Association study of germline variants in CCNB1 and CDK1 with breast cancer susceptibility, progression, and survival among Chinese Han women

Transcriptome Analysis of Transiently Reversible Cell Vacuolization Caused by Excessive Serum Concentration in Scophthalmus maximus

As an important research tool, cell lines play a vital role in life science research, medical research, and drug development. During the culture of the Scophthalmus maximus head kidney (TK) cell line, we found a phenomenon of cell vacuolization caused by excessive serum concentration. Moreover, the vacuolization of the cells gradually disappeared after passage by trypsin digestion. In clarifying the formation mechanism of this reversible cellular vacuolation, transcriptomics was utilized to explore the mechanism of cell vacuolization caused by excessive serum concentration. Transcriptome analysis indicated that excessive serum concentration could cause the up-regulated expression of PORCN and other genes to promote cell proliferation. Compared with cells whose vacuolization disappeared after trypsin digestion and passage, the expression of mitosis-related genes (BUB1, ttk, Mad2, Cdc20, CDK1, CCNB1), nuclear stability-related genes LMNB1 and tissue stress and repair-related genes HMMR in vacuolated cells caused by excessive serum concentration was significantly up-regulated. There is a regulatory system related to adaptation and stress repair in the cells, which can maintain cell stability to a certain extent. This study provides a theoretical basis for the stable culture of fish cell lines and the solution to the problem of cell vacuolation.

Study on the mechanism of quercetin in Sini Decoction Plus Ginseng Soup to inhibit liver cancer and HBV virus replication through CDK1

BACKGROUND

To explore the anti-tumor and anti-virus key active ingredients of Sini Decoction Plus Ginseng Soup (SNRS) and their mechanisms.

METHODS

The main ingredients of SNRS were analyzed by network pharmacology, and quercetin was identified as the key active ingredient. Then, we obtained the targets of quercetin by using Drugbank, PharmMapper, and SwissTargetPrediction databases. Then, the targets of HBV-related hepatocellular carcinoma (HBV-related HCC) were obtained by using Genecards database. In addition, using the gene expression profiles of HBV-related HCC patients in GEO database and the genes with the greatest survival difference in GEPIA 2 database identified the potential targets of quercetin. In addition, the mechanism of potential genes was studied through GO, KEGG analysis, and PPI network. Using AUC and survival analysis to evaluate the diagnostic and prognostic value of cyclin-dependent kinase 1 (CDK1) and CCNB1. Finally, the effects of quercetin on proliferation of Hep3B and HepG2215 cells and the level of CDK1 and CCNB1 were verified in vitro. ELISA was used to measure the expression levels of hepatitis B surface antigen (HBsAg) and hepatitis B e antigen (HBeAg) after the intervention by quercetin for 24 h and 48 h in HepG2215 cell.

RESULTS

The first 10 key ingredients of SNRS were identified, and quercetin was the most key ingredient. The 101 potential quercetin targets were identified for the treatment of HBV-related HCC. GO and KEGG showed that 101 potential target enrichment in cancer and cell cycle regulation. By Venn analysis, CDK1 and CCNB1 were intersection targets, which could be used as potential targets for the action of quercetin on HBV-related HCC. Moreover, the expression of CDK1 and CCNB1 was highly expressed in the high-risk group, while the OS rate was low. The 1-year, 3-year and 5-year area under the curve (AUC) curves of CDK1 and CCNB1 were 0.724, 0.676, 0.622 and 0.745, 0.678, 0.634, respectively. Moreover, experimental results also showed that quercetin inhibited cell proliferation and reduced CDK1 expression in Hep3B and HepG2215 cells. The expressions of HBsAg and HBeAg in HepG2215 cell supernatant and cell gradually decreased with the increase of intervention time of quercetin and CDK1 inhibitor.

CONCLUSIONS

Quercetin is a key ingredient of anti-HBV-related HCC activity and inhibits HBV replication in SNRS by inhibiting CDK1.

Upregulation of lnc-FOXD2-AS1, CDC45, and CDK1 in patients with primary non-M3 AML is associated with a worse prognosis

Acute myeloid leukemia (AML) is a heterogeneous hematologic malignancy with an unfavorable outcome. The present research aimed to identify novel biological targets for AML diagnosis and treatment. In this study, we performed an in-silico method to identify antisense RNAs (AS-RNAs) and their related co-expression genes. GSE68172 was selected from the AML database of the Gene Expression Omnibus and compared using the GEO2R tool to find DEGs. Antisense RNAs were selected from all the genes that had significant expression and a survival plot was drawn for them in the GEPIA database, FOXD2-AS1 was chosen for further investigation based on predetermined criteria (logFC ≥|1| and P < 0.05) and its noteworthy association between elevated expression level and a marked reduction in the overall survival (OS) in patients diagnosed with AML. The GEPIA database was utilized to investigate FOXD2-AS1-related co-expression and similar genes. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis and gene ontology (GO) function analysis of the mentioned gene lists were performed using the DAVID database. The protein-protein interaction (PPI) network was then constructed using the STRING database. Hub genes were screened using Cytoscape software. Pearson correlation analysis was conducted using the GEPIA database to explore the relationship between FOXD2-AS1 and the hub genes. The transcription of the selected coding and non-coding genes, including FOXD2-AS1, CDC45, CDC20, CDK1, and CCNB1, was validated in 150 samples, including 100 primary AML non-M3 blood samples and 50 granulocyte colony stimulating factor (G-CSF)-mobilized healthy donors, using quantitative Real-Time PCR (qRT-PCR). qRT-PCR results displayed significant upregulation of lnc-FOXD2-AS1, CDC45, and CDK1 in primary AML non-M3 blood samples compared to healthy blood samples (P = 0.0032, P = 0.0078, and P = 0.0117, respectively). The expression levels of CDC20 and CCNB1 were not statistically different between the two sets of samples (P = 0.8315 and P = 0.2788, respectively). We identified that AML patients with upregulation of FOXD2-AS1, CDK1, and CDC45 had shorter overall survival (OS) and Relapse-free survival (RFS) compared those with low expression of FOXD2-AS1, CDK1, and CDC45. Furthermore, the receiver operating characteristic (ROC) curve showed the potential biomarkers of lnc -FOXD2-AS1, CDC45, and CDK1 in primary AML non-M3 blood samples. This research proposed that the dysregulation of lnc-FOXD2-AS1, CDC45, and CDK1 can contribute to both disease state and diagnosis as well as treatment. The present study proposes the future evolution of the functional role of lnc-FOXD2-AS1, CDC45, and CDK1 in AML development.

