Downregulation of CENPF Remodels Prostate Cancer Cells and Alters Cellular Metabolism

Expression of circular RNA has-circ-0009158 and identification of associated miRNA-mRNA network in hepatocellular carcinoma

Primary hepatocellular carcinoma (HCC) affects people all over the world. Circular RNAs are involved in the growth and development of several malignancies and regulate a number of biological processes. However, the roles of has-circ-0009158 in HCC remain unknown. This study explored the expression and associated miRNA-mRNA network of has-circ-0009158 in HCC. Quantitative real-time polymerase chain reaction was used to measure the expression of hsa-circ-0009158 in the HCC tissues of 143 patients and four human HCC cell lines. Then, the potential relationship of hsa-circ-0009158 expression with clinical characteristics and prognosis of patients was analyzed using the GO and KEGG databases. Correlated miRNA-mRNA networks were forecasted using the TCGA database and Cytoscape software. The hsa-circ-0009158 expression was significantly upregulated in HCC tissues and cell lines (P<0.001). The multivariate Cox analysis revealed that HCC patients were associated with high hsa-circ-0009158 expression. The bioinformatics analysis screened 1 miRNA, and 248 mRNAs associated with the circRNA in HCC. A pathway analysis suggested that the differentially expressed genes (DEGs) may be linked to the development and growth of HCC tumors. Ten hub genes (MELK, NCAPG, BUB1B, BIRC5, CDCA8, CENPF, BUB1, CDK1, TTK, TPX2) were identified from the PPI network based on the 248 genes. Additionally, the 10 hub genes that were verified had an association between high expression levels and low overall survival rates. As a result, the high expression of hsa-circ-0009158 was found to be a separate risk factor for recurrence and a poor prognosis in HCC patients.

FOXM1 and CENPF are associated with a poor prognosis through promoting proliferation and migration in lung adenocarcinoma

Lung adenocarcinoma (LUAD) is a clinically challenging disease due to its poor prognosis and limited therapeutic methods. The aim of the present study was to identify prognosis-related genes and therapeutic targets for LUAD. Raw data from the GSE32863, GSE41271 and GSE42127 datasets were downloaded from the Gene Expression Omnibus database. Following normalization, the data were merged into a matrix, which was first used to identify differentially expressed genes (DEGs). Weighted gene co-expression network analysis (WGCNA) and survival analysis were performed to screen potential prognosis-related genes. Gene overlaps among DEGs, survival-related genes and WGCNA genes were finally constructed to obtain candidate genes. An analysis with the STRING database was performed to construct a protein-protein interaction network and hub genes were selected using Cytoscape. The candidate genes were finally identified by univariate and multivariate Cox regression analysis. Furthermore, in vivo and in vitro experiments, including immunohistochemistry, immunofluorescence, Cell Counting Kit-8, colony-formation and migration assays, were performed to validate the potential mechanism of these genes in LUAD. Two genes, namely forkhead box M1 (FOXM1) and centromere protein F (CENPF), were identified as unfavorable indicators of prognosis in patients with LUAD. High expression of FOXM1 and CENPF were associated with poor survival. Furthermore, LUAD cells with FOXM1 and CENPF knockdown showed a significant reduction in proliferation and migration (P<0.05). FOXM1 and CENPF may have an essential role in the prognosis of patients with LUAD by influencing cell proliferation and migration, and they provide potential molecular targets for LUAD therapy.

Long Non-Coding RNA Small Nucleolar RNA Host Gene 4 Induced by Transcription Factor SP1 Promoted the Progression of Nasopharyngeal Carcinoma Through Modulating microRNA-510-5p/Centromere Protein F Axis

Long non-coding RNAs (LncRNAs) are implicated with tumorigenesis and the development of nasopharyngeal carcinoma (NPC). Previous studies suggested that long non-coding RNA small nucleolar RNA host gene 4 (SNHG4) exerted oncogenic roles in various cancers. However, the function and molecular mechanism of SNHG4 in NPC have not been investigated. In our study, it was confirmed that the SNHG4 level was enriched in NPC tissues and cells. Functional assays indicated that SNHG4 depletion inhibited the proliferation and metastasis but promoted apoptosis of NPC cells. Furthermore, we identified miR-510-5p as a downstream gene of SNHG4 in NPC cells and SNHG4 upregulated CENPF expression by binding to miR-510-5p. Moreover, there was a positive (or negative) association between CENPF and SNHG4 (or miR-510-5p) expression in NPC. In addition, rescue experiments verified that CENPF overexpression or miR-510-5p silencing abrogated inhibitory effects on NPC tumorigenesis caused by SNHG4 deficiency. The study demonstrated that SNHG4 promoted NPC progression via miR-510-5p/CENPF axis, providing a novel potential therapeutic target for NPC treatments.

