ZWINT is the next potential target for lung cancer therapy

Four genes shared between rheumatoid arthritis and cervical cancer are associated with cervical cancer prognosis

Rheumatoid arthritis (RA) and cervical cancer (CC) are major global health challenges, yet the molecular connections between these two conditions remain poorly understood. To bridge this gap, our study employs bioinformatics approaches to explore shared genetic pathways and potential biomarkers. We started by identifying differentially expressed genes in RA and CC and then applied WGCNA to detect functionally related gene clusters using gene expression data from the GEO database. Additionally, we constructed protein-protein interaction (PPI) networks and examined the role of the immune microenvironment. To assess the prognostic relevance of key genes in CC, we leveraged survival data from TCGA. Our analysis identified 55 key genes common to RA and CC, with four-CXCL1, CXCL13, ZWINT, and PTTG1-emerging as significant. ROC curve validation confirmed their diagnostic potential, and a model incorporating these genes was associated with poorer prognosis in CC. Among them, CXCL1 stood out as especially crucial. Our findings suggest a potential link between chronic inflammation, immune dysregulation, and chemokine-related pathways in RA patients, which may contribute to an increased susceptibility to CC.

Transcriptional regulation of DLGAP5 by AR suppresses p53 signaling and inhibits CD8+T cell infiltration in triple-negative breast cancer

Triple-negative breast cancer (TNBC) is a challenging subtype with unclear biological mechanisms. Recently, the transcription factor androgen receptor (AR) and its regulation of the DLGAP5 gene have gained attention in TNBC pathogenesis. In this study, we found a positive correlation between high AR expression and TNBC cell proliferation and growth. Furthermore, we confirmed DLGAP5 as a critical downstream regulator of AR with high expression in TNBC tissues. Knockdown of DLGAP5 significantly inhibited TNBC cell proliferation, migration, and invasion. AR was observed to directly bind to the DLGAP5 promoter, enhancing its transcriptional activity and suppressing the activation of the p53 signaling pathway. In vivo experiments further validated that downregulation of AR or DLGAP5 inhibited tumor growth and enhanced CD8+T cell infiltration. This study highlights the crucial roles of AR and DLGAP5 in TNBC growth and immune cell infiltration. Taken together, AR inhibits the p53 signaling pathway by promoting DLGAP5 expression, thereby impacting CD8+T cell infiltration in TNBC.

A robust six-gene prognostic signature based on two prognostic subtypes constructed by chromatin regulators is correlated with immunological features and therapeutic response in lung adenocarcinoma

Accumulating evidence has demonstrated that chromatin regulators (CRs) regulate immune cell infiltration and are correlated with prognoses of patients in some cancers. However, the immunological and prognostic roles of CRs in lung adenocarcinoma (LUAD) are still unclear. Here, we systematically revealed the correlations of CRs with immunological features and the survival in LUAD patients based on a cohort of gene expression datasets from the public TCGA and GEO databases and real RNA-seq data by an integrative analysis using a comprehensive bioinformatics method. Totals of 160 differentially expressed CRs (DECRs) were identified between LUAD and normal lung tissues, and two molecular prognostic subtypes (MPSs) were constructed and evaluated based on 27 prognostic DECRs using five independent datasets (p =0.016, <0.0001, =0.008, =0.00038 and =0.00055, respectively). Six differentially expressed genes (DEGs) (CENPK, ANGPTL4, CCL20, CPS1, GJB3, TPSB2) between two MPSs had the most important prognostic feature and a six-gene prognostic model was established. LUAD patients in the low-risk subgroup showed a higher overall survival (OS) rate than those in the high-risk subgroup in nine independent datasets (p <0.0001, =0.021, =0.016, =0.0099, <0.0001, =0.0045, <0.0001, =0.0038 and =0.00013, respectively). Six-gene prognostic signature had the highest concordance index of 0.673 compared with 19 reported prognostic signatures. The risk score was significantly correlated with immunological features and activities of oncogenic signaling pathways. LUAD patients in the low-risk subgroup benefited more from immunotherapy and were less sensitive to conventional chemotherapy agents. This study provides novel insights into the prognostic and immunological roles of CRs in LUAD.

