CDK1-PLK1/SGOL2/ANLN pathway mediating abnormal cell division in cell cycle may be a critical process in hepatocellular carcinoma

Exploring the molecular mechanisms by which per- and polyfluoroalkyl substances induce polycystic ovary syndrome through in silico toxicogenomic data mining

The pathogeny of polycystic ovary syndrome (PCOS) is intricate, with endocrine disruptors (EDCs) being acknowledged as significant environmental factors. Research has shown a link between exposure to per- and polyfluoroalkyl substances (PFAS) and the development and progression of PCOS, although the precise mechanism is not fully understood. This study utilized toxicogenomics and comparative toxicogenomics databases to analyze data and investigate how PFAS mixtures may contribute to the development of PCOS. The results indicated that 74 genes are associated with both PFAS exposure and PCOS progression. Enrichment analysis suggested that cell cycle regulation and steroid hormone synthesis may be crucial pathways through which PFAS mixtures participate in the development of PCOS, involving important genes such as CCNB1 and SRD5A1. Furthermore, the study identified transcription factors (TFs) and miRNAs that may be involved in the onset and progression of PCOS, constructing regulatory networks encompassing TFs-mRNA interactions and miRNA-mRNA relationships to elucidate their regulatory roles in gene expression. By utilizing data mining techniques based on toxicogenomic databases, this study provides relatively comprehensive insights into the association between exposure factors and diseases compared to traditional toxicology studies. These findings offer new perspectives for further in vivo or in vitro investigations and contribute to understanding the pathogenesis of PCOS, thereby providing valuable references for identifying clinical treatment targets.

Hsa_circ_0079875 functions as a competitive endogenous RNA to promote hepatocellular carcinoma progression

Circular RNA (circRNA) can influence the development of hepatocellular carcinoma (HCC) as a competitive endogenous RNA (ceRNA). However, there are still many circRNAs whose functions are unknown. Our research explores the role of a novel circRNA, hsa_circ_0079875, in HCC. The expression of hsa_circ_0079875 in HCC was verified by next-generation sequencing, quantitative reverse transcription-polymerase chain reaction (qRT-PCR), and fluorescence in situ hybridization (FISH). The distribution of hsa_circ_0079875 in HCC cells was investigated by RNA subcellular isolation and FISH assays. The functional effects on HCC proliferation, invasion, migration, cell cycle, and apoptosis were verified by overexpression and knockdown of hsa_circ_0079875. Moreover, xenograft mouse models and immunohistochemistry experiments were used to assess the function of hsa_circ_0079875 in vivo. Hsa_circ_0079875 was up-regulated in HCC tissues and mainly distributed in the cytoplasm. Higher hsa_circ_0079875 leads to larger tumor tissue, more microvascular invasion(MVI) and higher AFP levels, which in turn leads to a poor prognosis. Overexpression of hsa_circ_0079875 can promote the proliferation, migration, and invasion of HCC cells and inhibit apoptosis in vitro and in vivo. Knocking down hsa_circ_0079875 has the opposite effect. Sequencing and biological information predicted the target miRNA and mRNA of hsa_circ_0079875. Further bioinformatics and clinical correlation analysis revealed that hsa_circ_0079875 promote the malignant biological behaviors of HCC through hsa_circ_0079875/miR-519d-59/NRAS ceRNA net. Therefore, hsa_circ_0079875 can be a potential prognostic marker and therapeutic target for HCC.

High SGO2 predicted poor prognosis and high therapeutic value of lung adenocarcinoma and promoted cell proliferation, migration, invasion, and epithelial-to-mesenchymal transformation

Background: Shugoshin 2 (SGO2), a component of the cell division cohesion complex, is involved in both mitotic and meiotic processes. Despite being overexpressed in various malignant tumors and is associated with poor prognosis, its exact role in lung adenocarcinoma (LUAD) and its biological effects on lung cancer cells are not well understood. Methods: The transcriptomics data and clinical information for LUAD were obtained from TCGA and GEO, and DEGs associated with prognostic risk factors were screened using Cox regression analysis and chi-square testing. Identify these gene functions using correlation heatmaps, protein interaction networks (PPIs), and KEGG enrichment assays. The expression of SGO2 in tissues was verified by PCR and IHC, and the prognostic value of SGO2 in LUAD was evaluated by survival analysis. In addition, the effects of SGO2 knockdown on lung cancer cell proliferation, migration, invasion, and epithelial-to-mesenchymal transition (EMT) were studied in vitro. After that, the TIMER database and single-sample GSEA (ssGSEA) analysis were used to investigate the correlation between SGO2 and immune infiltration. Finally, the tumor mutational burden (TMB) of different SGO2 clusters and the efficacy of the two clusters in multiple treatments were evaluated. Results: High-risk genes associated with poor prognosis in LUAD are involved in cell cycle regulation and proliferation. Among these genes, SGO2 exhibited high expression in LUAD and corresponded with the TNM stage. Furthermore, the knockdown of SGO2 led to a decrease in the proliferation, migration, invasion, and EMT processes of lung cancer cells. Notably, high SGO2 expression may have poorer anti-tumor immunity and may therefore be more suitable for immunotherapy to re-establish immune function, while its high expression with a higher TMB could enable LUAD to benefit from multiple therapies. Conclusion: Our findings suggest that SGO2 may be a promising prognostic biomarker for LUAD, particularly in regulating the cell cycle and benefiting from multiple therapies.

