Microarray analysis for the identification of specific proteins and functional modules involved in the process of hepatocellular carcinoma originating from cirrhotic liver

HIF‑1α and RACGAP1 promote the progression of hepatocellular carcinoma in a mutually regulatory way

Hypoxia, a condition characterized by low oxygen levels, serves an important role in the progression of hepatocellular carcinoma (HCC). However, the precise molecular mechanisms underlying hypoxia‑induced HCC progression are yet to be fully elucidated. The present study assessed the involvement of two key factors, hypoxia‑inducible factor‑1α (HIF‑1α) and Rac GTPase activating protein 1 (RACGAP1), in HCC development under hypoxic conditions. HIF‑1α and RACGAP1 genes were overexpressed and knocked down in Hep3B and Huh7 cells using lentiviral transduction and the levels of HIF‑1α and RACGAP1 in the cells were assessed using quantitative PCR, western blotting and immunofluorescence. Co‑immunoprecipitation experiments were performed to evaluate the interaction between HIF‑1α and RACGAP1. Subsequently, the proliferation, apoptosis, migration and invasion of Hep3B and Huh7 cells were assessed using the Cell Counting Kit‑8 assay, flow cytometry, Transwell assay and migration experiments. The expression levels of HIF‑1α and RACGAP1 in normal and HCC tumor samples were analyzed utilizing the Gene Expression Profiling Interactive Analysis database. Furthermore, correlations between HIF‑1α/RACGAP1 gene expression levels and patient survival outcomes were evaluated using the Kaplan‑Meier plotter. Knockdown of HIF‑1α resulted in a significant decrease in RACGAP1 expression, whilst overexpression of HIF‑1α resulted in a significant increase in RACGAP1 expression. Moreover, overexpression and knockdown of RACGAP1 had the same effect on HIF‑1α expression. Additionally, it was demonstrated that HIF‑1α and RACGAP1 interacted directly within a complex. Overexpression of HIF‑1α or RACGAP1 significantly increased proliferation, invasion and migration, and significantly decreased the proportion of apoptotic Hep3B and Huh7 cells. Conversely, knockdown of HIF‑1α or RACGAP1 significantly decreased proliferation, invasion and migration, and significantly increased the proportion of apoptotic Hep3B and Huh7 cells. In addition, the combined knockdown or overexpression of HIF‑1α and RACGAP1 had a more pronounced effect on HCC cell migration compared with knockdown of HIF‑1α alone. Furthermore, there was a significant positive correlation between the expression levels of HIF‑1α and RACGAP1 in HCC tissues and patients with HCC and upregulation of both HIF‑1α and RACGAP1 demonstrated a lower overall survival probability. In conclusion, HIF‑1α and RACGAP1 may synergistically contribute to the development of HCC, highlighting their potential as valuable targets for HCC therapy.

Transcriptome analysis creates a new era of precision medicine for managing recurrent hepatocellular carcinoma

The high incidence of hepatocellular carcinoma (HCC) recurrence negatively impacts outcomes of patients treated with curative intent despite advances in surgical techniques and other locoregional liver-targeting therapies. Over the past few decades, the emergence of transcriptome analysis tools, including real-time quantitative reverse transcription PCR, microarrays, and RNA sequencing, has not only largely contributed to our knowledge about the pathogenesis of recurrent HCC but also led to the development of outcome prediction models based on differentially expressed gene signatures. In recent years, the single-cell RNA sequencing technique has revolutionized our ability to study the complicated crosstalk between cancer cells and the immune environment, which may benefit further investigations on the role of different immune cells in HCC recurrence and the identification of potential therapeutic targets. In the present article, we summarized the major findings yielded with these transcriptome methods within the framework of a causal model consisting of three domains: primary cancer cells; carcinogenic stimuli; and tumor microenvironment. We provided a comprehensive review of the insights that transcriptome analyses have provided into diagnostics, surveillance, and treatment of HCC recurrence.

Integrated Analysis of the miRNA-mRNA Regulatory Network Involved in HIV-Associated Neurocognitive Disorder

HIV-associated neurocognitive disorder (HAND) is an array of neurocognitive changes associated with HIV infection, and the roles of microRNAs in HAND have not yet been completely revealed. Based on published data and publicly available databases, we constructed an integrated miRNA-mRNA network involved in HAND. Bioinformatics analyses, including gene ontology, network analysis, and KEGG pathway analysis, were applied for further study of the network and the genes of the network. The axon guidance KEGG pathway, three genes NTNG1, EFNB2, CXCL12, and 17 miRNAs which regulate these genes are spotlighted in our study. This study provides new perspectives to the knowledge of miRNAs’ roles in the progression of HAND, and our findings provide potential therapeutic targets and clues of HAND.

