KIF11 Promotes Proliferation of Hepatocellular Carcinoma among Patients with Liver Cancers

Di-(2-ethylhexyl) phthalate promotes benign prostatic hyperplasia through KIF11-Wnt/β-catenin signaling pathway

Di-(2-ethylhexyl) phthalate (DEHP) might led to chronic and long-term effects on human organs due to its widespread use and bioaccumulation. Despite some cohorts reporting an association between DEHP exposure and BPH, its underlying mechanisms have not been investigated. Our findings indicate that exposure to DEHP or MEHP (main metabolites of DEHP in the human body) leads to increased prostate weights, elevated prostate index, and notable epithelial thickening in rats. It has been observed to promote BPH-1 cell proliferation with effects ranging from low to high concentrations. Transcriptome sequencing analysis of rat prostate tissues identified KIF11 as the key hub gene. KIF11 is highly expressed after DEHP/MEHP exposure, and knocking down of KIF11 inhibits the MEHP-induced promotion of cell proliferation. Exposure to MEHP has been observed to increase the expression of p-GSK-3β and elevate the levels of β-catenin, thereby activating the Wnt/β-catenin signaling pathway. Knocking down of KIF11 significantly inhibits these effects. Histone H3 at Lysine 27 acetylation (H3K27ac) is implicated in the upregulation of KIF11 expression, as evidenced by the addition of the acetylation inhibitor C646. In summary, our findings established that DEHP exposure could promote BPH through H3K27ac regulated KIF11/Wnt/β-catenin signaling pathway.

Eg5 and Diseases: From the Well-Known Role in Cancer to the Less-Known Activity in Noncancerous Pathological Conditions

Eg5 is a protein encoded by KIF11 gene and is primarily involved in correct mitotic cell division. It is also involved in nonmitotic processes such as polypeptide synthesis, protein transport, and angiogenesis. The scientific literature sheds light on the ubiquitous functions of KIF11 and its involvement in the onset and progression of different pathologies. This review focuses attention on two main points: (1) the correlation between Eg5 and cancer and (2) the involvement of Eg5 in noncancerous conditions. Regarding the first point, several tumors revealed an overexpression of this kinesin, thus pushing to look for new Eg5 inhibitors for clinical practice. In addition, the evaluation of Eg5 expression represents a crucial step, as its overexpression could predict a poor prognosis for cancer patients. Referring to the second point, in specific pathological conditions, the reduced activity of Eg5 can be one of the causes of pathological onset. This is the case of Alzheimer's disease (AD), in which Aβ and Tau work as Eg5 inhibitors, or in acquired immune deficiency syndrome (AIDS), in which Tat-mediated Eg5 determines the loss of CD4+ T-lymphocytes. Reduced Eg5 activity, due to mutations of KIF11 gene, is also responsible for pathological conditions such as microcephaly with or without chorioretinopathy, lymphedema, or intellectual disability (MCLRI) and familial exudative vitreous retinopathy (FEVR). In conclusion, this review highlights the double impact that overexpression or loss of function of Eg5 could have in the onset and progression of different pathological situations. This emphasizes, on one hand, a possible role of Eg5 as a potential biomarker and new target in cancer and, on the other hand, the promotion of Eg5 expression/activity as a new therapeutic strategy in different noncancerous diseases.

Bioinformatics Research and qRT-PCR Verify Hub Genes and a Transcription Factor-MicroRNA Feedback Network in Intervertebral Disc Degeneration