ZWINT promotes the proliferation, migration, and invasion of cervical cancer cells by regulating the p53/p21 signaling pathway

Cervical cancer leads to 300,000 deaths annually and the mechanism of cervical carcinogenesis remains unclear. Zeste White 10-interacting kinetochore protein (ZWINT) is uniquely elevated in malignancies, promoting proliferation, migration, and colony formation of cancer cells. To investigate the role of ZWINT in proliferation, migration, invasion of cervical cancer, and evaluate the potential ability of ZWINT as a therapeutic target. First, ZWINT expression in cervical cancer was analyzed using the bioinformatic methods and assessed in several cervical cancer cell lines. The cell viability and colony formation assays were used to evaluate cell proliferation. Then, transwell assay was performed to investigate cell migration and invasion. Moreover, western blot was used to measure the expression level of ZWINT, matrix metalloproteinase 9 (MMP-9), N-cadherin, E-cadherin, p53 and p21 in CaSki and HeLa cells with ZWINT overexpression or knockdown. The bioinformatic analysis and western blot assay revealed the expression of ZWINT was significantly increased in cervical cancer. The cell viability and colony formation analysis illustrated that cell proliferation could be promoted by ZWINT overexpression and suppressed by ZWINT knockdown. Moreover, ZWINT promoted migration and invasion of CaSki and HeLa cells, through regulating the expression of MMP-9, N-cadherin, and E-cadherin. Furthermore, ZWINT attenuated the expression of p53 and p21 in cervical cancer cells. In summary, ZWINT functions in promoting cell proliferation, migration, and invasion of cervical cancer cells by suppressing p53/p21 signaling pathway, which indicated ZWINT is a potential therapeutic target for cervical cancer treatment.

Retracted: Up-regulated Linc00472 suppresses development of lung cancer cell via inhibition of MiR-196b-5p

The role of linc00472 in lung cancer (LC) has been rarely reported. We aimed to study the role of linc00472 in LC progression. Expressions of linc00472 and miR-196b-5p in LC cell lines were measured by qRT-PCR. The targeting relationship between linc00472 and miR-196b-5p was determined by Starbase and dual-luciferase reporter. The viability, migration, invasion, and apoptosis of LC cells were determined using CCK-8 assay, scratch test, transwell assay, and flow cytometry, respectively. The levels of epithelial-to-mesenchymal transition (EMT)-related proteins and apoptosis-related proteins in LC cells were determined by western blot. Down-regulated linc00472 was observed in five LC cell lines. Linc00472 overexpression suppressed viability, migration, invasion and EMT process, but elevated apoptotic rate in LC cells. MiR-196b-5p mimic promoted viability, migration, invasion, and EMT process, but decreased apoptotic rate, which was reversed by up-regulated linc00472. Linc00472 functioned as a cancer suppressor via negatively regulating miR-196b-5p of LC cells.

Identifying General Tumor and Specific Lung Cancer Biomarkers by Transcriptomic Analysis

The bioinformatic pipeline previously developed in our research laboratory is used to identify potential general and specific deregulated tumor genes and transcription factors related to the establishment and progression of tumoral diseases, now comparing lung cancer with other two types of cancer. Twenty microarray datasets were selected and analyzed separately to identify hub differentiated expressed genes and compared to identify all the deregulated genes and transcription factors in common between the three types of cancer and those unique to lung cancer. The winning DEGs analysis allowed to identify an important number of TFs deregulated in the majority of microarray datasets, which can become key biomarkers of general tumors and specific to lung cancer. A coexpression network was constructed for every dataset with all deregulated genes associated with lung cancer, according to DAVID’s tool enrichment analysis, and transcription factors capable of regulating them, according to oPOSSUM´s tool. Several genes and transcription factors are coexpressed in the networks, suggesting that they could be related to the establishment or progression of the tumoral pathology in any tissue and specifically in the lung. The comparison of the coexpression networks of lung cancer and other types of cancer allowed the identification of common connectivity patterns with deregulated genes and transcription factors correlated to important tumoral processes and signaling pathways that have not been studied yet to experimentally validate their role in lung cancer. The Kaplan–Meier estimator determined the association of thirteen deregulated top winning transcription factors with the survival of lung cancer patients. The coregulatory analysis identified two top winning transcription factors networks related to the regulatory control of gene expression in lung and breast cancer. Our transcriptomic analysis suggests that cancer has an important coregulatory network of transcription factors related to the acquisition of the hallmarks of cancer. Moreover, lung cancer has a group of genes and transcription factors unique to pulmonary tissue that are coexpressed during tumorigenesis and must be studied experimentally to fully understand their role in the pathogenesis within its very complex transcriptomic scenario. Therefore, the downstream bioinformatic analysis developed was able to identify a coregulatory metafirm of cancer in general and specific to lung cancer taking into account the great heterogeneity of the tumoral process at cellular and population levels.

