Prognostic value of DLGAP5 in colorectal cancer

Retracted article: MicroRNA-4521 targets hepatoma up-regulated protein (HURP) to inhibit the malignant progression of breast cancer

Changwen Li, Sen Pengb, and Chuangang Tanga. MicroRNA-4521 targets hepatoma up-regulated protein (HURP) to inhibit the malignant progression of breast cancer. Bioengineered. 2021 Oct. doi: 10.1080/21655979.2021.1996016.Since publication, significant concerns have been raised about the compliance with ethical policies for human research and the integrity of the data reported in the article.When approached for an explanation, the authors provided some original data but were not able to provide all the necessary supporting information. As verifying the validity of published work is core to the scholarly record's integrity, we are retracting the article. All authors listed in this publication have been informed.We have been informed in our decision-making by our editorial policies and the COPE guidelines.The retracted article will remain online to maintain the scholarly record, but it will be digitally watermarked on each page as 'Retracted.'

Integrative approach using network pharmacology, bioinformatics, and experimental methods to explore the mechanism of cantharidin in treating colorectal cancer

Cantharidin, a terpenoid produced by blister beetles, has been used in traditional Chinese medicine to treat various ailments and cancers. However, its biological activity, impact, and anticancer mechanisms remain unclear. The Cantharidin chemical gene connections were identified using various databases. The GSE21815 dataset was used to collect the gene expression information. Differential gene analysis and gene ontology analyses were performed. Gene set enrichment analysis was used to assess the activation of disease pathways. Weighted gene co-expression network analysis and differential analysis were used to identify illness-associated genes, examine differential genes, and discover therapeutic targets via protein-protein interactions. MCODE analysis of major subgroup networks was used to identify critical genes influenced by Cantharidin, examine variations in the expression of key clustered genes in colorectal cancer vs. control samples, and describe the subject operators. Single-cell GSE188711 dataset was preprocessed to investigate Cantharidin's therapeutic targets and signaling pathways in colorectal cancer. Single-cell RNA sequencing was utilized to identify 22 cell clusters and marker genes for two different cell types in each cluster. The effects of different Cantharidin concentrations on colorectal cancer cells were studied in vitro. One hundred and ninety-seven Cantharidin-associated target genes and 480 critical genes implicated in the development of the illness were identified. Cantharidin significantly inhibited the proliferation and migration of HCT116 cells and promoted apoptosis at certain concentrations. Patients on current therapy develop inherent and acquired resistance. Our study suggests that Cantharidin may play an anti-CRC role by modulating immune function.

Identification of Hub Genes for Psoriasis and Cancer by Bioinformatic Analysis

Psoriasis increases the risk of developing various cancers, including colon cancer. The pathogenesis of the co-occurrence of psoriasis and cancer is not yet clear. This study is aimed at analyzing the pathogenesis of psoriasis combined with cancer by bioinformatic analysis. Skin tissue data from psoriasis (GSE117239) and intestinal tissue data from colon cancer (GSE44076) were downloaded from the GEO database. One thousand two hundred ninety-six common differentially expressed genes and 688 common shared genes for psoriasis and colon cancer were determined, respectively, using the limma R package and weighted gene coexpression network analysis (WGCNA) methods. The results of the GO and KEGG enrichment analyses were mainly related to the biological processes of the cell cycle. Thirteen hub genes were selected, including AURKA, DLGAP5, NCAPG, CCNB1, NDC80, BUB1B, TTK, CCNB2, AURKB, TOP2A, ASPM, BUB1, and KIF20A. These hub genes have high diagnostic value, and most of them are positively correlated with activated CD4 T cells. Three hub transcription factors (TFs) were also predicted: E2F1, E2F3, and BRCA1. These hub genes and hub TFs are highly expressed in various cancers. Furthermore, 251 drugs were predicted, and some of them overlap with existing therapeutic drugs for psoriasis or colon cancer. This study revealed some genetic mechanisms of psoriasis and cancer by bioinformatic analysis. These hub genes, hub TFs, and predicted drugs may provide new perspectives for further research on the mechanism and treatment.

