Expression Levels of Three Key Genes CCNB1, CDC20, and CENPF in HCC Are Associated With Antitumor Immunity

The role of CXCL8 and CCNB1 in predicting hepatocellular carcinoma in the context of cirrhosis: implications for early detection and immune-based therapies

BACKGROUND

Cirrhosis is a serious condition characterized by the replacement of healthy liver tissue with scar tissue, which can progress to liver failure if left untreated. Hepatocellular carcinoma (HCC) is a concerning complication of cirrhosis. It can be challenge to identify individuals with cirrhosis who are at high risk of developing HCC, particularly in the absence of known risk factors.

METHODS

In this study, statistical and bioinformatics methods were utilized to construct a protein-protein interaction network and identify disease-related hub genes. We analyzed two hub genes, CXCL8 and CCNB1, and developed a mathematical model to predict the likelihood of developing HCC in individuals with cirrhosis. We also investigated immune cell infiltration, functional analysis under ontology terms, pathway analysis, distinct clusters of cells, and protein-drug interactions.

RESULTS

The results indicated that CXCL8 and CCNB1 were associated with the development of cirrhosis-induced HCC. A prognostic model based on these two genes was able to predict the occurrence and survival time of HCC. In addition, the candidate drugs were also discovered based on our model.

CONCLUSION

The findings offer the potential for earlier detection of cirrhosis-induced HCC and provide a new instrument for clinical diagnosis, prognostication, and the development of immunological medications. This study also identified distinct clusters of cells in HCC patients using UMAP plot analysis and analyzed the expression of CXCL8 and CCNB1 within these cells, indicating potential therapeutic opportunities for targeted drug therapies to benefit HCC patients.

The potential role of CDC20 in tumorigenesis, cancer progression and therapy: A narrative review

The cell division cycle 20 homologue (CDC20) is known to regulate the cell cycle. Many studies have suggested that dysregulation of CDC20 is associated with various pathological processes in malignant solid tumors, including tumorigenesis, progression, chemoradiotherapy resistance, and poor prognosis, providing a biomarker for cancer diagnosis and prognosis. Some researchers have demonstrated that CDC20 also regulates apoptosis, immune microenvironment, and tumor angiogenesis. In this review, we have systematically summarized the biological functions of CDC20 in solid cancers. Furthermore, we briefly synthesized multiple medicines that inhibited CDC20. We anticipate that CDC20 will be a promising and effective biomarker and therapeutic target for the treatment of human cancer.

Hsa-circ-0006091 modulates the proliferation of hepatocellular carcinoma via the miR-622/CCNB1 axis

Background/aim

Hepatocellular carcinoma (HCC) is a common type of cancer. We hypothesize that circular RNA-0006091 (circ-0006091) affects the progression of HCC. The study aims to investigate the effect of circ-0006091 in HCC cells.

Materials and methods

The levels of circ-0006091, microRNA-622 (miR-622), and cyclin B1 (CCNB1) were assayed using qRT-PCR and western blotting. The metastasis of the HCC cells was measured with wound healing and transwell assays. The protein expression levels of MMP-2 and MMP-9 were assayed with western blotting. Dual-luciferase reporter and RNA-pulldown assays were used to determine the link between miR-622 and circ-0006091 or CCNB1. Mice-based tests were used to determine the effect of circ-0006091 on the proliferation of HCC cells.

Results

The levels of circ-0006091 and CCNB1 were increased in the HCC cells, but miR-622 was down-regulated. Deficiency of circ-0006091 reduced the metastasis of the HCC cells, and silencing of circ-0006091 decreased the activities of MMP-2 and MMP-9 in the same cells. Circ-0006091 modulated the CCNB1 level in the HCC cells via miR-622. Silencing of circ-0006091 suppressed the proliferation of the HCC cells in vivo.

Conclusion

Circ-0006091 regulated HCC cell metastasis via the miR-622/CCNB1 axis, a possible therapeutic target in managing HCC.

