Hypermethylation of GNA14 and its tumor-suppressive role in hepatitis B virus-related hepatocellular carcinoma

Invasion and metastasis in cancer: molecular insights and therapeutic targets

The progression of malignant tumors leads to the development of secondary tumors in various organs, including bones, the brain, liver, and lungs. This metastatic process severely impacts the prognosis of patients, significantly affecting their quality of life and survival rates. Research efforts have consistently focused on the intricate mechanisms underlying this process and the corresponding clinical management strategies. Consequently, a comprehensive understanding of the biological foundations of tumor metastasis, identification of pivotal signaling pathways, and systematic evaluation of existing and emerging therapeutic strategies are paramount to enhancing the overall diagnostic and treatment capabilities for metastatic tumors. However, current research is primarily focused on metastasis within specific cancer types, leaving significant gaps in our understanding of the complex metastatic cascade, organ-specific tropism mechanisms, and the development of targeted treatments. In this study, we examine the sequential processes of tumor metastasis, elucidate the underlying mechanisms driving organ-tropic metastasis, and systematically analyze therapeutic strategies for metastatic tumors, including those tailored to specific organ involvement. Subsequently, we synthesize the most recent advances in emerging therapeutic technologies for tumor metastasis and analyze the challenges and opportunities encountered in clinical research pertaining to bone metastasis. Our objective is to offer insights that can inform future research and clinical practice in this crucial field.

Epigenetic modification of hepatitis B virus infection and related hepatocellular carcinoma

Hepatitis B virus (HBV) infection poses a challenge to global public health. Persistent liver infection with HBV is associated with an increased risk of developing severe liver disease. The complex interaction between the virus and the host is the reason for the persistent presence of HBV and the risk of tumor development. Chronic liver inflammation, integration of viral genome with host genome, expression of HBx protein, and viral genotype are all key participants in the pathogenesis of hepatocellular carcinoma (HCC). Epigenetic regulation in HBV-associated HCC involves complex interactions of molecular mechanisms that control gene expression and function without altering the underlying DNA sequence. These epigenetic modifications can significantly affect the onset and progression of HCC. This review summarizes recent research on the epigenetic regulation of HBV persistent infection and HBV-HCC development, including DNA methylation, histone modification, RNA modification, non-coding RNA, etc. Enhanced knowledge of these mechanisms will offer fresh perspectives and potential targets for intervention tactics in HBV-HCC.

GNA14 may be a potential prognostic biomarker in nasopharyngeal carcinoma

Background

Nasopharyngeal carcinoma (NPC) is a highly invasive malignant tumor. Recurrence and distant metastasis represent the primary causes of treatment failure. This study aimed to identify biomarkers highly associated with NPC and investigate its roles in tumor progression.

Methods

Transcriptome sequencing (RNA-seq) data of NPC and normal tissues were downloaded from the Gene Expression Omnibus (GEO) database. By analyzing the RNA-seq data, we found that G Protein Subunit Alpha 14 (GNA14) is closely associated with the diagnosis and prognosis of NPC. Immunohistochemistry (IHC) was used to detect the expression of GNA14 in tumor tissues of 165 NPC patients, and we analyzed the relationship between GNA14 expression and patient prognosis. The potential mechanisms by which GNA14 affects tumor prognosis were preliminarily analyzed using bioinformatics analysis.

Results

Analysis of RNA-seq data and IHC showed that GNA14 expression was downregulated in NPC (p < 0.001, p < 0.01, respectively), and low expression of GNA14 was closely associated with poor prognosis. IHC analysis showed that patients with low GNA14 expression had significantly shorter progression-free survival (PFS) and distant metastasis-free survival (DMFS) than those with high GNA14 expression (p = 0.023, p = 0.008, respectively). Multivariate analysis indicated that the GNA14 expression was an independent risk factor for DMFS (p = 0.030). The DMFS nomogram included GNA14 expression, EBV DNA, and N stage as prognostic factors and the concordance index (C-index) of the nomogram was 0.73. Bioinformatics analysis indicated that NPC patients with low GNA14 expression might represent lower levels of immune cell infiltration and poorer drug sensitivity.

Conclusion

Low GNA14 expression may be a risk factor for poor prognosis in NPC.

War or peace: Viruses and metastasis

Metastasis, the dissemination of malignant cells from a primary tumor to secondary sites, poses a catastrophic burden to cancer treatment and is the predominant cause of mortality in cancer patients. Metastasis as one of the main aspects of cancer progression could be strongly under the influence of viral infections. In fact, viruses have been central to modern cancer research and are associated with a great number of cancer cases. Viral-encoded elements are involved in modulating essential pathways or specific targets that are implicated in different stages of metastasis. Considering the continuous emergence of new viruses and the establishment of their contribution to cancer progression, the warfare between viruses and cancer appears to be endless. Here we aimed to review the critical mechanism and pathways involved in cancer metastasis and the influence of viral machinery and various routes that viruses adopt to manipulate those pathways for their benefit.