The present study explores the potentials of bioinformatics analysis to identify hub genes linked to intervertebral disc degeneration (IDD) and explored the potential molecular mechanism of transcription factor-microRNA regulatory network. Furthermore, the hub genes were identified through quantitative reverse transcriptase PCR (qRT-PCR). GEO database expression profile datasets for candidate genes (GSE124272) were downloaded. Genes that were differentially expressed (DEGs) were detected utilizing limma technique in the R programming language. Search Tool for the Retrieval of Interacting Genes/Proteins and NetworkAnalyst software identified hub genes. The Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis as well as Gene Ontology annotation of the DEGs were performed using Metascape. Using Bioinformatics data from the TRRUST, StarBase, and TransmiR databases, a TF-miRNA-hub genes network was constructed. qRT-PCR was utilized to confirm the result. As compared to healthy persons, 521 DEGs, comprising 203 down-regulated and 318 up-regulated genes, as well as 7 core genes, were found in people with IDD. Analysis revealed that all seven essential genes were under-expressed. qRT-PCR further confirmed the low expression of these seven important genes. Based on the TRRUST database, 16 TFs that could target five junction genes were then predicted. According to the StarBase database, four miRNAs were linked to crucial genes, while the TransmiR database predicted regulatory connections between four miRNAs and five TFs. The expression of the TP53-(hsa-miR-183-5p)-CCNB1 TF-miRNA-mRNA interaction network was discovered to be correlated with IDD. Throughout this investigation, a network of TF-miRNA-mRNA connections was built for investigation of the probable molecular mechanisms responsible for IDD. The identification of hub genes associated with IDD may reveal promising IDD treatment strategies.

Mitotic Functions and Characters of KIF11 in Cancers

Mitosis mediates the accurate separation of daughter cells, and abnormalities are closely related to cancer progression. KIF11, a member of the kinesin family, plays a vital role in the formation and maintenance of the mitotic spindle. Recently, an increasing quantity of data have demonstrated the upregulated expression of KIF11 in various cancers, promoting the emergence and progression of cancers. This suggests the great potential of KIF11 as a prognostic biomarker and therapeutic target. However, the molecular mechanisms of KIF11 in cancers have not been systematically summarized. Therefore, we first discuss the functions of the protein encoded by KIF11 during mitosis and connect the abnormal expression of KIF11 with its clinical significance. Then, we elucidate the mechanism of KIF11 to promote various hallmarks of cancers. Finally, we provide an overview of KIF11 inhibitors and outline areas for future work.

The role of kinesin family members in hepatobiliary carcinomas: from bench to bedside

As a major component of the digestive system malignancies, tumors originating from the hepatic and biliary ducts seriously endanger public health. The kinesins (KIFs) are molecular motors that enable the microtubule-dependent intracellular trafficking necessary for mitosis and meiosis. Normally, the stability of KIFs is essential to maintain cell proliferation and genetic homeostasis. However, aberrant KIFs activity may destroy this dynamic stability, leading to uncontrolled cell division and tumor initiation. In this work, we have made an integral summarization of the specific roles of KIFs in hepatocellular and biliary duct carcinogenesis, referring to aberrant signal transduction and the potential for prognostic evaluation. Additionally, current clinical applications of KIFs-targeted inhibitors have also been discussed, including their efficacy advantages, relationship with drug sensitivity or resistance, the feasibility of combination chemotherapy or other targeted agents, as well as the corresponding clinical trials. In conclusion, the abnormally activated KIFs participate in the regulation of tumor progression via a diverse range of mechanisms and are closely associated with tumor prognosis. Meanwhile, KIFs-aimed inhibitors also carry out a promising tumor-targeted therapeutic strategy that deserves to be further investigated in hepatobiliary carcinoma (HBC).

Inhibition of KIF11 ameliorates osteoclastogenesis via regulating mTORC1-mediated NF-κB signaling

Osteoporosis, characterized by over-production and activation of osteoclasts, has become a major health problem especially in elderly women. In our study, we first tested the effect of Caudatin (Cau) in osteoclastogenesis, which is separated from Cynanchum auriculatum as a species of C-21 steroidal glyosides. The results indicated that Cau suppressed osteoclastogenesis in a time- and dose-dependent manner in vitro. Mechanistically, Cau was identified to inhibit NF-κB signaling pathway via modulation of KIF11-mediated mTORC1 activity. In vivo, by establishing an ovariectomized (OVX) mouse model to mimic osteoporosis, we confirmed that Cau treatment prevented OVX-induced bone loss in mice. In conclusion, we demonstrated that Cau inhibited NF-κB signaling pathway via modulation of KIF11-mediated mTORC1 activity to suppress osteoclast differentiation in vitro as well as OVX-induced bone loss in vivo. This provides the possibility of a novel prospective drug for osteoporosis remedies.

