CENPE expression is associated with its DNA methylation status in esophageal adenocarcinoma and independently predicts unfavorable overall survival

CENPE is a diagnostic and prognostic biomarker for cervical cancer

Cervical squamous cell carcinoma (CESC) is a common cancer in women. Despite advancements in early diagnosis through high-risk human papillomavirus (HPV) screening, challenges remain in predicting and treating the disease. Hence, the identification of novel biomarkers for prognosis and therapeutic targets is crucial. CENPE, a microtubule-end directed motor protein that accumulates during the G2 phase, is recognized for its involvement in promoting cancer growth and progression. However, its specific role in CESC remains unclear. This research investigated the expression of CENPE in CESC utilizing data from The Cancer Genome Atlas (TCGA), which was further validated through gene expression profiles, the Human Protein Atlas (HPA), and clinical data. The study utilized Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Set Enrichment Analysis (GSEA), and immune infiltration analysis to elucidate the role of CENPE in CESC. Additionally, Protein-protein interaction (PPI) networks and competing endogenous RNA (CeRNA) networks involving CENPE and its differentially expressed genes were established. Furthermore, Kaplan-Meier survival analysis was conducted to evaluate the impact of CENPE on patient prognosis. Our study revealed an upregulation of CENPE expression in cervical cancer tissues, which promotes the progression of CESC through IL-6-mediated PI3K-Akt and MAPK signaling pathways. The significant associations with ACNG3, LY6H, and SLC6A7 suggest that CENPE may play a role in tumor growth and metastasis, potentially involving the nervous system. Moreover, the correlations with ARIH1, KDM1A, KDM5B, and NSD3 indicate that CENPE could be a promising target for drug development. Our analysis of the ROC curve demonstrated a high diagnostic accuracy of CENPE in CESC (AUC: 0.997, CI: 0.990-1.000). Subgroup analysis highlighted substantial effects in patients under 50 years old, those with a height under 160 cm, individuals in peri- and post-menopausal stages, and patients in clinical stages 1 and 4. Additionally, COX regression analysis indicated that older age, lower BMI, and higher CENPE expression are associated with decreased 1-year, 3-year, and 5-year survival rates. In conclusion, CENPE emerges as a crucial factor in the initiation and advancement of cervical cancer, showing potential as a novel target for therapeutic interventions.

Analyzing the expression and clinical significance of CENPE in gastric cancer

BACKGROUND

Gastric cancer (GC) is a prevalent type of malignant gastrointestinal tumor. Many studies have shown that CENPE acts as an oncogene in some cancers. However, its expression level and clinical value in GC are not clear.

METHODS

Obtaining clinical data information on gastric adenocarcinoma from TCGA and GEO databases. The gene expression profiling interaction analysis (GEPIA) was used to evaluate the relationship between prognosis and CENPE expression in gastric cancer patients. Utilizing the UALCAN platform, the correlation between CENPE expression and clinical parameters was examined. Functions and signaling pathways of CENPE were analyzed using the Gene Ontology (GO), the Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA). The association between immunological infiltrating cells and CENPE expression was examined using TIMER2.0. Validation was performed by real-time quantitative PCR (qPT-PCR) and immunohistochemical analysis.

RESULTS

According to the analysis of the GEPIA database, the expression of CENPE is increased in gastric cancer tissues compared to normal tissues. It was also found to have an important relationship with the prognosis of the patient (p<0.05). The prognosis was worse and overall survival was lower in individuals with increased expression of CENPE. In line with the findings of the GEPIA, real-time fluorescence quantitative PCR (qPT-PCR) confirmed that CENPE was overexpressed in gastric cancer cells. Furthermore, It was discovered that H. pylori infection status and tumor grade were related to CENPE expression. Enrichment analysis revealed that CENPE expression was linked to multiple biological functions and tumor-associated pathways. CENPE expression also correlated with immune-infiltrating cells in the gastric cancer microenvironment and was positively connected to NK cells and mast cells. According to immunohistochemical examination, paracancerous tissues had minimal expression of CENPE, but gastric cancer showed significant expression of the protein.

CONCLUSIONS

According to our findings, CENPE is substantially expressed in GC and may perhaps contribute to its growth. CENPE might be a target for gastric cancer therapy and a predictor of a bad prognosis.