Signaling Pathways and Genes Associated with Hexavalent Chromium-Induced Hepatotoxicity

Exposure to hexavalent chromium [Cr(VI)] causes human and animal hepatotoxicity. However, it is unclear how Cr(VI) induces hepatotoxicity, nor is it clear which pathways and genes may be involved. This study aimed to identify the key molecular pathways and genes engaged in Cr(VI)-induced hepatotoxicity. Publicly available microarray GSE19662 was downloaded from the Gene Expression Omnibus database. GSE19662 consists of primary rat hepatocyte (PRH) groups treated with or without 0.10 ppm potassium dichromate (PD), with three samples per group. Compared to the control group, a total of 400 differentially expressed genes were obtained. Specially 262 and 138 genes were up- and downregulated in PD-treated PRHs, respectively. Gene ontology (GO) enrichment indicated that those DEGs were primarily engaged in many biological processes, including androgen biosynthetic process, the positive regulation of cell death, the response to activity, the toxic substance and hepatocyte growth factor stimulus, and others. Kyoto Encyclopedia of Genes and Genomes (KEGG) suggested that the DEGs are fundamentally enriched in hepatocellular carcinoma (HCC), hepatitis B, p53, PI3K-Akt, MAPK, AMPK, metabolic pathways, estrogen, cGMP-PKG, metabolic pathways, etc. Moreover, many genes, including UBE2C, TOP2A, PRC1, CENPF, and MKI67, might contribute to Cr(VI)-induced hepatotoxicity. Taken together, this study enhances our understanding of the regulation, prevention, and treatment strategies of Cr(VI)-induced hepatotoxicity.

Identification of Key MicroRNAs and Genes between Colorectal Adenoma and Colorectal Cancer via Deep Learning on GEO Databases and Bioinformatics

Background

Deep learning techniques are gaining momentum in medical research. Colorectal adenoma (CRA) is a precancerous lesion that may develop into colorectal cancer (CRC) and its etiology and pathogenesis are unclear. This study aims to identify transcriptome differences between CRA and CRC via deep learning on Gene Expression Omnibus (GEO) databases and bioinformatics in the Chinese population.

Methods

In this study, three microarray datasets from the GEO database were used to identify the differentially expressed genes (DEGs) and differentially expressed miRNAs (DEMs) in CRA and CRC. The FunRich software was performed to predict the targeted mRNAs of DEMs. The targeted mRNAs were overlapped with DEGs to determine the key DEGs. Molecular mechanisms of CRA and CRC were evaluated using enrichment analysis. Cytoscape was used to construct protein-protein interaction (PPI) and miRNA-mRNA regulatory networks. We analyzed the expression of key DEMs and DEGs, their prognosis, and correlation with immune infiltration based on the Kaplan-Meier plotter, UALCAN, and TIMER databases.

Results

A total of 38 DEGs are obtained after the intersection, including 11 upregulated genes and 27 downregulated genes. The DEGs were involved in the pathways, including epithelial-to-mesenchymal transition, sphingolipid metabolism, and intrinsic pathway for apoptosis. The expression of has-miR-34c (P = 0.036), hsa-miR-320a (P = 0.045), and has-miR-338 (P = 0.0063) was correlated with the prognosis of CRC patients. The expression levels of BCL2, PPM1L, ARHGAP44, and PRKACB in CRC tissues were significantly lower than normal tissues (P < 0.001), while the expression levels of TPD52L2 and WNK4 in CRC tissues were significantly higher than normal tissues (P < 0.01). These key genes are significantly associated with the immune infiltration of CRC.

Conclusion

This preliminary study will help identify patients with CRA and early CRC and establish prevention and monitoring strategies to reduce the incidence of CRC.

Combined multiomics analysis reveals the mechanism of CENPF overexpression-mediated immune dysfunction in diffuse large B-cell lymphoma in vitro