Research Progress on the Role of Epigenetic Methylation Modification in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) stands as the prevailing form of primary liver cancer, characterized by a poor prognosis and high mortality rate. A pivotal factor in HCC tumorigenesis is epigenetics, specifically the regulation of gene expression through methylation. This process relies significantly on the action of proteins that modify methylation, including methyltransferases, their associated binding proteins, and demethylases. These proteins are crucial regulators, orchestrating the methylation process by regulating enzymes and their corresponding binding proteins. This orchestration facilitates the reading, binding, detection, and catalysis of gene methylation sites. Methylation ences the development, prolisignificantly influferation, invasion, and prognosis of HCC. Furthermore, methylation modification and its regulatory mechanisms activate distinct biological characteristics in HCC cancer stem cells, such as inducing cancer-like differentiation of stem cells. They also influence the tumor microenvironment (TME) in HCC, modulate immune responses, affect chemotherapy resistance in HCC patients, and contribute to HCC progression through signaling pathway feedback. Given the essential role of methylation in genetic information, it holds promise as a potential tool for the early detection of HCC and as a target to improve drug resistance and promote apoptosis in HCC cells.

Methylation-regulated tumor suppressor gene PDE7B promotes HCC invasion and metastasis through the PI3K/AKT signaling pathway

BACKGROUND

Hepatocellular carcinoma (HCC) has a high mortality rate, and the mechanisms underlying tumor development and progression remain unclear. However, inactivated tumor suppressor genes might play key roles. DNA methylation is a critical regulatory mechanism for inactivating tumor suppressor genes in HCC. Therefore, this study investigated methylation-related tumor suppressors in HCC to identify potential biomarkers and therapeutic targets.

METHODS

We assessed genome-wide DNA methylation in HCC using whole genome bisulfite sequencing (WGBS) and RNA sequencing, respectively, and identified the differential expression of methylation-related genes, and finally screened phosphodiesterase 7B (PDE7B) for the study. The correlation between PDE7B expression and clinical features was then assessed. We then analyzed the changes of PDE7B expression in HCC cells before and after DNA methyltransferase inhibitor treatment by MassArray nucleic acid mass spectrometry. Furthermore, HCC cell lines overexpressing PDE7B were constructed to investigate its effect on HCC cell function. Finally, GO and KEGG were applied for the enrichment analysis of PDE7B-related pathways, and their effects on the expression of pathway proteins and EMT-related factors in HCC cells were preliminarily explored.

RESULTS

HCC exhibited a genome-wide hypomethylation pattern. We screened 713 hypomethylated and 362 hypermethylated mCG regions in HCC and adjacent normal tissues. GO analysis showed that the main molecular functions of hypermethylation and hypomethylation were "DNA-binding transcriptional activator activity" and "structural component of ribosomes", respectively, whereas KEGG analysis showed that they were enriched in "bile secretion" and "Ras-associated protein-1 (Rap1) signaling pathway", respectively. PDE7B expression was significantly down-regulated in HCC tissues, and this low expression was negatively correlated with recurrence and prognosis of HCC. In addition, DNA methylation regulates PDE7B expression in HCC. On the contrary, overexpression of PDE7B inhibited tumor proliferation and metastasis in vitro. In addition, PDE7B-related genes were mainly enriched in the PI3K/ATK signaling pathway, and PDE7B overexpression inhibited the progression of PI3K/ATK signaling pathway-related proteins and EMT.

CONCLUSION

PDE7B expression in HCC may be regulated by promoter methylation. PDE7B can regulate the EMT process in HCC cells through the PI3K/AKT pathway, which in turn affects HCC metastasis and invasion.

