Role of DTL in Hepatocellular Carcinoma and Its Impact on the Tumor Microenvironment

Multi-population Genome-Wide Association Study Identifies Multiple Novel Loci associated with Asymptomatic Intracranial Large Artery Stenosis

Background

Intracranial large artery stenosis (ILAS) is one of the most common causes of stroke worldwide and is associated with the risk for future vascular events. Asymptomatic ILAS is a frequent finding on neuroimaging and shares many risk factors with atherosclerotic vascular disease. Whether asymptomatic ILAS is driven by genetic variants is not well-understood.

Methods and Results

This study included 4960 participants from seven geographically diverse population-based cohorts (34% Whites, 16% African Americans, 22% Hispanics, 24% Asians, 5% native Ecuadorians). We defined asymptomatic ILAS as luminal stenosis > 50% in any large brain artery using time-of-flight magnetic resonance angiography (MRA). A genome-wide association study revealed one variant in RP11-552D8.1 (rs75615271; OR, 1.22 [1.11-1.33]; P =4.85×10 -8 ) associated with global ILAS at genome-wide significance ( P <5×10 -8 ). Gene-based association analysis identified a gene-set enriched in chr1q32 region, including NEK2 , LPGAT1 , INTS7 , DTL , and TMEM206 , in global ILAS ( P =1.34 ×10 -7 ) and anterior ILAS ( P =1.77 ×10 -8 ).

Conclusion

This study reveals one variant rs75615271 associated with asymptomatic ILAS in a multi-population. Further functional studies may help elucidate the role that this variant plays in the pathophysiology of asymptomatic ILAS.

HBx/DTL Positive Feedback Loop Promotes HBV-Related Hepatocellular Carcinoma Progression

Although hepatitis B virus (HBV) infection is a well-documented etiologic factor for hepatocellular carcinoma (HCC), which ranks as the third leading cause of cancer-related mortality globally, the mechanism by which HBV facilitates cancer development remains largely elusive. In this study, we employed advanced methodologies including, single-cell RNA sequencing, flow cytometry, western blot analysis, chromatin immunoprecipitation-qPCR and Cut&Tag to investigate the expression of DTL and its biological functions in HCC. We observed that DTL is overexpressed in HBV-positive HCC samples, with its elevated expression being associated with increased tumor cell proliferation and reduced overall and disease-free survival rates. The upregulation of DTL expression was specifically induced by the HBV regulatory protein HBx, thereby substantiating the oncogenic potential of HBV. Mechanistically, our findings indicated that the HBx protein augments DTL transcription by binding to its promoter region, subsequently facilitating HCC cell proliferation and modulating cell cycle progression, particularly by increasing the proportion of cells in the S phase. Furthermore, DTL was identified as a protein that interacts with HBx and associates with the Cullin4-RING ubiquitin ligases (CRL4s), thereby stabilizing HBx by reducing its ubiquitin-mediated degradation. In vivo experiments demonstrated that DTL not only facilitated cancer cell proliferation by modulating the cell cycle but also promoted tumorigenesis in nude mice. Moreover, DTL expression modifies the tumor immune microenvironment by increasing the proportion of regulatory T cells, thereby contributing to immune evasion. In summary, our findings underscore the pivotal role of DTL as a key regulator in HBV-related HCC by influencing cell cycle progression and establishing a positive feedback loop involving the HBx-DTL-CRL4s. These insights expand our understanding of HBV oncogenic mechanisms and suggest that DTL could serve as a novel biomarker and therapeutic target, potentially enhancing patient outcomes.

Identification of Crucial Cancer Stem Cell Genes Linked to Immune Cell Infiltration and Survival in Hepatocellular Carcinoma

Hepatocellular carcinoma is characterized by high recurrence rates and poor prognosis. Cancer stem cells contribute to tumor heterogeneity, treatment resistance, and recurrence. This study aims to identify key genes associated with stemness and immune cell infiltration in HCC. We analyzed RNA sequencing data from The Cancer Genome Atlas to calculate mRNA expression-based stemness index in HCC. A weighted gene co-expression network analysis was performed to identify stemness-related gene modules. A single-sample gene set enrichment analysis was used to evaluate immune cell infiltration. Key genes were validated using RT-qPCR. The mRNAsi was significantly higher in HCC tissues compared to adjacent normal tissues and correlated with poor overall survival. WGCNA and subsequent analyses identified 10 key genes, including minichromosome maintenance complex component 2, cell division cycle 6, forkhead box M1, NIMA-related kinase 2, Holliday junction recognition protein, DNA topoisomerase II alpha, denticleless E3 ubiquitin protein ligase homolog, maternal embryonic leucine zipper kinase, protein regulator of cytokinesis 1, and kinesin family member C1, associated with stemness and low immune cell infiltration. These genes were significantly upregulated in HCC tissues. A functional enrichment analysis revealed their involvement in cell cycle regulation. This study identified 10 key genes related to stemness and immune cell infiltration in HCC. These genes, primarily involved in cell cycle regulation, may serve as potential targets for developing more effective treatments to reduce HCC recurrence and improve patient outcomes.