Diffuse large B-cell lymphoma (DLBCL) is one of the most common aggressive B-cell lymphomas with significant heterogeneity. More than half of patients are cured, but 40%-45% still face relapse or develop drug resistance, and the mechanism is not yet known. In this study, Centrimeric protein F (CENPF) overexpression was found in several DLBCL patients with relapsed or refractory disease compared to patients with complete remission. Thus, the human DLBCL cell line SU-DHL-4 was chosen for this study, and CENPF was upregulated in that cell line by using an adenovirus in vitro. Mass spectrometry-based quantitative proteome analysis was first performed, and the results showed that the expression levels of various proteins were increased when CENPF was upregulated, and these proteins are mainly involved in cellular processes, biological regulation, immune system processes and transcriptional regulator activity. Bioinformatics data analysis revealed that the main enriched proteins, including UBE2A, UBE2C, UBE2S, TRIP12, HERC2, PIRH2, and PIAS, were involved in various ubiquitin-related kinase activities and ubiquitination processes. Thus, ubiquitinome analysis was further performed, and the results demonstrated that proteins in many immune-related cellular pathways, such as natural killer cell-mediated cytotoxicity, the T-cell receptor signaling pathway and the B-cell receptor signaling pathway, were significantly deubiquitinated after CENPF was upregulated in DLBCL cells. Furthermore, TIMER2.0 was also used to reveal the association between CENPF and immune infiltration in DLBCL. The results showed that CENPF expression was positively correlated with CD8⁺ T cells, NK cells and B lymphocytes in DLBCL samples but negatively correlated with regulatory T cells. Aberrant activation of CENPF may induce immune dysregulation in DLBCL cells by mediating protein deubiquitination in various immune signaling pathways, which leads to tumor escape of DLBCL, but further experimental validation is still needed.

Differentially Expressed Cell Cycle Genes and STAT1/3-Driven Multiple Cancer Entanglement in Psoriasis, Coupled with Other Comorbidities

Psoriasis is a persistent T-cell-supported inflammatory cutaneous disorder, which is defined by a significant expansion of basal cells in the epidermis. Cell cycle and STAT genes that control cell cycle progression and viral infection have been revealed to be comorbid with the development of certain cancers and other disorders, due to their abnormal or scanty expression. The purpose of this study is to evaluate the expression of certain cell cycle and STAT1/3 genes in psoriasis patients and to determine the types of comorbidities associated with these genes. To do so, we opted to adopt the in silico methodology, since it is a quick and easy way to discover any potential comorbidity risks that may exist in psoriasis patients. With the genes collected from early research groups, protein networks were created in this work using the NetworkAnalyst program. The crucial hub genes were identified by setting the degree parameter, and they were then used in gene ontology and pathway assessments. The transcription factors that control the hub genes were detected by exploring TRRUST, and DGIdb was probed for remedies that target transcription factors and hubs. Using the degree filter, the first protein subnetwork produced seven hub genes, including STAT3, CCNB1, STAT1, CCND1, CDC20, HSPA4, and MAD2L1. The hub genes were shown to be implicated in cell cycle pathways by the gene ontology and Reactome annotations. The former four hubs were found in signaling pathways, including prolactin, FoxO, JAK/STAT, and p53, according to the KEGG annotation. Furthermore, they enhanced several malignancies, including pancreatic cancer, Kaposi's sarcoma, non-small cell lung cancer, and acute myeloid leukemia. Viral infections, including measles, hepatitis C, Epstein-Barr virus, and HTLV-1 and viral carcinogenesis were among the other susceptible diseases. Diabetes and inflammatory bowel disease were conjointly annotated. In total, 129 medicines were discovered in DGIdb to be effective against the transcription factors BRCA1, RELA, TP53, and MYC, as opposed to 10 medications against the hubs, STAT3 and CCND1, in tandem with 8 common medicines. The study suggests that the annotated medications should be tested in suitable psoriatic cell lines and animal models to optimize the drugs used based on the kind, severity, and related comorbidities of psoriasis. Furthermore, a personalized medicine protocol must be designed for each psoriasis patient that displays different comorbidities.

CENPO is Associated with Immune Cell Infiltration and is a Potential Diagnostic and Prognostic Marker for Hepatocellular Carcinoma

Purpose

To examine the expression, clinical significance, and potential regulatory mechanism of centromere protein O (CENPO) in hepatocellular carcinoma (HCC).

Methods

CENPO expression in pan-cancer was studied using the TCGA-GTEx database, in HCC and normal liver tissues using the GEO and TCGA databases, and in clinical HCC samples by RT-qPCR. The diagnostic value of CENPO was assessed using receiver operating characteristic curves. Univariate and multivariate regression analyses of factors associated with HCC prognosis were performed. CENPO function and its mechanism in HCC were explored using GO, KEGG, and GSEA analyses of differentially expressed genes (DEGs). Association of CENPO expression with immune cell infiltration and immune checkpoint-associated molecules was conducted using TCGA data and the TIMER2.0 database. Relationships between CENPO expression and DNA methylation were analyzed using the UALCAN and cBioPortal databases. CENPO expression in HCC cell lines was detected using RT-qPCR.