Establishment and Evaluation of Exosomes-Related Gene Risk Model in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is a challenging disease to evaluate in terms of prognosis, requiring close attention to the prognosis of HCC patients. Exosomes have been shown to play an important role in HCC development and have significant potential in managing HCC patient prognosis, as they are detectable in patients' blood. By using small extracellular vesicular RNA, liquid biopsies can reflect the underlying physiological and pathological status of the originating cells, providing a valuable assessment of human health. No study has explored the diagnostic value of mRNA expression changes in exosomes for liver cancer. The present study investigated establishing a risk prognosis model based on mRNA expression levels in exosomes from blood samples of liver cancer patients and evaluated its diagnostic and prognostic value, providing new targets for liver cancer detection. We obtained mRNA data from HCC patients and normal controls from the TCGA and exoRBase 2.0 databases and established a risk prognostic assessment model using exosomes-related risk genes selected through prognostic analysis and Lasso Cox analysis. The patients were divided into high-risk and low-risk groups based on median risk score values to validate the independence and evaluability of the risk score. The clinical value of the model was further analyzed using a nomograph model, and the efficacy of immunotherapy and cell-origin types of prognostic risk genes were further assessed in the high- and low-risk groups by immune checkpoint and single-cell sequencing. A total of 44 genes were found to be significantly associated with the prognosis of HCC patients. From this group, we selected six genes (CLEC3B, CYP2C9, GNA14, NQO1, NT5DC2, and S100A9) as exosomal risk genes and used them as a basis for the risk prognosis model. The clinical information of HCC patients from the TCGA and ICGC databases demonstrated that the risk prognostic score of the model established in this study was an independent prognostic factor with good robustness. When pathological stage and risk prognostic score were incorporated into the model to predict clinical outcomes, the nomograph model had the best clinical benefit. Furthermore, immune checkpoint assays and single-cell sequencing analysis suggested that exosomal risk genes were derived from different cell types and that immunotherapy in the high-risk groups could be beneficial. Our study demonstrated that the prognostic scoring model based on exosomal mRNA was highly effective. The six genes selected using the scoring model have been previously reported to be associated with the occurrence and development of liver cancer. However, this study is the first to confirm that these related genes existed in the blood exosomes, which could be used for liquid biopsy of patients with liver cancer, thereby avoiding the need for puncture diagnosis. This approach has a high value in clinical application. Through single-cell sequencing, we found that the six genes in the risk model originate from multiple cell types. This finding suggests that the exosomal characteristic molecules secreted by different types of cells in the microenvironment of liver cancer may serve as diagnostic markers.

SERPINE2 promotes liver cancer metastasis by inhibiting c-Cbl-mediated EGFR ubiquitination and degradation

BACKGROUND

Liver cancer is a malignancy with high morbidity and mortality rates. Serpin family E member 2 (SERPINE2) has been reported to play a key role in the metastasis of many tumors. In this study, we aimed to investigate the potential mechanism of SERPINE2 in liver cancer metastasis.

METHODS

The Cancer Genome Atlas database (TCGA), including DNA methylation and transcriptome sequencing data, was utilized to identify the crucial oncogene associated with DNA methylation and cancer progression in liver cancer. Data from the TCGA and RNA sequencing for 94 pairs of liver cancer tissues were used to explore the correlation between SERPINE2 expression and clinical parameters of patients. DNA methylation sequencing was used to detect the DNA methylation levels in liver cancer tissues and cells. RNA sequencing, cytokine assays, immunoprecipitation (IP) and mass spectrometry (MS) assays, protein stability assays, and ubiquitination assays were performed to explore the regulatory mechanism of SERPINE2 in liver cancer metastasis. Patient-derived xenografts and tumor organoid models were established to determine the role of SERPINE2 in the treatment of liver cancer using sorafenib.

RESULTS

Based on the public database screening, SERPINE2 was identified as a tumor promoter regulated by DNA methylation. SERPINE2 expression was significantly higher in liver cancer tissues and was associated with the dismal prognosis in patients with liver cancer. SERPINE2 promoted liver cancer metastasis by enhancing cell pseudopodia formation, cell adhesion, cancer-associated fibroblast activation, extracellular matrix remodeling, and angiogenesis. IP/MS assays confirmed that SERPINE2 activated epidermal growth factor receptor (EGFR) and its downstream signaling pathways by interacting with EGFR. Mechanistically, SERPINE2 inhibited EGFR ubiquitination and maintained its protein stability by competing with the E3 ubiquitin ligase, c-Cbl. Additionally, EGFR was activated in liver cancer cells after sorafenib treatment, and SERPINE2 knockdown-induced EGFR downregulation significantly enhanced the therapeutic efficacy of sorafenib against liver cancer. Furthermore, we found that SERPINE2 knockdown also had a sensitizing effect on lenvatinib treatment.

CONCLUSIONS

SERPINE2 promoted liver cancer metastasis by preventing EGFR degradation via c-Cbl-mediated ubiquitination, suggesting that inhibition of the SERPINE2-EGFR axis may be a potential target for liver cancer treatment.

A prognostic model based on DNA methylation-related gene expression for predicting overall survival in hepatocellular carcinoma

Background

Hepatocellular carcinoma (HCC) continues to increase in morbidity and mortality among all types of cancer. DNA methylation, an important epigenetic modification, is associated with cancer occurrence and progression. The objective of this study was to establish a model based on DNA methylation risk scores for identifying new potential therapeutic targets in HCC and preventing cancer progression.

Methods

Transcriptomic, clinical, and DNA methylation data on 374 tumor tissues and 50 adjacent normal tissues were downloaded from The Cancer Genome Atlas-Liver Hepatocellular Carcinoma database. The gene expression profiles of the GSE54236 liver cancer dataset, which contains data on 161 liver tissue samples, were obtained from the Gene Expression Omnibus database. We analyzed the relationship between DNA methylation and gene expression levels after identifying the differentially methylated and expressed genes. Then, we developed and validated a risk score model based on the DNA methylation-driven genes. A tissue array consisting of 30 human hepatocellular carcinoma samples and adjacent normal tissues was used to assess the protein and mRNA expression levels of the marker genes by immunohistochemistry and qRT-PCR, respectively.