Kinesin-7 CENP-E in tumorigenesis: Chromosome instability, spindle assembly checkpoint, and applications

Kinesin motors are a large family of molecular motors that walk along microtubules to fulfill many roles in intracellular transport, microtubule organization, and chromosome alignment. Kinesin-7 CENP-E (Centromere protein E) is a chromosome scaffold-associated protein that is located in the corona layer of centromeres, which participates in kinetochore-microtubule attachment, chromosome alignment, and spindle assembly checkpoint. Over the past 3 decades, CENP-E has attracted great interest as a promising new mitotic target for cancer therapy and drug development. In this review, we describe expression patterns of CENP-E in multiple tumors and highlight the functions of CENP-E in cancer cell proliferation. We summarize recent advances in structural domains, roles, and functions of CENP-E in cell division. Notably, we describe the dual functions of CENP-E in inhibiting and promoting tumorigenesis. We summarize the mechanisms by which CENP-E affects tumorigenesis through chromosome instability and spindle assembly checkpoints. Finally, we overview and summarize the CENP-E-specific inhibitors, mechanisms of drug resistances and their applications.

The function and immune role of cuproptosis associated hub gene in Barrett's esophagus and esophageal adenocarcinoma

Barrett's esophagus (BE) is a precancerous lesion of esophageal adenocarcinoma (EAC), with approximately 3-5% of patients developing EAC. Cuproptosis is a kind of programmed cell death phenomenon discovered in recent years, which is related to the occurrence and development of many diseases. However, its role in BE and EAC is not fully understood. We used single sample Gene Set Enrichment Analysis (ssGSEA) for differential analysis of BE in the database, followed by enrichment analysis of Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Ontology (GO) and GSEA, Protein-Protein Interaction (PPI), Weighted Gene Co-expression Network Analysis (WGCNA), Receiver Operating Characteristic Curve (ROC) and finally Quantitative Real Time Polymerase Chain Reaction (qRT-PCR) and immunohistochemistry (IHC) of clinical tissues. Two hub genes can be obtained by intersection of the results obtained from the cuproptosis signal analysis based on BE. The ROC curves of these two genes predicted EAC, and the Area Under the Curve (AUC) values could reach 0.950 and 0.946, respectively. The mRNA and protein levels of Centrosome associated protein E (CENPE) and Shc SH2 domain binding protein 1 (SHCBP1) were significantly increased in clinical EAC tissues. When they were grouped by protein expression levels, high expression of CENPE or SHCBP1 had a poor prognosis. The CENPE and SHCBP1 associated with cuproptosis may be a factor promoting the development of BE into EAC which associated with the regulation of NK cells and T cells.

CENPE and LDHA were potential prognostic biomarkers of chromophobe renal cell carcinoma

BACKGROUND

Most sarcomatoid differentiated renal cell carcinoma was differentiated from Chromophobe renal cell carcinoma (KICH) and related to a bad prognosis. Thus, finding biomarkers is important for the therapy of KICH.

METHODS

The UCSC was used for determining the expression of mRNA and miRNA and clinical data in KICH and normal samples. KEGG and GO were used for predicting potential function of differently expressed genes (DEGs). Optimal prognostic markers were determined by Lasso regression. Kaplan-Meier survival, ROC, and cox regression were used for assessing prognosis value. GSEA was used for predicting potential function of markers. The relations between markers and immune cell infiltration were determined by Pearson method. The upstream miRNA of markers was predicted in TargetScan and DIANA.

RESULTS

The 6162 upregulated and 13,903 downregulated DEGs were identified in KICH. Further CENPE and LDHA were screened out as optimal prognostic risk signatures. CENPE was highly expressed while LDHA was lowly expressed in KICH samples, and the high expressions of 2 genes contributed to bad prognosis. The functions of CENPE and LDHA were mainly enriched in proliferation related pathways such as cell cycle and DNA replication. In addition, the correlation of 2 genes with immune infiltrates in KICH was also observed. Finally, we found that has-miR-577 was the common upstream of 2 genes and the binding sites can be predicted.

CONCLUSION

CENPE and LDHA were identified as the important prognostic biomarkers in KICH, and they might be involved in the proliferation of cancer cell.