Identification of immune-infiltrating cell-related biomarkers in hepatocellular carcinoma based on gene co-expression network analysis

Background

Hepatocellular carcinoma (HCC) is often caused by chronic liver infection or inflammation. Searching for potential immunotherapy targets will aid the early diagnosis and treatment of HCC.

Methods

Firstly, detailed HCC data were downloaded from The Cancer Genome Atlas database. GDCRNATools was used for the comprehensive analysis of RNA sequencing data. Subsequently, the CIBERSORT package was used to estimate infiltration scores of 22 types of immune cells in complex samples. Furthermore, hub genes were identified via weighted gene co-expression network analysis (WGCNA) and protein-protein interaction (PPI) network analysis. In addition, multiple databases were used to validate the expression of hub gene in the tumor tissue. Finally, prognostic, diagnostic and immunohistochemical analysis of key hub genes was performed.

Results

In the present study, 9 hub genes were identified using WGCNA and PPI network analysis. Furthermore, the expression levels of 9 genes were positively correlated with the infiltration levels of CD8-positive T (CD8⁺ T) cells. In multiple dataset validations, the expression levels of CCL5, CXCR6, CD3E, and LCK were decreased in cancer tissues. In addition, survival analysis revealed that patients with LCK low expression had a poor survival prognosis (P < 0.05). Immunohistochemistry results demonstrated that CCL5, CD3E and LCK were expressed at low levels in HCC cancer tissues.

Conclusion

The identification of CCL5, CXCR6, CD3E and LCK may be helpful in the development of early diagnosis and therapy of HCC. LCK may be a potential prognostic biomarker for immunotherapy for HCC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13000-021-01118-y.

Identification of differentially expressed genes and biological pathways in para-carcinoma tissues of HCC with different metastatic potentials

Hepatocellular carcinoma (HCC) is a malignant tumor with extensive metastasis. Changes in the tumor microenvironment provide favorable conditions for tumor metastasis. However, the role of changes to the tumor microenvironment in HCC metastasis is yet to be elucidated. The Gene Expression Omnibus expression profile GSE5093 consists of 20 noncancerous tissues surrounding HCC tissues, including 9 metastasis-inclined microenvironment samples with detectable metastases and 11 metastasis-averse microenvironment samples without detectable metastases. The present study assessed 35 HCC samples to verify the results of chip analysis. In total, 712 upregulated and 459 downregulated genes were identified, with 1,033 nodes, 7,589 edges and 10 hub genes. Gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis revealed that the differentially expressed genes were significantly enriched in ‘cell-cell adhesion’, ‘cell proliferation’ and ‘protein binding’. The top 10 hub genes were identified via a protein-protein interaction analysis. The 3 most significant modules were identified from the protein-protein network. Moreover, an association between hub genes and patient prognosis was identified. In conclusion, these candidate genes and pathways may help elucidate the mechanisms underlying HCC metastasis and identify more options for targeted therapy.

Dissecting the expression landscape of cytochromes P450 in hepatocellular carcinoma: towards novel molecular biomarkers

Hepatocellular carcinoma (HCC) is the second leading cause of cancer-related deaths around the world. Recent advances in genomic technologies have allowed the identification of various molecular signatures in HCC tissues. For instance, differential gene expression levels of various cytochrome P450 genes (CYP450) have been reported in studies performed on limited numbers of HCC tissue samples, or focused on a small subset on CYP450s. In the present study, we monitored the expression landscape of all the members of the CYP450 family (57 genes) in more than 200 HCC tissues using RNA-Seq data from The Cancer Genome Atlas. Using stringent statistical filters and data from paired tissues, we identified significantly dysregulated CYP450 genes in HCC. Moreover, the expression level of selected CYP450s was validated by qPCR on cDNA samples from an independent cohort. Threshold values (sensitivity and specificity) based on dysregulated gene expression were also determined to allow for confident identification of HCC tissues. Finally, a global look at expression levels of the 57 members of the CYP450 family across ten different cancer types revealed specific expression signatures. Overall, this study provides useful information on the transcriptomic landscape of CYP450 genes in HCC and on new potential HCC biomarkers.