ZNF765 is a prognostic biomarker of hepatocellular carcinoma associated with cell cycle, immune infiltration, m6A modification, and drug susceptibility

Hepatocellular carcinoma (HCC) is an ongoing challenge worldwide. Zinc finger protein 765 (ZNF765) is an important zinc finger protein that is related to the permeability of the blood-tumor barrier. However, the role of ZNF765 in HCC is unclear. This study evaluated the expression of ZNF765 in hepatocellular carcinoma and the impact of its expression on patient prognosis based on The Cancer Genome Atlas (TCGA). Immunohistochemical assays (IHC) were used to examine protein expression. Besides, a colony formation assay was used to examine cell viability. We also explored the relationship between ZNF765 and chemokines in the HCCLM3 cells by qRT-PCR. Moreover, we examined the effect of ZNF765 on cell resistance by measurement of the maximum half-inhibitory concentration. Our research revealed that ZNF765 expression in HCC samples was higher than that in normal samples, whose upregulation was not conducive to the prognosis. The results of GO, KEGG, and GSEA showed that ZNF765 was associated with the cell cycle and immune infiltration. Furthermore, we confirmed that the expression of ZNF765 had a strong connection with the infiltration level of various immune cells, such as B cells, CD4+ T cells, macrophages, and neutrophils. In addition, we found that ZNF765 was associated with m6A modification, which may affect the progression of HCC. Finally, drug sensitivity testing found that patients with HCC were sensitive to 20 drugs when they expressed high levels of ZNF765. In conclusion, ZNF765 may be a prognostic biomarker related to cell cycle, immune infiltration, m6A modification, and drug sensitivity for hepatocellular carcinoma.

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.

N6-Methyladenosine Modification of ANLN Enhances Hepatocellular Carcinoma Bone Metastasis

Bones are categorized as the second most prevalent location of extra-hepatic metastasis in Hepatocellular Carcinoma (HCC), which is linked to an extremely poor prognosis due to limited therapeutic options. N⁶-methyladenosine (m⁶A) is a prominent modification involved in HCC, but the exact mechanisms on how m⁶A modifications induce HCC bone metastases (BM) remain unclear. The key modulators responsible for the abundant m⁶A RNA modification-induced HCC BM was found to be the METTL3 and YTHDF1. The expression of Anillin actin-binding protein (ANLN) was dramatically higher in HCC with BM tissues, and its messenger RNA (mRNA) stability was enhanced via m⁶A epitranscriptomic regulation by METTL3 and YTHDF1. High METTL3 and YTHDF1 expression along with nuclear ANLN protein was clinically correlated with BM in HCC patients. Furthermore, HCC BM was attributed to over-expression of nuclear ANLN forming a transcriptional complex with SP1 which enhanced KIF2C transcriptional activity to activate the mTORC1 pathway, therefore increased the expression of RANKL and disproportionated RANKL-OPG expression in bone microenvironment leading to malignant neoplasms invade bone tissue. In addition, inhibition of ANLN m⁶A modification by DZNeP attenuated HCC BM. This data provides meaningful understanding of the modulation and association of m⁶A epitranscriptomic-regulated BM in HCC, and moreover, defines potentially valuable therapeutic targets.

Significance of Identifying Key Genes Involved in HBV-Related Hepatocellular Carcinoma for Primary Care Surveillance of Patients with Cirrhosis

Cirrhosis is frequently the final stage of disease preceding the development of hepatocellular carcinoma (HCC) and is one of the risk factors for HCC. Preventive surveillance for early HCC in patients with cirrhosis is advantageous for achieving early HCC prevention and diagnosis, thereby enhancing patient prognosis and reducing mortality. However, there is no highly sensitive diagnostic marker for the clinical surveillance of HCC in patients with cirrhosis, which significantly restricts its use in primary care for HCC. To increase the accuracy of illness diagnosis, the study of the effective and sensitive genetic biomarkers involved in HCC incidence is crucial. In this study, a set of 120 significantly differentially expressed genes (DEGs) was identified in the GSE121248 dataset. A protein-protein interaction (PPI) network was constructed among the DEGs, and Cytoscape was used to extract hub genes from the network. In TCGA database, the expression levels, correlation analysis, and predictive performance of hub genes were validated. In total, 15 hub genes showed increased expression, and their positive correlation ranged from 0.80 to 0.90, suggesting they may be involved in the same signaling pathway governing HBV-related HCC. The GSE10143, GSE25097, GSE54236, and GSE17548 datasets were used to investigate the expression pattern of these hub genes in the progression from cirrhosis to HCC. Using Cox regression analysis, a prediction model was then developed. The ROC curves, DCA, and calibration analysis demonstrated the superior disease prediction accuracy of this model. In addition, using proteomic analysis, we investigated whether these key hub genes interact with the HBV-encoded oncogene X protein (HBx), the oncogenic protein in HCC. We constructed stable HBx-expressing LO2-HBx and Huh-7-HBx cell lines. Co-immunoprecipitation coupled with mass spectrometry (Co-IP/MS) results demonstrated that CDK1, RRM2, ANLN, and HMMR interacted specifically with HBx in both cell models. Importantly, we investigated 15 potential key genes (CCNB1, CDK1, BUB1B, ECT2, RACGAP1, ANLN, PBK, TOP2A, ASPM, RRM2, NEK2, PRC1, SPP1, HMMR, and DTL) participating in the transformation process of HBV infection to HCC, of which 4 hub genes (CDK1, RRM2, ANLN, and HMMR) probably serve as potential oncogenic HBx downstream target molecules. All these findings of our study provided valuable research direction for the diagnostic gene detection of HBV-related HCC in primary care surveillance for HCC in patients with cirrhosis.