In Silico Mixed Ligand/Structure-Based Design of New CDK-1/PARP-1 Dual Inhibitors as Anti-Breast Cancer Agents

CDK-1 and PARP-1 play crucial roles in breast cancer progression. Compounds acting as CDK-1 and/or PARP-1 inhibitors can induct cell death in breast cancer with a selective synthetic lethality mechanism. A mixed treatment by means of CDK-1 and PARP-1 inhibitors resulted in radical breast cancer cell growth reduction. Inhibitors with a dual target mechanism of action could arrest cancer progression by simultaneously blocking the DNA repair mechanism and cell cycle, resulting in advantageous monotherapy. To this aim, in the present work, we identified compound 645656 with a significant affinity for both CDK-1 and PARP-1 by a mixed ligand- and structure-based virtual screening protocol. The Biotarget Predictor Tool was used at first in a Multitarget mode to filter the large National Cancer Institute (NCI) database. Then, hierarchical docking studies were performed to further screen the compounds and evaluate the ligands binding mode, whose putative dual-target mechanism of action was investigated through the correlation between the antiproliferative activity data and the target proteins' (CDK-1 and PARP-1) expression pattern. Finally, a Molecular Dynamics Simulation confirmed the high stability of the most effective selected compound 645656 in complex with both PARP-1 and CDK-1.

Biomedical association analysis between G2/M checkpoint genes and susceptibility to HIV-1 infection and AIDS progression from a northern chinese MSM population

BACKGROUND

MSM are at high risk of HIV infection. Previous studies have shown that the cell cycle regulation plays an important role in HIV-1 infection, especially at the G2/M checkpoint. ATR, Chk1, Cdc25C and CDK1 are key genes of G2/M checkpoint. However, the association between SNPs of these genes and susceptibility to HIV-1 infection and AIDS progression remains unknown.

METHODS

In this study, 42 tSNPs from the above four G2/M checkpoint genes were genotyped in 529 MSM and 529 control subjects from northern China to analyze this association.

RESULTS

The results showed that rs34660854 A and rs75368165 A in ATR gene and rs3756766 A in Cdc25C gene could increase the risk of HIV-1 infection (P = 0.049, OR = 1.234, 95% CI 1.001-1.521; P = 0.020, OR = 1.296, 95% CI 1.042-1.611; P = 0.011, OR = 1.392, 95% CI 1.080-1.794, respectively), while Chk1 rs10893405 (P = 0.029, OR = 1.629, 95% CI 1.051-2.523) were significantly associated with AIDS progression. Besides, rs34660854 (P = 0.019, OR = 1.364, 95% CI 1.052-1.769; P = 0.022, OR = 1.337, 95% CI 1.042-1.716, under Codominant model and Dominant model, respectively) and rs75368165 (P = 0.006, OR = 1.445, 95% CI = 1.114-1.899; P = 0.007, OR = 1.418, 95% CI 1.099-1.831, under Codominant model and Dominant model, respectively) in ATR gene, rs12576279 (P = 0.013, OR = 0.343, 95% CI 0.147-0.800; P = 0.048, OR = 0.437, 95% CI 0.192-0.991, under Codominant model and Dominant model, respectively) and rs540436 (P = 0.012, OR = 1.407, 95% CI 1.077-1.836; P = 0.021, OR = 1.359, 95% CI 1.048-1.762, under Codominant model and Dominant model, respectively) in Chk1 gene, rs3756766 (P = 0.013, OR = 1.455, 95% CI 1.083-1.954; P = 0.009, OR = 1.460, 95% CI 1.098-1.940, under Codominant model and Dominant model, respectively) in Cdc25C gene and rs139245206 (P = 0.022, OR = 5.011, 95% CI 1.267-19.816; P = 0.020, OR = 5.067, 95% CI 1.286-19.970, under Codominant model and Recessive model, respectively) in CDK1 gene were significantly associated with HIV-1 infection under different models.

CONCLUSIONS

We found that genetic variants of G2/M checkpoint genes had a molecular influence on the occurrence of HIV-1 infection and AIDS progression in a northern Chinese MSM population.

Comprehensive Multiomics Analysis Reveals Potential Diagnostic and Prognostic Biomarkers in Adrenal Cortical Carcinoma

Adrenal cortical carcinoma (ACC) is a severe malignant tumor with low early diagnosis rates and high mortality. In this study, we used a variety of bioinformatic analyses to find potential prognostic markers and therapeutic targets for ACC. Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) data sets were used to perform differential expressed analysis. WebGestalt was used to perform enrichment analysis, while String was used for protein-protein analysis. Our study first detected 28 up-regulation and 462 down-regulation differential expressed genes through the GEO and TCGA databases. Then, GO functional analysis, four pathway analyses (KEGG, REACTOME, PANTHER, and BIOCYC), and protein-protein interaction network were performed to identify these genes by WebGestalt tool and KOBAS website, as well as String database, respectively, and finalize 17 hub genes. After a series of analyses from GEPIA, including gene mutations, differential expression, and prognosis, we excluded one candidate unrelated to the prognosis of ACC and put the remaining genes into pathway analysis again. We screened out CCNB1 and NDC80 genes by three algorithms of Degree, MCC, and MNC. We subsequently performed genomic analysis using the TCGA and cBioPortal databases to better understand these two hub genes. Our data also showed that the CCNB1 and NDC80 genes might become ACC biomarkers for future clinical use.