Deciphering the miRNA-mRNA Interaction Landscape between Breast Cancer and Triple-Negative Breast Cancer: An Integrated Bioinformatics Approach

Breast cancer (BC) is globally recognized as the second most prevalent form of cancer. It predominantly affects women and can be categorized into distinct types based on the overexpression of specific cancer receptors.The key receptors implicated in this context are the human epidermal growth factor receptor-2 (HER2), estrogen receptor (ER), and progesterone receptor (PR), alongside a particularly intricate subclass known as triple-negative breast cancer (TNBC). This subclassification is critical for the stratification of breast cancer and informs therapeutic decision-making processes. Due to a lack of therapeutic targets, such as growth factor receptors, TNBC is the most aggressive type. Hence, identifying targetable regulators such as miRNAs could pave the way for potential therapeutic interventions. To identify common differentially expressed mRNAs (DE-mRNAs) in BC, including TNBC, we leveraged two data sets from the GEO collection and The Cancer Genome Atlas (TCGA). Significant DE-mRNAs were identified through PPI, MCODE, CytoNCA, and CytoHubba analyses. Following this, miRNAs were predicted using mirDIP. We utilized GSE42568, GSE185645, and TCGA and identified 159 common DE-mRNAs. Using Cytoscape plug-ins, we identified the 10 most significant DE-mRNAs in BC. Using mirDIP, target miRNAs for 10 DE-mRNAs were identified. We conducted an advanced analysis on the TNBC GEO data set (GSE45498) to corroborate the significance of shared DE-mRNAs and DE-miRNAs in TNBC. We identified four downregulated DE-miRNAs, including hsa-miR-802, hsa-miR-1258, hsa-miR-548a-3p, and hsa-miR-2053, significantly associated with TNBC. Our study revealed significant miRNA-mRNA interactions, specifically hsa-miR-802/MELK, hsa-miR-1258/NCAPG, miR-548a-3p/CCNA2, and hsa-miR-2053/NUSAP1, in both BC and TNBC. The observed downregulation of hsa-miR-548a-3p is associated with diminished survival rates in BC patients, emphasizing their potential utility as prognostic indicators. Furthermore, the differential expression of mRNAs, including CCNB2, UBE2C, MELK, and KIF2C, correlates with reduced survival outcomes, signifying their critical role as potential targets for therapeutic intervention in both BC and TNBC. These findings highlight specific regulatory mechanisms that are potentially crucial for understanding and treating these cancer types.

DLGAP5 triggers proliferation and metastasis of bladder cancer by stabilizing E2F1 via USP11

Bladder cancer (BLCA) is one of the most widespread malignancies worldwide, and displays significant tumor heterogeneity. Understanding the molecular mechanisms exploitable for treating aggressive BLCA represents a crucial objective. Despite the involvement of DLGAP5 in tumors, its precise molecular role in BLCA remains unclear. BLCA tissues exhibit a substantial increase in DLGAP5 expression compared with normal bladder tissues. This heightened DLGAP5 expression positively correlated with the tumor's clinical stage and significantly affected prognosis negatively. Additionally, experiments conducted in vitro and in vivo revealed that alterations in DLGAP5 expression notably influence cell proliferation and migration. Mechanistically, the findings demonstrated that DLGAP5 was a direct binding partner of E2F1 and that DLGAP5 stabilized E2F1 by preventing the ubiquitination of E2F1 through USP11. Furthermore, as a pivotal transcription factor, E2F1 fosters the transcription of DLGAP5, establishing a positive feedback loop between DLGAP5 and E2F1 that accelerates BLCA development. In summary, this study identified DLGAP5 as an oncogene in BLCA. Our research unveils a novel oncogenic mechanism in BLCA and offers a potential target for both diagnosing and treating BLCA.

Identification of potential key genes for colorectal cancer based on bioinformatics analysis

This study aimed to explore key genes as potential biomarkers for colorectal cancer (CRC) diagnosis and prognosis in order to improve their clinical utility. To identify and screen candidate genes involved in CRC carcinogenesis and disease progression, we downloaded the microarray datasets GSE143939, GSE196006, and GSE200427 from the GEO database and applied the GEO2R tool to obtain differentially expressed genes (DEGs) between colorectal cancer tissue samples and normal tissue samples. Differentially expressed genes were analyzed using the DAVID online database for gene ontology and Kyoto encyclopedia of genes and genomes pathway enrichment analyses. Protein-protein interaction network was constructed and related module analysis was performed using STRING and Cytoscape. In total, 241 DEGs were identified, including 127 downregulated and 114 upregulated genes. DEGs enriched functions and pathways included cellular response to chemical stimulus, extracellular region, carbonate dehydratase activity, cell division, spindle, and cell division. The abundant functions and pathways of DEGs included cellular response to chemical stimulus, extracellular region, carbonate dehydratase activity, cell division, spindle, cell adhesion molecule binding, Aldosterone-regulated sodium reabsorption, and Cell cycle-related processes. Fifteen key genes were identified, and bioprocess analyses showed that these genes were mainly enriched in cell cycle, cell division, mitotic spindle, and tubulin binding processes. It was found that CDK1, CEP55, MKI67, and TOP2A may be involved in CRC cancer invasion and recurrence. The pivotal genes identified in this study contribute to our understanding of the molecular and pathogenic mechanisms of CRC carcinogenesis and progression, and provide possible biomarkers for the diagnosis and treatment of CRC.