SGOL2 is a novel prognostic marker and fosters disease progression via a MAD2-mediated pathway in hepatocellular carcinoma

Background

Shugoshin-like protein 2 (SGOL2) is a centromeric protein that ensures the correct and orderly process of mitosis by protecting and maintaining centripetal adhesions during meiosis and mitosis. Here, we examined the potential role of SGOL2 in cancers, especially in hepatocellular carcinoma (HCC).

Methods

One hundred ninety-nine normal adjacent tissues and 202 HCC samples were collected in this study. Human HCC cells (SK-HEP-1 and HEP-3B) were employed in the present study. Immunohistochemistry, immunofluorescence, western blot, Co-Immunoprecipitation technique, and bioinformatic analysis were utilized to assess the role of SGOL2 in HCC development process.

Results

Overexpression of SGOL2 predicted an unfavorable prognosis in HCC by The Cancer Genome Atlas database (TCGA), which were further validated in our two independent cohorts. Next, 47 differentially expressed genes positively related to both SGOL2 and MAD2 were identified to be associated with the cell cycle. Subsequently, we demonstrated that SGOL2 downregulation suppressed the malignant activities of HCC in vitro and in vivo. Further investigation showed that SGOL2 promoted tumor proliferation by regulating MAD2-induced cell-cycle dysregulation, which could be reversed by the MAD2 inhibitor M2I-1. Consistently, MAD2 upregulation reversed the knockdown effects of SGOL2-shRNA in HCC. Moreover, we demonstrated that SGOL2 regulated MAD2 expression level by forming a SGOL2-MAD2 complex, which led to cell cycle dysreuglation of HCC cells.

Conclusion

SGOL2 acts as an oncogene in HCC cells by regulating MAD2 and then dysregulating the cell cycle, providing a potential therapeutic target in HCC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40364-022-00422-z.

A review on the role of cyclin dependent kinases in cancers

The Cyclin-dependent kinase (CDK) class of serine/threonine kinases has crucial roles in the regulation of cell cycle transition and is mainly involved in the pathogenesis of cancers. The expression of CDKs is controlled by a complex regulatory network comprised of genetic and epigenetic mechanisms, which are dysregulated during the progression of cancer. The abnormal activation of CDKs results in uncontrolled cancer cell proliferation and the induction of cancer stem cell characteristics. The levels of CDKs can be utilized to predict the prognosis and treatment response of cancer patients, and further understanding of the function and underlying mechanisms of CDKs in human tumors would pave the way for future cancer therapies that effectively target CDKs. Defects in the regulation of cell cycle and mutations in the genes coding cell-cycle regulatory proteins lead to unrestrained proliferation of cells leading to formation of tumors. A number of treatment modalities have been designed to combat dysregulation of cell cycle through affecting expression or activity of CDKs. However, effective application of these methods in the clinical settings requires recognition of the role of CDKs in the progression of each type of cancer, their partners, their interactions with signaling pathways and the effects of suppression of these kinases on malignant features. Thus, we designed this literature search to summarize these findings at cellular level, as well as in vivo and clinical levels.

Gene coexpression network analysis identifies hubs in hepatitis B virus-associated hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) is among the leading causes of cancer-related death worldwide. The molecular pathogenesis of HCC involves multiple signaling pathways. This study utilizes systems and bioinformatic approaches to investigate the pathogenesis of HCC.

METHODS

Gene expression microarray data were obtained from 50 patients with chronic hepatitis B and HCC. There were 1649 differentially expressed genes inferred from tumorous and nontumorous datasets. Weighted gene coexpression network analysis (WGCNA) was performed to construct clustered coexpressed gene modules. Statistical analysis was used to study the correlation between gene coexpression networks and demographic features of patients. Functional annotation and pathway inference were explored for each coexpression network. Network analysis identified hub genes of the prognostic gene coexpression network. The hub genes were further validated with a public database.

RESULT

Five distinct gene coexpression networks were identified by WGCNA. A distinct coexpressed gene network was significantly correlated with HCC prognosis. Pathway analysis of this network revealed extensive integration with cell cycle regulation. Ten hub genes of this gene network were inferred from protein-protein interaction network analysis and further validated in an external validation dataset. Survival analysis showed that lower expression of the 10-gene signature had better overall survival and recurrence-free survival.

CONCLUSION

This study identified a crucial gene coexpression network associated with the prognosis of hepatitis B virus-related HCC. The identified hub genes may provide insights for HCC pathogenesis and may be potential prognostic markers or therapeutic targets.