Chrysosplenol D can inhibit the growth of prostate cancer by inducing reactive oxygen species and autophagy

OBJECTIVE

To uncover the effects of chrysosplenol D (CHD) on the progression of prostate cancer in vitro as well as in mice.

METHODS

DU145 and PC-3 cells were treated with increasing doses of CHD for 24, 48, or 72 h. Cell Counting Kit-8 (CCK-8) and colony formation assays were conducted to confirm the effects of CHD on cell viability. Flow cytometry (FCM) and immunostaining assays showed the effects of CHD on cell apoptosis and oxidative stress. Immunoblot was performed to detect the effects of CHD on autophagy. Besides, tumor growth assays were conducted to confirm the role of CHD in tumor growth in mice. GraphPad 6.0 was used for statistical analysis. All data were represented as mean ± SD. p < .05 and the significant difference was indicated by an asterisk.

RESULTS

CHD suppressed the viability of prostate cancer cells in CCK-8 assays, decreased colony number in colony formation assays, and induced cell apoptosis in FCM and immunostaining assays. CHD also restrained the oxidative stress with a decreased 2'-7'-dichlorofluorescein diacetate staining intensity. CHD restrained the autophagy of prostate cancer cells, as well as suppressed tumor growth in mice.

CONCLUSION

CHD could serve as a drug for prostate cancer.

Integrated pan-cancer analysis of centromere protein F and experimental verification of its role and clinical significance in cholangiocarcinoma

Centromere protein F (CENPF), a protein related to the cell cycle, is a key part of the kinetochore-centromere complex involved in cell division, differentiation, and proliferation. CENPF expression is upregulated in various types of cancer and plays a role in oncogenesis and tumor progression. However, the expression pattern, prognostic significance, and biological role of CENPF in these cancer types are poorly understood. Therefore, in this study, we conducted a pan-cancer analysis of the role of CENPF, which we considered a cut point, to investigate its utility as a prognostic and immunological indicator for malignancies, especially cholangiocarcinoma (CCA). Using systematic bioinformatics analysis, we investigated the expression patterns, prognostic relevance, molecular function, signaling pathways, and immune infiltration patterns of CENPF in the pan-cancer analysis. Western blot and immunohistochemistry staining assays were performed to evaluate the expression profiles of CENPF in CCA tissues and cell lines. Furthermore, Cell Counting Kit-8, colony formation, wound healing, and Transwell assays, as well as CCA xenograft mouse models, were employed to determine the role and function of CENPF in CCA. The results showed that CENPF expression was upregulated and strongly linked to a worse prognosis in most cancer types. CENPF expression was substantially associated with immune cell infiltration, tumor microenvironment, genes related to immune checkpoints, tumor mutational burden, microsatellite instability, and immunotherapy response in diverse malignancies. CENPF was considerably overexpressed in CCA tissues and cells. Functionally, inhibiting CENPF expression significantly reduced the proliferating, migrating, and invading abilities of CCA cells. CENPF expression also affects the prognosis of multiple malignancies, which is highly associated with immunotherapy response and tumor immune cell infiltration. In conclusion, CENPF may act as an oncogene and an immune infiltration-related biomarker and can accelerate tumor development in CCA.

Identification of the novel therapeutic targets and biomarkers associated of prostate cancer with cancer-associated fibroblasts (CAFs)