Stemness genes and miR-1247-3p expression associate with clinicopathological parameters and prognosis in lung adenocarcinoma

Lung cancer makes up one-fourth of all cancer-related mortality with the highest mortality rate among all cancers. Despite recent scientific advancements in cancer therapeutics, the 5-year survival rate of lung adenocarcinoma (LUAD) cancer patients remains below 15 percent. It has been suggested that the high mortality rate of LUAD is linked to the acquisition of progenitor-like cells with stem-like characteristics that assist the whole tumor in regulating immune cell infiltration. To examine this hypothesis further, this study mined several databases to explore the presence of stemness-related genes and miRNAs in LUAD cancers. We examine their association with immune and accessory cell infiltration rates and patient survival. We found 3 stem cell-related genes, ORC1L, KIF20A, and DLGAP5, present in LUAD that also correlate with changes in immune infiltration rates and reduced patient survival rates. Additionally, the modulation in myeloid-derived suppressor cell (MDSC) infiltration and miRNA hsa-mir-1247-3p mediated targeting of tumor suppressor SLC24A4 and oncogenes RAB3B and HJURP appears to primarily regulate LUAD patient survival. Given these findings, hsa-mir-1247-3p and/or its associated gene targets may offer a promising avenue to enhance patient survivability.

DLGAP5 knockdown inactivates the Wnt/β-catenin signal to repress endometrial cancer cell malignant activities

Human discs large-associated protein 5 (DLGAP5), a microtubule-associated protein, has been reported to be upregulated in several tumors. However, the role of DLGAP5 in endometrial cancer (EC) progression and the related underlying mechanism were still unknown. A bioinformatics analysis was performed to analyze the expression and prognostic significance of DLGAP5 in EC tissues using TCGA, CPTAC, Human Protein Atlas, and GSE63678 databases, UALCAN web tool, and the Kaplan-Meier plotter. Effects of DLGAP on EC cell malignant properties were evaluated by CCK-8, flow cytometry analysis, TUNEL assay, caspase-3 activity assay, and Transwell invasion assay. The expression of DLGAP5, Wnt3, c-Myc, Ki67, and cleaved caspase-3 was detected by western blot analysis. DLGAP5 was highly expressed and correlated with poor prognosis in EC patients. DLGAP5 knockdown inhibited proliferation and invasion, triggered apoptosis, and increased caspase-3 activity in EC cells. Additionally, DLGAP5 knockdown inactivated the Wnt/β-catenin signaling pathway in EC cells. Moreover, β-catenin overexpression abolished the effects of DLGAP5 knockdown on the malignant phenotypes of EC cells. DLGAP5 silencing suppressed the malignant properties in EC cells by inactivating the Wnt/β-catenin pathway.

Exploring Core Genes by Comparative Transcriptomics Analysis for Early Diagnosis, Prognosis, and Therapies of Colorectal Cancer

Colorectal cancer (CRC) is one of the most common cancers with a high mortality rate. Early diagnosis and therapies for CRC may reduce the mortality rate. However, so far, no researchers have yet investigated core genes (CGs) rigorously for early diagnosis, prognosis, and therapies of CRC. Therefore, an attempt was made in this study to explore CRC-related CGs for early diagnosis, prognosis, and therapies. At first, we identified 252 common differentially expressed genes (cDEGs) between CRC and control samples based on three gene-expression datasets. Then, we identified ten cDEGs (AURKA, TOP2A, CDK1, PTTG1, CDKN3, CDC20, MAD2L1, CKS2, MELK, and TPX2) as the CGs, highlighting their mechanisms in CRC progression. The enrichment analysis of CGs with GO terms and KEGG pathways revealed some crucial biological processes, molecular functions, and signaling pathways that are associated with CRC progression. The survival probability curves and box-plot analyses with the expressions of CGs in different stages of CRC indicated their strong prognostic performance from the earlier stage of the disease. Then, we detected CGs-guided seven candidate drugs (Manzamine A, Cardidigin, Staurosporine, Sitosterol, Benzo[a]pyrene, Nocardiopsis sp., and Riccardin D) by molecular docking. Finally, the binding stability of four top-ranked complexes (TPX2 vs. Manzamine A, CDC20 vs. Cardidigin, MELK vs. Staurosporine, and CDK1 vs. Riccardin D) was investigated by using 100 ns molecular dynamics simulation studies, and their stable performance was observed. Therefore, the output of this study may play a vital role in developing a proper treatment plan at the earlier stages of CRC.