Unravelling hub genes as potential therapeutic targets in lung cancer using integrated transcriptomic meta-analysis and in silico approach

Lung cancer (LC) is the leading cause of cancer-related deaths worldwide. Smoking has been identified as the main contributing cause of the disease's development. The study aimed to identify the key genes in small cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC), the two major types of LC. Meta-analysis was performed with two datasets GSE74706 and GSE149507 obtained from Gene Expression Omnibus (GEO). Both the datasets comprised samples from cancerous and adjacent non-cancerous tissues. Initially, 633 differentially expressed genes (DEGs) were identified. To understand the underlying molecular mechanism of the identified genes, pathway enrichment, gene ontology (GO) and protein-protein interaction (PPI) analyses were done. A total of 9 hub genes were identified which were subjected to mutation study analysis in LC patients using cBioPortal. These   9 genes (i.e. AURKA, AURKB, KIF23, RACGAP1, KIF2C, KIF20A, CENPE, TPX2 and PRC1) have shown overexpression in LC patients and can be explored as potential candidates for prognostic biomarkers. TPX2 reported a maximum mutation of 4 % . This was followed with high throughput screening and docking analysis to identify the potential drug candidates following competitive inhibition of the AURKA-TPX2 complex. Four compounds, CHEMBL431482, CHEMBL2263042, CHEMBL2385714, and CHEMBL1206617 were identified. The results signify that the selected 9 genes can be explored as biomarkers in disease prognosis and targeted therapy. Also, the identified 4 compounds can be further analyzed as promising therapeutic candidates.Communicated by Ramaswamy H. Sarma.

Aberrant activation of five embryonic stem cell-specific genes robustly predicts a high risk of relapse in breast cancers

BACKGROUND

In breast cancer, as in all cancers, genetic and epigenetic deregulations can result in out-of-context expressions of a set of normally silent tissue-specific genes. The activation of some of these genes in various cancers empowers tumours cells with new properties and drives enhanced proliferation and metastatic activity, leading to a poor survival prognosis.

RESULTS

In this work, we undertook an unprecedented systematic and unbiased analysis of out-of-context activations of a specific set of tissue-specific genes from testis, placenta and embryonic stem cells, not expressed in normal breast tissue as a source of novel prognostic biomarkers. To this end, we combined a strict machine learning framework of transcriptomic data analysis, and successfully created a new robust tool, validated in several independent datasets, which is able to identify patients with a high risk of relapse. This unbiased approach allowed us to identify a panel of five biomarkers, DNMT3B, EXO1, MCM10, CENPF and CENPE, that are robustly and significantly associated with disease-free survival prognosis in breast cancer. Based on these findings, we created a new Gene Expression Classifier (GEC) that stratifies patients. Additionally, thanks to the identified GEC, we were able to paint the specific molecular portraits of the particularly aggressive tumours, which show characteristics of male germ cells, with a particular metabolic gene signature, associated with an enrichment in pro-metastatic and pro-proliferation gene expression.

CONCLUSIONS

The GEC classifier is able to reliably identify patients with a high risk of relapse at early stages of the disease. We especially recommend to use the GEC tool for patients with the luminal-A molecular subtype of breast cancer, generally considered of a favourable disease-free survival prognosis, to detect the fraction of patients undergoing a high risk of relapse.

Comprehensive pan-cancer analysis identifies centromere associated protein E as a novel prognostic and immunological biomarker in human tumors

Centromere-associated protein E (CENP-E), a core component of the kinetochore, mediates chromosome congression and spindle microtubule capture during mitosis. Partial experimental evidence has illustrated the carcinogenic effects of CENPE in tumors, but the corresponding pan-cancer analysis of CENPE still lacking. Based on public databases, including the Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), and Human Protein Atlas (HPA), we take an array of bioinformatics methods to investigate the potential oncogenic roles of CENPE. Then, we validated CENPE, cell cycle-related proteins, and immune checkpoint molecule findings expression in clinical colon cancer samples by western blot. Our results showed that CENPE was up-regulated in almost all tumors, and the expression level of CENPE was associated with worse overall survival (OS) and disease-specific survival (DSS) in patients. The strong relationship between CENPE with gene mutation and MMR has also been validated. Moreover, CENPE gene expression was positively correlated with immune checkpoint molecular, and reversely correlated with infiltration levels of most immune cells. In the human colon cancer tissues, the expression of CENPE, cell cycle-related proteins, and immune checkpoint molecules were significantly higher than in the adjacent normal tissues. Our results indicated that CENPE can function as an oncogene in various cancers, and may be regarded as a promising prognostic and diagnostic biomarker in cancer treatment.