Results

Three methylation-related differential genes were identified in our study: GLS, MEX3B, and GNA14. The results revealed that their DNA methylation levels were negatively correlated with local gene expression regulation. The gene methylation levels correlated strongly with the prognosis of patients with liver cancer. This was confirmed by qRT-PCR and immunohistochemical verification of the expression of these genes or proteins in tumors and adjacent tissues. These results revealed the relationship between the level of relevant gene methylation and the prognosis of patients with liver cancer as well as the underlying cellular and biological mechanisms. This allows our gene signature to provide more accurate and appropriate predictions for clinical applications.

Conclusion

Through bioinformatics analysis and experimental validation, we obtained three DNA methylation marker: GLS, MEX3B, and GNA14. This helps to predict the prognosis and may be a potential therapeutic target for HCC patients.

A pan-cancer analysis of TNFAIP8L1 in human tumors

TNFAIP8L1, as a recently identified member in TNFAIP8 family, plays an important role in tumorigenesis. However, a pan-cancer analysis of TNFAIP8L1 in human tumors has not been conducted until now. The main purpose of study is to investigate TNFAIP8L1 during 33 different types of human tumors by using TCGA and GTEx. The pan-cancer analysis showed that TNFAIP8L1 was significantly over-expressed in 15 cancers and low-expressed in 9 cancers. There were distinct relations between TNFAIP8L1 expression and prognosis of patients with cancer. Furthermore, we also found that DNA methylation and RNA modification of TNFAIP8L1 were associated with many cancers. And then, we detected that TNFAIP8L1 level was positively associated with cancer-associated fibroblasts (CAFs) in many tumors. And, we obtained that TNFAIP8L1 expression was related with most of immune inhibitory and stimulatory genes in multiple types of tumors. We also found TNFAIP8L1 expression was correlated with most of chemokine, receptor, MHC, immunoinhibitor and immunostimulator gens in most of cancers. Moreover, we detected TNFAIP8L1 expression was associated with TMB and MSI in several tumors. Finally, TNFAIP8L1 gene had a significant positive association with 5 genes including BCL6B, DLL4, PCDH12, COL4A1 and DLL4 in the majority of tumors. GO enrichment and KEGG pathway analyses showed that TNFAIP8L1 in thepathogenesis of cancer may be related to "purine nucleoside binding," "purine ribonucleoside binding," "ECM-receptor interaction," etc. Our first pan-cancer study may provide a deep comprehending of TNFAIP8L1 in tumoeigenesis from different tumors.

Multi-cohort validation study of a four-gene signature for risk stratification and treatment response prediction in hepatocellular carcinoma

BACKGROUND

The intricate molecular landscape of hepatocellular carcinoma (HCC) presents a significant challenge to achieving precise risk stratification through clinical genetic testing. At present, there is a paucity of robust gene signatures that could assist clinicians in making clinical decisions for patients with HCC.

METHODS

We obtained gene expression profiles of patients with HCC from 20 independent cohorts available in public databases. A gene signature was developed by employing two machine learning algorithms. In addition to validating the signature with high-throughput data in public cohorts, we external validated the signature in 64 HCC cases by RT-PCR method. We compared genomic, transcriptomic and proteomic features between different subgroups. We also compared our signature to 130 gene signatures that have already been published.

RESULTS

We developed a novel four-gene signature, designated as HCC4, that demonstrates significant potential for the prediction of survival outcomes in more than 1300 patients with HCC. The HCC4 also has potential for predicting recurrence and tumor volume doubling time, assessing transcatheter arterial chemoembolization and immunotherapy responses, and non-invasive detection of HCC. The high HCC4 score group shows a higher frequency of mutations in genes TP53, RB1 and TSC1/2, as well as increased activity of cell-cycle, glycolysis and hypoxia signaling pathways, higher cancer stemness score, and lower lipid metabolism activity. In seven HCC cohorts, HCC4 exhibited a higher average C-index in predicting overall survival compared to the 130 signatures previously published. Drug screening indicated that patients with high HCC4 scores were more sensitive to agents targeting AURKA, TUBB, JMJD6 and KIFC1.

CONCLUSIONS

Our findings demonstrated that HCC4 is a powerful tool for improving risk stratification and for identifying HCC patients who are most likely to benefit from TACE treatment, immunotherapy, and other experimental therapies.

Oncoviruses: Induction of cancer development and metastasis by increasing anoikis resistance

The phenomenon of cell death is a vital aspect in the regulation of aberrant cells such as cancer cells. Anoikis is a kind of cell death that occurs when cells get separated from the extracellular matrix. Some cancer cells can inhibit anoikis in order to progress metastasis. One of the key variables that might be implicated in anoikis resistance (AR) is viral infections. The most important viruses involved in this process are Epstein-Barr virus, human papillomavirus, hepatitis B virus, human herpes virus 8, human T-cell lymphotropic virus type 1, and hepatitis C virus. A better understanding of how carcinogenic viruses suppress anoikis might be helpful in developing an effective treatment for virus-associated cancers. In the current study, we review the role of the mentioned viruses and their gene products in anoikis inhibition.