Hypoxia-induced DTL promotes the proliferation, metastasis, and sorafenib resistance of hepatocellular carcinoma through ubiquitin-mediated degradation of SLTM and subsequent Notch pathway activation

Denticleless E3 ubiquitin protein ligase homolog (DTL), the substrate receptor of the CRL4A complex, plays a central role in genome stability. Even though the oncogenic function of DTL has been investigated in several cancers, its specific role in hepatocellular carcinoma (HCC) still needs further elucidation. Data from a clinical cohort (n = 209), RNA-sequencing, and public database (TCGA and GEO) were analyzed, indicating that DTL is closely related to patient prognosis and could serve as a promising prognostic indicator in HCC. Functionally, DTL promoted the proliferation, metastasis, and sorafenib resistance of HCC in vitro. In the orthotopic tumor transplantation and tail vein injection model, DTL promoted the growth and metastasis of HCC in vivo. Mechanically, we revealed for the first time that DTL was transcriptionally activated by hypoxia-inducible factor 1α (HIF-1α) under hypoxia and functioned as a downstream effector molecule of HIF-1α. DTL promotes the ubiquitination of SAFB-like transcription modulator (SLTM) and subsequently relieves the transcriptional repression of Notch1. These results suggested that DTL may be a potential biomarker and therapeutic target for HCC.

Enhanced anticancer activity of silver doped zinc oxide magnetic nanocarrier loaded with sorafenib for hepatocellular carcinoma treatment

Drug delivery is the process or method of delivering a pharmacological product to have therapeutic effects on humans or animals. The use of nanoparticles to deliver medications to cells is driving the present surge in interest in improving human health. Green nanodrug delivery methods are based on chemical processes that are acceptable for the environment or that use natural biomaterials such as plant extracts and microorganisms. In this study, zinc oxide-superparamagnetic iron oxide-silver nanocomposite was synthesized via green synthesis method using Fusarium oxysporum fungi mycelia then loaded with sorafenib drug. The synthesized nanocomposites were characterized by UV-visibile spectroscopy, FTIR, TEM and SEM techniques. Sorafenib is a cancer treatment and is also known by its brand name, Nexavar. Sorafenib is the only systemic medication available in the world to treat hepatocellular carcinoma. Sorafenib, like many other chemotherapeutics, has side effects that restrict its effectiveness, including toxicity, nausea, mucositis, hypertension, alopecia, and hand-foot skin reaction. In our study, 40 male albino rats were given a single dose of diethyl nitrosamine (DEN) 60 mg/kg b.wt., followed by carbon tetrachloride 2 ml/kg b.wt. twice a week for one month. The aim of our study is using the zinc oxide-superparamagnetic iron oxide-silver nanocomposite that was synthesized by Fusarium oxysporum fungi mycelia as nanocarrier for enhancement the sorafenib anticancer effect.

Evaluation of Genes and Molecular Pathways Involved in Pathogenesis of Sickle Cell Anemia: A Bioinformatics Analysis and Future Perspective

Background

Sickle cell disease (SCD) is one of the hematological disorders characterized by a defect in the structure and function of globin chains. Hereditary factors play an important role in the pathogenesis of SCD. We aimed to investigate the genes and pathways related to the pathogenesis of SCD.

Methods

Microarray dataset was downloaded from the Gene Expression Omnibus (GEO) database. LIMMA package of R-software was used to detect UP and Down regulations between SCD and control subjects. Enrichment analysis and Protein-protein interaction (PPI) networks were performed using GeneCodis4 software and GeneMANIA database, respectively. PrognoScan database was used to evaluate the relationship between the hub genes and patients' survival.

Results

Overall, 447 DEGs were identified in SCD patients compared to control subjects. Out of 447 DEGs, 345 genes were up-regulated and 102 genes were down-regulated. Effective hub genes in SCD pathogenesis include SLC4A1, DTL, EPB42, SNCA, and TOP2A. In addition, hub genes had a high diagnostic value.