Identification of potential druggable targets of cell cycle with small-molecule inhibitors in oral squamous cell carcinoma

Oral squamous cell carcinoma (OSCC) is one of the most common malignant tumors worldwide and there are few crucial regulators and druggable targets for early diagnosis. Therefore, the identification of biomarkers for the early diagnosis and druggable targets of OSCC is imminent. In this study, we integrated gene set enrichment analysis, differential gene expression analysis based on the negative binomial distribution, weighted correlation network analysis, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes into analyzing the OSCC cohort downloaded from The Cancer Genome Atlas, and found that cell cycle and related biologic processes are significantly enriched. Then, we constructed the core gene network of OSCC, which showed the connection of encode human Cyclin-A2 protein, encode RAD51-associated protein 1, encode human centromere-associated protein E (CENPE), encode humans centromere protein I (CENPI) and encode polo-like kinase 1 (PLK1) to several cell cycle-related genes. Survival analysis further showed that low expression of these genes was associated with a better prognosis. Furthermore, we utilized a high-throughput virtual screening to find new CENPE and PLK1 inhibitors, and one of the CENPE inhibitor DB04517 suppressed the proliferation of OSCC cells by cell cycle arrest of cell cycle. Taken together, these candidate regulators could serve as the candidate diagnostic and prognostic biomarkers for OSCC, and specific suppression of these genes may be a potential approach to prevent and treat OSCC with the candidate inhibitors.

Upregulation of Centromere Proteins as Potential Biomarkers for Esophageal Squamous Cell Carcinoma Diagnosis and Prognosis

Esophageal squamous cell carcinoma (ESCC) has a high incidence and low survival rate, necessitating the identification of novel specific biomarkers. Centromere-associated proteins (CENPs) have been reported to be biomarkers for many cancers, but their roles in ESCC have seldom been investigated. Here, the potential clinical roles of CENPs in ESCC patients were demonstrated by a systematic bioinformatics analysis. Most CENP-encoding genes were differentially expressed between tumor and normal tissues. CENPA, CENPE, CENPF, CENPI, CENPM, CENPN, CENPQ, and CENPR were upregulated universally in the three datasets. Survival analysis demonstrated that high expression of CENPE and CENPQ was positively correlated with the outcomes of ESCC patients. The CENPE-based forecast model was more accurate than the tumor-node-metastasis (TNM) staging-based model, which was classified as stage I/II vs. III/IV. More importantly, the forecast model based on the commonly upregulated CENPs exhibited a much higher area under the curve (AUC) value (0.855) than the currently known TTL, ZNF750, AC016205.1, and BOLA3 biomarkers. The nomogram model integrating the CENPs, TNM stage, and sex was highly accurate in the prognosis of ESCC patients ( $\text{AUC}=0.906$ ). Besides, gene set enrichment analysis (GSEA) demonstrated that CENPE expression is significantly correlated with cell cycle, G2/M checkpoint, mitotic spindle, p53, etc. Finally, in validation experiments, we also found that CENPE and CENPQ were significantly overexpressed in esophageal cancer cells. Taken together, these results clearly suggest that CENPs are clinically promising diagnostic and prognostic biomarkers for ESCC patients.

Functional roles of the SHCBP1 and KIF23 interaction in modulating the cell-cycle and cisplatin resistance of head and neck squamous cell carcinoma

BACKGROUND

This study aimed to explore the functional roles of Shc SH2-domain-binding protein 1 (SHCBP1) and Kinesin Family Member 23 (KIF23) in HPV-negative head and neck squamous cell carcinoma (HNSCC).

METHODS

Bioinformatic analysis was conducted using data from The Cancer Genome Atlas (TCGA) and GSE103322. HNSCC cell lines were used for in vitro and in vivo analysis.

RESULTS

SHCBP1 upregulation was associated with unfavorable survival. SHCBP1 knockdown reduced cell proliferation and increased the cisplatin sensitivity of SCC9/SCC25 cells. SHCBP1 interacted with KIF23 via its Nesd homology domain (NHD) domain, which was important for its nucleus localization. SHCBP1 positively modulated KIF23 expression and activated phosphoinositide 3-kinase (PI3K)/protein kinase B (Akt), extracellular signal regulated kinase (ERK)1/2, nuclear factor kappa B (NF/κB)-p65, and Wnt/β-catenin signaling. KIF23 knockdown abrogated cisplatin resistance induced by SHCBP1 overexpression.

CONCLUSION

SHCBP1 interacts with KIF23 and cooperatively regulates cell-cycle progression and cisplatin resistance of HNSCC tumor cells.