Integration of scRNA-seq and bulk RNA-seq constructs a stemness-related signature for predicting prognosis and immunotherapy responses in hepatocellular carcinoma

PURPOSE

Cancer stem cells are associated with unfavorable prognosis in hepatocellular carcinoma (HCC). However, existing stemness-related biomarkers and prognostic models are limited.

METHODS

The stemness-related signatures were derived from taking the union of the results obtained by performing WGCNA and CytoTRACE analysis at the bulk RNA-seq and scRNA-seq levels, respectively. Univariate Cox regression and the LASSO were applied for filtering prognosis-related signatures and selecting variables. Finally, ten gene signatures were identified to construct the prognostic model. We evaluated the differences in survival, genomic alternation, biological processes, and degree of immune cell infiltration in the high- and low-risk groups. pRRophetic and Tumor Immune Dysfunction and Exclusion (TIDE) algorithms were utilized to predict chemosensitivity and immunotherapy response. Human Protein Atlas (HPA) database was used to evaluate the protein expressions.

RESULTS

A stemness-related prognostic model was constructed with ten genes including YBX1, CYB5R3, CDC20, RAMP3, LDHA, MTHFS, PTRH2, SRPRB, GNA14, and CLEC3B. Kaplan-Meier and ROC curve analyses showed that the high-risk group had a worse prognosis and the AUC of the model in four datasets was greater than 0.64. Multivariate Cox regression analyses verified that the model was an independent prognostic indicator in predicting overall survival, and a nomogram was then built for clinical utility in predicting the prognosis of HCC. Additionally, chemotherapy drug sensitivity and immunotherapy response analyses revealed that the high-risk group exhibited a higher likelihood of benefiting from these treatments.

CONCLUSION

The novel stemness-related prognostic model is a promising biomarker for estimating overall survival in HCC.

Tumor-Promoting Role of GNA14 in Colon Cancer Development

Recent studies have shown that mutations in members of the G-protein α family contribute to the onset and progression of cancer. However, the role of GNA14 in CRC remains unknown. In this study, we examined the effect of GNA14 on CRC through genetic approaches in vitro and in vivo. We found that GNA14 knockdown by small interfering RNA (siRNA) inhibited the proliferation of CRC cells SW403 and HT29. Gna14 knockout mice developed normally without obvious abnormalities. However, the number of polyps in the small intestine was significantly reduced in Gna14 knockout mice compared to control mice after mating with ApcMin mice, a representative CRC mouse model. In particular, deletion of the Gna14 inhibited polyp growth, especially in the distal end of the small intestine. Histological examination showed that Gna14 knockout mice suppressed malignant tumor progression due to decreased proliferation and increased apoptosis in polyps compared to controls. In addition, GNA14 knockdown in CRC cells resulted in downregulation of ERK phosphorylation and β-catenin and β-catenin phosphorylation at S675. Similarly, ERK phosphorylation and phospho-β-catenin phosphorylation at S675 were decreased in polyps of Gna14 knockout mice. Collectively, these analyses show that GNA14 may accelerate CRC cell proliferation and malignant tumor progression through ERK and β-catenin pathways.

Dapar ML, Zhang X, Chen Y. A pan-cancer analysis of the oncogenic role of YKT6 in human tumors

YKT6, as a Soluble N-ethylmaleimide-sensitive factor attachment protein receptor (SNARE) protein with vesicle trafficking, plays an essential role in the development and progression of tumor. However, the gene of YKT6 has not been fully assessed in pan-cancer studies. We aim to investigate the gene of YKT6 across 33 different types of tumor by using the Cancer Genome Atlas, Gene Expression Omnibus database, and other several kinds of bioinformatic tools. YKT6 is significantly up-regulated in most tumors, and we found that overexpression of YKT6 is positively associated with poor prognosis of overall survival and poor disease-free survival prognosis in several tumors, such as Adrenocortical carcinoma, Bladder Urothelial Carcinoma, Head and Neck squamous cell carcinoma. We also detected distinct associations exist between YKT6 and tumor mutational burden or microsatellite instability with tumors. YKT6 expression was positively related to cancer-associated fibroblasts for TCGA tumors of colon adenocarcinoma and LGG. Furthermore, we discovered a significantly positively correlation between YKT6 expression and endothelial cell in tumors of colon adenocarcinoma, HNSC-HPV+, OV, READ and THCA. While a negative relationship was obtained between YKT6 expression and endothelial cell in KIRC. Moreover, "Syntaxin binding," "SNARE complex," "vesicle fusion" and "DNA replication" are involved in the influence of YKT6 on tumor pathogenesis. Our pan-cancer analysis offers a deep comprehending the gene of YKT6 in tumoeigenesis from viewpoint of clinical tumor samples.