Globally, prostate cancer remains a leading cause of mortality and morbidity despite advances in treatment. Research on prostate cancer has primarily focused on the malignant epithelium, but the tumor microenvironment has recently been recognized as an important factor in the progression of prostate cancer. Cancer-associated fibroblasts (CAFs) play an important role in prostate cancer progression among multiple cell types in the tumor microenvironment. In order to develop new treatments and identify predictive and prognostic biomarkers for CAFs, further research is needed to understand the mechanism of action of prostate cancer and CAF. In this work, we performed the single-cell RNA sequence analysis to obtain the biomarkers for CAFs, and ten genes were finally regarded as the marker genes for CAFs. Based on the ssGSEA algorithm, the prostate cancer cohort was divided into low- and high-CAFs groups. Further analysis revealed that the CAFs-score is associated with many immune-related cells and immune-related pathways. In addition, between the low- and high-CAFs tissues, a total of 127 hub genes were discovered, which is specific in CAFs. After constructing the prognostic prediction model, SLPI, VSIG2, CENPF, SLC7A1, SMC4, and ITPR2 were finally regarded as the key genes in the prognosis of patients with prostate cancer. Each patient was assigned with the risk score as follows: SLPI* 0.000584811158157081 + VSIG2 * -0.01190627068889 + CENPF * -0.317826812875334 + SLC7A1 * -0.0410213995358753 + SMC4 * 0.202544454923637 + ITPR2 * -0.0824652047622673 + TOP2A * 0.140312081524807 + OR51E2 * -0.00136602095885459. The GSVA revealed the biological features of CAFs, many cancer-related pathways, such as the adipocytokine signaling pathway, ERBB signaling pathway, GnRH signaling pathway, insulin signaling pathway, mTOR signaling pathway and PPAR signaling pathway are closely associated with CAFs. As a result of these observations, similar transcriptomics may be involved in the transition from normal fibroblasts to CAFs in adjacent tissues. As one of the biomarkers for CAFs, CENPF can promote the proliferation ability of prostate cancer cells. The overexpress of CENPF could promote the proliferation ability of prostate cancer cells. In conclusion, we discuss the potential prognostic and therapeutic value of CAF-dependent pathways in prostate cancer.

CENPF promotes the proliferation of renal cell carcinoma in vitro

Background

Metastasis and drug resistance are the main causes of renal cell carcinoma (RCC) mortality. Currently, there are still a limited number of targeted therapies against advanced RCC. It is critical to develop new effective clinical biomarkers and drug targets in RCC. Several studies have shown that centromere protein F (CENPF), a microtubule binding protein, promotes cancer progression in various types of cancer. The purpose of this study was to explore the role of CENPF in RCC.

Methods

Peripheral blood and corresponding tissue samples of 23 RCC patients and 23 normal physical examination patients who were treated in our hospital from 2018 to 2020 were collected, and CENPF expression was detected by quantitative real-time polymerase chain reaction (qRT-PCR), western blot, and immunohistochemical (IHC) methods. The expression of CENPF was downregulated by small interfering RNA (siRNA) transfection, and the proliferation of the corresponding RCC cells and the corresponding cell cycle were detected.

Results

According to The Cancer Genome Atlas (TCGA) data analysis, CENPF is highly expressed in RCC, and its expression level is significantly related to the overall survival (OS) and recurrence-free survival (RFS) of RCC. In addition, high expression of CENPF was found in the tissues of RCC patients in our hospital. Knockdown of CENPF significantly reduced the proliferation of RCC cells in vitro, and knockdown of CENPF regulated the cell cycle by inhibiting the expression of cyclins such as CDK4, CDK6, and CyclinD1.

Conclusions

CENPF can be used as an independent prognostic factor of RCC and regulate the proliferation ability and cell cycle of RCC cells. CENPF is a potential oncogene and prognostic marker in RCC.

Combined multiomics analysis reveals the mechanism of CENPF overexpression-mediated immune dysfunction in diffuse large B-cell lymphoma in vitro

Diffuse large B-cell lymphoma (DLBCL) is one of the most common aggressive B-cell lymphomas with significant heterogeneity. More than half of patients are cured, but 40%-45% still face relapse or develop drug resistance, and the mechanism is not yet known. In this study, Centrimeric protein F (CENPF) overexpression was found in several DLBCL patients with relapsed or refractory disease compared to patients with complete remission. Thus, the human DLBCL cell line SU-DHL-4 was chosen for this study, and CENPF was upregulated in that cell line by using an adenovirus in vitro. Mass spectrometry-based quantitative proteome analysis was first performed, and the results showed that the expression levels of various proteins were increased when CENPF was upregulated, and these proteins are mainly involved in cellular processes, biological regulation, immune system processes and transcriptional regulator activity. Bioinformatics data analysis revealed that the main enriched proteins, including UBE2A, UBE2C, UBE2S, TRIP12, HERC2, PIRH2, and PIAS, were involved in various ubiquitin-related kinase activities and ubiquitination processes. Thus, ubiquitinome analysis was further performed, and the results demonstrated that proteins in many immune-related cellular pathways, such as natural killer cell-mediated cytotoxicity, the T-cell receptor signaling pathway and the B-cell receptor signaling pathway, were significantly deubiquitinated after CENPF was upregulated in DLBCL cells. Furthermore, TIMER2.0 was also used to reveal the association between CENPF and immune infiltration in DLBCL. The results showed that CENPF expression was positively correlated with CD8⁺ T cells, NK cells and B lymphocytes in DLBCL samples but negatively correlated with regulatory T cells. Aberrant activation of CENPF may induce immune dysregulation in DLBCL cells by mediating protein deubiquitination in various immune signaling pathways, which leads to tumor escape of DLBCL, but further experimental validation is still needed.