Potential molecular target screening and bioinformatics analysis of cholangiocarcinoma based on GEO database

BACKGROUND

Cholangiocarcinoma is a highly malignant tumor with a poor prognosis. Targeted therapy is important for the treatment of cholangiocarcinoma, and it is therefore of great clinical importance to identify novel molecular targets for targeted therapy of this malignancy.

AIM

To identify potential molecular targets for the treatment of cholangiocarcinoma and identify the key genes involved in cholangiocarcinoma by bioinformatics analysis.

METHODS

We downloaded two sets of cholangiocarcinoma expression profile data from GEO database. GEO2R online analysis tool was used to screen differentially expressed genes in cholangiocarcinoma tumor tissues and normal tissues, and we performed GO enrichment analysis, KEGG pathway analysis, and protein interaction network for differentially expressed genes. We used Cytoscape software to calculate key genes. The GEPIA database was used to verify the expression of hub genes in cholangiocarcinoma tissues.

RESULTS

A total of 158 differentially expressed genes were identified. GO enrichment analysis showed that these differential genes were mainly involved in the cellular response to zinc ion, negative regulation of growth, cell adhesion, metabolic process, and protein homotetramerization. They were enriched in exosomes, extracellular spaces, elastic fibers, and organelle membranes. The main molecular functions are related to heparin binding, cysteine-type endopeptidase inhibitor activity, protein homodimerization activity, receptor binding, and pyridoxal phosphate binding. KEGG pathway analysis showed that differential genes are mainly involved in processes such as mineral absorption, carbon and propanoate metabolism, PPAR signaling pathway, and fatty acid degradation. A protein interaction network diagram was constructed based on the String database, and the CytoHubba plug-in of the Cytoscape software was used to calculate the key genes. The key genes were all up-regulated ones. GEPIA analysis verified that the expression of key genes in cholangiocarcinoma tissues was significantly higher than that in normal tissues.

CONCLUSION

In this study, eight key genes related to cholangiocarcinoma were identified, including NUSAP1, TOP2A, RAD51AP1, MCM4, KIAA0101, CDCA5, TYMS, and ZWINT. These genes provide new ideas for in-depth study of the targeted therapy of cholangiocarcinoma, and are expected to become new molecular therapeutic targets.

Identification of Master Regulators Driving Disease Progression, Relapse, and Drug Resistance in Lung Adenocarcinoma

Backgrounds: Lung cancer is the leading cause of cancer related death worldwide. Current treatment strategies primarily involve surgery, chemotherapy, radiotherapy, targeted therapy, and immunotherapy, determined by TNM stages, histologic types, and genetic profiles. Plenty of studies have been trying to identify robust prognostic gene expression signatures. Even for high performance signatures, they usually have few shared genes. This is not totally unexpected, since a prognostic signature is associated with patient survival and may contain no upstream regulators. Identification of master regulators driving disease progression is a vital step to understand underlying molecular mechanisms and develop new treatments.

Methods: In this study, we have utilized a robust workflow to identify potential master regulators that drive poor prognosis in patients with lung adenocarcinoma. This workflow takes gene expression signatures that are associated with poor survival of early-stage lung adenocarcinoma, EGFR-TKI resistance, and responses to immune checkpoint inhibitors, respectively, and identifies recurrent master regulators from seven public gene expression datasets by a regulatory network-based approach.

Results: We have found that majority of the master regulators driving poor prognosis in early stage LUAD are cell-cycle related according to Gene Ontology annotation. However, they were demonstrated experimentally to promote a spectrum of processes such as tumor cell proliferation, invasion, metastasis, and drug resistance. Master regulators predicted from EGFR-TKI resistance signature and the EMT pathway signature are largely shared, which suggests that EMT pathway functions as a hub and interact with other pathways such as hypoxia, angiogenesis, TNF-α signaling, inflammation, TNF-β signaling, Wnt, and Notch signaling pathways. Master regulators that repress immunotherapy are enriched with MYC targets, E2F targets, oxidative phosphorylation, and mTOR signaling.