Cell cycle kinases (AUKA, CDK1, PLK1) are prognostic biomarkers and correlated with tumor-infiltrating leukocytes in HBV related HCC

Hepatocellular carcinoma (HCC) is one of the high incidence cancers and third leading cause of cancer-related mortality. HBV is the top most risk factor accounting for 50-80% of the HCC cases. Kinases: Aurora kinase A (AURKA), cyclin-dependent kinase (CDK1) and Polo-like kinase 1 (PLK1), the key regulators of cell mitosis are overexpressed in varieties of cancers including HCC. However, the exact role of these genes in prognosis of HCC is not fully unveiled. In addition, there is no such an accurate prognostic biomarker for HBV-related HCC. To address this issue, we performed a multidimensional analysis of AURKA, CDK1 and PLK1 with a series of publicly available databases in multiple cancers and with experimental validation in HBV-related HCC tissues. Overexpression of AURKA, CDK1 and PLK1 was found in multiple cancers including HCC. Elevated expression of these genes could result from lowered DNA methylation and genomic alterations. Transcriptional overexpression was significantly correlated with poor prognosis of HCC patients. The expression levels were also significantly positively associated with tumor grades and stages. Furthermore, the expression levels of these genes had a strong correlation with infiltration of immune cells. Our analysis shows that AURKA, CDK1 and PLK1 are correlated with immune infiltration and are the prognostic biomarkers for HBV-induced HCC.Communicated by Ramaswamy H. Sarma.

Identification of potential biomarkers for systemic lupus erythematosus by integrated analysis of gene expression and methylation data

INTRODUCTION

Systemic lupus erythematosus (SLE) is a heterogeneous and chronic autoimmune disease. Aberrant DNA methylation occurs during various processes of SLE development regulating the mRNA expression of interrelated genes. This study aims to screen potential DNA methylation markers for SLE.

METHODS

Gene expression and methylation datasets were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) between SLE patients and healthy controls were screened using the limma R package, and differentially methylated positions (DMPs) and regions (DMRs) were identified using dmpfinder and bumphunter (minfi). Additionally, the DNA methylation markers to distinguish SLE patients from healthy controls were explored through receiver operating characteristic (ROC) curves and logistic regression analyses. Finally, we validated the results of the bioinformatic analysis by pyrosequencing.

RESULTS

In total, 91 DEGs, 90,092 DMPs, 15 DMRs, and 13 DMR-associated genes were identified. Through the integrative analysis of DEG- and DMR-associated genes, we identified five type I interferon (IFN)-related genes as key epigenetic-driven genes in SLE. GO enrichment analysis showed that the five SLE-associated epigenetic-driven genes were mainly enriched in the type I IFN signaling pathway involved in immune response and defense response to virus. Moreover, we identified two SLE-specific DNA methylation markers, three SLE without lupus nephritis (SLE-LN^-)-specific DNA methylation markers, and two SLE with lupus nephritis (SLE-LN⁺)-specific DNA methylation markers by stepwise logistic regression.

CONCLUSIONS

Overall, our study demonstrates potential DNA methylation markers of SLE, SLE-LN^-, and SLE-LN⁺, which may help the diagnosis, boost the development of new epigenetic therapy, and contribute to individualized treatment. Key Points • This study identified five type I IFN-related genes as key epigenetic-driven genes in SLE, which support the importance of the type I IFN pathway in the pathogenesis of SLE • We identified novel DNA methylation biomarkers in SLE, SLE-LN-, and SLE-LN+ by a comprehensive analysis of bioinformatics methods and executed experimental validation, and binary logistic regression analysis showed that they have excellent potential • These results may provide new insights into the biological mechanisms of SLE, and identify reliable biomarkers for SLE, SLE-LN-, and SLE-LN+, which may contribute to diagnosis and individualized treatment.

Comprehensive analysis of ESR1-related ceRNA axis as a novel prognostic biomarker in hepatocellular carcinoma

Aims: To further understand, detect and treat hepatocellular carcinoma (HCC), it is urgent to conduct more in-depth research on the mechanism of sex-associated differences. Materials & methods: We established a ceRNA triple regulatory axis associated with ESR1 in HCC and performed expression, survival and nuclear-cytoplasmic localization analyses. In addition to this, we performed methylation analysis and immune infiltration analysis of the ceRNA axis. Results: We constructed the LINC01018/hsa-miR-197-3p/GNA14 (lncRNA/miRNA/mRNA) ceRNA axis to further explain the mechanism of sex-related prognosis in the development of HCC and to provide new insights into candidate biomarkers for targeted therapies. Conclusion: Our study is an innovative attempt at demonstrating the mechanism underlying the prognosis associated with sex differences in HCC by constructing a ceRNA axis (LINC01018/hsa-miR-197-3p/GNA14).