Centromere protein F promotes progression of hepatocellular carcinoma through ERK and cell cycle-associated pathways

Hepatocellular carcinoma (HCC) is one of the deadliest cancer types worldwide. The centromere proteins (CENPs) are critical for the mitosis-related protein complex and are involved in kinetochore assembly and spindle checkpoint signaling during mitosis. However, the clinical significance of CENPs in the recurrence and progression of HCC remains poorly understood. Here, we examined the expression of all CENPs and their association with recurrence and survival of HCC patients using the global gene expression profile dataset established in our laboratory. The effect of silencing CENPF on cell viability, migration, and epithelial-mesenchymal transition (EMT) were detected using CCK-8, transwell, and western blot, respectively. RT-qPCR and western blot were performed to confirm the silencing of CENPF and the relationship between STAT5A and CENPF, while tumorigenesis was tested using the HCC Huh7 xenograft mouse model. Most of the CENPs is overexpressed in HCC, and overexpression of CENPF was significantly associated with the poor survival of HCC patients. CENPF promoted HCC cell lines migration and EMT progression. Knockdown CENPF inhibited cell growth activity against human HCC cells in vitro and xenograft tumors in vivo. Bioinformatics analysis revealed that CENPF genes are enriched in the cell cycle. Silencing CENPF arrested cell cycle at the G2/M phase and inhibited Cyclin B1 and Cyclin E1 expressions. Meanwhile, silencing CENPF prohibited phosphorylation of ERK and the expression of NEK2. Additionally, we found that STAT5A down-regulated CENPF expression and inhibited cancer cell growth viability. In conclusion, our data suggested that CENPF could be potentially developed into a theranostic biomarker to tackle HCC progression.

MiR-1-3p targets CENPF to repress tumor-relevant functions of gastric cancer cells

Here we noted significantly downregulated miR-1-3p in gastric cancer (GC) tissue compared with adjacent normal tissue through qRT-PCR. Lowly expressed miR-1-3p correlated GC progression. Overexpressing miR-1-3p could restrain tumor-relevant cell behaviors in GC, while miR-1-3p inhibitor treatment triggered the opposite results. Moreover, dual-luciferase reporter gene detection identified specific binding sites of miR-1-3p in CENPF 3’untranslated region. Upregulating miR-1-3p constrained cell progression of GC via CENPF downregulation. Western blot, qRT-PCR and dual-luciferase detections manifested that miR-1-3p negatively mediated CENPF expression in GC cells. Thus, we demonstrated that miR-1-3p negatively mediated CENPF to hamper GC progression. CENPF may be an underlying target for GC therapy.

Comprehensive Analysis of the Expression and Prognostic Significance of the CENP Family in Breast Cancer

Background

Centromere proteins (CENPs) are a set of protein-coding genes involved in the transient assembly of the kinetochore which occurs during mitosis. This study intended to clarify the expression patterns, prognosis and potential mechanisms of CENPs in breast cancer (BC).

Methods

Coexpedia was used to screen GEO datasets and PubMed articles related to CENPs and BC. CENPs expressions, prognosis and alteration were analyzed by Oncomine, Ualcan and Kaplan Meier plotter and cBioPortal. The correlation and interaction of CENPs was performed by Breast Cancer Gene-Expression Miner, GeneMANIA and STRING portal. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were conducted to clarify the functional roles of CENPs. CENPF, E, U, A, N, I, K, W, M, L were selected for further analysis.