Anti-malarial drug dihydroartemisinin downregulates the expression levels of CDK1 and CCNB1 in liver cancer

Liver cancer is the third leading cause of cancer-associated mortality worldwide. By the time liver cancer is diagnosed, it is already in the advanced stage. Therefore, novel therapeutic strategies need to be identified to improve the prognosis of patients with liver cancer. In the present study, the profiles of GSE84402, GSE19665 and GSE121248 were used to screen differentially expressed genes (DEGs). Subsequently, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses for DEGs were conducted using the Database for Annotation, Visualization and Integrated Discovery. The protein-protein interaction network was established to screen the hub genes associated with liver cancer. Additionally, the expression levels of hub genes were validated using the Gene Expression Profiling Interactive Analysis and Oncomine databases. In addition, the prognostic value of hub genes in patients with liver cancer was analyzed using Kaplan-Meier Plotter. It was demonstrated that 132 and 246 genes were upregulated and downregulated, respectively, in patients with liver cancer. Among these DEGs, 10 hub genes with high connected node values were identified, which were AURKA, BIRC5, BUB1B, CCNA2, CCNB1, CCNB2, CDC20, CDK1, DLGAP5 and MAD2L1. CDK1 and CCNB1 had the most connection nodes and the highest score and were therefore, the most significantly expressed. In addition, it was demonstrated that high expression levels of CDK1 and CCNB1 were associated with poor overall survival time of patients with liver cancer. Dihydroartemisinin (DHA) is a Food and Drug Administration-approved drug, which is derived from the traditional Chinese medicine Artemisia annua Linn. DHA inhibits cell proliferation in numerous cancer types, including liver cancer. In our previous study, it was revealed that DHA inhibited the proliferation of HepG2215 cells. In the present study, it was further demonstrated that DHA reduced the expression levels of CDK1 and CCNB1 in liver cancer. Overall, CDK1 and CCNB1 were the potential therapeutic targets of liver cancer, and DHA reduced the expression levels of CDK1 and CCNB1, and inhibited the proliferation of liver cancer cells.

CDK1 in Breast Cancer: Implications for Theranostic Potential

Breast cancer has been identified as one of the main cancer-related deaths among women during some last decades. Recent advances in the introduction of novel potent anti-cancer therapeutics in association with early detection methods led to a decrease in the mortality rate of breast cancer. However, the scenario of breast cancer is yet going on and further improvements in the current anti-cancer therapeutic approaches are needed. Several factors are present in the tumor microenvironment which help to cancer progression and suppression of anti-tumor responses. Targeting these cancer-promoting factors in the tumor microenvironment has been suggested as a potent immunotherapeutic approach for cancer therapy. Among the various tumorsupporting factors, Cyclin-Dependent Kinases (CDKs) are proposed as a novel promising target for cancer therapy. These factors in association with cyclins play a key role in cell cycle progression. Dysregulation of CDKs which leads to increased cell proliferation has been identified in various cancers, such as breast cancer. Accordingly, the development and use of CDK-inhibitors have been associated with encouraging results in the treatment of breast cancer. However, it is unknown that the inhibition of which CDK is the most effective strategy for breast cancer therapy. Since the selective blockage of CDK1 alone or in combination with other therapeutics has been associated with potent anti-cancer outcomes, it is suggested that CDK1 may be considered as the best CDK target for breast cancer therapy. In this review, we will discuss the role of CDK1 in breast cancer progression and treatment.

Expression patterns and prognostic values of the cyclin-dependent kinase 1 and cyclin A2 gene cluster in pancreatic adenocarcinoma

Objective

Pancreatic adenocarcinoma (PAAD) is one of the most lethal malignant tumors worldwide. Various studies based on cell lines, preclinical mouse models, and human tissue samples have shown that cell cycle-associated proteins are involved in the tumorigenesis and progression of PAAD.

Methods

Herein, we analyzed the relationships between CDK1 and CCNA2 gene expression and prognosis in patients with pancreatic cancer, using information from the Oncomine, cBioportal, Kaplan–Meier Plotter, and GEPIA databases.

Results

Expression levels of CDK1 and CCNA2 were significantly higher in PAAD compared with control tissues, and were associated with more advanced tumor stage. Survival analyses using the Kaplan–Meier Plotter database further confirmed that increased expression levels of CDK1 and CCNA2 were associated with a poor prognosis in patients with pancreatic cancer.

Conclusions

The results of this study suggest that CDK1 and CCNA2 may be potential therapeutic targets and prognostic biomarkers in patients with PAAD.

Identification of LINC00665-miR-let-7b-CCNA2 competing endogenous RNA network associated with prognosis of lung adenocarcinoma

Prognosis of patients with lung cancer remains extremely poor; thus, we sought to unearth novel competing endogenous RNA (ceRNA) networks associated with the prognosis of lung adenocarcinoma (LUAD). Aberrant mRNAs were identified from the intersection of three Gene Expression Omnibus (GEO) datasets. A protein–protein interaction (PPI) network was constructed, and miRNAs and long noncoding RNAs (lncRNAs) upstream of mRNAs were predicted. In the present study, 402 upregulated and 638 downregulated genes in lung cancer tissues were identified. Functional analysis showed significant enrichment of cancer pathways. In these top hub genes, 10 upregulated and 7 downregulated genes had substantial prognostic values in LUAD. Thirty-seven miRNAs were predicted to target 17 key genes, and only five miRNAs exhibited prognostic correlation. Through stepwise reverse prediction and validation from miRNA to lncRNA, four key lncRNAs were identified using expression and survival analysis. Ultimately, the co-expression analysis identified LINC00665-miR-let-7b-CCNA2 as the key ceRNA network associated with the prognosis of LUAD. We successfully constructed a novel ceRNA network wherein each component was significantly associated with the prognosis of LUAD. Hence, we propose that this network may provide key biomarkers or potential therapeutic targets for LUAD prognosis.