High Expression of DLGAP5 Indicates Poor Prognosis and Immunotherapy in Lung Adenocarcinoma and Promotes Proliferation through Regulation of the Cell Cycle

Background

Lung adenocarcinoma (LUAD) is one of the most common types of cancer in the respiratory system, with a high mortality and recurrence rate. The role of disc large-associated protein 5 (DLGAP5) in LUAD progression and tumor microenvironment (TME) remains unclear. This study is aimed at revealing the functional role of DLGAP5 in LUAD based on bioinformatics analysis and experimental validation.

Methods

Differential expression analysis, protein-protein interaction (PPI) network, and Cox regression analysis were applied to screen potential prognostic biomarkers. The mRNA and protein levels of DLGAP5 were analyzed using The Cancer Genome Atlas (TCGA) and the Human Protein Atlas (HPA) databases. The CCK-8 and colony formation assays were performed to assess the effect of DLGAP5 on cell proliferation. RNA sequencing (RNA-seq) and enrichment analyses were utilized to explore the biological functions of DLGAP5. Furthermore, flow cytometry was used to explore the role of DLGAP5 on the cell cycle. The ssGSEA algorithm in the R package "GSVA" was applied to quantify immune infiltrating cells, and the tumor immune dysfunction and exclusion (TIDE) algorithm was used to predict the efficacy of immunotherapy. Moreover, analyses using the cBioPortal and MethSurv databases were performed to evaluate the mutation and methylation of DLGAP5, respectively. Finally, the prognostic value of DLGAP5 was estimated using the TCGA and the Gene Expression Omnibus (GEO) databases. The nomogram model was constructed using the TCGA-LUAD cohort and evaluated by adopting calibration curves, time-dependent receiver operating characteristic (ROC) curves, and decision curve analysis (DCA).

Results

DLGAP5 mRNA and protein abundance were significantly elevated in LUAD, and knockdown of DLGAP5 remarkably suppressed lung cancer cell proliferation through induction of cell cycle G1 arrest. In addition, DLGAP5 expression was positively correlated with Th2 cells and negatively correlated with B cells, T follicular helper cells, and mast cells. LUAD patients with high DLGAP5 expression may be resistant to immunotherapy. Hypermethylation levels of the cg23678254 site of DLGAP5 or its enhanced expression were unfavorable for the survival of LUAD patients. Meanwhile, DLGAP5 expression was associated with TNM stages, tumor status, and therapy outcome. Notably, the prognostic model constructed based on DLGAP5 expression exhibited great predictive capability, which was promising for clinical applications.

Conclusion

DLGAP5 promotes lung cancer cell proliferation through regulation of the cell cycle and is associated with multiple immune infiltrating cells. Furthermore, DLGAP5 predicts poor prognosis and response to immunotherapy in lung adenocarcinoma.

DLGAP4 acts as an effective prognostic predictor for hepatocellular carcinoma and is closely related to tumour progression

Disc large associated protein 4 (DLGAP4) plays an important role in neurological diseases, but the role and mechanism of DLGAP4 in hepatocellular carcinoma (HCC) remain unclear. In this study, the prognostic effect of DLGAP4 on HCC patients was investigated by means of bioinformatics. The correlation of DLGAP4 expression with the prognosis of HCC patients was evaluated by TCGA data analysis, and the correlation between DLGAP4 expression and the clinical characteristics of HCC patients was evaluated by the Wilcoxon signed rank test and logistic regression analysis. Kaplan‒Meier and Cox regression methods were used to assess the effect of DLGAP4 expression level on overall survival, and nomograms were used to illustrate the correlation between DLGAP4 gene expression and HCC risk. The genes related to DLGAP4 in HCC were screened, and GO/KEGG enrichment analysis was performed. Furthermore, in vitro and in vivo experiments were conducted to detect the effect of DLGAP4 expression on the proliferation, migration and metastasis of HCC cells. We also examined the effect of DLGAP4 expression on enriched pathway proteins to explore the possible mechanism. The expression levels of DLGAP4 were significantly higher in HCC cell lines and tissue samples than in normal liver cell lines and tissues. The expression of DLGAP4 was significantly associated with clinical characteristics. Survival analysis showed that high expression of DLGAP4 was associated with a poor prognosis in HCC. Multivariate analysis showed that high expression of DLGAP4 was an independent risk factor affecting the overall survival rate in HCC patients. By means of ROC curve analysis and nomograms, we determined the value of DLGAP4 expression in the diagnosis and prognosis evaluation of HCC. GO/KEGG enrichment analysis showed that the PPAR signalling pathway was differentially enriched in patients with high expression of DLGAP4. According to in vitro and in vivo experiments, DLGAP4 knockdown inhibited the proliferation and metastasis of HCC cells and decreased the expression of PPARβ/δ protein. In contrast, overexpression of DLGAP4 promoted the proliferation and metastasis of HCC cell, and increased the expression of PPARβ/δ protein.In contrast, overexpression of DLGAP4 promoted the proliferation and metastasis of HCC cells and increased the expression of PPARβ/δ protein. The results show a close correlation between DLGAP4 expression and clinicopathological features of HCC, and DLGAP4 can be used as a prediction biomarker of HCC.