Gene expression in meningeal lymphatic endothelial cells following traumatic brain injury in mice

Meningeal lymphatic vessels transport both the cerebrospinal fluid and interstitial fluid to the deep cervical lymph nodes. Traumatic brain injury (TBI) is accompanied by meningeal injury. We hypothesized that the TBI-induced meningeal injury would damage lymphatic vessels and affect brain function. We observed altered gene expression in meningeal lymphatic endothelial cells (LECs) in a mouse model of TBI. Through flow cytometry–based cell sorting, meningeal LECs were obtained from a mouse model of controlled cortical impact 3 days after TBI. Microarray analysis, real-time polymerase chain reaction assays, and enzyme-linked immunosorbent assays were performed to determine mRNA and protein expression levels in meningeal LECs. The number of meningeal LECs was significantly lower in the injury group than in the sham group 3 days after TBI. Additionally, the mRNA expression of lymphatic vessel endothelial hyaluronan receptor 1 (a specific marker of lymphatic vessels) in meningeal LECs was significantly lower in the injury group than in the sham group. The mRNA and protein expression of FMS-like tyrosine kinase 4 and neuropilin 2 (markers of lymphangiogenesis) in meningeal LECs was significantly higher in the injury group than in the sham group. Our findings indicate that TBI is associated with the impairment of meningeal LECs and meningeal lymphangiogenesis, which implicates lymphatic vessel injury in the pathogenesis of this condition.

Pan-cancer analysis of the prognostic and immunological role of ANLN: An onco-immunological biomarker

Anillin actin-binding protein (ANLN) is crucially involved in cell proliferation and migration. Moreover, ANLN is significantly in tumor progression in several types of human malignant tumors; however, it remains unclear whether ANLN acts through common molecular pathways within different tumor microenvironments, pathogeneses, prognoses and immunotherapy contexts. Therefore, this study aimed to perform bioinformatics analysis to examine the correlation of ANLN with tumor immune infiltration, immune evasion, tumor progression, immunotherapy, and tumor prognosis. We observed increased ANLN expression in multiple tumors, which could be involved in tumor cell proliferation, migration, infiltration, and prognosis. The level of ANLN methylation and genetic alteration was associated with prognosis in numerous tumors. ANLN facilitates tumor immune evasion through different mechanisms, which involve T-cell exclusion in different cancer types and tumor-infiltrating immune cells in colon adenocarcinoma, kidney renal clear cell carcinoma, liver hepatocellular carcinoma, and prostate adenocarcinoma. Additionally, ANLN is correlated with immune or chemotherapeutic outcomes in malignant cancers. Notably, ANLN expression may be a predictive biomarker for the response to immune checkpoint inhibitors. Taken together, our findings suggest that ANLN can be used as an onco-immunological biomarker and could serve as a hallmark for tumor screening, prognosis, individualized treatment design, and follow-up.

SETD3 Methyltransferase Regulates PLK1 Expression to Promote In Situ Hepatic Carcinogenesis

Background

The development of a new strategy to overcome chemoresistance to hepatocellular carcinoma (HCC) treatment is a long-standing issue. We have previously found that upregulated SETD3 levels are closely correlated with HCC. This study aims to explore the mechanism underlying how upregulation of SETD3 promotes liver carcinogenesis.

Methods

RNA-Sequencing analysis was used to explore the correlation of SETD3 with regulatory targets. In vitro assays including cell proliferation and migration were performed to study the oncogenic roles of SETD3 and PLK1. Western blotting, immunohistochemical staining, and blood biochemical assays were performed to examine protein expression or pathological index in tumor tissues and mice liver tissues. Luciferase reporter system and chromatin immunoprecipitation assays were used to explore the mechanism.

Results

We revealed that SETD3 regulates gene expression in subgroups, including cell division, cell proliferation, and cell cycle, in hepatocellular tumor cells. We found that SETD3 upregulation is associated with elevated PLK1 level in both hepatic tumor cells and clinical liver tissues. We further showed that overexpression of SETD3 promoted tumor cell proliferation and migration, whereas inhibition of PLK1 activity attenuated these phenotypes caused by SETD3. By taking advantage of the Sleep Beauty transposase system, we confirmed that upregulated mouse Setd3 promoted hepatic carcinogenesis in situ, but knockdown of mouse Plk1 mitigated Setd3-promoted tumorigenesis in mice. Mechanistically, we showed that SETD3 could be recruited to the promoter of PLK1 gene to facilitate PLK1 transcription.

Conclusions

Our data demonstrate that elevated SETD3 may promote HCC by enhancing PLK1 expression, which suggests that SETD3 may act as a potential drug target combined with PLK1 inhibition to treat HCC.

SPDL1 Overexpression Is Associated With the 18F-FDG PET/CT Metabolic Parameters, Prognosis, and Progression of Esophageal Cancer

Esophageal cancer (ESCA) is one of the common malignant tumors. The roles and signaling mechanisms of spindle apparatus coiled-coil protein 1 (SPDL1) in ESCA progression have not been reported previously. Therefore, the expression levels and potential clinical roles of SPDL1 were investigated using data from multiple databases and tissue samples of 53 ESCA patients who underwent 18F-FDG positron emission tomography (PET)/computed tomography (CT) before therapy. The signaling mechanisms of SPDL1 involved in ESCA progression were investigated via bioinformatics analysis. The effects of SPDL1 on the growth and migration of ESCA cells were investigated using CCK-8, Edu, and transwell assays. SPDL1 was upregulated in ESCA tissues. Increased SPDL1 expression was associated with age, grade, drinking history, cancer stage, lymph node metastasis, TP53 mutation, and poor prognosis in patients with ESCA. SPDL1 overexpression was significantly correlated with SUVmax, SUVmean, and TLG of PET/CT. SPDL1 silencing inhibited cell proliferation, migration, and invasion. SPDL1 was significantly enriched in cell cycle, spliceosome, DNA replication, and other processes. The hub genes of a constructed protein–protein interaction network included CDK1, BUB1, CCNB1, BUB1B, CCNA2, CDC20, MAD2L1, AURKB, NDC80, and PLK1, which were related to SPDL1 expression. The findings of this study suggest that SPDL1 may serve as a biomarker of ESCA prognosis.