High-throughput sequencing-based analysis of gene expression of hepatitis B virus infection-associated human hepatocellular carcinoma

Hepatitis B virus (HBV) infection is a critical factor for the initiation and progression of hepatocellular carcinoma (HCC). Gene expression profiles for HBV-associated HCC may provide valuable insight for the diagnosis and treatment of this type of HCC. The present study aimed to screen the differential genes in human HCC tissues based on high-throughput sequencing and to predict the potential therapeutic targets. Total mRNA was extracted from human HCC tissues and paracancerous tissues and sequenced using the Hiseq4000 sequencing platform. Differential gene expressions were screened and further analyzed using quantitative PCR and immunohistochemistry. A total of 2,386 differentially expressed genes were screened. Of these, 1119 were upregulated and 1,267 were downregulated in paracancerous tissues compared with tumor tissues. Gene Ontology term analysis demonstrated that differentially expressed genes were involved in carboxylic acid catabolism, monocarboxylic acid metabolic processes and α-amino acid metabolic processes. Molecular functional analysis revealed that the differentially expressed genes functioned in oxidoreductase activity, for example acting on CH-OH group of donors and permitting identical protein binding, anion binding, coenzyme binding and monocarxylic acid transporter activity. The Kyoto Encyclopedia of Genes and Genomes analysis reported that the differentially expressed genes were primarily concentrated in 20 signaling pathways, such as valine, leucine and leucine degradation, retinol metabolism and the cell cycle. Differential expression of proteins regulating the cell cycle, including stratifin, cyclin B1 and cyclin-dependent kinase 1, were significantly higher in tumor tissue compared with those in paracancerous tissue at both the mRNA and protein levels. These results were consistent with those obtained from high-throughput sequencing, indicating the reliability of the high-throughput sequencing. Together, these results identified differentially expressed genes and predicted the subsequent signaling pathways, which may be involved in the occurrence and development of HCC. Therefore, the present study may provide novel implications in the therapeutic and diagnosis of HCC.

Hybrid Stem Cell States: Insights Into the Relationship Between Mammary Development and Breast Cancer Using Single-Cell Transcriptomics

Similarities between stem cells and cancer cells have implicated mammary stem cells in breast carcinogenesis. Recent evidence suggests that normal breast stem cells exist in multiple phenotypic states: epithelial, mesenchymal, and hybrid epithelial/mesenchymal (E/M). Hybrid E/M cells in particular have been implicated in breast cancer metastasis and poor prognosis. Mounting evidence also suggests that stem cell phenotypes change throughout the life course, for example, through embryonic development and pregnancy. The goal of this study was to use single cell RNA-sequencing to quantify cell state distributions of the normal mammary (NM) gland throughout developmental stages and when perturbed into a stem-like state in vitro using conditional reprogramming (CR). Using machine learning based dataset alignment, we integrate multiple mammary gland single cell RNA-seq datasets from human and mouse, along with bulk RNA-seq data from breast tumors in the Cancer Genome Atlas (TCGA), to interrogate hybrid stem cell states in the normal mammary gland and cancer. CR of human mammary cells induces an expanded stem cell state, characterized by increased expression of embryonic stem cell associated genes. Alignment to a mouse single-cell transcriptome atlas spanning mammary gland development from in utero to adulthood revealed that NM cells align to adult mouse cells and CR cells align across the pseudotime trajectory with a stem-like population aligning to the embryonic mouse cells. Three hybrid populations emerge after CR that are rare in NM: KRT18+/KRT14+ (hybrid luminal/basal), EPCAM+/VIM+ (hybrid E/M), and a quadruple positive population, expressing all four markers. Pseudotime analysis and alignment to the mouse developmental trajectory revealed that E/M hybrids are the most developmentally immature. Analyses of single cell mouse mammary RNA-seq throughout pregnancy show that during gestation, there is an enrichment of hybrid E/M cells, suggesting that these cells play an important role in mammary morphogenesis during lactation. Finally, pseudotime analysis and alignment of TCGA breast cancer expression data revealed that breast cancer subtypes express distinct developmental signatures, with basal tumors representing the most “developmentally immature” phenotype. These results highlight phenotypic plasticity of normal mammary stem cells and provide insight into the relationship between hybrid cell populations, stemness, and cancer.

Upregulated cyclins may be novel genes for triple-negative breast cancer based on bioinformatic analysis

BACKGROUND

Triple-negative breast cancer (TNBC) is one of the leading causes of death among females around the world. However, the molecular mechanism of the disease among TNBC patients remains to be further studied.

METHODS

In our study, four microarray data and two high throughput sequencing data were acquired from the GEO database, and the differentially expressed genes (DEGs) between TNBC and normal tissues had been analyzed. Analysis of functional enrichment and pathway enrichment of DEGs was conducted by the Funrich software, and protein-protein interaction (PPI) network gained from the STRING, and hub genes were confirmed by the Cytoscape. Kaplan-Meier plotter (KM plotter) online dataset had been used to analyze DEGs of overall survival (OS), and progression-free survival (PFS).

RESULTS

In total, 1638 DEGs were gained in our study covering 984 upregulated and 654 downregulated genes. Moreover, a PPI network was constructed, and cyclin-dependent kinase 1 (CDK1), cyclin B1 (CCNB1), and cyclin A2 (CCNA2) were found as top genes with higher node degrees. CDK1, CCNA2, and CCNB1were obviously enriched in the cell cycle. The top upregulated genes including CDK1, CCNB1, CCNA2, and PLK1 were overexpressed in TNBC, and correlated with worse OS in breast cancer. High expression of CCNB1 was correlated with worse PFS in TNBC (HR = 1.42, 95% CI: 1.04-1.94, P = 0.028). Besides, there was a correlation between CCNB1 and CDK1 in TNBC, as well as between CCNA2 and CDK1 (r = 0.804, P < 0.001; r = 0.577, P < 0.001, respectively).

CONCLUSION

Our results suggest that cyclin CDK1, CCNB1, and CCNA2 are overexpressed in TNBC and they could act as novel biomarkers for the diagnosis and treatment of TNBC.