Kinesin family member 11 promotes progression of hepatocellular carcinoma via the OCT4 pathway

Hepatocellular carcinoma (HCC) is the tumor with the second highest mortality rate worldwide. Recent research data show that KIF11, a member of the kinesin family (KIF), plays an important role in the progression of various tumors. However, its expression and molecular mechanism in HCC remain elusive. Here, we evaluated the potential role of KIF11 in HCC. The effect of KIF11 was evaluated using the hepatocellular carcinoma cell lines, LM3 and Huh7, after genetic or pharmacological treatment. Evaluating the role of KIF11 in the xenograft animal models using its specific inhibitor. The role of KIF11 was systematically evaluated using specimens obtained from the aforementioned animal and cell models after various in vivo and in vitro experiments. The clinicopathological analysis showed that KIF11 was expressed at high levels in patients with hepatocellular carcinoma. Cell experiments in vitro showed that KIF11 deficiency significantly slowed the proliferation of liver tumor cells. And in the experiment using liver cancer cells overexpressing OCT4, overexpression of OCT4 substantially increased the proliferation of tumor cells compared with tumor cells with KIF11 knockdown alone. Both in vitro cell experiment and in vivo xenotransplantation tumor experiment showed that monastrol, an inhibitor of KIF11, could effectively delay the proliferation and migration of tumor cells. Based on these results, KIF11 is expressed at high levels in hepatocellular carcinoma and promotes tumor proliferation in an OCT4-dependent manner. KIF11 may become a therapeutic target for hepatocellular carcinoma, and its inhibitor monastrol may become a clinical antitumor drug.

An Eight-mRNA Prognostic Model to Predict Survival in Hepatic Cellular Cancer

Background. Transcriptional dysregulation plays a critical role in the onset and development of malignant tumors. Employing gene dysregulation to forecast the change of tumors is valuable for cancer diagnosis. However, the prognostic prediction for HCC using combined gene models remains insufficient. Methods. The expression profiles of GSE103512 and TCGA-LIHC were downloaded. Gene Ontology (Go) was used to evaluate the overlapping differential genes (DEG) in TCGA and GSE103512. The core genes in the critical module most significantly related to HCC were obtained by WGCNA. Eight genes most significantly related to HCC and OS were identified by reweighted coexpression network analysis and Cox regression. Results. We selected eight genes, FZEB1, CDK1, RAD54L, COL1A2, ATP1B3, CASP8, USP39, and HOXB7. Moreover, we constructed an eight-gene model and forecasted the prognosis of HCC. ROC curve of the eight-mRNA prognostic model was screened out ( $\text{AUC}=0.635$ ), suggesting that this model exhibited a good prediction performance. Survival analysis showed that the survival rate of patients in the high-risk group was significantly lower than that in the low-risk group. Conclusion. The eight-mRNAs model might forecast the OS of HCC patients and advance remedial decision-making.

SKA1/2/3 is a biomarker of poor prognosis in human hepatocellular carcinoma

BACKGROUND

Spindle and kinetochore-associated complex subunits 1-3 (SKA1-3) stabilize the kinetochore-attached spindle microtubules in metaphase. Due to the dysregulation in multiple cancers, SKA1-3 is considered a predictor for the prognosis of the patients. However, the potential clinical applications of SKA1-3, particularly in hepatocellular carcinoma (HCC) prognosis and progression, have completely unknown yet.

METHODS

For the analysis of SKA1-3 expression and applications in clinics in HCC patients, several databases, such as STRING, UALCAN, GEO, and TCGA, were searched. In addition, the underlying mechanisms of SKA for the regulation of HCC occurrence, development, and progression were also explored.