Identification of a DNA Methylation-Driven Genes-Based Prognostic Model and Drug Targets in Breast Cancer: In silico Screening of Therapeutic Compounds and in vitro Characterization

DNA methylation is a vital epigenetic change that regulates gene transcription and helps to keep the genome stable. The deregulation hallmark of human cancer is often defined by aberrant DNA methylation which is critical for tumor formation and controls the expression of several tumor-associated genes. In various cancers, methylation changes such as tumor suppressor gene hypermethylation and oncogene hypomethylation are critical in tumor occurrences, especially in breast cancer. Detecting DNA methylation-driven genes and understanding the molecular features of such genes could thus help to enhance our understanding of pathogenesis and molecular mechanisms of breast cancer, facilitating the development of precision medicine and drug discovery. In the present study, we retrospectively analyzed over one thousand breast cancer patients and established a robust prognostic signature based on DNA methylation-driven genes. Then, we calculated immune cells abundance in each patient and lower immune activity existed in high-risk patients. The expression of leukocyte antigen (HLA) family genes and immune checkpoints genes were consistent with the above results. In addition, more mutated genes were observed in the high-risk group. Furthermore, a in silico screening of druggable targets and compounds from CTRP and PRISM databases was performed, resulting in the identification of five target genes (HMMR, CCNB1, CDC25C, AURKA, and CENPE) and five agents (oligomycin A, panobinostat, (+)-JQ1, voxtalisib, and arcyriaflavin A), which might have therapeutic potential in treating high-risk breast cancer patients. Further in vitro evaluation confirmed that (+)-JQ1 had the best cancer cell selectivity and exerted its anti-breast cancer activity through CENPE. In conclusion, our study provided new insights into personalized prognostication and may inspire the integration of risk stratification and precision therapy.

High mRNA Expression of CENPL and Its Significance in Prognosis of Hepatocellular Carcinoma Patients

Centromere proteins (CENPs) are the main constituent proteins of kinetochore, which are essential for cell division. In recent years, several studies have revealed that several CENPs were aberrantly expressed in hepatocellular carcinoma (HCC). However, numerous centromere proteins have not been studied in HCC. In this study, we used databases of Oncomine, Gene Expression Profiling Interactive Analysis (GEPIA), the Kaplan-Meier Plotter, cBioPortal, the Human Protein Atlas (HPA), and TIMER (Tumor Immune Estimation Resource) and immunohistochemical staining of clinical specimens to investigate the expression of 15 major centromere proteins in HCC to evaluate their potential prognostic value. We found that the mRNA levels of 4 out of 15 centromere proteins (CENPL, CENPQ, CENPR, and CENPU) were significantly higher in HCC than in normal tissues, and their mRNA levels were associated with the tumor stages (p values < 0.01). Patients with higher mRNA levels of CENPL had poorer overall survival, progression-free survival, relapse-free survival, and disease-specific survival (p values < 0.05). Furthermore, the higher levels of CENPL mRNA were associated with worse overall survival in males without hepatitis virus infection (p values < 0.05). The protein expression level of CENPL in human HCC tissue was higher than that in normal liver tissue. In addition, the expression of CENPL was positively correlated with the levels of the tumor-infiltrating lymphocytes. The results suggest that the high mRNA expression of CENPL may be a potential predictor of prognosis in HCC patients.

Identification of DNA-Repair-Related Five-Gene Signature to Predict Prognosis in Patients with Esophageal Cancer

Esophageal cancer (ESCA) is a leading cause of cancer-related mortality, with poor prognosis worldwide. DNA damage repair is one of the hallmarks of cancer. Loss of genomic integrity owing to inactivation of DNA repair genes can increase the risk of cancer progression and lead to poor prognosis. We aimed to identify a novel gene signature related to DNA repair to predict the prognosis of ESCA patients. Based on gene expression profiles of ESCA patients from The Cancer Genome Atlas and gene set enrichment analysis, 102 genes related to DNA repair were identified as candidates. After stepwise Cox regression analysis, we established a five-gene prognostic model comprising DGCR8, POM121, TAF9, UPF3B, and BCAP31. Kaplan-Meier survival analysis confirmed a strong correlation between the prognostic model and survival. Moreover, we verified the clinical value of the prognostic signature under the influence of different clinical parameters. We found that small-molecule drugs (trametinib, selumetinib, and refametinib) could help to improve patient survival. In summary, our study provides a novel and promising prognostic signature based on DNA-repair-related genes to predict survival of patients with ESCA. Systematic data mining provides a theoretical basis for further exploring the molecular pathogenesis of ESCA and identifying therapeutic targets.

CENPE Inhibition Leads to Mitotic Catastrophe and DNA Damage in Medulloblastoma Cells

Simple Summary

Medulloblastoma (MB) is the most frequent brain tumor in children. The standard treatment consists in surgery, followed by radiotherapy and chemotherapy. These therapies are only partially effective, since many patients still die and those who survive suffer from neurological and endocrine disorders. Therefore, more effective therapies are needed. CENPE is a gene critical for normal proliferation and survival of neural progenitors. Since there is evidence that MB cells are very similar to neural progenitors, we hypothesized that CENPE could be an effective target for MB treatment. In MB cell lines, CENPE depletion induced defects in division and resulted in cell death. To consolidate CENPE as a target for MB treatment, we tested GSK923295, a specific inhibitor already in clinical trials for other cancer types. GSK923295 induced effects similar to CENPE depletion at low nM levels, supporting the idea that CENPE’s inhibition could be a viable strategy for MB treatment.