CDK1, CCNB1, CDC20, BUB1, MAD2L1, MCM3, BUB1B, MCM2, and RFC4 May Be Potential Therapeutic Targets for Hepatocellular Carcinoma Using Integrated Bioinformatic Analysis

Hepatocellular carcinoma (HCC) is a malignant tumor with high mortality. The abnormal expression of genes is significantly related to the occurrence of HCC. The aim of this study was to explore the differentially expressed genes (DEGs) of HCC and to provide bioinformatics basis for the occurrence, prevention and treatment of HCC. The DEGs of HCC and normal tissues in GSE102079, GSE121248, GSE84402 and GSE60502 were obtained using R language. The GO function analysis and KEGG pathway enrichment analysis of DEGs were carried out using the DAVID database. Then, the protein–protein interaction (PPI) network was constructed using the STRING database. Hub genes were screened using Cytoscape software and verified using the GEPIA, UALCAN, and Oncomine database. We used HPA database to exhibit the differences in protein level of hub genes and used LinkedOmics to reveal the relationship between candidate genes and tumor clinical features. Finally, we obtained transcription factor (TF) of hub genes using NetworkAnalyst online tool. A total of 591 overlapping up-regulated genes were identified. These genes were related to cell cycle, DNA replication, pyrimidine metabolism, and p53 signaling pathway. Additionally, the GEPIA database showed that the CDK1, CCNB1, CDC20, BUB1, MAD2L1, MCM3, BUB1B, MCM2, and RFC4 were associated with the poor survival of HCC patients. UALCAN, Oncomine, and HPA databases and qRT-PCR confirmed that these genes were highly expressed in HCC tissues. LinkedOmics database indicated these genes were correlated with overall survival, pathologic stage, pathology T stage, race, and the age of onset. TF analysis showed that MYBL2, KDM5B, MYC, SOX2, and E2F4 were regulators to these nine hub genes. Overexpression of CDK1, CCNB1, CDC20, BUB1, MAD2L1, MCM3, BUB1B, MCM2, and RFC4 in tumor tissues predicted poor survival in HCC. They may be potential therapeutic targets for HCC.

Serum tRNA-derived fragments (tRFs) as potential candidates for diagnosis of nontriple negative breast cancer

Breast cancer has become the most common cancer in women, and nontriple negative breast cancer (non-TNBC) accounts for 80-90% of all invasive breast cancers. Early detection, diagnosis, and treatment are considered key to a successful cure. Conventionally, breast imaging and needle core biopsy are used for detection and monitoring. However, small variations in volume might be ignored in imaging, and traditional biopsies are spatially and temporally limited, leading to a significant delay in cancer detection and thus prompting renewed focus on early and accurate diagnosis. In this article, we investigated whether there is an accurate molecule in peripheral blood that can help diagnose breast cancer. Similar to microRNAs, tRNA-derived fragments (tRFs) have been reported to be involved in many pathological processes in breast cancer, but whether they can serve as candidate biomarkers for breast cancer remains unclear. Using high-throughput sequencing technology, we identified 4,021 differentially expressed tRFs in normal and breast cancer cell lines, and eight tRFs were selected to establish a signature as a predictive biomarker of non-TNBC. Furthermore, quantitative reverse-transcriptase polymerase chain reaction was performed to verify the expression of the signature and analyze the correlation between dysregulated tRFs and breast cancer. The results indicated that tDR-7816, tDR-5334, and tDR-4733 might be promising biomarkers. Through further bioinformatics analysis, we predicted that tDR-7816 influences the xenobiotic metabolic processes that support the oncogenesis of breast cancer. In summary, our results provide a rationale for using circulating tDR-7816 expression as a novel potential biomarker for the diagnosis of patients with early non-TNBC.

Integrated bioinformatics analysis to identify 15 hub genes in breast cancer

The aim of the present study was to identify the hub genes and provide insight into the tumorigenesis and development of breast cancer. To examine the hub genes in breast cancer, integrated bioinformatics analysis was performed. Gene expression profiles were obtained from the Gene Expression Omnibus (GEO) database and the differentially expressed genes (DEGs) were identified using the ‘limma’ package in R. Gene Ontology enrichment analysis and Kyoto Encyclopedia of Genes and Genomes pathway analysis was used to determine the functional annotations and potential pathways of the DEGs. Subsequently, a protein-protein interaction network analysis and weighted correlation network analysis (WGCNA) were conducted to identify hub genes. To confirm the reliability of the identified hub genes, RNA gene expression profiles were obtained from The Cancer Genome Atlas (TCGA)-breast cancer database, and WGCNA was used to screen for genes that were markedly correlated with breast cancer. By combining the results from the GEO and TCGA datasets, 15 hub genes were identified to be associated with breast cancer pathophysiology. Overall survival analysis was performed to examine the association between the expression of hub genes and the overall survival time of patients with breast cancer. Higher expression of all hub genes was associated with significantly shorter overall survival in patients with breast cancer compared with patients with lower levels of expression of the respective gene.

Overexpression of BUB1B, CCNA2, CDC20, and CDK1 in tumor tissues predicts poor survival in pancreatic ductal adenocarcinoma

Overexpressed genes in tumors usually contributed to aggressiveness in pancreatic ductal adenocarcinoma (PDAC). Using Gene Expression Omnibus (GEO) profiles including GSE46234, GSE71989, and GSE107610, we detected overexpressed genes in tumors with R program, which were enriched by Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene ontology (GO), and Reactome pathway databases. Then, we performed a survival analysis of enriched genes based on TCGA profile. Our results revealed that high BUB1B, CCNA2, CDC20, and CDK1 expression in tumors was significantly associated with worse overall survival (OS) (Log rank P=0.00338, P=0.0447, P=0.00965, and P=0.00479, respectively), which was validated using a Kaplan–Meier plotter with a median cutoff (Log rank P=0.028, P=0.0035, P=0.039, and P=0.0033, respectively). Moreover, overexpression of BUB1B, CCNA2, CDC20, and CDK1 in tumor tissues was significantly associated with disease-free survival (DFS) in PDAC patients (Log rank P=0.00565, P=0.0357, P=0.00104, and P=0.00121, respectively). BUB1B, CCNA2, CDC20, and CDK1 were significantly overexpressed in deceased PDAC patients (all P<0.01) and in patients with recurrence/disease progression (all P<0.05). In addition, PDAC patients with neoplasms of histologic grade G3-4 had significantly higher BUB1B, CCNA2 and CDC20 levels (all P<0.05). In conclusion, the up-regulation of BUB1B, CCNA2, CDC20, CDK1, and WEE1 in tumor tissues are associated with worse OS and DFS in PDAC and is correlated with advanced tumor stage and tumor development.