RESULTS

Compared to the normal controls, HCC patients showed dramatically elevated SKA1-3 expression at the mRNA level, and the values of the area under the curve (AUC) were 0.982, 0.887, and 0.973, respectively. Increased SKA1-3 expression levels were associated with the clinical stage, age, body mass index, tumor grade, tissue subtype, and Tp53 mutation status in HCC patients. The analyses of Kyoto Encyclopedia of Genes and Genome (KEGG) and Gene ontology (GO) demonstrated that SKA1-3 are enriched mainly in the Fanconi anemia, homologous recombination, spliceosome, DNA replication, and cell cycle signaling pathways. The hub genes, such as CDK1, CCNB1, CCNA2, TOP2A, BUB1, AURKB, CCNB2, BUB1B, NCAPG, and KIF11, were identified in protein-protein interactions (PPIs). The expression levels of hub genes were increased in HCC patients and predictive of a poor prognosis. Finally, the expression levels of SKA1-3 were determined using the GEO database.

CONCLUSIONS

SKA1-3 are potential prognostic biomarkers of and targets for HCC. In addition, SKA1-3 may affect HCC prognosis via the Fanconi anemia pathway, homologous recombination, spliceosome, DNA replication, and cell cycle signaling pathway.

Single-cell transcriptomics reveals the role of Macrophage-Naïve CD4 + T cell interaction in the immunosuppressive microenvironment of primary liver carcinoma

Background

Liver carcinoma generally presents as an immunosuppressive microenvironment that promotes tumor evasion. The intercellular crosstalk of immune cells significantly influences the construction of an immunosuppressive microenvironment. This study aimed to investigate the important interactions between immune cells and their targeting drugs in liver carcinoma, by using single-cell and bulk transcriptomic data.

Methods

Single-cell and bulk transcriptomic data were retrieved from Gene Expression Omnibus (GSE159977, GSE136103, and GSE125449) and The Cancer Genome Atlas (TGCA-LIHC), respectively. Quality control, dimension reduction, clustering, and annotation were performed according to the Scanpy workflow based on Python. Cell–cell interactions were explored using the CellPhone database and CellChat. Trajectory analysis was executed using a partition-based graph abstraction method. The transcriptomic factors (TFs) were predicted using single-cell regulatory network inference and clustering (SCENIC). The target genes from TFs were used to establish a related score based on the TCGA cohort; this score was subsequently validated by survival, gene set enrichment, and immune cell infiltration analyses. Drug prediction was performed based on the Cancer Therapeutics Response Portal and PRISM Repurposing datasets.

Results

Thirty-one patients at four different states, including health, hepatitis, cirrhosis, and cancer, were enrolled in this study. After dimension reduction and clustering, twenty-two clusters were identified. Cell–cell interaction analyses indicated that macrophage-naive CD4 + T cell interaction significantly affect cancerous state. In brief, macrophages interact with naive CD4 + T cells via different pathways in different states. The results of SCENIC indicated that macrophages present in cancer cells were similar to those present during cirrhosis. A macrophage-naive CD4 + T cell (MNT) score was generated by the SCENIC-derived target genes. Based on the MNT score, five relevant drugs (inhibitor of polo-like kinase 1, inhibitor of kinesin family member 11, dabrafenib, ispinesib, and epothilone-b) were predicted.

Conclusions

This study reveals the crucial role of macrophage-naive CD4 + T cell interaction in the immunosuppressive microenvironment of liver carcinoma. Tumor-associated macrophages may be derived from cirrhosis and can initiate liver carcinoma. Predictive drugs that target the macrophage-naive CD4 + T cell interaction may help to improve the immunosuppressive microenvironment and prevent immune evasion. The relevant mechanisms need to be further validated in experiments and cohort studies.

Graphical Abstract

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-022-03675-2.

The role of PI3K/AKT signaling pathway in gallbladder carcinoma

OBJECTIVES

The prognosis of gallbladder carcinoma (GBC) is poor, with a less than 5% five-year survival rate. Identifying the mechanisms underlying GBC occurrence and advancement is necessary to improve GBC patient prognosis and survival rates. The phosphatidylinositol 3-kinase (PI3K)/serine-threonine kinase (AKT) pathway is involved in cancer deterioration, tumor growth, cell proliferation, and distant metastasis. Studying the impacts of the PI3K/AKT pathway has resulted in the identification of key factors involved in GBC progression that might serve as therapeutic targets, promoting the development of new treatments.

METHODS

We reviewed recent literature exploring abnormal regulation of the PI3K/AKT pathway in gallbladder cancer, with a focus on abnormal RNA levels, protein level regulation, and drug treatment advances.