Results

All CENPs were highly expressed in BC compared to normal tissue. High expression of CENPF, E, U, A, N, I, W, M, L and CENPF, E, U, A, N, I, M correlated with worse relapse free survival (RFS) and worse overall survival (OS), respectively. All of 10 CENPs indicated positive correlations and complex interactions between each other at mRNA expression and protein level. CENPs were enriched GO terms mainly in centromere complex assembly and KEGG terms in progesterone-mediated oocyte maturation, cell cycle and oocyte meiosis.

Conclusion

The 10 CENPs could be diagnostic biomarkers and all of them except CENPK can be used as prognosis biomarkers in BC. CENPs play an oncogenic role and may be the potential therapy targets of treatment for BC patients.

A Unified Transcriptional, Pharmacogenomic, and Gene Dependency Approach to Decipher the Biology, Diagnostic Markers, and Therapeutic Targets Associated with Prostate Cancer Metastasis

Simple Summary

This manuscript demonstrates how integrated bioinformatic and statistical reanalysis of publicly available genomic datasets can be utilized to identify molecular pathways and biomarkers that may be clinically relevant to metastatic prostate cancer (mPrCa) progression. The most notable observation is that the transition from primary prostate cancer to mPrCa is characterized by upregulation of processes associated with DNA replication, metastasis, and events regulated by the serine/threonine kinase PLK1. Moreover, our analysis also identified over-expressed genes that may be exploited for potential targeted therapeutics and minimally invasive diagnostics and monitoring of mPrCa. The primary data analyzed were two transcriptional datasets for tissues derived from normal prostate, primary prostate cancer, and mPrCa. Also incorporated in the analysis were the transcriptional, gene dependency, and drug response data for hundreds of cell lines, including those derived from prostate cancer tissues.

Abstract

Our understanding of metastatic prostate cancer (mPrCa) has dramatically advanced during the genomics era. Nonetheless, many aspects of the disease may still be uncovered through reanalysis of public datasets. We integrated the expression datasets for 209 PrCa tissues (metastasis, primary, normal) with expression, gene dependency (GD) (from CRISPR/cas9 screen), and drug viability data for hundreds of cancer lines (including PrCa). Comparative statistical and pathways analyses and functional annotations (available inhibitors, protein localization) revealed relevant pathways and potential (and previously reported) protein markers for minimally invasive mPrCa diagnostics. The transition from localized to mPrCa involved the upregulation of DNA replication, mitosis, and PLK1-mediated events. Genes highly upregulated in mPrCa and with very high average GD (~1) are potential therapeutic targets. We showed that fostamatinib (which can target PLK1 and other over-expressed serine/threonine kinases such as AURKA, MELK, NEK2, and TTK) is more active against cancer lines with more pronounced signatures of invasion (e.g., extracellular matrix organization/degradation). Furthermore, we identified surface-bound (e.g., ADAM15, CD276, ABCC5, CD36, NRP1, SCARB1) and likely secreted proteins (e.g., APLN, ANGPT2, CTHRC1, ADAM12) that are potential mPrCa diagnostic markers. Overall, we demonstrated that comprehensive analyses of public genomics data could reveal potentially clinically relevant information regarding mPrCa.

miR-383-5p inhibits human malignant melanoma cells function via targeting CENPF

Human malignant melanoma (MM), is a type of skin cancer with high morbidity and mortality. In this study, we investigated the role of miR-383-5p in human MM cells in vitro. miR-383-5p expression was downregulated in MM cell lines compared with the human normal melanocyte cell line, and miR-383-5p overexpression inhibited the proliferation, migration, and invasion of M14 and A375 cells. Furthermore, miR-383-5p was able to effectively bind to the 3'UTR of CENPF mRNA. miR-383-5p expression was negatively correlated with CENPF expression and miR-383-5p overexpression inhibited CENPF protein expression in M14 and A375 cells. The overexpression of CENPF could effectively rescue the inhibitory effect on proliferation and invasion caused by miR-383-5p. Additionally, using publicly available databases, we showed that CENPF expression was upregulated in human MM tissues and could predict the prognosis of MM. In conclusion, miR-383-5p acts as a tumor suppressor in human MM by targeting CENPF, suggesting CENPF as a potential therapeutic target for human MM.

Bioinformatics Analysis Reveals Centromere Protein K Can Serve as Potential Prognostic Biomarker and Therapeutic Target for Non-small Cell Lung Cancer

Background:

Non-small cell lung carcinoma (NSCLC) accounts for 80% of all lung cancer cases, which have been a leading cause of morbidity and mortality worldwide. Previous studies demonstrated that centromere proteins were dysregulated and involved in regulating the tumorigenesis and development of human cancers. However, the roles of centromere protein family members in NSCLC remained to be further elucidated.