A Cell Cycle-Related 13-mRNA Signature to Predict Prognosis in Hepatocellular Carcinoma

We aimed to propose a cell cycle-related multi/mRNA signature (CCS) for prognosis prediction and uncover new tumor-driver genes for hepatocellular carcinoma (HCC). Cell cycle-related gene sets and HCC samples with mRNA-Seq data were retrieved from public sources. The genes differentially expressed in HCCs relative to normal peritumoral tissues were extracted through statistical analysis. The CCS was constructed by Cox regression analyses. Predictive capacity and clinical practicality of the signature were evaluated and validated. The expression of the function-unknown genes in the CCS was determined by RT-qPCR. Candidate gene TICRR was selected for subsequent validation through functional experiments. A cell cycle-related 13-mRNA signature was generated from the exploratory cohort [The Cancer Genome Atlas (TCGA), n = 371)]. HCC cases were classified as high- vs. low-risk groups per overall survival (OS) [hazard ratio (HR) = 2.699]. Significantly, the CCS exhibited great predictive value for prognosis in three independent cohorts, particularly in GSE76427 cohort [area under the curve (AUC) = 0.835/0.822/0.808/0.821/0.826 at 1/2/3/4/5 years]. The nomogram constructed by integrating clinicopathological features with the CCS indicated high accuracy and practicability. Significant enrichment of tumorigenesis-associated pathways was observed in the high-risk patients by Gene Set Enrichment Analysis (GSEA). RT-qPCR revealed that TICRR was overexpressed in HCC samples. Increased TICRR expression implied poor prognosis in HCC patients. Furthermore, depletion of TICRR in HCC cells decreased cell proliferation and the G1/S transition. In conclusion, the established 13-CCS had efficacy in prognostic prediction of HCC patients. Additionally, TICRR was demonstrated as a tumor-driver gene for this deadly disease.

Identification and Validation of Hub Genes with Poor Prognosis in Hepatocellular Carcinoma by Integrated Bioinformatical Analysis

Background

Hepatocellular carcinoma (HCC) is the reason for the world’s second largest cancer-related death. It is clinically valuable to study the molecular mechanisms of HCC occurrence and development for formulating more effective diagnosis and treatment strategies.

Methods

The five microarray data sets GSE45267, GSE101685, GSE84402, GSE62232 and GSE45267 were downloaded from Gene Expression Omnibus (GEO) database, including 165 HCC tissues and 73 normal tissues. Differential expressed genes (DEGs) between HCC tissues and normal tissues were determined by GEO2R. Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and the protein–protein interaction network (PPI) network analysis were employed to identify DEGs and to evaluate the clinical significance in prognosis of HCC.

Results

A total of 152 genes differentially expressed in HCC tissues and normal tissues were identified. GO and KEGG functional enrichment analysis revealed that 39 up-regulated genes were mainly enriched in mitosis, cell cycle and oocyte meiosis, while those down-regulated genes (113) were concentrated in exogenous drug catabolism and the metabolism of cytochrome P450 on exogenous drugs. Totally, 19 hub genes were chosen by PPI network and module analysis and verified by The Cancer Genome Atlas (TCGA) database. Finally, 8 hub genes were selected, including CDK1, CYP2C8, CCNB1, AURKA, CYP2C9, BUB1B, MAD2L1 and TTK, which were associated with the overall survival rate of HCC patients.

Conclusion

This study presented eight target genes connected to the prognosis of HCC patients. Those mainly exists in cell cycle and drug catabolism, which may be latent targets for clinical treatment.

MiR-16-5p suppresses breast cancer proliferation by targeting ANLN

BACKGROUND

In recent years, gene expression-based analysis has been used for disease biomarker discovery, providing ways for better diagnosis, leading to improvement of clinical treatment efficacy. This study aimed to explore the role of miR-16-5p and ANLN in breast cancer (BC).

METHODS

Cohort datasets of BC were obtained from the Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA) and analyzed by bioinformatics tools. qRT-PCR and western blotting were applied to validate ANLN and its protein expression. A dual-luciferase reporter assay was used to prove the regulatory relationship of miR-16-5p and ANLN. Finally, MTT, wound healing, Transwell invasion and flow cytometry analyses of the cell cycle and apoptosis were performed to assess cell proliferation, migration, invasion, cell cycle and apoptosis, respectively.

RESULTS

A total of 195 differentially expressed genes (DEGs) and 50 overlapping microRNAs (miRNAs) were identified. Among these DEGs and miRNAs, ANLN, associated with poor overall survival in BC, overlapped in the GSE29431, GSE42568, TCGA and GEPIA2 databases. Moreover, ANLN was highly expressed, while miR-16-5p was lower in BC cells than in breast epithelial cells. Then, we confirmed that ANLN was directly targeted by miR-16-5p in BC cells. Over-expression of miR-16-5p and knock-down of ANLN remarkably inhibited cell proliferation and migration as well as cell invasion, arrested the cells in G2/M phase and induced apoptosis in BC cells.