Conclusion: Our study uncovered possible mechanisms underlying recurrence, resistance to targeted therapy, and immunotherapy. The predicted master regulators may serve as potential therapeutic targets in patients with lung adenocarcinoma.

Hypoxia-Induced ZWINT Mediates Pancreatic Cancer Proliferation by Interacting With p53/p21

p53/p21 signaling plays a vital role in pancreatic cancer (PC) progression. ZWINT was shown to function as an oncoprotein in the progression of multiple cancers. However, the involvement of ZWINT and p53 activation in the progression of PC remains poorly understood. Bioinformatics and tissue array chip analyses were performed to evaluate ZWINT expression in pancreatic cancer. ZWINT mRNA and protein expression were evaluated in normoxia and hypoxia. CHIP was used to evaluate HIF1α interaction with the ZWINT promoter. CCK8, colony formation, EDU, and cell cycle analysis were used to examine PC cell proliferation. Immunoprecipitation and immunofluorescence were used to examine the interaction of ZWINT, MDM2, and p53. p53 activity was evaluated by q-PCR and luciferase assay. Protein degradation and ubiquitination assays were used to analyze the role of ZWINT in p53 ubiquitination. ZWINT was overexpressed in pancreatic cancer and induced in hypoxia. ZWINT promoted pancreatic cancer growth and cell cycle progression. Bioinformatic analysis revealed that ZWINT may regulate the p53 signal pathway. ZWINT interacts with p53 and promotes its ubiquitination and degradation. ZWINT promoted proliferation via p53/p21. Immunohistochemistry of clinical specimens revealed that that ZWINT expression was significantly negatively correlated with p53/p21. Our data showed that hypoxia regulates the expression of ZWINT, which activated p53/p21 signaling pathway to promote PC growth.

Zwint facilitates melanoma progression by promoting c-Myc expression

ZW10 interactor (Zwint) is upregulated in various types of tumors and exerts a carcinogenic effect. However, little is known about the expression profile, function and molecular mechanisms of action of Zwint in melanoma. Therefore, the aim of the present study was to investigate the expression levels of Zwint in melanoma cell lines and tissues. It was revealed that Zwint was highly expressed in melanoma samples. Functional experiments indicated that Zwint knockdown suppressed the proliferation and migration of A375 melanoma cells. Further mechanistic studies demonstrated that Zwint knockdown decreased the protein expression levels of c-Myc, MMP-2, Slug, mTOR, phosphorylated (p)-mTOR, p-p38 and fibronectin, while it increased the protein expression levels of E-cadherin and MMP-9. Among these genes, c-Myc, MMP-2 and Slug were overexpressed to investigate their effects on cell proliferation following Zwint knockdown. The results demonstrated that overexpression of c-Myc, but not MMP-2 or Slug, rescued the effects of Zwint knockdown on melanoma cell proliferation and migration. Taken together, the results of the present study suggested that Zwint may act as an oncogene in melanoma by regulating c-Myc expression.

Genome-wide association analysis of cognitive function in Danish long-lived individuals

Cognitive function is a substantially heritable trait related to numerous important life outcomes. Several genome-wide association studies of cognitive function have in recent years led to the identification of thousands of significantly associated loci and genes. Individuals included in these studies have rarely been nonagenarians and centenarians, and since cognitive function is an important component of quality of life for this rapidly expanding demographic group, there is a need to explore genetic factors associated with individual differences in cognitive function at advanced ages. In this study, we pursued this by performing a genome-wide association study of cognitive function in 490 long-lived Danes (age range 90.1-100.8 years). While no genome-wide significant SNPs were identified, suggestively significant SNPs (P < 1 × 10^-5) were mapped to several interesting genes, including ZWINT, CELF2, and DNAH5, and the glutamate receptor genes GRID2 and GRM7. Additionally, results from a gene set over-representation analysis indicated potential roles of gene sets related to G protein-coupled receptor (GPCR) signaling, interaction between L1 and ankyrins, mitogen-activated protein kinase (MAPK) signaling, RNA degradation, and cell cycle. Larger studies are needed to shed further light on the possible importance of these suggestive genes and pathways in cognitive function in nonagenarians and centenarians.