A novel meta-analysis based on data augmentation and elastic data shared lasso regularization for gene expression

Background

Gene expression analysis can provide useful information for analyzing complex biological mechanisms. However, many reported findings are unrepeatable due to small sample sizes relative to a large number of genes and the low signal-to-noise ratios of most gene expression datasets.

Results

Meta-analysis of multi-data sets is an efficient method for tackling the above problem. To improve the performance of meta-analysis, we propose a novel meta-analysis framework. It consists of two parts: (1) a novel data augmentation strategy. Various cross-platform normalization methods exist, which can preserve original biological information of gene expression datasets from different angles and add different “perturbations” to the dataset. Using such perturbation, we provide a feasible means for gene expression data augmentation; (2) elastic data shared lasso (DSL-\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${{\varvec{L}}}_{\mathbf{2}}$$\end{document}L2). The DSL-\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\mathbf{L}}_{\mathbf{2}}$$\end{document}L2 method spans the continuum between individual models for each dataset and one model for all datasets. It also overcomes the shortcomings of the data shared lasso method when dealing with highly correlated features. Comprehensive simulation experiment results show that the proposed method has high prediction and gene selection performance. We then apply the proposed method to non-small cell lung cancer (NSCLC) blood gene expression data in order to identify key tumor-related genes. The outcomes of our experiment indicate that the method could be used for identifying a set of robust disease-related gene signatures that may be used for NSCLC early diagnosis or prognosis or even targeting.

Conclusion

We propose a novel and effective meta-analysis method for biological research, extrapolating and integrating information from multiple gene expression datasets.

MicroRNA-409-5p inhibits cell proliferation, and induces G2/M phase arrest and apoptosis by targeting DLGAP5 in ovarian cancer cells

MicroRNA (miRNA/miR)-409-5p has been reported to be implicated in prostate and breast cancers; however, its functional role in ovarian cancer (OC) remains unclear. Therefore the aim of the present study was to investigate the clinical significance and biological function of miR-409-5p in OC. Here, reverse transcription-quantitative PCR analysis was performed to detect miR-409-5p expression in OC tissues and cell lines. The association between miR-409-5p expression and the clinicopathological characteristics of patients with OC was assessed using the Fisher's exact test. Furthermore, the Cell Counting Kit-8 assay was performed to assess cell proliferation. Cell cycle distribution and apoptosis were evaluated via flow cytometric analysis, and the target gene of miR-409-5p was validated via the dual-luciferase reporter assay. The results demonstrated that miR-409-5p expression was significantly downregulated in OC tissues and cell lines compared with adjacent normal tissues and epithelial cells, respectively. In addition, low miR-409-5p expression was significantly associated with tumor size (P=0.044) and the International Federation of Gynecology and Obstetrics staging system (P=0.005). Notably, overexpression of miR-409-5p suppressed cell proliferation, and induced G₂/M phase arrest and apoptosis of OC cells. Mechanistically, discs large-associated protein 5 (DLGAP5) was identified as a novel target of miR-409-5p, which was negatively regulated by miR-409-5p. DLGAP5 expression was significantly upregulated in OC tissues and cell lines compared with adjacent normal tissues and epithelial cells, respectively. Furthermore, overexpression of DLGAP5 reversed the effects of miR-409-5p on SKOV-3 cell proliferation, and G₂/M phase and apoptosis. Taken together, these results suggest that miR-409-5p acts as a tumor suppressor in OC by modulating DLGAP5 expression.

NEAT1/MALAT1/XIST/PKD--Hsa-Mir-101-3p--DLGAP5 Axis as a Novel Diagnostic and Prognostic Biomarker Associated With Immune Cell Infiltration in Bladder Cancer

Background: The clinical value of the biomarkers of bladder cancer (BC) is limited due to their low sensitivity or specificity. As a biomarker, DLG associated protein 5 (DLGAP5) is a potential cell cycle regulator in cancer cell carcinogenesis. However, its functional part in BC remains unclear. Therefore, this study aims to identify DLGAP5 expression in BC and its potential diagnostic and prognostic values. Eventually, it predicts the possible RNA regulatory pathways of BC.

