissue may permit the early detection or prevention of HCC emergence and recurrence. In this review, we compile the current omics based evidence of the contribution of CLD tissues to the emergence and recurrence of HCC.

An Overview on Single-Cell Technology for Hepatocellular Carcinoma Diagnosis

Hepatocellular carcinoma is a primary liver cancer caused by the accumulation of genetic mutation patterns associated with epidemiological conditions. This lethal malignancy exhibits tumor heterogeneity, which is considered as one of the main reasons for drug resistance development and failure of clinical trials. Recently, single-cell technology (SCT), a new advanced sequencing technique that analyzes every single cell in a tumor tissue specimen, aids complete insight into the genetic heterogeneity of cancer. This helps in identifying and assessing rare cell populations by analyzing the difference in gene expression pattern between individual cells of single biopsy tissue which normally cannot be identified from pooled cell gene expression pattern (traditional sequencing technique). Thus, SCT improves the clinical diagnosis, treatment, and prognosis of hepatocellular carcinoma as the limitations of other techniques impede this cancer research progression. Application of SCT at the genomic, transcriptomic, and epigenomic levels to promote individualized hepatocellular carcinoma diagnosis and therapy. The current review has been divided into ten sections. Herein we deliberated on the SCT, hepatocellular carcinoma diagnosis, tumor microenvironment analysis, single-cell genomic sequencing, single-cell transcriptomics, single-cell omics sequencing for biomarker development, identification of hepatocellular carcinoma origination and evolution, limitations, challenges, conclusions, and future perspectives.

Transcriptomic Signatures of Airway Epithelium Infected With SARS-CoV-2: A Balance Between Anti-infection and Virus Load

COVID-19 pneumonia requires effective medical therapies. However, it is a challenge to find therapeutic drugs that not only inhibit viral replication, but also inhibit the accompanying cytokine storm and maintain an appropriate immune response. In this study, the effects of SARS-CoV-2 on gene expression in lung epithelial cells from patients with COVID-19 were systematically evaluated with bioinformatics analysis methods. Transcriptome expression specific to bystander (exposed but uninfected) and infected cells were found, and the vital pathways were identified by conducting differentially expressed gene analysis regarding the relationship between gene signatures of COVID-19 infection and disease severity. We found that a high viral load did not necessarily imply a low response of epithelial cells or a poor disease convalescence. The ability to distinguish the role of virus-correlated genes facilitates the development of potential new medicines and therapies for COVID-19 infection.