Objective:

The present study aimed to explore the roles of centromere protein family members in NSCLC.

Method:

GEPIA (http://gepia.cancer-pku.cn/) was used to analyze the target’s expression between normal and human cancers. We explored the prognostic value of centromere proteins in NSCLC using the Kaplan–Meier plotter (http://kmplot.com). The protein-protein interaction among centromere proteins were determined using GeneMANIA (http://www.genemania.org). TISIDB (http://cis.hku.hk/TISIDB) database was used to detect the relationship between centromere proteins expression and clinical stages, lymphocytes, immunomodulators and chemokines in NSCLC. The DAVID database (https://david.ncifcrf.gov) was used to detect potential roles of CENPK using its co-expressing genes

Results:

The present study for the first time showed that centromere protein family members including CENPA, CENPF, CENPH, CENPI, CENPK, CENPM, CENPN, CENPO, CENPQ, CENPU were dysregulated and correlated to the poor prognosis of patients with LUAD. CENPK showed the greatest correlation with the prognosis of patients with NSCLC. We found that CENPK was significantly highly expressed in LUAD samples and overexpression of CENPK was remarkably correlated to the shorter OS and DFS on patients with different stage NSCLC. Of note, this study for the first time showed that CENPK was significantly correlated to the lymphocytes and immunomodulators using the TISIDB database

Conclusion:

In summary, CENPK can serve as a novel biomarker for the diagnosis of patients with NSCLC.

Transcriptome analysis revealed CENPF associated with glioma prognosis

Gliomas are common malignant tumors of the central nervous system. Despite the surgical resection and postoperative radiotherapy and chemotherapy, the prognosis of glioma remains poor. Therefore, it is important to reveal the molecular mechanisms that promotes glioma progression. Microarray datasets were obtained from the Gene Expression Omnibus (GEO) database. The GEO2R tool was used to identify 428 differentially expressed genes (DEGs) and a core module from three microarray datasets. Heat maps were drawn based on DEGs. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed using the DAVID database. The core module was significantly involved in several KEGG pathways, such as "cell cycle", "viral carcinogenesis", "progesterone-mediated oocyte maturation", "p53 signaling pathway". The protein-protein interaction (PPI) networks and modules were built using the STRING database and the MCODE plugin, respectively, which were visualized using Cytoscape software. Identification of hub genes in the core module using the CytoHubba plugin. The top modular genes AURKA, CDC20, CDK1, CENPF, and TOP2A were associated with glioma development and prognosis. In the Human Protein Atlas (HPA) database, CDC20, CENPF and TOP2A have significant protein expression. Univariate and multivariate cox regression analysis showed that only CENPF had independent influencing factors in the CGGA database. GSEA analysis found that CENPF was significantly enriched in the cell cycle, P53 signaling pathway, MAPK signaling pathway, DNA replication, spliceosome, ubiquitin-mediated proteolysis, focal adhesion, pathway in cancer, glioma, which was highly consistent with previous studies. Our study revealed a core module that was highly correlated with glioma development. The key gene CENPF and signaling pathways were identified through a series of bioinformatics analysis. CENPF was identified as a candidate biomarker molecule.

CENPF promotes papillary thyroid cancer progression by mediating cell proliferation and apoptosis

Papillary thyroid cancer (PTHCA) accounts for ~85% cases of thyroid cancer and exhibits high incidence. Targeted therapy is an effective method to combat this disease; however, novel therapeutic targets are required. Centromere protein F (CENPF), a member of centromere proteins and a transient kinetochore protein, regulates various cellular processes such as cell migration and mitosis, and its upregulation has been observed in multiple types of cancer, including breast cancer and gastric cancer. However, the potential role of CENPF in PTHCA progression is remains unclear. The results of the current study demonstrated that CENPF expression was enhanced in human PTHCA tissues through IHC assays. Furthermore, the expression of CENPF was correlated with the prognosis and the clinicopathological features, including T stage (P=0.021) and intraglandular dissemination (P=0.042) in patients with PTHCA. CENPF regulated the proliferation, apoptosis and cell cycle of PTHCA cells in vitro, which was confirmed through colony formation, MTT and flow cytometry assays, and affected tumor growth in vivo in mice. In conclusion, the current study reported the involvement of CENPF in PTHCA progression and provided a promising therapeutic target for PTHCA treatment.