Identification and analysis of DNA methylation-driven signatures for prognostic and immune microenvironments evaluation in hepatocellular carcinoma

Liver cancer is the main reason of cancer deaths globally, with an unfavorable prognosis. DNA methylation is one of the epigenetic modifications and maintains the right adjustment of gene expression and steady gene silencing. We aim to explore the novel signatures for prognosis by using DNA methylation-driven genes. To acquire the DNA methylation-driven genes, we perform the difference analysis from the gene expression data and DNA methylation data in TCGA or GEO databases. And we obtain the 31 DNA methylation-driven genes. Subsequently, consensus clustering analysis was utilized to identify the molecular subtypes based on the 31 DNA methylation-driven genes. So, two molecular subtypes were identified to perform those analyses: Survival, immune cell infiltration, and tumor mutation. Results showed that two subtypes were clustered with distinct prognoses, tumor-infiltrating immune cell and tumor mutation burden. Furthermore, the 31 DNA methylation-driven genes were applied to perform the survival analysis to select the 14 survival-related genes. Immediately, a five methylation-driven genes risk model was built, and the patients were divided into high and low-risk groups. The model was established with TCGA as the training cohort and GSE14520 as the validation cohort. According to the risk model, we perform the systematical analysis, including survival, clinical feature, immune cell infiltration, somatic mutation status, underlying mechanisms, and drug sensitivity. Results showed that the high and low groups possessed statistical significance. In addition, the ROC curve was utilized to measure the accuracy of the risk model. AUCs at 1-year, 3-years, and 5-years were respectively 0.770, 0.698, 0.676 in training cohort and 0.717, 0.649, 0.621 in validation cohort. Nomogram was used to provide a better prediction for patients’ survival. Risk score increase the accuracy of survival prediction in HCC patients. In conclusion, this study developed a novel risk model of five methylation-driven genes based on the comprehensive bioinformatics analysis, which accurately predicts the survival of HCC patients and reflects the immune and mutation features of HCC. This study provides novel insights for immunotherapy of HCC patients and promotes medical progress.

Role of germline variants in the metastasis of breast carcinomas

Most cancer-related deaths in breast cancer patients are associated with metastasis, a multistep, intricate process that requires the cooperation of tumour cells, tumour microenvironment and metastasis target tissues. It is accepted that metastasis does not depend on the tumour characteristics but the host’s genetic makeup. However, there has been limited success in determining the germline genetic variants that influence metastasis development, mainly because of the limitations of traditional genome-wide association studies to detect the relevant genetic polymorphisms underlying complex phenotypes. In this work, we leveraged the extreme discordant phenotypes approach and the epistasis networks to analyse the genotypes of 97 breast cancer patients. We found that the host’s genetic makeup facilitates metastases by the dysregulation of gene expression that can promote the dispersion of metastatic seeds and help establish the metastatic niche—providing a congenial soil for the metastatic seeds.

HBx Mediated Increase of DDX17 Contributes to HBV-Related Hepatocellular Carcinoma Tumorigenesis

HBV is strongly associated with HCC development and DEAD-box RNA helicase 17 (DDX17) is a very important member of the DEAD box family that plays key roles in HCC development by promoting cancer metastasis. However, the important role of DDX17 in the pathogenesis of HBV-related HCC remains unclear. In this study, we investigated the role of DDX17 in the replication of HBV and the development of HBV-associated HCC. Based on data from the GEO database and HBV-infected cells, we found that DDX17 was upregulated by the HBV viral protein X (HBx). Mechanistically, increased DDX17 expression promoted HBV replication and transcription by upregulating ZWINT. Further study showed that DDX17 could promote HBx-mediated HCC metastasis. Finally, the promotive effect of DDX17 on HBV and HBV-related HCC was confirmed in vivo. In summary, the results revealed the novel role of DDX17 in the replication of HBV and the metastasis of HBV-associated HCC.

Hepatitis B virus X protein mediated epigenetic alterations in the pathogenesis of hepatocellular carcinoma

Chronic hepatitis B virus (HBV) infection is a worldwide health problem. Hepatitis B virus X protein (HBx), a pleiotropic regulatory protein encoded by HBV, is necessary for the transcription of HBV covalently closed circular DNA (cccDNA) minichromosomes, and affects the epigenetic regulation of host cells. The epigenetic reprogramming of HBx on host cell genome is strongly involved in HBV-related HCC carcinogenesis. Here, we review the latest findings of the epigenetic regulation induced by HBx protein in hepatocellular carcinoma (HCC), including DNA methylation, histone modification and non-coding RNA expression. The influence of HBx on the epigenetic regulation of cccDNA is also summarized. In addition, preliminary studies of targeted drugs for epigenetic changes induced by HBx are also discussed. The exploration of epigenetic markers as potential targets will help to develop new prevention and/or treatment methods for HBx-related HCC.