CONCLUSIONS

These findings suggest that miR-16-5p restrains proliferation, migration and invasion while affecting cell cycle and promotes apoptosis by regulating ANLN, thereby providing novel candidate biomarkers for the diagnosis and treatment of BC.

[CDK1, CCNB1 and NDC80 are associated with prognosis and progression of hepatitis B virus-associated hepatocellular carcinoma: a bioinformatic analysis]

OBJECTIVE

To identify the key genes involved in the transformation of hepatitis B virus (HBV) into hepatocellular carcinoma (HCC) and explore the underlying molecular mechanisms.

METHODS

We analyzed the mRNA microarray data of 119 HBV-related HCC tissues and 252 HBV-related non-tumor tissues in GSE55092, GSE84044 and GSE121248 from the GEO database, and the "sva" R package was used to remove the batch effects. Integration analysis was performed to identify the differentially expressed genes (DEGs) in HBV-related liver cancer and liver tissues with HBV infection. The significant DEGs were functionally annotated using GO and KEGG analyses, and the most important modules and hub genes were explored with STRING analysis. Kaplan-Meier and Oncomine databases were used to verify the HCC gene expression data in the TCGA database to explore the correlations of the hub genes with the occurrence, progression and prognosis of HCC. We also examined the expressions of the hub genes in 17 pairs of surgical specimens of HCC and adjacent tissues using RT-qPCR.

RESULTS

We identified a total of 121 DEGs and 3 genetic markers in HCC (P < 0.01). These DEGs included cyclin1 (CDK1), cyclin B1 (CCNB1), and nuclear division cycle 80 (NDC80), which participated in cell cycle, pyrimidine metabolism and DNA replication and were highly correlated (P < 0.05). Analysis of the UALCAN database confirmed high expressions of these 3 genes in HCC tissues, which were correlated with a low survival rate of the patients, as shown by Kaplan-Meier analysis of the prognostic data from the UALCAN database. CDK1, CCNB1 and NDC80 were all correlated with the clinical grading of HCC (P < 0.05). The results of RT-qPCR on the surgical specimens verified significantly higher expressions of CDK1, CCNB1 and NDC80 mRNA in HCC tissues than in the adjacent tissues.

CONCLUSION

CDK1, CCNB1 and NDC80 genes can be used as prognostic markers of HBV-related HCC and may serve as potential targets in preclinical studies and clinical treatment of HCC.

Identification of hub genes associated with prognosis, diagnosis, immune infiltration and therapeutic drug in liver cancer by integrated analysis

Background

Liver cancer is one of the most common cancers and causes of cancer death worldwide. The objective was to elucidate novel hub genes which were benefit for diagnosis, prognosis, and targeted therapy in liver cancer via integrated analysis.

Methods

GSE84402, GSE101685, and GSE112791 were filtered from the Gene Expression Omnibus (GEO). Differentially expressed genes (DEGs) were identified by using the GEO2R. The GO and KEGG pathway of DEGs were analyzed in the DAVID. PPI and TF network of the DEGs were constructed by using the STRING, TRANSFAC, and Harmonizome. The relationship between hub genes and prognoses in liver cancer was analyzed in UALCAN based on The Cancer Genome Atlas (TCGA). The diagnostic value of hub genes was evaluated by ROC. The relationship between hub genes and tumor-infiltrate lymphocytes was analyzed in TIMER. The protein levels of hub genes were verified in HPA. The interaction between the hub genes and the drug were identified in DGIdb.

Results

In total, 108 upregulated and 60 downregulated DEGs were enriched in 148 GO terms and 20 KEGG pathways. The mRNA levels and protein levels of CDK1, HMMR, PTTG1, and TTK were higher in liver cancer tissues compared to normal tissues, which showed excellent diagnostic and prognostic value. CDK1, HMMR, PTTG1, and TTK were positively correlated with tumor-infiltrate lymphocytes, which might involve tumor immune response. The CDK1, HMMR, and TTK had close interaction with anticancer agents.

Conclusions

The CDK1, HMMR, PTTG1, and TTK were hub genes in liver cancer; hence, they might be potential biomarkers for diagnosis, prognosis, and targeted therapy of liver cancer.

High SGO2 Expression Predicts Poor Overall Survival: A Potential Therapeutic Target for Hepatocellular Carcinoma

Shugoshin2 (SGO2) may participate in the occurrence and development of tumors by regulating abnormal cell cycle division, but its prognostic value in hepatocellular carcinoma (HCC) remains unclear. In this study, we accessed The Cancer Genome Atlas (TCGA) database to get the clinical data and gene expression profile of HCC. The expression of SGO2 in HCC tissues and nontumor tissues and the relationship between SGO2 expression, survival, and clinicopathological parameters were analyzed. The SGO2 expression level was significantly higher in HCC tissues than in nontumor tissues (p < 0.001). An analysis from the Oncomine and Gene Expression Profiling Interactive Analysis 2 (GEPIA2) databases also demonstrated that SGO2 was upregulated in HCC (all p < 0.001). A logistic regression analysis revealed that the high expression of SGO2 was significantly correlated with gender, tumor grade, pathological stage, T classification, and Eastern Cancer Oncology Group (ECOG) score (all p < 0.05). The overall survival (OS) of HCC patients with higher SGO2 expression was significantly poor (p < 0.001). A multivariate analysis showed that age and high expression of SGO2 were independent predictors of poor overall survival (all p < 0.05). Twelve signaling pathways were significantly enriched in samples with the high-SGO2 expression phenotype. Ten proteins and 34 genes were significantly correlated with SGO2. In conclusion, the expression of SGO2 is closely related to the survival of HCC. It may be used as a potential therapeutic target and prognostic marker of HCC.