Abstract

Medulloblastoma (MB) is the most frequent brain tumor in children. The standard treatment consists in surgery, followed by radiotherapy and chemotherapy. These therapies are only partially effective since many patients still die and those who survive suffer from neurological and endocrine disorders. Therefore, more effective therapies are needed. Primary microcephaly (MCPH) is a rare disorder caused by mutations in 25 different genes. Centromere-associated protein E (CENPE) heterozygous mutations cause the MCPH13 syndrome. As for other MCPH genes, CENPE is required for normal proliferation and survival of neural progenitors. Since there is evidence that MB shares many molecular features with neural progenitors, we hypothesized that CENPE could be an effective target for MB treatment. In ONS-76 and DAOY cells, CENPE knockdown induced mitotic defects and apoptosis. Moreover, CENPE depletion induced endogenous DNA damage accumulation, activating TP53 or TP73 as well as cell death signaling pathways. To consolidate CENPE as a target for MB treatment, we tested GSK923295, an allosteric inhibitor already in clinical trial for other cancer types. GSK923295, induced effects similar to CENPE depletion with higher penetrance, at low nM levels, suggesting that CENPE’s inhibition could be a therapeutic strategy for MB treatment.

Kinesin Family Member C1 (KIFC1) Regulated by Centrosome Protein E (CENPE) Promotes Proliferation, Migration, and Epithelial-Mesenchymal Transition of Ovarian Cancer

Background

Centrosome amplification is recognized as a hallmark of cancer. Kinesin family member C1 (KIFC1), a centrosome-clustering molecule, is essential for the viability of extra centrosome-bearing cancer cells and may be the basis for the progression of ovarian cancer. However, its biological function and mechanism in ovarian cancer have not yet been studied.

Material/Methods

Quantitative reverse-transcription polymerase chain reaction was performed to detect the levels of KIFC1 and centrosome protein E (CENPE). Further, cell viability was analyzed with CCK-8 assay, and immunofluorescence was used to measure the expression of Ki67 and PCNA. Cell migration was analyzed with wound healing and transwell assays. Western blot analysis was performed to measure the expression of proteins in ovarian cancer cells. The relationship between KIFC1 and CENPE was investigated by performing co-immunoprecipitation.

Results

KIFC1 was upregulated in ovarian cancer cells, especially in SKOV3 cells. Additionally, we found that KIFC1 silencing in SKOV3 cells inhibited cell proliferation and downregulated the expression of Ki67 and PCNA. Further, the knockdown of KIFC1 suppressed cell migration and epithelial-mesenchymal transition (EMT) and regulated the expression of matrix metalloproteinase (MMP)2, MMP9, E-cadherin, N-cadherin, Snail, and ZEB1. Next, we found that KIFC1 bound to and positively regulated CENPE, a tumor promoter in certain human cancers. All the suppressive effects triggered by KIFC1 inhibition were reversed by CENPE overexpression.

Conclusions

KIFC1 contributed to cell proliferation, migration, and EMT via interacting with CENPE in ovarian cancer. KIFC1 might be a potential biomarker and therapeutic target in ovarian cancer patients.

KIF14 and KIF23 Promote Cell Proliferation and Chemoresistance in HCC Cells, and Predict Worse Prognosis of Patients with HCC

Background

Hepatocellular carcinoma (HCC) is one of the most common human malignant tumors. The prognosis of HCC patients is still unsatisfying. In this study, we performed the integrated bioinformatics analysis to identify potential biomarkers and biological pathways in HCC.

Methods

Gene expression profiles were obtained from the Gene Expression Omnibus database (GSE55048, GSE55758, and GSE56545) for the screening of the common differentially expressed genes (DEGs) between HCC tissues and matched non-tumor tissues. DEGs were subjected to Gene Ontology, KEGG pathway, and Reactome pathway analysis. The hub genes were identified by using protein–protein interaction (PPI) network analysis. The hub genes in HCC were further subjected to overall survival analysis of HCC patients. The hub genes were further validated by in vitro functional assays.