Integrated Bioinformatic Analysis Identifies TIPIN as a Prognostic Biomarker in Hepatocellular Carcinoma

BACKGROUND

Gene expression and DNA methylation analyses have long been used to identify cancer markers. However, a combination analysis of the gene expression and DNA methylation has yet to be performed to identify potential biomarkers of hepatocellular carcinoma (HCC).

METHODS

By matching gene expression profiles and promoter methylation data in The Cancer Genome Atlas (TCGA), genes with discrepant expression as well as genes with differential promoter methylation were identified. High-expression genes with low promoter methylation were defined as epigenetically induced (EI), while low-expression genes with high promoter methylation were defined as epigenetically suppressed (ES). The human protein interaction network was further integrated to construct the EI/ES gene interaction network, and the key genes in the subnet were identified as potential HCC biomarkers. The expression differences and prognostic values were verified in TCGA and Gene Expression Omnibus (GEO) databases, as well as with tissue chip technology.

RESULTS

Four key genes were identified: TIPIN, RBM15B, DUSP28, and TRIM31, which demonstrated the differential gene expression and prognostic value in TCGA and GEO databases. Tissue microarray analysis (TMA) revealed that TIPIN levels were altered in HCC. The upregulated TIPIN expression was associated with worse overall survival. Univariate and multivariate analyses showed that the TIPIN expression was an independent predictor of HCC.

CONCLUSION

TIPIN might be a potential novel prognostic biomarker for HCC.

GNA14's interaction with RACK1 inhibits hepatocellular carcinoma progression through reducing MAPK/JNK and PI3K/AKT signaling pathway

Gαq subfamily proteins play critical roles in many biological functions including cardiovascular development, angiogenesis, and tumorigenesis of melanoma. However, the understanding of G Protein Subunit Alpha 14 (GNA14) in diseases, especially in cancers is limited. Here, we revealed that GNA14 was significantly low expression in Human hepatocellular carcinoma (HCC) samples. Low GNA14 expression was correlated with aggressive clinicopathological features. Moreover, the overall survival (OS) and disease-free survival (DFS) of high GNA14 expression HCC patients were much better than low GNA14 expression group. Lentivirus-mediated GNA14 knockdown significantly promoted the growth of liver cancer in vitro and in vivo. However, opposing results were observed when GNA14 is upregulated. Mechanistically, We identified receptor for activated C kinase 1 (RACK1) as a binding partner of GNA14 by co-immunoprecipitation and mass spectrometry (MS). Glutathione-S-transferase (GST) pull-down assay further verified the direct interaction between GNA14 and RACK1. RNA-Seq and loss- and gain-of-function assays also confirmed that GNA14 reduced the activity of both MAPK/JNK and PI3K/AKT signaling pathways through RACK1. GNA14 synergized with U73122 (PLC inhibitor) to enhance this effect. Further studies suggested that GNA14 potentially competed with protein kinase C (PKC) to bind with RACK1, consequently reducing the stability of PKC. Moreover, we also showed that GNA14’supression of p-AKT protein level depended on sufficient RACK1 expression. In conclusion, we indicated a different role of GNA14, which acted as a suppressor inhibiting liver cancer progression through MAPK/JNK and PI3K/AKT signaling pathways. Due to this, GNA14 served as a potentially valuable prognostic biomarker for liver cancer.

Advances in Multi-Omics Applications in HBV-Associated Hepatocellular Carcinoma

Hepatitis B virus (HBV) specifically infects liver cells, leading to progressive liver cirrhosis and significantly increasing the risk of hepatocellular carcinoma (HCC). The maturity of sequencing technology, improvement in bioinformatics data analysis and progress of omics technologies had improved research efficiency. The occurrence and progression of HCC are affected by multisystem and multilevel pathological changes. With the application of single-omics technologies, including genomics, transcriptomics, metabolomics and proteomics in tissue and body fluid samples, and even the novel development of multi-omics analysis on a single-cell platform, HBV-associated HCC changes can be better analyzed. The review summarizes the application of single omics and combined analysis of multi-omics data in HBV-associated HCC and proposes the importance of multi-omics analysis in the type of HCC, which provide the possibility for the precise diagnosis and therapy of HBV-associated HCC.

Viral Manipulation of the Host Epigenome as a Driver of Virus-Induced Oncogenesis

Tumorigenesis due to viral infection accounts for a high fraction of the total global cancer burden (15–20%) of all human cancers. A comprehensive understanding of the mechanisms by which viral infection leads to tumor development is extremely important. One of the main mechanisms by which viruses induce host cell proliferation programs is through controlling the host’s epigenetic machinery. In this review, we dissect the epigenetic pathways through which oncogenic viruses can integrate their genome into host cell chromosomes and lead to tumor progression. In addition, we highlight the potential use of drugs based on histone modifiers in reducing the global impact of cancer development due to viral infection.