Identification of key candidate genes and biological pathways in bladder cancer

Background

Bladder cancer is a malignant tumor in the urinary system with high mortality and recurrence rates. However, the causes and recurrence mechanism of bladder cancer are not fully understood. In this study, we used integrated bioinformatics to screen for key genes associated with the development of bladder cancer and reveal their potential molecular mechanisms.

Methods

The GSE7476, GSE13507, GSE37815 and GSE65635 expression profiles were downloaded from the Gene Expression Omnibus database, and these datasets contain 304 tissue samples, including 81 normal bladder tissue samples and 223 bladder cancer samples. The RobustRankAggreg (RRA) method was utilized to integrate and analyze the four datasets to obtain integrated differentially expressed genes (DEGs), and the gene ontology (GO) functional annotation and Kyoto encyclopedia of genes and genomes (KEGG) pathway analysis were performed. Protein-protein interaction (PPI) network and module analyses were performed using Cytoscape software. The OncoLnc online tool was utilized to analyze the relationship between the expression of hub genes and the prognosis of bladder cancer.

Results

In total, 343 DEGs, including 111 upregulated and 232 downregulated genes, were identified from the four datasets. GO analysis showed that the upregulated genes were mainly involved in mitotic nuclear division, the spindle and protein binding. The downregulated genes were mainly involved in cell adhesion, extracellular exosomes and calcium ion binding. The top five enriched pathways obtained in the KEGG pathway analysis were focal adhesion (FA), PI3K-Akt signaling pathway, proteoglycans in cancer, extracellular matrix (ECM)-receptor interaction and vascular smooth muscle contraction. The top 10 hub genes identified from the PPI network were vascular endothelial growth factor A (VEGFA), TOP2A, CCNB1, Cell division cycle 20 (CDC20), aurora kinase B, ACTA2, Aurora kinase A, UBE2C, CEP55 and CCNB2. Survival analysis revealed that the expression levels of ACTA2, CCNB1, CDC20 and VEGFA were related to the prognosis of patients with bladder cancer. In addition, a KEGG pathway analysis of the top 2 modules identified from the PPI network revealed that Module 1 mainly involved the cell cycle and oocyte meiosis, while the analysis in Module 2 mainly involved the complement and coagulation cascades, vascular smooth muscle contraction and FA.

Conclusions

This study identified key genes and pathways in bladder cancer, which will improve our understanding of the molecular mechanisms underlying the development and progression of bladder cancer. These key genes might be potential therapeutic targets and biomarkers for the treatment of bladder cancer.

Genetic polymorphisms in CDH1 are associated with endometrial carcinoma susceptibility among Chinese Han women

The cadherin 1 (CDH1) gene plays critical roles in the epithelial-mesenchymal transition process, potentially offering us a glimpse into the development of endometrial carcinoma (EC). The present study aimed to identify whether genetic variants in CDH1 affect EC susceptibility in Chinese Han women, using a strategy combining haplotype-tagging single nucleotide polymorphisms (htSNPs) association analysis with fine-scale mapping. A total of 9 htSNPs in CDH1 were genotyped among 516 cases and 706 age-matched cancer-free controls. Logistic regression analyses revealed 3 htSNPs (rs17715799, rs6499199 and rs13689) to be associated with increased EC risk and 3 htSNPs (rs12185157, rs10431923 and rs4783689) with decreased EC risk. Furthermore, 14 newly imputed SNPs of CDH1 were identified to be associated with EC risk (P<0.05) using genotype imputation analysis. Notably, multivariate logistic analysis demonstrated that rs13689, rs10431923 and rs10431924 could affect EC susceptibility independently (P≤0.001). Subsequent Generalized Multifactor Dimensionality Reduction analysis revealed several best fitting models for predicting EC risk, including SNP-SNP interactions among rs7100190, rs12185157, rs10431923, rs7186053, rs6499199, rs4783689, rs13689, rs6499197 and rs10431924, and SNP-environment interactions between related SNPs and number of childbirth. Moreover, functional annotations suggest that the majority of these susceptible variants may carry potential biological functions that affect certain gene regulatory elements. In summary, this study suggested that the genetic polymorphisms of CDH1 were indeed associated with EC susceptibility on several levels. If further additional functional studies could verify these findings, these genetic variants may serve as future personalized markers for the early prediction of endometrial cancer in Chinese Han women.

Upregulation of BUB1B, CCNB1, CDC7, CDC20, and MCM3 in Tumor Tissues Predicted Worse Overall Survival and Disease-Free Survival in Hepatocellular Carcinoma Patients

OBJECTIVE

To evaluate the association between upregulated differentially expressed genes (DEGs) and the outcomes of patients with hepatocellular carcinoma (HCC).

METHODS

Using Gene Expression Omnibus (GEO) datasets including GSE45436, GSE55092, GSE60502, GSE84402, and GSE17548, we detected upregulated DEGs in tumors. KEGG, GO, and Reactome enrichment analysis of the DEGs was conducted to clarify their function. The impact of the upregulated DEGs on patients' survival was analyzed based on TCGA profile.