Conclusion

Evaluation of hub genes in SCD can be used as a diagnostic panel to detect high-risk patients. In addition, by identifying the UP and Down stream pathways, treatment strategies in the monitoring and treatment of patients can be designed.

Gastric Cancer Biomarker Candidates Identified by Machine Learning and Integrative Bioinformatics: Toward Personalized Medicine

Gastric cancer (GC) is among the leading causes of cancer-related deaths worldwide. The discovery of robust diagnostic biomarkers for GC remains a challenge. This study sought to identify biomarker candidates for GC by integrating machine learning (ML) and bioinformatics approaches. Transcriptome profiles of patients with GC were analyzed to identify differentially expressed genes between the tumor and adjacent normal tissues. Subsequently, we constructed protein-protein interaction networks so as to find the significant hub genes. Along with the bioinformatics integration of ML methods such as support vector machine, the recursive feature elimination was used to select the most informative genes. The analysis unraveled 160 significant genes, with 88 upregulated and 72 downregulated, 10 hub genes, and 12 features from the variable selection method. The integrated analyses found that EXO1, DTL, KIF14, and TRIP13 genes are significant and poised as potential diagnostic biomarkers in relation to GC. The receiver operating characteristic curve analysis found KIF14 and TRIP13 are strongly associated with diagnosis of GC. We suggest KIF14 and TRIP13 are considered as biomarker candidates that might potentially inform future research on diagnosis, prognosis, or therapeutic targets for GC. These findings collectively offer new future possibilities for precision/personalized medicine research and development for patients with GC.

Pan-cancer analysis and experimental validation of DTL as a potential diagnosis, prognosis and immunotherapy biomarker

BACKGROUND

DTL has been found to be related with multiple cancers. However, comprehensive analyses, which identify the prediction value of DTL in diagnosis, prognosis, immune infiltration and treatment, have rarely been reported so far.

METHODS

Combined with the data online databases, the gene expression, gene mutation, function enrichment and the correlations with the immunity status and clinical indexes of DTL were analyzed. Expression of DTL and the degree of immune cell infiltration were examined by immunofluorescence (IF) and immunohistochemistry (IHC) and analyzed by statistical analysis. Furthermore, the influences of DTL on the cell cycle, cell proliferation and apoptosis were detected by live cell imaging, IF and flow cytometric (FC) analysis. Genomic stability assays were conducted by chromosome slide preparation.

RESULTS

DTL was widely expressed in various cells and tissues, while it was overexpressed in tumor tissues except acute myeloid leukemia (LAML). Pan-cancer bioinformatics analysis showed that the expression of DTL was correlated with the prognosis, immunotherapy, and clinical indexes in various cancers. In addition, gene set enrichment analysis (GSEA) uncovered that DTL was enriched in oocyte meiosis, pyrimidine metabolism, the cell cycle, the G2M checkpoint, mTORC1 signaling and E2F targets. Furthermore, the overexpression of DTL, and its association with immune cell infiltration and clinical indexes in liver hepatocellular carcinoma (LIHC), bladder urothelial carcinoma (BLCA) and stomach adenocarcinoma (STAD) were verified in our study. It was also verified that overexpression of DTL could regulate the cell cycle, promote cell proliferation and cause genomic instability in cultured cells, which may be the reason why DTL plays a role in the occurrence, progression and treatment of cancer.

CONCLUSIONS

Collectively, this study suggested that DTL is of clinical value in the diagnosis, prognosis and treatment of various cancers, and may be a potential biomarker in certain cancers.

Analysis of risk factors of hepatocellular carcinoma and establishment of a clinical prognosis model

Liver cancer is a common malignancy of the digestive system. Hepatocellular carcinoma (HCC) accounts for the most majority of these tumors and it has brought a heavy medical burden to underdeveloped countries and regions. Many factors affect the prognosis of HCC patients, however, there is no specific statistical model to predict the survival time of clinical patients. This study derived a risk factor signature of HCC and reliable clinical prediction model by statistically analyzing The Surveillance, Epidemiology, and End Results (SEER) database patient information using an open source package in the python environment.