Prognostic and Clinicopathological Value of ZWINT Expression Levels in Patients with Lung Adenocarcinoma: A Systematic Review and Meta-analysis

The current study found that high Zeste White 10 interactor (ZWINT) expression is related to the poor prognosis of patients with a variety of cancers. This study mainly explored the relationship between the expression level of ZWINT and the prognosis of patients with lung adenocarcinoma (LUAD). Briefly, four English databases and two high-throughput sequencing databases were searched and relevant data for meta-analysis were extracted. Pooled mean difference and 95% confidence interval (CI) were used to assess the relationships between clinical features and the expression of ZWINT. Pooled hazard ratio and 95% CI were also used to assess the relationships between clinical features and the expression level of ZWINT. This meta-analysis was registered in PROSPERO (CRD42021249475). A total of 16 high-quality datasets comprising 2,847 LUAD patients were included in this study. Higher ZWINT expression levels were found in patients younger than 65 years, males, and smokers, and were correlated with advanced TNM stages and poor prognosis. Notably, there was no publication bias in this meta-analysis. Overall, our findings indicate that ZWINT is a potential biomarker for poor prognosis and clinicopathological outcomes of patients with LUAD.

Pulsatilla saponin E suppresses viability, migration, invasion and promotes apoptosis of NSCLC cells through negatively regulating Akt/FASN pathway via inhibition of flotillin-2 in lipid raft

PURPOSE

Pulsatilla saponins from pulsatilla chinensis (Bunge) Regel have potential anti-tumor activities to certain human cancers. However, the roles of pulsatilla saponin E separated from pulsatilla saponins in non-small cell lung cancer (NSCLC) have not been reported.

MATERIALS AND METHODS

After treating NSCLC cells by pulsatilla saponin E at different concentrations, cell viability was measured by MTT and CCK-8 assays, and cell migration, invasion and apoptosis were detected by scratch wound-healing, transwell and flow cytometry assays. The contents of free cholesterol (FC) and total cholesterol (TC) were measured by high performance liquid chromatography (HPLC). The expression levels of flotillin-1, flotillin-2, Akt, fatty acid synthase (FASN) were detected by qRT-PCR and Western blot assays.

RESULTS

Pulsatilla saponin E suppressed viability, migration, invasion and promoted apoptosis of NSCLC cells followed by regulation of apoptosis-related proteins, reduced contents of FC and TC, and the expression levels of flotillin-1, flotillin-2, Akt, and FASN in a concentration-dependent manner. However, the inhibitory effects of pulsatilla saponin E on viability, migration, invasion of A549 cells and the expression levels of flotillin-1, flotillin-2, Akt, and FASN were reversed by flotillin-2 overexpression.

CONCLUSIONS

Our study revealed that pulsatilla saponin E suppressed migration, invasion and promoted apoptosis of NSCLC cells through negatively regulating Akt/FASN signaling pathway via the inhibition of flotillin-2 in lipid raft (LR). The current findings could be explored for developing a novel therapeutic drug for NSCLC treatment.

Involvement of the NF-κB signaling pathway in proliferation and invasion inhibited by Zwint-1 deficiency in Pancreatic Cancer Cells

Pancreatic cancer (PC) is an intractable cancer that is difficult to diagnose early and has a 5-year survival rate of less than 8%. ZW10-interacting kinetochore protein (ZWINT) is a crucial gene that contributes to chromosome instability and is essential for spindle assembly and kinetochore-microtubule attachment during meiosis and mitosis. However, the mechanism through which Zwint-1 promotes PC progression is yet to be elucidated. Here, we report that Zwint-1 is highly expressed in clinical PC specimens (based on analysis of the Gene Expression Profiling Interactive Analysis database) and various PC cell lines. Importantly, Zwint-1-deficient PC cells showed reduced nuclear factor-kappa B (NF-κB) (Ser536) phosphorylation along with inhibited proliferation and colony formation due to downregulation of NF-κB-regulated genes such as CCND1, cIAP1/2, and XIAP. In addition, Zwint-1-deficient PC cells showed reduced invasion and migration abilities, and decreased expression levels of the metalloproteinases MMP2 and MMP9. Furthermore, Zwint-1 deficiency arrested the PC cell cycle at the G2/M phase because the chromosomes failed to segregate properly, and the apoptosis rate in these cells gradually increased, accompanied by increased caspase-3 activation and anti-poly (ADP ribose) polymerase cleavage. Apoptosis caused by Zwint-1 deficiency was demonstrated to occur through caspase-dependent pathways based on experiments involving treatment with a pan-caspase inhibitor (Z-VAD-Fmk). Thus, Zwint-1 contributes to cell growth, invasion, and survival through NF-κB signaling pathways, suggesting that it could serve as a PC biomarker and new therapeutic target.