Methods: Data on DLGAP5 expression levels in BC and normal bladder tissues were obtained from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. The receiver operating characteristic (ROC), Kaplan–Meier survival curves, and the univariate and multivariate Cox regression analysis determined the diagnostic and prognostic values of DLGAP5 in BC patients. Finally, the StarBase predicted the target RNAs and constructed networks using Cytoscape.

Results: DLGAP5 expression was significantly upregulated in BC tissue, verified by the TCGA (p < 0.001), GSE3167, GSE7476, and GSE65635 datasets (p < 0.01). BC patients with increased DLGAP5 had poor overall survival (OS) (p = 0.01), disease specific survival (DSS) (p = 0.006) and progress free interval (DFI) (p = 0.007). The area under the ROC curve (AUC) was 0.913. The multivariate Cox analysis identified that lymphovascular invasion (p = 0.007) and DLGAP5 (p = 0.002) were independent prognostic factors.

Conclusion: Increased DLGAP5 expression was closely associated with a poor prognosis in BC patients. In this case, DLGAP5 might be a diagnostic and prognostic biomarker for BC. DLGAP5 expression might be regulated by NEAT1/MALAT1/XIST/PKD--Hsa-mir-101-3p pathways.

Chromatin Separation Regulators Predict the Prognosis and Immune Microenvironment Estimation in Lung Adenocarcinoma

Background: Abnormal chromosome segregation is identified to be a common hallmark of cancer. However, the specific predictive value of it in lung adenocarcinoma (LUAD) is unclear.

Method: The RNA sequencing and the clinical data of LUAD were acquired from The Cancer Genome Atlas (TACG) database, and the prognosis-related genes were identified. The Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) were carried out for functional enrichment analysis of the prognosis genes. The independent prognosis signature was determined to construct the nomogram Cox model. Unsupervised clustering analysis was performed to identify the distinguishing clusters in LUAD-samples based on the expression of chromosome segregation regulators (CSRs). The differentially expressed genes (DEGs) and the enriched biological processes and pathways between different clusters were identified. The immune environment estimation, including immune cell infiltration, HLA family genes, immune checkpoint genes, and tumor immune dysfunction and exclusion (TIDE), was assessed between the clusters. The potential small-molecular chemotherapeutics for the individual treatments were predicted via the connectivity map (CMap) database.

Results: A total of 2,416 genes were determined as the prognosis-related genes in LUAD. Chromosome segregation is found to be the main bioprocess enriched by the prognostic genes. A total of 48 CSRs were found to be differentially expressed in LUAD samples and were correlated with the poor outcome in LUAD. Nine CSRs were identified as the independent prognostic signatures to construct the nomogram Cox model. The LUAD-samples were divided into two distinct clusters according to the expression of the 48 CSRs. Cell cycle and chromosome segregation regulated genes were enriched in cluster 1, while metabolism regulated genes were enriched in cluster 2. Patients in cluster 2 had a higher score of immune, stroma, and HLA family components, while those in cluster 1 had higher scores of TIDES and immune checkpoint genes. According to the hub genes highly expressed in cluster 1, 74 small-molecular chemotherapeutics were predicted to be effective for the patients at high risk.

Conclusion: Our results indicate that the CSRs were correlated with the poor prognosis and the possible immunotherapy resistance in LUAD.

Identification of Hub Genes for Early Diagnosis and Predicting Prognosis in Colon Adenocarcinoma

Colon adenocarcinoma (COAD) is among the most common digestive system malignancies worldwide, and its pathogenesis and gene signatures remain unclear. This study explored the genetic characteristics and molecular mechanisms underlying colon cancer development. Three gene expression data sets were obtained from the Gene Expression Omnibus (GEO) database. GEO2R was used to determine differentially expressed genes (DEGs) between COAD and normal tissues. Then, the intersection of the data sets was obtained. Metascape was used to perform the functional enrichment analyses. Next, STRING was used to build protein-protein interaction (PPI) networks. Hub genes were identified and analysed using Cytoscape. Next, survival analysis and expression analysis of the hub genes were performed. ROC curve analysis was performed for further test of the diagnostic efficacy. Finally, alterations in the hub genes were predicted and analysed by cBioPortal. Altogether, 436 DEGs were detected. The DEGs were mainly enriched in cell cycle phase transition, nuclear division, meiotic nuclear division, and cytokinesis. Based on PPI networks, 20 hub genes were selected. Among them, 6 hub genes (CCNB1, CCNA2, AURKA, NCAPG, DLGAP5, and CENPE) showed significant prognostic value in colon cancer (P < 0.05), while 5 hub genes (CDK1, CCNB1, CCNA2, MAD2L1, and DLGAP5) were associated with early colon cancer diagnosis and ROC curve analysis showed good diagnostic accuracy. In conclusion, integrated bioinformatics analysis was used to identify hub genes that reveal the potential mechanism of carcinogenesis and progression of colon cancer. The hub genes might be novel biomarkers for early diagnosis, treatment, and prognosis of colon cancer.