Evolutionary Conserved Short Linear Motifs Provide Insights into the Cellular Response to Stress

Short linear motifs (SLiMs) are evolutionarily conserved functional modules of proteins composed of 3 to 10 residues and involved in multiple cellular functions. Here, we performed a search for SLiMs that exert sequence similarity to two segments of alpha-fetoprotein (AFP), a major mammalian embryonic and cancer-associated protein. Biological activities of the peptides, LDSYQCT (AFP_14-20) and EMTPVNPGV (GIP-9), have been previously confirmed under in vitro and in vivo conditions. In our study, we retrieved a vast array of proteins that contain SLiMs of interest from both prokaryotic and eukaryotic species, including viruses, bacteria, archaea, invertebrates, and vertebrates. Comprehensive Gene Ontology enrichment analysis showed that proteins from multiple functional classes, including enzymes, transcription factors, as well as those involved in signaling, cell cycle, and quality control, and ribosomal proteins were implicated in cellular adaptation to environmental stress conditions. These include response to oxidative and metabolic stress, hypoxia, DNA and RNA damage, protein degradation, as well as antimicrobial, antiviral, and immune response. Thus, our data enabled insights into the common functions of SLiMs evolutionary conserved across all taxonomic categories. These SLiMs can serve as important players in cellular adaptation to stress, which is crucial for cell functioning.

Deciphering cervical cancer-associated biomarkers by integrated multi-omics approach

OBJECTIVES

Cervical Squamous Cell Carcinoma (CESC) is one of the most fatal female malignancies, and the underlying molecular mechanisms governing this disease have not been fully explored. In this research, we planned to conduct the analysis of Gene Expression Omnibus (GEO) cervical squamous cell carcinoma microarray datasets by a detailed in silico approach and to explore some novel biomarkers of CESC.

METHODS

The top commonly differentially expressed genes (DEGs) from the GSE138080 and GSE113942 datasets were analyzed by Limma package-based GEO2R tool. The protein-protein interaction (PPI) network of the DEGs was drawn through Search Tool for the Retrieval of Interacting Genes (STRING), and top 6 hub genes were obtained from Cytoscape. Expression analysis and validation of hub genes expression in CESC samples and cell lines were done using UALCAN, OncoDB, GENT2, and HPA. Additionally, cBioPortal, Gene set enrichment analysis (GSEA) tool, Kaplan-Meier (KM) plotter, ShinyGO, and DGIdb databases were also used to check some important values of hub genes in CESC.

RESULTS

Out of 79 DEGs, the minichromosome maintenance complex component 4 (MCM4), nucleolar and spindle-associated protein 1 (NUSAP1), cell division cycle associated 5 (CDCA5), cell division cycle 45 (CDC45), denticleless E3 ubiquitin protein ligase homolog (DTL), and chromatin licensing and DNA replication factor 1 (CDT1) genes were regarded as hub genes in CESC. Further analysis revealed that the expressions of all these hub genes were significantly elevated in CESC cell lines and samples of diverse clinical attributes. In this study, we also documented some important correlations between hub genes and some other diverse measures, including DNA methylation, genetic alterations, and Overall Survival (OS). Last, we also identify hub genes associated ceRNA network and 31 important chemotherapeutic drugs.

CONCLUSION

Through detailed in silico methodology, we identified 6 hub genes, including MCM4, NUSAP1, CDCA5, CDC45, DTL, and CDT1, which are likely to be associated with CESC development and diagnosis.

A PARP1-related prognostic signature constructing and PARP-1 inhibitors screening for glioma

The current standard treatments of glioma include surgical resection, supplemented with radiotherapy and chemotherapy, but the prognosis is poor. PARP-1 (Poly ADP-ribose polymerase 1) is a hot spot for cancer-targeted therapy and was reported to be significantly elevated in glioma. In this study, we analyzed the role of PARP-1 in DNA damage repair, constructed a PARP1-related DNA-repair prognostic signature (DPS), and screened targeted drugs for glioma. RNA-seq data of 639 glioma samples were downloaded from the GEO (Gene Expression Omnibus) database and divided into PARP1_H and PARP1_L according to the front and rear thirds of the expression level of PARP-1. First, we systematically analyzed the influence of PARP-1 on DNA damage repair, prognosis, and chemoradiotherapy sensitization of glioma. All glioma patients and patients with radiotherapy or chemotherapy had a better prognosis in PARP1_L than in PARP1_H. Next, differentially expressed DNA-repair related genes (DEGs) were identified between PARP1_H and PARP1_L by LASSO (Least Absolute Shrinkage and Selection Operator) Cox analysis and applied for constructing DPS. Based on the four-gene DPS, we then developed a new nomogram to assess overall survival in glioma patients. Additionally, PARP-1 was proved an effective target for glioma therapy. So, a series of computer-aided techniques, including Discovery Studio 4.5, Schrodinger, and PyMol, were applied for the virtual screening of favorable PARP-1 inhibitors. In conclusion, this study investigated the effect of PARP-1 on glioma prognosis and the sensitization effect of radiotherapy and chemotherapy, established a novel nomogram to evaluate the overall survival of glioma patients, and further explored targeted therapy for glioma.