RESULTS

161 shared upregulated DEGs were identified among GSE45436, GSE55092, GSE60502, and GSE84402 profiles. Cell cycle was the shared pathway/biological process in the gene sets investigation among databases of KEGG, GO, and Reactome. After being validated in GSE17548, 13 genes including BUB1B, CCNA2, CCNB1, CCNE2, CDC20, CDC6, CDC7, CDK1, CDK4, CDKN2A, CHEK1, MAD2L1, and MCM3 in cell cycle pathway were shared in the three databases for enrichment. The expression of BUB1B, CCNB1, CDC7, CDC20, and MCM3 was upregulated in HCC tissues when compared with adjacent normal tissues in 6.67%, 7.5%, 8.06%, 5.56%, and 9.72% of HCC patients, respectively. Overexpression of BUB1B, CCNB1, CDC7, CDC20, and MCM3 in HCC tissues accounted for poorer overall survival (OS) and disease-free survival (DFS) in HCC patients (all log rank P < 0.05). BUB1B, CCNB1, CDC7, CDC20, and MCM3 were all overexpressed in HCC patients with neoplasm histologic grade G3-4 compared to those with G1-2 (all P < 0.05). BUB1B, CCNB1, and CDC20 were significantly upregulated in HCC patients with vascular invasion (all P < 0.05). Additionally, levels of BUB1B, CCNB1, CDC7, and CDC20 were significantly higher in HCC patients deceased, recurred, or progressed (all P < 0.05).

CONCLUSION

Correlated with advanced histologic grade and/or vascular invasion, upregulation of BUB1B, CCNB1, CDC7, CDC20, and MCM3 in HCC tissues predicted worse OS and DFS in HCC patients. These genes could be novel therapeutic targets for HCC treatment.

Polymorphisms of CCNB1 Associated With the Clinical Outcomes of Platinum-Based Chemotherapy in Chinese NSCLC Patients

As a crucial cell cycle regulator and G2/M phase promotor, CCNB1 played an essential role in progression of chemotherapy related cell death. Platinum-based chemotherapy is still the first-line chemotherapy regimen for most advanced NSCLC patients. We aim to investigate the correlation of CCNB1 polymorphisms to the efficiency of platinum-based chemotherapy in Chinese advanced NSCLC patients. We enrolled 972 patients with advanced NSCLC, and extracted DNA from their peripheral blood for genotyping CCNB1 four tagSNPs which selected from the Hapmap database. We analyzed the association of CCNB1 four tagSNPs with efficiency of platinum-based chemotherapy. We found that rs2069429 and rs2069433 of CCNB1 were associated with the OS of advanced NSCLC patients. Patients with GG genotype of rs2069429 had longer OS than non-GG patients (HR=0.81, 95%CI=0.68-0.95, p=0.009); and patients with AA genotype of rs2069433 had longer OS than non-AA patients (HR=0.78, 95%CI=0.61-0.98, p=0.036). And the haplotype GAAA of CCNB1 was a putative factor in subgroup patients with clinical stage IV. The association of CCNB1 polymorphisms and toxicities after platinum-based chemotherapy was assessed. Rs2069433 and rs350104 were related with gastrointestinal toxicity of platinum-based chemotherapy. The patients with GG genotype of rs2069433 (p=0.013) and/or non-GG genotype of rs350104 (p=0.042) may have a severe gastrointestinal toxicity after chemotherapy, and then clinician may can reduce the dosage of chemotherapy agents to avoid sever toxicities in these patients. In summary, CCNB1 polymorphisms may contribute to the clinical efficiency of platinum-based chemotherapy in advanced NSCLC patients, and it is helpful for the personalized treatment.

Dipalmitoylphosphatidic acid inhibits tumor growth in triple-negative breast cancer

Triple-negative breast cancer (TNBC) is a subtype of breast cancer with a poor prognosis, accounting for approximately 12-24% of breast cancer cases. Accumulating evidence has indicated that there is no effective targeted therapy available for TNBC. Dipalmitoylphosphatidic acid (DPPA) is a bioactive phospholipid. However, the function of DPPA in the growth of TNBC has not yet been studied. In this study, we employed TNBC cells and a subcutaneous tumor model to elucidate the possible effect of DPPA on tumor growth in TNBC. We showed that DPPA significantly inhibited tumor growth in the mouse subcutaneous tumor model and suppressed cell proliferation and angiogenesis in TNBC tumor tissues. This inhibition was mediated partly by suppressing the expression of cyclin B1 (CCNB1), which directly promoted the accumulation of cells in the G2 phase and arrested cell cycle progression in human TNBC. In addition, the inhibition of tumor growth by DPPA may also be mediated by the suppression of tumor angiogenesis in TNBC. This work provides initial evidence that DPPA might be vital as an anti-tumor drug to treat TNBC.

Myomir dysregulation and reactive oxygen species in aged human satellite cells

Satellite cells that reside on the myofibre surface are crucial for the muscle homeostasis and regeneration. Aging goes along with a less effective regeneration of skeletal muscle tissue mainly due to the decreased myogenic capability of satellite cells. This phenomenon impedes proper maintenance and contributes to the age-associated decline in muscle mass, known as sarcopenia. The myogenic potential impairment does not depend on a reduced myogenic cell number, but mainly on their difficulty to complete a differentiation program. The unbalanced production of reactive oxygen species in elderly people could be responsible for skeletal muscle impairments. microRNAs are conserved post-transcriptional regulators implicated in numerous biological processes including adult myogenesis. Here, we measure the ROS level and analyze myomiR (miR-1, miR-133b and miR-206) expression in human myogenic precursors obtained from Vastus lateralis of elderly and young subjects to provide the molecular signature responsible for the differentiation impairment of elderly activated satellite cells.