Results

A total of 544 common differentially expressed genes were screened from three datasets. Gene Ontology, KEGG and Reactome analysis results showed that DEGs are significantly associated with the biological process of cell cycle, cell division, and DNA replication. PPI network analysis identified 20 hub genes from the DEGs. These hub genes except CENPE were all significantly up-regulated in the HCC tissues when compared to non-tumor tissues. The Kaplan–Meier survival analysis results showed that the high expression of the 20 hub genes was associated with shorter survival of the HCC patients. Further validation studies showed that knockdown of KIF14 and KIF23 both suppressed the proliferative potential, increased the caspase-3/-7 activity, up-regulated Bax expression, and promoted the invasive and migratory abilities in the HCC cells. In addition, knockdown of KIF14 and KIF23 enhanced chemosensitivity to cisplatin and sorafenib in the HCC cells. Finally, the high expression of KIF14 and KIF23 was associated with shorter progression-free survival, recurrence-free survival, and disease-specific survival of patients with HCC.

Conclusion

In conclusion, the present study performed the integrated bioinformatics analysis and showed that KIF14 and KIF23 silence attenuated cell proliferation, invasion, and migration, and promoted chemosensitivity of HCC cells. KIF14 and KIF23 may serve as potential biomarkers for predicting the worse prognosis of patients with HCC.

CENPE, PRC1, TTK, and PLK4 May Play Crucial Roles in the Osteosarcoma Progression

Osteosarcoma (OS) is a cancerous tumor in a bone. We aimed to identify the critical genes involved in OS progression, and then try to elucidate the molecular mechanisms of this disease. The microarray data of GSE32395 was used for the present study. We analyzed differentially expressed genes (DEGs) in OS cells compared with control group by Student’s t-test. The significant enriched gene ontology (GO) and kyoto encyclopedia of genes and genomes (KEGG) pathways were analyzed for upregulated genes and downregulated genes, respectively. In addition, a protein-protein interaction (PPI) network was constructed. GO and KEGG enrichment analyses were conducted for genes in the PPI network. In total, 183 DEGs, including 100 upregulated DEGs and 83 downregulated DEGs were screened. The upregulated DEGs were significantly enriched in 2 KEGG pathways, such as “Glycosaminoglycan biosynthesis-chondroitin sulfate” and the downregulated DEGs were significantly enriched in 12 pathways, including “cell adhesion molecules,” “pentose phosphate pathway” and “allograft rejection.” GO enrichment analysis indicated that the upregulated DEGs were significantly involved in biological process, such as “multicellular organismal metabolic process” and “limb morphogenesis,” while the downregulated DEGs were significantly enriched in biological process, such as “Positive regulation of pathway-restricted SMAD protein phosphorylation.” The PPI network included 84 interactions and 51 nodes. The “glycosaminoglycan biosynthesis-chondroitin sulfate pathway,” “microtubule motor activityfunction,” and “regulation of mitosis process” were significantly enriched by genes in PPI network. In particular, CENPE, PRC1, TTK, and PLK4 had higher degrees in the PPI network. The interactions between TTK and PLK4 as well as CENPE and PRC1 may involve in the OS development. These 4 genes might be possible biomarkers for the treatment and diagnosis of OS.

Identification of unique long non-coding RNAs as putative biomarkers for chromophobe renal cell carcinoma

Aim: To investigate whether long non-coding RNAs (lncRNAs) can be utilized as molecular biomarkers in predicting the occurrence and progression of chromophobe renal cell carcinoma. Methods & results: Genetic and related clinical traits of chromophobe renal cell carcinoma were downloaded from the Cancer Genome Atlas and used to construct modules using weighted gene coexpression network analysis. In total, 44,889 genes were allocated into 21 coexpression modules depending on intergenic correlation. Among them, the green module was the most significant key module identified by module-trait correlation calculations (R² = 0.43 and p = 4e-04). Gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses demonstrated that genes in the green module were enriched in many pathways. Coexpression, protein-protein interaction networks, screening for differentially expressed genes, and survival analysis were used to select hub lncRNAs. Five hub lncRNAs (TTK, CENPE, KIF2C, BUB1, and RAD51AP1) were selected out. Conclusion: Our findings suggest that the five lncRNAs may act as potential biomarkers for chromophobe renal cell carcinoma progression and prognosis.

CDK1 and CDC20 overexpression in patients with colorectal cancer are associated with poor prognosis: evidence from integrated bioinformatics analysis

BACKGROUND

Colorectal cancer (CRC) is one of the most common malignancies of the digestive system, which causes severe financial burden worldwide. However, the specific mechanisms involved in CRC are still unclear.