Bioinformatics Profiling of Five Immune-Related lncRNAs for a Prognostic Model of Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC), one of the most common tumors worldwide, has the fifth highest mortality rate, which is increasing every year. At present, many studies have revealed that immunotherapy has an important effect on many malignant tumors. The main purpose of our research was to verify and establish a new immune-related lncRNA model and to explore the potential immune mechanisms. We analysed the pathways and mechanisms of immune-related lncRNAs by bioinformatics analysis, screened key lncRNAs based on Cox regression analysis, and determined the characteristics of the immune-related lncRNAs. On this basis, a predictive model was established. Through a comparison of specificity and sensitivity, we found that the constructed model was superior to the known markers of HCC. Then, the cell types were identified by the relative subgroup (CIBERSORT) algorithm for RNA transcripts. A signature model was eventually constructed, and we proved that it was a survival factor for HCC. Moreover, five kinds of immune cells were significantly positively correlated with the signature. The results indicated that these five kinds of lncRNAs may be related to the immune infiltration of hepatocellular carcinoma. To verify these findings, we selected the top coexpressed lncRNA, AC099850.3, for further study. We found that AC099850.3 could promote the migration and proliferation of hepatocellular carcinoma cells in vitro. RT-PCR experiments found that AC099850.3 could promote the expression of the cell cycle molecules BUB1, CDK1, PLK1, and TTK, and western blotting to prove that the expression of the molecules CD155 and PD-L1 was inhibited in the interference group. In conclusion, we used five kinds of immune-related lncRNAs to construct prognostic signatures to explore the mechanism, which provides a new way to study therapies for HCC.

Actin-binding protein anillin promotes the progression of hepatocellular carcinoma in vitro and in mice

Hepatocellular carcinoma (HCC) is a common type of tumor with high mortality worldwide. Investigations associated with the molecular etiology of HCC and screening novel therapeutic targets are still urgently in need. Anillin (ANLN), as a type of evolutionarily conserved actin-binding protein, is involved in multiple cellular processes. ANLN widely affected the progression and metastasis of several types of cancer, and its overexpression was frequently demonstrated in previous studies. The present study demonstrated high expression of ANLN in human HCC tissues, which was also associated the prognosis of patients with HCC. The associations between ANLN expression and the clinicopathological features were determined, including the number of tumor nodes (P=0.011) and tumor size (P=0.003) of patients with HCC. It was found that ANLN promoted cell proliferation, invasion and migration of HCC cells in vitro, and affected tumor growth in vivo. Therefore, ANLN is suggested as a promising therapeutic target for the treatment of HCC.

Cytokinesis regulators as potential diagnostic and therapeutic biomarkers for human hepatocellular carcinoma

Cytokinesis, the final step of mitosis, is critical for maintaining the ploidy level of cells. Cytokinesis is a complex, highly regulated process and its failure can lead to genetic instability and apoptosis, contributing to the development of cancer. Human hepatocellular carcinoma is often accompanied by a high frequency of aneuploidy and the DNA ploidy pattern observed in human hepatocellular carcinoma results mostly from impairments in cytokinesis. Many key regulators of cytokinesis are abnormally expressed in human hepatocellular carcinoma, and their expression levels are often correlated with patient prognosis. Moreover, preclinical studies have demonstrated that the inhibition of key cytokinesis regulators can suppress the growth of human hepatocellular carcinoma. Here, we provide an overview of the current understanding of the signaling networks regulating cytokinesis, the key cytokinesis regulators involved in the initiation and development of human hepatocellular carcinoma, and their applications as potential diagnostic and therapeutic biomarkers.

Bioinformatics Analysis of Candidate Genes and Pathways Related to Hepatocellular Carcinoma in China: A Study Based on Public Databases

Background and Objective: Hepatocellular carcinoma (HCC) is a highly aggressive malignant tumor of the digestive system worldwide. Chronic hepatitis B virus (HBV) infection and aflatoxin exposure are predominant causes of HCC in China, whereas hepatitis C virus (HCV) infection and alcohol intake are likely the main risk factors in other countries. It is an unmet need to recognize the underlying molecular mechanisms of HCC in China.

Methods: In this study, microarray datasets (GSE84005, GSE84402, GSE101685, and GSE115018) derived from Gene Expression Omnibus (GEO) database were analyzed to obtain the common differentially expressed genes (DEGs) by R software. Moreover, the gene ontology (GO) functional annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed by using Database for Annotation, Visualization and Integrated Discovery (DAVID). Furthermore, the protein-protein interaction (PPI) network was constructed, and hub genes were identified by the Search Tool for the Retrieval of Interacting Genes (STRING) and Cytoscape, respectively. The hub genes were verified using Gene Expression Profiling Interactive Analysis (GEPIA), UALCAN, and Kaplan-Meier Plotter online databases were performed on the TCGA HCC dataset. Moreover, the Human Protein Atlas (HPA) database was used to verify candidate genes’ protein expression levels.