Results

CENPO is upregulated in most cancers, including HCC and cell lines, and is a potential biomarker for HCC diagnosis (AUC = 0.936, 95% CI: 0.911–0.960). Higher CENPO expression was associated with poorer outcomes in patients with HCC (OS, p = 0.004; DSS, p = 0.002; PFI, p < 0.001), and CENPO was an independent predictor of factors influencing overall survival in HCC. DEGs between samples with high and low CENPO levels were enriched in various biological processes, including activation of the G2M checkpoint and other signaling pathways, while CENPO expression correlated with HCC immune cell infiltration and immune checkpoint-associated molecules, as well as CENPO promoter methylation (p < 0.001).

Conclusion

In HCC and cell lines, CENPO is overexpressed, a potential diagnostic marker and an indicator of poor prognosis. CENPO may regulate HCC development by influencing nuclear division and tumor immune infiltration and is regulated by methylation, making it a potential target for HCC immunotherapy.

CENPF as an independent prognostic and metastasis biomarker corresponding to CD4+ memory T cells in cutaneous melanoma

Owing to recent advances in immunotherapies, the overall survival of patients with skin cutaneous melanoma (SKCM) has increased; however, the 5-year survival rate of metastatic patients remains poor. Skin cutaneous melanoma-upregulated genes were screened via analysis of differentially expressed genes (GSE3189 and GSE46517), and metastasis-related oncogenes were identified via weighted gene coexpression network analysis of the GSE46517 dataset. As confirmed by the Tumor Immune Estimation Resource, we found highly expressed centromere protein F (CENPF) in SKCM and its metastases. Immunostaining of human melanoma tissues demonstrated high CENPF expression. According to the Kaplan-Meier survival curve log-rank test, receiver-operating characteristic curve, and univariate and multivariate analyses, the Cancer Genome Atlas (TCGA) database suggested CENPF be a typical independent predictor of SKCM. The CIBERSORT algorithm classified the types of the immune cells from GSE46517 and showed higher proportion of CD4+ memory-activated T cells in metastatic melanoma. Single-sample gene set enrichment analysis of TCGA data confirmed the correlation between CENPF and activated CD4+ T cells. Centromere protein F was positively correlated with tumor mutational burden and CD4+ memory T cell markers (interleukin [IL]-23A, CD28, and CD62L), negatively associated with memory T cell maintenance factors (IL-7 and IL-15) by correlation analysis. Moreover, immunofluorescence showed high coexpression of CENPF and IL23A, CD4 in melanoma. Upregulated CENPF might lead to premature depletion of CD4+ memory T cells and immunosuppression. Nomogram indicated CENPF clinical predictive value for 1-, 3-, 5-, and 7-year melanoma overall survival. Therefore, CENPF plays a vital role in the progression and metastasis of melanoma and can be an effective therapeutic target.

Immune infiltration and a ferroptosis-related gene signature for predicting the prognosis of patients with cholangiocarcinoma

Cholangiocarcinoma (CHOL) is a digestive tract tumor with high malignancy and poor prognosis and is extremely challenging to treat. At present, induced cell death holds great promise in tumor therapy. Ferroptosis is a recently proposed pattern of programmed cell death, and numerous studies have shown that it is intimately involved in tumors. However, the roles of differentially expressed ferroptosis-related genes (DEFRGs) in CHOL have not been investigated. Our study was based on The Cancer Genome Atlas (TCGA) database, and DEFRGs were obtained to construct a prognostic riskScore model of CHOL by univariate and multivariate Cox regression analyses. Subsequently, the model was evaluated by nomogram construction, survival analysis, receiver operating characteristic (ROC) analysis, and exploration of the immune microenvironment. The mRNA and protein expression levels of each gene in the model were validated by the Gene Expression Omnibus (GEO) database, quantitative real-time PCR (qRT-PCR) and immunohistochemistry (IHC) staining. Our study found that the construction of a nomogram confirmed the predictive value of the model for overall survival (OS), and it was confirmed to have high diagnostic value by ROC analysis. Our experimental results were almost consistent with our bioinformatics results. In conclusion, we found that the prognostic model showed extremely high diagnostic and prognostic value and could predict the possibility of immunotherapy, thus providing a new direction for individualized treatment of patients with CHOL.