RESULTS

Further investigation of the regulation of small molecules and proteins by the PI3K/AKT pathway might ultimately provide new diagnostic or prognostic markers or cancer treatment targets. Recent studies have focused on RNA and proteins involved in the regulation of the cell cycle or cell movement in cancer progression via PI3K/AKT pathway, the use of anticancer drug combinations, or the anticancer effects of drugs not currently utilized for cancer treatment.

CONCLUSIONS

We herein review the known available molecules that affect the PI3K/AKT pathway in patients with GBC and the mechanisms of drug action associated with this pathway.

KIF11: A potential prognostic biomarker for predicting bone metastasis‑free survival of prostate cancer

Most prostate cancer (PCa) cases remain indolent with a relatively good prognosis. However, bone metastasis of PCa can quickly worsen prognoses and lead to mortality. Metastasis-free survival (MFS), a strong surrogate for overall survival, is widely used in PCa prognosis research. The present study identified molecules that affect bone MFS in PCa, with clinical validation. Three datasets (GSE32269, GSE74367 and GSE77930) were downloaded from the Gene Expression Omnibus database. Hub genes most relevant to clinical traits (bone metastasis-associated morbidity) were identified by weighted gene co-expression network analysis (WGCNA) and subjected to logistic regression analysis. Patient samples were obtained between January 2014 and December 2016, with a clinically annotated follow-up in December 2021. Clinical data and follow-up information for 60 patients with PCa were used in MFS analysis. Tumor samples were retrieved, and immunohistochemistry was performed to detect vascular endothelial growth factor (VEGF). The prognostic potential of the two molecules was assessed using Cox proportional hazards regression analysis. A total of 16 gene modules were obtained via WGCNA, and the tan module, containing 147 genes, was most closely linked to bone metastasis. In total, 877 differentially expressed genes (DEGs) were detected. The DEG-tan module intersection yielded seven hub genes [BUB1, kinesin family member (KIF)2C, RACGAP1, CENPE, KIF11, TTK and KIF20A]. Using univariate and multivariate logistic regression analyses for independent risk factors of bone metastasis, KIF11 and VEGF were found to be significantly associated with a higher T stage, prostate-specific antigen level and Gleason score. In addition, KIF11 and VEGF expression levels were positively correlated (P<0.001). Using univariate Cox analysis, KIF11 and VEGF were found to exhibit a significant association with poor MFS (P<0.05). However, only KIF11 was significantly associated with MFS upon multivariate analysis (P=0.007; hazard ratio, 2.776; 95% confidence interval, 1.315-5.859). Markers of bone metastasis in PCa were identified. Overall, KIF11 is an independent indicator that can predict bone metastasis for patients with PCa, which could be used to guide clinical practice.

Glioma Subtypes Based on the Activity Changes of Immunologic and Hallmark Gene Sets in Cancer

Purpose

Glioma is the most common primary cranial brain tumor that arises from the cancelation of glial cells (which can be in the brain or spinal cord). It is due to innate genetic risk factors or induced by a carcinogenic environment. If left untreated, the disease has a poor prognosis.

Methods

In this study, we downloaded glioma data from TCGA database and GEO (GSE4412). The GSEA database was used to screen tumor microenvironment-related gene sets. Cancer subtypes were classified by GSVA enrichment method.

Results

By GSVA enrichment analysis, we obtain three Gliomas cancer subtypes. After further survival prognosis analysis and biological function analysis, we obtained 13 tumor microenvironment gene sets and 14 core genes that affect patients' survival prognosis, and these genes have the potential to become targets for targeted therapies and disease detection.

Conclusion

We screened a total of 13 gene sets through a series of enrichment analyses, statistical and prognostic analyses, etc. Among them, 14 core genes were identified, namely: TOP2A, TPX2, BUB1, AURKB, AURKA, CDK1, BUB1B, CCNA2, CCNB2, CDCA8, CDC20, KIF11, KIF20A and KIF2C.