Involvement of MiRNA-211-5p and Arhgap11a Interaction During Osteogenic Differentiation of MC3T3-E1 Cells

Objective

MicroRNAs (miRNAs) are well-recognized for their abilities to regulate gene expression post-transcriptionally in plants and animals. Recently, miRNA-messenger RNA (mRNA) regulatory relationships have been confirmed during biological processes, including osteogenic differentiation. This study aimed to find out more candidate miRNA-mRNA pairs involved in the osteogenic differentiation of MC3T3-E1 cells.

Methods

An MC3T3-E1-based microarray dataset (accessioned as GSE46400) downloaded from the Gene Expression Omnibus included MC3T3-E1 cells with or without 14-day osteoblast differentiation osteoblast induction. Multiple miRNA-mRNA prediction databases were searched by differentially expressed genes (DEGs) to obtain pairs of a miRNA-DEG regulatory network. The MC3T3-E1 cells were cultured and incubated in the osteogenic differentiation medium for 14 days. The expressions of candidate miRNAs and mRNAs were determined by real-time quantitative PCR(RT-qPCR) in MC3T3-E1 cells. The miRNA-mRNA interactions were verified by dual-luciferase reporter gene assays and experiments using mimics miRNA or their inhibitors.

Results

We identified 715 upregulated DEGs and 603 downregulated DEGs between MC3T3-E1 cells with and without osteoblast induction by analyzing the raw data of the GSE46400 dataset. There were 7 overlapped miRNA-mRNA pairs identified during osteogenic differentiation of MC3T3-E1 cells, including mmu-miR-204-5p-Arhgap11a, mmu-miR-211-5p-Arhgap11a, mmu-miR-24-3p-H2afx, mmu-miR-3470b-Chek2, mmu-miR-3470b-Dlgap5, mmu-miR-466b-3p-Chek1, and mmu-miR-466c-3p-Chek1. The Arhgap11a, H2afx, Chek2, Dlgap5, and Chek1 were hub genes downregulated in MC3T3-E1 cells after osteogenic differentiation, verified by RT-qPCR results. The RT-qPCR also determined declined expressions of miR-204-5p and miR-24-3p concomitant with elevated expressions of miR-211-5p, miR-3470b, miR-466b-3p, and miR-466c-3p in the MC3T3-E1 cells, with osteoblast induction compared with undifferentiated MC3T3-E1 cells. Dual-luciferase reporter gene assays demonstrated Arhgap11a as the target of miR-211-5p. MiR-211-5p upregulation by its mimic increased Arhgap11a expression in MC3T3-E1 cells.

Conclusion

Our study characterizes miR-211-5p targeting Arhgap11a promotes the osteogenic differentiation of MC3T3-E1 cells, which provides novel targets to promote the osteogenesis process during bone repair.

Identification of key regulators associated with colon cancer prognosis and pathogenesis

Colon cancer (CC) is the fourth deadliest cancer in the world. New insights into prognostication might be helpful to define the optimal adjuvant treatments for patients in routine clinical practice. Here, a microarray dataset with 30 primary tumors and 30 normal samples was analyzed using GEO2R to find differentially expressed genes (DEGs). Then, DAVID, KEGG, ChEA and X2K were used to analyze DEGs-related Gene Ontology, pathways, transcription factors (TFs) and kinases, respectively. Protein-protein interaction (PPI) networks were constructed using the STRING database and Cytoscape. The modules and hub genes of DEGs was determined through MCODE and CytoHubba plugins, and the expression of hub genes was verified using GEPIA. To find microRNAs and metabolites associated with DEGs, miRTarBase and HMDB were used, respectively. It was found that 233 and 373 genes were upregulated and downregulated in CC, respectively. GO analysis showed that the upregulated DEGs were mainly involved in mitotic nuclear division and cell division. Top 10 hub genes were identified, including AURKB, CDK1, DLGAP5, AURKA, CCNB2, CCNB1, BUB1B, CCNA2, KIF20A and BUB1. Whereas, FOMX1, E2F7, E2F1, E2F4 and AR were identified as top 5 TFs in CC. Moreover, CDK1, CDC2, MAPK14, ATM and CK2ALPHA was identified as top 5 kinases in CC. miRNAs analysis showed that Hsa-miR-215-5p hsa-miR-193b-3p, hsa-miR-192-5p and hsa-miR-16-5p could target the largest number of CC genes. Taken together, CC-related genes, especially the hub genes, TFs, and metabolites might be used as novel biomarkers for CC, as well as for diagnosis and guiding therapeutic strategies for CC.