A tumor-specific modulation of heterogeneous ribonucleoprotein A0 promotes excessive mitosis and growth in colorectal cancer cells

RNA regulation mediating RNA-binding proteins (RBPs) have been shown to be related to the maintenance of homeostasis as well as cancer progression. However, the tumor-associated functions as well as the detailed mechanisms underlying the anti-tumor effects of most RBPs have yet to be explored. We herein report that the phosphorylated heterogeneous ribonucleoprotein (hnRNP) A0 promotes mitosis through the RAS-associated protein 3 GTPase-activating protein catalytic subunit 1 (RAB3GAP1)-Zeste white 10 interactor (ZWINT1) cascade. The downregulation assay of 20 representative hnRNPs, a major family of RNA-binding proteins, in colorectal cancer cells revealed that hnRNPA0 is a strong regulator of cancer cell growth. The tumor promotive function of hnRNPA0 was confirmed in gastrointestinal cancer cells, including pancreatic, esophageal, and gastric cancer cells, but not in non-cancerous cells. Flow cytometry and Western blotting analyses revealed that hnRNPA0 inhibited the apoptosis through the maintenance of G2/M phase promotion in colorectal cancer cells. A comprehensive analysis of mRNAs regulated by hnRNP A0 and immunostaining revealed that mitotic events were regulated by the hnRNPA0-RAB3GAP1 mRNA-mediated ZWINT-1 stabilization in colorectal cancer cells, but not in non-tumorous cells. The interaction of hnRNP A0 with mRNAs was dramatically changed by the deactivation of its phosphorylation site in cancer cells, but not in non-tumorous cells. Therefore, the tumor-specific biological functions characterized by the abnormal phosphorylation of RBPs are considered to be an attractive target for tumor treatment.

ZW10 Binding Factor (ZWINT), a Direct Target of Mir-204, Predicts Poor Survival and Promotes Proliferation in Breast Cancer

BACKGROUND ZW10 binding factor (ZWINT) has been reported to be upregulated in various human cancers and predict worse survival. However, the expression profile, clinical significance, and biological role of ZWINT remains unclear in breast cancer. MATERIAL AND METHODS In this study, we investigated messenger RNA (mRNA) and protein expression levels of ZWINT in breast cancer tissues, and the prognostic value of ZWINT protein expression was validated in a cohort of breast cancer patients using immunohistochemistry analysis. Then, different bioinformatic analyses were combined to explore the potential cancer-related hallmark underlying ZWINT in breast cancer, and a series of experiments in vitro were performed to reveal the oncogenic role of ZWINT in breast cancer. RESULTS Significant upregulation of ZWINT was observed in breast cancer tissues compared to normal and para-tumor tissues and upregulation of ZWINT predicts poor prognosis in breast cancer patients. Additionally, ZWINT could promote breast cancer proliferation via cell cycle regulation, especially by influencing the expression of some critical cell cycle regulators involved in G1 phase and G1/S transition. Finally, miR-204 was identified as a tumor suppressor microRNA which directly targets a specific site in 3'-UTR of ZWINT. CONCLUSIONS Overall, our results indicated that miR-204/ZWINT/cell cycle process might play an important role in breast cancer progression.