An Integrative Human Pan-Cancer Analysis of Cyclin-Dependent Kinase 1 (CDK1)

Simple Summary

Cyclin-dependent kinase 1 (CDK1), one of the key regulators of the G2/M checkpoint, is expressed in many cells and plays an important role in cell cycle control. However, CDK1 expression is substantially increased in many tumors of diverse origins and is associated with tumorigenesis. Targeting CDK1 shows promising results for several tumors. However, a systematic and integrative analysis of CDK1 in cancer has not been conducted. The present study aims to use pan-cancer analysis to investigate the relationship, similarities, and differences in genetic and cellular changes associated with CDK1 in various tumors and tumor microenvironments. Our findings elucidate that CDK1 expression increases in more than 20 human tumors and is highly correlated with oncogenic signature gene sets, biological pathways, immune cell infiltration, tumor mutational burden, microsatellite instability, and lower survival rate across multiple tumors. Targeting CDK1 may provide a novel and effective strategy for cancer immunotherapy.

Abstract

Cyclin-dependent kinase 1 (CDK1) is essential for cell division by regulating the G2/M phase and mitosis. CDK1 overexpression can also promote the development and progression of a variety of cancers. However, the significance of CDK1 in the formation, progression, and prognosis of human pan-cancer remains unclear. In the present study, we used The Cancer Genome Atlas database, Clinical Proteomic Tumor Analysis Consortium, Human Protein Atlas, Genotype-Tissue Expression, and other well-established databases to comprehensively examine CDK1 genetic alterations and gene/protein expression in various cancers and their relationships with the prognosis, immune reactivities, and clinical outcomes for 33 tumor types. Gene set enrichment analysis was also conducted to examine the potential mechanisms of CDK1 in tumorigenesis. The data showed that CDK1 mutation was frequently present in multiple tumors. CDK1 expression was significantly increased in various types of tumors as compared with normal tissues and was associated with poor overall and disease-free survival. In addition, CDK1 expression was significantly correlated with oncogenic genes, proteins, cellular components, myeloid-derived suppressor cell infiltration, ESTMATEScore, and signaling pathways associated with tumor development and progression and tumor microenvironments. These data indicate that CDK1 could serve as a promising biomarker for predicting tumor prognosis and a potential target for cancer treatment.

Development an Immune-Related MicroRNA Risk Index in Hepatocellular Carcinoma

Purpose

Hepatocellular carcinoma (HC) has emerged as one of the most prevalent malignancies on a global scale. Recently, immunotherapy has achieved favorable effectiveness in the management of multiple cancers. However, there are limited therapeutic options for advanced HC. As the liver is a special immune organ, we intend to uncover potential and effective immunotherapeutic modalities for HC. Our study was designed to develop specific immune-related miRNAs (IRMs) for outcome assessment and individualized strategies for the management of HC.

Methods

The miRNA-seq and survival data of TCGA-LIHC dataset was enrolled into this program. We first collected IRMs from Immune-miR website. Differentially expression analysis was applied to screen aberrantly expressed IRMs. In order to set up an IRM-related index (IRMRI) in HC, we conducted the Cox relevant methods. Next, the statistical approaches (survival curve and ROC curve analyses) were utilized to detect the evaluation capacity of our IRMRI. Subsequently, we obtained the target genes of hub miRNAs from IRMRI through three miRNA-related predictive online tools (miRDB, miRTarBase, and TargetScan websites).

Results

Five IRMs were determined to develop the IRMRI. It can effectively segregate all HC cases from two different risk subgroups. We identified a marked discrepancy in survival outcome between the two groups by survival analysis and confirmed the reliability of IRMRI in two testing sets. Moreover, we collected 10 hub target genes (ESR1, IGF1, PDGFRB, JUN, MYC, ZWINT, MAD2L1, TOP2A, KIF11, and CDCA8) which were strongly linked to HC progression and malignant behavior.

Conclusion

We screened out five hub IRMs with clinical value and constructed a risk index model in HC, which can precisely assess the risk status and outcome of patients to a certain extent.

Combined screening analysis of aberrantly methylated-differentially expressed genes and pathways in hepatocellular carcinoma

BACKGROUND

Methylation plays an important role in hepatocellular carcinoma (HCC) by altering the expression of key genes. The aim of this study was to screen the aberrantly methylated-differentially expressed genes (DEGs) in HCC and elucidate their underlying molecular mechanism.