Association of Genetic Polymorphisms in CDH1 and CTNNB1 with Breast Cancer Susceptibility and Patients' Prognosis among Chinese Han Women

This study aims to investigate whether the germline variants in CDH1 and CTNNB1 would affect breast cancer susceptibility and patients’ prognosis among Chinese Han women using a haplotype-based association analysis. We genotyped 12 haplotype-tagging single nucleotide polymorphisms (htSNPs) in CDH1 and CTNNB1 among 1,160 BC cases and 1,336 age-matched cancer-free controls using the TaqMan^® Genotyping Assay. For association analyses of germline variants with breast cancer susceptibility, the results showed that rs7200690, rs7198799, rs17715799, rs13689 and diplotype CGC/TGC (rs7200690 + rs12185157 + rs7198799) in CDH1 as well as rs2293303 in CTNNB1 were associated with increased breast cancer risk. In addition, the Generalized Multifactor Dimensionality Reduction (GMDR) and logistic regression analysis predicted an interaction on breast cancer risk between rs17715799 and rs13689 as well as rs13689 and menarche-FFTP (First Full-Term Pregnancy) interval. For survival analyses, the results demonstrated that the minor allele homozygotes of rs13689 and haplotype TGC in CDH1 were linked with unfavorable event-free survival of breast cancer, whereas, rs4783689 of CDH1 showed the opposite effect under dominant model. Notably, the stratified analysis revealed that rs7186053 was associated with favorable event-free survival among patients with estrogen receptor (ER)-positive, progesterone receptor (PR)-positive or lymph node metastasis negative patients. Moreover, rs7200690 and rs7198799 in CDH1 as well as rs4533622 in CTNNB1 were associated with worse event-free survival among patients with clinical stage 0-I tumors. This study indicated that the genetic polymorphisms of CDH1 and CTNNB1 were associated with breast cancer susceptibility and patients’ prognosis.

Effects of β-catenin on differentially expressed genes in multiple myeloma

This study aimed to identify the differentially expressed genes after silencing of β-catenin in multiple myeloma transduced with β-catenin shRNA. The DNA microarray dataset GSE17385 was downloaded from Gene Expression Omnibus, including 3 samples of MM1.S (human multiple myeloma cell lines) cells transduced with control shRNA and 3 samples of MM1.S cells transduced with β-catenin shRNA. Then the differentially expressed genes (DEGs) were screened by using Limma. Their underlying functions were analyzed by employing Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses. Moreover, DEGs annotation was conducted based on the databases of tumor associated genes, tumor suppressed genes and the transcriptional regulation from patterns to profiles. Furthermore, the protein-protein interaction (PPI) relationship was obtained from STRING and the protein-protein interaction network and the functional modules were visualized by Cytoscape. Then, the pathway enrichment for the DEGs in the functional module was performed. A total of 301 DEGs, including 124 up-regulated and 117 down-regulated DEGs, were screened. Functional enrichment showed that CCNB1 and CDK1 were significantly related to the function of cell proliferation. FOS and JUN were related to innate immune response-activating signal transduction. Pathway enrichment analysis indicated that CCNB1 and CDK1 were most significantly enriched in the pathway of cell cycle. Besides, FOS and JUN were significantly enriched in the Toll-like receptor signaling pathway. FOXM1 was identified as a transcription factor. Moreover, there existed interactions among CCNB1, FOXM1 and CDK1 in PPI network. The expression of FOS, JUN, CCNB1, FOXM1 and CDK1 may be affected by β-catenin in multiple myeloma.

Identification of differently expressed genes with specific SNP Loci for breast cancer by the integration of SNP and gene expression profiling analyses

This study aims to explore the relationship between gene polymorphism and breast cancer, and to screen DEGs (differentially expressed genes) with SNPs (single nucleotide polymorphisms) related to breast cancer. The SNPs of 17 patients and the preprocessed SNP profiling GSE 32258 (38 cases of normal breast cells) were combined to identify their correlation with breast cancer using chi-square test. The gene expression profiling batch8_9 (38 cases of patients and 8 cases of normal tissue) was preprocessed with limma package, and the DEGs were filtered out. Then fisher's method was applied to integrate DEGs and SNPs associated with breast cancer. With NetBox software, TRED (Transcriptional Regulatory Element Database) and UCSC (University of California Santa Cruz) database, genes-associated network and transcriptional regulatory network were constructed using cytoscape software. Further, GO (Gene Ontology) and KEGG analyses were performed for genes in the networks by using siggenes. In total, 332 DEGs were identified. There were 160 breast cancer-related SNPs related to 106 genes of gene expression profiling (19 were significant DEGs). Finally, 11co-correlated DEGs were selected. In genes-associated network, 9 significant DEGs were correlated to 23 LINKER genes while, in transcriptional regulatory network, E2F1 had regulatory relationships with 7 DEGs including MTUS1, CD44, CCNB1 and CCND2. KRAS with SNP locus of rs1137282 was involved in 35 KEGG pathways. The genes of MTUS1, CD44, CCNB1, CCND2 and KRAS with specific SNP loci may be used as biomarkers for diagnosis of breast cancer. Besides, E2F1 was recognized as the transcription factor of 7 DEGs including MTUS1, CD44, CCNB1 and CCND2.

Refinement of breast cancer risk prediction with concordant leading edge subsets from prognostic gene signatures

Several prognostic signatures have been identified for breast cancer. However, these signatures vary extensively in their gene compositions, and the poor concordance of the risk groups defined by the prognostic signatures hinders their clinical applicability. Breast cancer risk prediction was refined with a novel approach to finding concordant genes from leading edge analysis of prognostic signatures. Each signature was split into two gene sets, which contained either up-regulated or down-regulated genes, and leading edge analysis was performed within each array study for all up-/down-regulated gene sets of the same signature from all training datasets. Consensus of leading edge subsets among all training microarrays was used to synthesize a predictive model, which was then tested in independent studies by partial least squares regression. Only a small portion of six prognostic signatures (Amsterdam, Rotterdam, Genomic Grade Index, Recurrence Score, and Hu306 and PAM50 of intrinsic subtypes) was significantly enriched in the leading edge analysis in five training datasets (n = 2,380), and that the concordant leading edge subsets (43 genes) could identify the core signature genes that account for the enrichment signals providing prognostic power across all assayed samples. The proposed concordant leading edge algorithm was able to discriminate high-risk from low-risk patients in terms of relapse-free or distant metastasis-free survival in all training samples (hazard ratios: 1.84-2.20) and in three out of four independent studies (hazard ratios: 3.91-8.31). In some studies, the concordant leading edge subset remained a significant prognostic factor independent of clinical ER, HER2, and lymph node status. The present study provides a statistical framework for identifying core consensus across microarray studies with leading edge analysis, and a breast cancer risk predictive model was established.