Identification of the Hub Genes Associated with the Prognosis of Ovarian Cancer Patients via Integrated Bioinformatics Analysis and Experimental Validation

Background

This study aimed to identify the hub genes associated with prognosis of patients with ovarian cancer by using integrated bioinformatics analysis and experimental validation.

Methods

Four microarray datasets (GSE12470, GSE14407, GSE18521 and GSE46169) were analyzed by the GEO2R tool to screen common differentially expressed genes (DEGs). Gene Ontology, the Kyoto Encyclopedia of Genes and Genomes, the (KEGG) pathway and Reactome pathway enrichment analysis, protein–protein interaction (PPI) construction, and the identification of hub genes were performed. Furthermore, we performed the survival and expression analysis of the hub genes. In vitro functional assays were performed to assess the effects of hub genes on ovarian cancer cell proliferation, caspase-3/7 activity and invasion.

Results

A total of 89 common DEGs were identified among these four datasets. The KEGG and Reactome pathway results showed that the DEGs were mainly associated with cell cycle, mitotic and p53 signaling pathway. A total of 20 hub genes were identified from the PPI network by using sub-module analysis. The survival analysis revealed that high expression of six hub genes (AURKA, BUB1B, CENPF, KIF11, KIF23 and TOP2A) were significantly correlated with shorter overall survival and progression-free survival of patients with ovarian cancer. Furthermore, the expression of the six hub genes were validated by the GEPIA database and Human Protein Atlas, and functional studies revealed that knockdown of KIF11 and KIF23 suppressed the SKOV3 cell proliferation, increased caspase-3/7 activity and attenuated invasive potentials of SKOV3 cells. In addition, knockdown of KIF11 and KIF23 up-regulated E-cadherin mRNA expression but down-regulated N-cadherin and vimentin mRNA expression in SKOV3 cells.

Conclusion

Our results showed that six hub genes were up-regulated in ovarian cancer tissues and may predict poor prognosis of patients with ovarian cancer. KIF11 and KIF23 may play oncogenic roles in ovarian cancer cell progression via promoting ovarian cancer cell proliferation and invasion.

Overexpression of CENPF is associated with progression and poor prognosis of lung adenocarcinoma

Background and aim: The molecular signatures of lung adenocarcinoma (LUAD) are not well understood. Centromere protein F (CENPF) has been shown to promote oncogenesis in many cancers; however, its role in LUAD has not been illustrated. We explored the role of CENPF in LUAD. Methods: CENPF expression level was investigated in public online database firstly, the prognosis of CENPF in LUAD were also assessed by Kaplan-Meier analysis. Then quantitative reverse transcription-polymerase chain reaction (qRT-PCR) was performed using 13 matched pairs of clinical LUAD tissue samples. Subsequently, the impact of CENPF expression on cell proliferation, cell cycle, apoptosis, colony formation was investigated by 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl tetrazolium bromide (MTT), flow cytometric analysis and colony formation assay, respectively. Finally, experimental xenograft lung cancer model of nude mice armpit of right forelimb to determine the effect of CENPF on LUAD tumorigenesis. Results: CENPF mRNA expression was significantly elevated in LUAD tissues compared with adjacent non-tumor lung tissues in Gene Expression Profiling Interactive Analysis (GEPIA) (P < 0.001). Up-regulated CENPF was remarkably positively associated with pathological stage, relapse free survival (RFS) as well as overall survival (OS) of LUAD patients. Besides, CENPF knockdown greatly suppressed A549 cell proliferation, induced S phase arrest, promoted apoptosis and decreased colony numbers of LUAD cells. Furthermore, knockdown of CENPF significantly inhibited the tumor growth of the LUAD cells in an experimental xenograft lung cancer model of nude mice armpit of right forelimb. Conclusion: Taken together, these results demonstrated that CENPF may serve as a potential biomarker of prognostic relevance and a potential therapeutic target for LUAD.

TOP2A and CENPF are synergistic master regulators activated in cervical cancer

Background

Identification of master regulators (MRs) using transcriptome data in cervical cancer (CC) could help us to develop biomarkers and find novel drug targets to fight this disease.