METHODS

Gene expression microarrays (GSE101685) and gene methylation microarrays (GSE44909) were selected. DEGs and differentially methylated genes (DMGs) were screened. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed using the Database for Annotation, Visualization, and Integrated discovery (DAVID). The Search Tool for the Retrieval of Interacting Genes (STRING) database was used to analyze the functional protein-protein interaction (PPI) network. Molecular Complex Detection (MCODE) analysis was performed using the Cytoscape software. Hub genes were verified in The Cancer Genome Atlas (TCGA) database.

RESULTS

A total of 80 hypomethylation-high expression genes (Hypo-HGs) were identified. Pathway enrichment analysis showed DNA replication, cell cycle, viral carcinogenesis, and the spliceosome. The top 5 hub genes were minichromosome maintenance complex component 3 (MCM3), checkpoint kinase 1 (CHEK1), kinesin family member 11 (KIF11), PDZ binding kinase (PBK), and Rac GTPase activating protein 1 (RACGAP1). In addition, 189 hypermethylation-low expression genes (Hyper-LGs) were identified. Pathway enrichment analysis indicated enrichment in metabolic pathways, drug metabolism-other enzymes, and chemical carcinogenesis. The top 5 hub genes were leukocyte immunoglobulin like receptor B2 (LILRB2), formyl peptide receptor 1 (FPR1), S100 calcium binding protein A9 (S100A9), S100 calcium binding protein A8 (S100A8), and myeloid cell nuclear differentiation antigen (MNDA). The methylation status and mRNA expression of MCM3, CHEK1, KIF11, PBK, and S100A9 were consistent in the TCGA database and significantly correlated with the prognosis of patients.

CONCLUSIONS

Combined screening of aberrantly methylated-DEGs based on bioinformatic analysis may provide new clues for elucidating the epigenetic mechanism in HCC. Hub genes, including MCM3, CHEK1, KIF11, PBK, and S100A9, may serve as biomarkers for the precise diagnosis of HCC.

ZWINT is a Promising Therapeutic Biomarker Associated with the Immune Microenvironment of Hepatocellular Carcinoma

Background

The prognosis of patients with advanced hepatocellular carcinoma (HCC) is still poor, effective therapeutic targets are needed. ZW10 interacting kinetochore protein (Zwint) is an essential component of the mitotic spindle checkpoint and is upregulated in cancers. Disappointing, the role of ZWINT in HCC has not been fully illuminated.

Methods

Multiple tools, including TIMER2.0, Oncomine, GEPIA2, UALCAN, LinkedOmics, Kaplan-Meier Plotter, cBioPortal, and MethSurv, etc. were applied to comprehensively analyze the expression, genetic alternations, clinicopathological relevance, prognostic value, and DNA methylation of ZWINT, along with its correlations with immune infiltration in HCC. Besides, gene set enrichment analysis (GSEA) and protein-protein interaction (PPI) analysis were performed for the correlated genes of ZWINT, closely interconnected clusters and hub proteins in the PPI network were discovered to learn the underlying biological mechanisms.

Results

We found ZWINT was significantly upregulated in diverse cancers including HCC, compared with the corresponding normal controls. ZWINT upregulation was significantly associated with unfavorable clinicopathological features and survivals of HCC patients. Genetic alternations of ZWINT frequently occurred, which were linked to worse outcomes of HCC patients. The results of GSEA displayed ZWINT and its correlated genes might be components of condensed chromosomes and spindles, which participated in biological processes and signaling pathways involving DNA replication, cytokinesis, and cell cycle checkpoint, etc. Three highly interconnected clusters and 10 hub proteins were identified from the PPI network constructed with the correlated genes of ZWINT. Moreover, ZWINT expression was found positively correlated with infiltration levels of various immune cells, especially myeloid-derived suppressor cells.

Conclusion

This study demonstrated ZWINT might be a promising unfavorable prognostic biomarker and a therapeutic target of HCC, which could regulate HCC progression through cell division and immunosuppression.