METHODS

To identify the significant genes and pathways involved in the initiation and progression of CRC, the microarray dataset GSE126092 was downloaded from Gene Expression Omnibus (GEO) database, and then, the data was analyzed to identify differentially expressed genes (DEGs). Subsequently, the Gene Ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed on these DEGs using the DAVID database, and the protein-protein interaction (PPI) network was constructed using the STRING database and analyzed using the Cytoscape software. Finally, hub genes were screened, and the survival analysis was performed on these hub genes using the Kaplan-Meier curves in the cBioPortal database.

RESULTS

In total, 937 DEGs were obtained, including 316 upregulated genes and 621 downregulated genes. GO analysis revealed that the DEGs were mostly enriched in terms of nuclear division, organelle fission, cell division, and cell cycle process. KEGG pathway analysis showed that the DEGs were mostly enriched in cell cycle, oocyte meiosis, cytokine-cytokine receptor interaction, and cGMP-PKG signaling pathway. The PPI network comprised 608 nodes and 3100 edges, and 4 significant modules and 10 hub genes with the highest degree were identified using the Cytoscape software. Finally, survival analysis showed that overexpression of CDK1 and CDC20 in patients with CRC were statistically associated with worse overall survival.

CONCLUSIONS

This bioinformatics analysis revealed that CDK1 and CDC20 might be candidate targets for diagnosis and treatment of CRC, which provided valuable clues for CRC.

Bioinformatic analysis identifies potentially key differentially expressed genes in oncogenesis and progression of clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) is one of the most common and lethal types of cancer within the urinary system. Great efforts have been made to elucidate the pathogeny. However, the molecular mechanism of ccRCC is still not well understood. The aim of this study is to identify key genes in the carcinogenesis and progression of ccRCC. The mRNA microarray dataset GSE53757 was downloaded from the Gene Expression Omnibus database. The GSE53757 dataset contains tumor and matched paracancerous specimens from 72 ccRCC patients with clinical stage I to IV. The linear model of microarray data (limma) package in R language was used to identify differentially expressed genes (DEGs). The protein–protein interaction (PPI) network of the DEGs was constructed using the search tool for the retrieval of interacting genes (STRING). Subsequently, we visualized molecular interaction networks by Cytoscape software and analyzed modules with MCODE. A total of 1,284, 1,416, 1,610 and 1,185 up-regulated genes, and 932, 1,236, 1,006 and 929 down-regulated genes were identified from clinical stage I to IV ccRCC patients, respectively. The overlapping DEGs among the four clinical stages contain 870 up-regulated and 645 down-regulated genes. The enrichment analysis of DEGs in the top module was carried out with DAVID. The results showed the DEGs of the top module were mainly enriched in microtubule-based movement, mitotic cytokinesis and mitotic chromosome condensation. Eleven up-regulated genes and one down-regulated gene were identified as hub genes. Survival analysis showed the high expression of CENPE, KIF20A, KIF4A, MELK, NCAPG, NDC80, NUF2, TOP2A, TPX2 and UBE2C, and low expression of ACADM gene could be involved in the carcinogenesis, invasion or recurrence of ccRCC. Literature retrieval results showed the hub gene NDC80, CENPE and ACADM might be novel targets for the diagnosis, clinical treatment and prognosis of ccRCC. In conclusion, the findings of present study may help us understand the molecular mechanisms underlying the carcinogenesis and progression of ccRCC, and provide potential diagnostic, therapeutic and prognostic biomarkers.

Expression of CENPE and its Prognostic Role in Non-small Cell Lung Cancer

Background

Non-small cell lung cancer (NSCLC) is one of the most important causes of death worldwide. Most patients are diagnosed in the advanced stage and have a poor prognosis. This study was to investigate the expression and significance of CENPE in NSCLC.

Method

Collecting information about CENPE in the Oncoming database, and perform a further analysis of the data in the current database to conduct a meta-analysis for its functional role in NSCLC. Patient life cycle analysis using Kaplan-Meier Plotter and GEPIA databases are used to perform patient survival analysis.

Result

A total of 12 studies involved the expression of CENPE in NSCLC cancer tissues and normal tissues, including 1195 samples. CENPE was highly expressed in NSCLC cell carcinoma compared with the control group (P < 0.05). Moreover, the expression of CENPE was correlated with the overall survival rate of CENPE. The overall survival rate of patients with high expression of CENPE was poor, and the prognosis of patients with low expression of CENPE was better (P<0.05).

Conclusion

We propose high expression of CENPE in NSLCL tissue is related to the prognosis of NSCLC, which may provide important basis for the development of tumor drugs.