ZWINT: A potential therapeutic biomarker in patients with glioblastoma correlates with cell proliferation and invasion

Glioblastoma (GBM) is the most aggressive primary intracranial tumor in adults. Chemoradiotherapy resistance and recurrence after surgery are the main malignant progression factors, leading to a high mortality rate. Therefore, the exploration of novel biomarkers and molecular mechanisms of GBM is urgent. Differentially expressed genes (DEGs) of GBM were screened in a TCGA dataset. Homo sapiens ZW10 interacting kinetochore protein (ZWINT) was found to be upregulated in GBM, which was confirmed by immunohistochemical staining of a tissue microarray. Gene Ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed using the Database for Annotation, Visualization and Integrated Discovery (DAVID) database. A protein-protein interaction (PPI) network was established by the STRING database, and hub genes were visualized by Cytoscape. The correlation results were verified with the GSE15824 dataset. Bioinformatic analysis confirmed that ZWINT was significantly positively correlated with kinetochore protein NDC80 homolog (NDC80), serine/threonine-protein kinase PLK1 (PLK1) and spindle and kinetochore associated complex subunit 1 (SKA1) and together are involved in regulating mitosis and the cell cycle of GBM. ZWINT expression was knocked down in U251 and U87 MG GBM cells by lentiviral vectors carrying a small hairpin RNA (shRNA) targeting ZWINT. The effect of ZWINT silencing on cell proliferation, invasion and apoptosis was determined by the Celigo assay, MTT assay, Transwell assay, flow cytometry and caspase-3/7 assay in vitro. A subcutaneous xenograft tumor model was established to explore the influence of ZWINT knockdown on GBM growth in vivo. Our preliminary study demonstrated that ZWINT knockdown effectively inhibited proliferation and invasion and induced apoptosis of GBM cells and notably suppressed GBM growth in vivo. Therefore, we speculate that ZWINT may be a potential therapeutic biomarker for GBM, with NDC80 and PLK1 conjointly involved in regulating cell division and the mitotic cell cycle.

Identifying Tumorigenesis and Prognosis-Related Genes of Lung Adenocarcinoma: Based on Weighted Gene Coexpression Network Analysis

Lung adenocarcinoma is the most frequently diagnosed subtype of nonsmall cell lung cancer. The molecular mechanisms of the initiation and progression of lung adenocarcinoma remain to be further determined. This study aimed to screen genes related to the progression of lung adenocarcinoma. By weighted gene coexpression network analysis (WGCNA), we constructed a free-scale gene coexpression network to evaluate the correlations between multiple gene sets and patients' clinical traits, then further identify predictive biomarkers. GSE11969 was obtained from the Gene Expression Omnibus (GEO) database which contained the gene expression data of 90 lung adenocarcinoma patients. Data of the Cancer Genome Atlas (TCGA) were employed as the validation cohort. After the average linkage hierarchical clustering, a total of 9 modules were generated. In the clinical significant module (R = 0.44, P < 0.0001), we identified 29 network hub genes. Subsequent verification in the TCGA database showed that 11 hub genes (ANLN, CDCA5, FLJ21924, LMNB1, MAD2L1, RACGAP1, RFC4, SNRPD1, TOP2A, TTK, and ZWINT) were significantly associated with poor survival data of lung adenocarcinomas. Besides, the results of receiver operating characteristic curves indicated that the mRNA levels of this group of genes exhibited high specificity and sensitivity to distinguish malignant lesions from nonmalignant tissues. Apart from mRNA levels, we found that the protein abundances of these 11 genes were remarkably upregulated in lung adenocarcinomas compared with normal tissues. In conclusion, by the WGCNA method, a panel of 11 genes were identified as predictive biomarkers for tumorigenesis and poor prognosis of lung adenocarcinomas.

A panel of autoantibodies against tumor-associated antigens in the early immunodiagnosis of lung cancer

OBJECTIVE

Lung cancer (LC) is one of the most common malignant tumors worldwide with low five-year survival rate due to lack of effective diagnosis. This study aims to find an optimal combination of autoantibodies for detecting of early-stage LC.

METHODS

Nine relatively novel autoantibodies against tumor-associated (TAAs) (PSIP1, TOP2A, ACTR3, RPS6KA5, HMGB3, MMP12, GREM1, ZWINT and NUSAP1) were detected by using ELISA. Diagnostic models were developed by using the training set (n = 644) and further validated in another independent set (n = 248). We also evaluated the diagnostic accuracy of the model to detect benign lung diseases (BLD) from the early-stage lung cancer.