Results: A total of 293 common DEGs were screened, including 103 up-regulated genes and 190 down-regulated genes. Moreover, GO analysis implied that common DEGs were mainly involved in the oxidation-reduction process, cytosol, and protein binding. KEGG pathway enrichment analysis presented that common DEGs were mainly enriched in metabolic pathways, complement and coagulation cascades, cell cycle, p53 signaling pathway, and tryptophan metabolism. In the PPI network, three subnetworks with high scores were detected using the Molecular Complex Detection (MCODE) plugin. The top 10 hub genes identified were CDK1, CCNB1, AURKA, CCNA2, KIF11, BUB1B, TOP2A, TPX2, HMMR and CDC45. The other public databases confirmed that high expression of the aforementioned genes related to poor overall survival among patients with HCC.

Conclusion: This study primarily identified candidate genes and pathways involved in the underlying mechanisms of Chinese HCC, which is supposed to provide new targets for the diagnosis and treatment of HCC in China.

Overexpression of Taspase 1 Predicts Poor Prognosis in Patients with Hepatocellular Carcinoma

Background

Taspase 1 (TASP1) is a highly conserved protease involved in site-specific proteolysis. Existing researches have revealed a link between TASP1 expression and carcinogenesis. However, limited data are available regarding the prognosis and functions of TASP1 in hepatocellular carcinoma (HCC).

Methods

Western Blotting and qRT-PCR were employed to evaluate the level of TASP1 in HCC cell lines and clinical specimens. TASP1 expression was further calculated in clinical specimens by immunohistochemistry and the mRNA level of TASP1 in HCC was analyzed using Oncomine and UALCAN databases. The TASP1 promoter methylation modification was shown via MEXPRESS and UALCAN. The association between TASP1 expression and postoperative prognosis was evaluated using Kaplan–Meier and Cox regression analysis in clinical patients. The effect of TASP1 on HCC prognosis was analyzed via Kaplan-Meier plotter, GEPIA and UALCAN. Additionally, the regulators, kinases, miRNA and transcription factor targets of TASP1 were identified using LinkedOmics. Moreover, cBioPortal was used to detect the genetic alteration of TASP1. Finally, TIMER was utilized to assess the relation between TASP1 and the immune cell infiltration, whereas the correlation of TASP1 with three immune factors was detected through TISIDB.

Results

TASP1 expression was increased in HCC cell lines and HCC tissues. CNV and DNA methylation of TASP1 were changed. Survival analysis revealed that high TASP1 expression was correlated with overall survival (OS). Functional network analysis about TASP1 in HCC showed that the double-strand break repair, peptidyl-threonine modification, spindle organization, peptidyl-lysine modification and microtubule-based movement were modulated. Furthermore, TASP1 expression revealed puissant relation to the infiltration of immune cells and three immune factors in HCC.

Conclusion

These data indicate that TASP1 may act as a potential prognostic marker in HCC and regulate HCC via multiple mechanisms.

Identification of Potential Hub Genes and Signal Pathways Promoting the Distinct Biological Features of Cord Blood-Derived Endothelial Progenitor Cells Via Bioinformatics

Background: Numerous studies, ranging from the alleviation of tissue ischemia to the assessment of cancer prognosis, have demonstrated the fundamental biological differences between human umbilical cord blood-derived endothelial progenitor cells (CB-EPCs) and adult peripheral blood-derived endothelial progenitor cells (PB-EPCs). However, the underlying molecular mechanisms that produce these differences are not clear.The purpose of this study was to identify potential hub genes, key protein interactive networks, and correlated signal pathways unique to CB-EPC biology via bioinformatic methods. Materials and Methods: We selected the microarray dataset GSE39763 and identified the differentially expressed genes (DEGs) using the "limma" package in the RStudio software. These DEGs were annotated by gene ontology enrichment analyses and signal pathway analyses. A protein-protein interaction (PPI) analysis was then performed to construct PPI networks and identify a hub protein module. We further validated candidate DEGs from the selected module in the gene expression profiling interactive analysis (GEPIA) database because the DEGs were enriched in cancer pathways. Results: Setting an adjusted p-value <0.01 and |Log₂ fold change (FC)| ≥ 2 as cutoff criteria, a total of 346 DEGs, including 314 upregulated genes and 32 downregulated genes in CB-EPCs, were identified. Expression of the genes encoding the AT-Hook Containing Transcription Factor 1 (AHCTF1), the Cancer Susceptibility Candidate 5 (CASC5), the Centromere Protein C (CENPC), the Centromere Protein E (CENPE), the Centromere Protein F (CENPF), the NUF2 Component of NDC80 Kinetochore Complex (NUF2), the RAN-Binding Protein 2 (RANBP2), the Shugoshin-like 2 (SGOL2), the Structural Maintenance of Chromosomes 3 (SMC3), and the Spindle Apparatus Coiled-Coil Protein 1 (SPDL1) proteins were specifically associated with CB-EPCs. Except for CENPC, the other nine genes' expression are all associated with a poorer overall survival rate in cancers. The expression levels of the CENPF and NUF2 genes in tumor patients were significantly higher than those in the controls. Conclusion: The CB-EPCs express genes with greater potential for proliferation and increased migration compared to PB-EPCs; in this regard they are similar to cancer cells.