Methods

We performed differential expression (DE) analyses of public microarray and RNA-seq transcriptome data of CC and normal cervical tissues (N). Virtual Inference of Protein activity by Enriched Regulon analysis (VIPER) was used to convert the DE outcomes to differential activity (DA) signature for MRs. Synergy analysis was conducted to study synergistic effect of MR-pairs. TCGA and microarray data were used to test the association of expression of a MR and a clinical feature or a molecular feature (e.g. somatic mutations). Various bioinformatic tools/websites (DAVID, GEPIA2, Oncomine, cBioPortal) were used to analyze the expression of the top MRs and their regulons.

Results

Ten DE and 10 DA signatures were generated for CC. Two MRs, DNA topoisomerase II alpha (TOP2A) and centromere protein F (CENPF) were found to be up-regulated, activated and synergistic in CC compared to N across the 10 datasets. The two MRs activate a common set of genes (regulons) with functions in cell cycle, chromosome, DNA damage etc. Higher expression of CENPF was associated with metastasis. High expression of both MRs is associated with somatic mutation of a set of genes including tumor suppressors (TP53, MSH2, RB1) and genes involved in cancer pathways, cell cycle, DNA damage and repair. The magnitude of up-regulation and the absolute expression level of both MRs in CC are significantly higher compared to many other cancer types.

Conclusion

TOP2A and CENPF are a synergistic pair of MRs that are overexpressed and activated in CC. Their high expression is correlated with some prognosis features (e.g. metastasis) and molecular features (e.g. somatic mutations) and distinctly high in CC vs. many other cancer types. They may be good biomarkers and anticancer drug targets for CC.

Comprehensive analysis of transcriptome data stemness indices identifies key genes for controlling cancer stem cell characteristics in gastric cancer

BACKGROUND

Cancer stem cells (CSCs) are the tumor cell of origin with self-renewing ability and multi-differentiation potency. CSCs can play vital roles in gastric cancer (GC) metastasis and relapse. However, the genes that regulate the stemness maintenance of CSCs in GC patients remain largely unknown. In the present study, we sought to determine the key genes associated with stemness in GC patients.

METHODS

mRNA expression-based stemness index (mRNA SI) was analyzed with regard to the differential expression levels between normal and GC tissues, as well as clinical features and survival outcomes. Weighted gene co-expression network analysis (WGCNA) was performed to identify modules of interest and key genes. The differences in mRNA expression of key genes between normal and GC tissues were calculated by "ggpubr" package in R. Gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) analysis were carried out to annotate the function of key genes. Protein-protein interaction (PPI) and gene co-expression analyses were conducted using STRING and "corrplot" package in R, respectively.

RESULTS

mRNA SI score was markedly increased in GC tumor compared to normal tissues. High mRNA SI score was remarkably associated with more advanced tumor stage and higher pathologic grade, but longer survival times. Based on the results of WGCNA, 19 key genes (i.e., BUB1, BUB1B, KIF14, NCAPH, RACGAP1, KIF15, CENPF, TPX2, RAD54L, KIF18B, TTX, KIF4A, SGO2, PLK4, ARHGAP11A, XRCC2, C1orf112, NCAPG, ORC6) were identified. GO and KEGG functional analyses revealed that these 19 key genes were mainly related to cell proliferation. From PPI and gene co-expression analyses, these 19 key genes were discovered to be intensively associated with each other at both protein and transcription levels.

CONCLUSIONS

our study identified 19 key genes that play vital roles in the stemness maintenance of CSCs in GC patients. Targeting these key genes may help to control CSC characteristics in GC.

OSacc: Gene Expression-Based Survival Analysis Web Tool For Adrenocortical Carcinoma

Gene expression profiling data with long-term clinical follow-up information are great resources to screen, develop, evaluate and validate prognostic biomarkers in translational cancer research. However, an easy-to-use interactive online tool is needed to analyze these profiling and clinical data. In the current work, we developed OSacc (Online consensus Survival analysis of ACC), a web tool that provides rapid and user-friendly survival analysis based on seven independent transcriptomic profiles with long-term clinical follow-up information of 259 ACC patients gathered from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. OSacc allows researchers and clinicians to evaluate the prognostic value of genes of interest by Kaplan–Meier (KM) survival plot with hazard ratio (HR) and log-rank test in ACC. OSacc is freely available at http://bioinfo.henu.edu.cn/ACC/ACCList.jsp.