RESULTS

The areas under the receiver operating characteristic curve (AUC) for the model with three TAAs panel (GREM1, HMGB3 and PSIP1) was 0.711(95% CI 0.674-0.746) in the training set and 0.858 (95% CI 0.808-0.899) in the validation set, which demonstrated a higher diagnostic capability. The AUC of this three TAAs model was 0.833 (95%CI 0.780-0.878) in discriminating LC from BLD. This model could identify early-stage LC patients from normal control (NC) individuals, with AUC of 0.687(95% CI 0.634-0.736) in training set and AUC of 0.920(95% CI 0.860-0.960) in validation set, and the overall AUC for early-stage LC was 0.779(95% CI 0.739-0.816) when the training set and validation set were combined.

CONCLUSIONS

The model with three TAAs panel would detect LC with higher effectiveness, and might be potential screening method for the early LC.

The overexpression of ZWINT in integrated bioinformatics analysis forecasts poor prognosis in breast cancer

BACKGROUND

Zeste White 10 interactor (ZW10 interactor, ZWINT) is a centromeric complex required for a mitotic spindle checkpoint. According to previous studies, it was overexpressed in people with recurrent tumors. However, the expression of ZWINT in breast cancer has not been thoroughly studied. In addition, the correlations of ZWINT to prognosis in breast cancer remain unclear.

METHODS

In this study, the expression of ZWINT in different types of tumors was analyzed based on the Oncomine database, and the effect of ZWINT expression on clinical prognosis was evaluated by Kaplan-Meier plotter.

RESULTS

In breast cancer, lung cancer, sarcoma, ovarian cancer, bladder cancer, liver cancer and cervical cancer, the expression of ZWINT was higher than that in normal tissues, but in gastric cancer, prostate cancer, myeloma, renal cancer and pancreatic cancer, the expression of ZWINT was lower. In addition, a meta-analysis of 22 cancer database studies found that the ZWINT gene was over-expressed in breast cancer tissues compared with normal tissues (P=4.05×10-6). Through the survival analysis of Kaplan-Meier plotter, it is found that the high expression of ZWINT is related to the worse overall survival (OS) [hazard ratio (HR) =1.73, 95% confidence interval (CI): 1.39-2.51, P=5.4×10-7], RFS (HR =1.68, 95% CI: 1.51-1.88, P<1×10-16) and distant metastasis-free survival (DMFS) (HR =1.55, 95% CI: 1.28-1.89, P=7.9×10-6) in all BC patients.

CONCLUSIONS

Our results strongly suggest that over expression of ZWINT is closely related to poor prognosis of breast cancer. ZWINT may be a prognostic biomarker for the treatment of BC.

Integrated Analysis To Identify Molecular Biomarkers Of High-Grade Serous Ovarian Cancer

Purpose

Ovarian cancer is the leading cause of gynecologic cancer-related death worldwide. Early diagnosis of ovarian cancer can significantly improve patient prognosis. Hence, there is an urgent need to identify key diagnostic and prognostic biomarkers specific for ovarian cancer. Because high-grade serous ovarian cancer (HGSOC) is the most common type of ovarian cancer and accounts for the majority of deaths, we identified potential biomarkers for the early diagnosis and prognosis of HGSOC.

Methods

Six datasets (GSE14001, GSE18520, GSE26712, GSE27651, GSE40595, and GSE54388) were downloaded from the Gene Expression Omnibus database for analysis. Differentially expressed genes (DEGs) between HGSOC and normal ovarian surface epithelium samples were screened via integrated analysis. Hub genes were identified by analyzing protein-protein interaction (PPI) network data. The online Kaplan-Meier plotter was utilized to evaluate the prognostic roles of these hub genes. The expression of these hub genes was confirmed with Oncomine datasets and validated by quantitative real-time PCR and Western blotting.

Results

A total of 103 DEGs in patients with HGSOC-28 upregulated genes and 75 downregulated genes-were successfully screened. Enrichment analyses revealed that the upregulated genes were enriched in cell division and cell proliferation and that the downregulated genes mainly participated in the Wnt signaling pathway and various metabolic processes. Ten hub genes were associated with HGSOC pathogenesis. Seven overexpressed hub genes were partitioned into module 1 of the PPI network, which was enriched in the cell cycle and DNA replication pathways. Survival analysis revealed that MELK, CEP55 and KDR expression levels were significantly correlated with the overall survival of HGSOC patients (P < 0.05). The RNA and protein expression levels of these hub genes were validated experimentally.

Conclusion

Based on an integrated analysis, we propose the further investigation of MELK, CEP55 and KDR as promising diagnostic and prognostic biomarkers of HGSOC.