Pan-cancer analysis and experiments with cell lines reveal that the slightly elevated expression of DLGAP5 is involved in clear cell renal cell carcinoma progression

AIMS

Discs large-associated protein 5 (DLGAP5), a kinetochore fibers-binding protein, functions as a oncoprotein in many cancers. However, its expression patterns in pan-cancer including clear cell renal cell carcinoma (ccRCC) are not analyzed. Herein, we aimed to evaluate its expression in more common cancers, especially in ccRCC.

MAIN METHODS

Data from Genotype-Tissue Expression, The Cancer Genome Atlas, and Tumor Immune Estimation Resource were used to analyze the DLGAP5 expression in normal tissues, cancer cell lines, and cancer tissues, as well as the immune infiltration levels. The analysis results were verified with ccRCC cell lines via RNAi, western blotting, and the cytological analysis.

KEY FINDINGS

Low DLGAP5 expression in 31 types of normal tissues, the upregulation in 21 cancer cell lines, and the significant elevated expression in 26 types of cancers, were found, Surprisingly, kidney cancer including ccRCC, DLGAP5 exhibited a slightly elevated but statistically significant expression among 26 types of cancers. In addition, elevated DLGAP5 expression was significantly positive correlated with immune infiltration level in ccRCC. The survival probability of some cancers including kidney cancer, clinical TNM stage of ccRCC patients were significantly related to upregulated DLGAP5 expression. The experiments results showed DLGAP5 upregulation in ccRCC tissues and the cell lines, its knockdown inhibited the cells viability and proliferation, and compromised the cells migration and invasion.

SIGNIFICANCE

Elevated DLGAP5 expression occurred in common cancers. However, its slightly upregulated expression is related with ccRCC progression, it is therefore a prognostic risk factor for ccRCC, but not an independent factor.

Screening and predicted value of potential biomarkers for breast cancer using bioinformatics analysis

Breast cancer is the most common cancer and the leading cause of cancer-related deaths in women. Increasing molecular targets have been discovered for breast cancer prognosis and therapy. However, there is still an urgent need to identify new biomarkers. Therefore, we evaluated biomarkers that may aid the diagnosis and treatment of breast cancer. We searched three mRNA microarray datasets (GSE134359, GSE31448 and GSE42568) and identified differentially expressed genes (DEGs) by comparing tumor and non-tumor tissues using GEO2R. Functional and pathway enrichment analyses of the DEGs were performed using the DAVID database. The protein-protein interaction (PPI) network was plotted with STRING and visualized using Cytoscape. Module analysis of the PPI network was done using MCODE. The associations between the identified genes and overall survival (OS) were analyzed using an online Kaplan-Meier tool. The redundancy analysis was conducted by DepMap. Finally, we verified the screened HUB gene at the protein level. A total of 268 DEGs were identified, which were mostly enriched in cell division, cell proliferation, and signal transduction. The PPI network comprised 236 nodes and 2132 edges. Two significant modules were identified in the PPI network. Elevated expression of the genes Discs large-associated protein 5 (DLGAP5), aurora kinase A (AURKA), ubiquitin-conjugating enzyme E2 C (UBE2C), ribonucleotide reductase regulatory subunit M2(RRM2), kinesin family member 23(KIF23), kinesin family member 11(KIF11), non-structural maintenance of chromosome condensin 1 complex subunit G (NCAPG), ZW10 interactor (ZWINT), and denticleless E3 ubiquitin protein ligase homolog(DTL) are associated with poor OS of breast cancer patients. The enriched functions and pathways included cell cycle, oocyte meiosis and the p53 signaling pathway. The DEGs in breast cancer have the potential to become useful targets for the diagnosis and treatment of breast cancer.

ARHGAP11A Is a Prognostic Biomarker and Correlated With Immune Infiltrates in Gastric Cancer

Background: ARHGAP11A, belongs to RhoGAPs family, is vital for cell motility. However, the role of ARHGAP11A in gastric cancer is obscure. Methods: The expression level of ARHGAP11A was analyzed by Oncomine database. The correlation of ARHGAP11A expression with immune infiltrates and associated gene markers was clarified by Tumor IMmune Estimation Resource and Gene Expression Profiling Interactive Analysis database. The correlation between ARHGAP11A expression and the patient prognosis was identified by Kaplan-Meier plotter and PrognoScan. Genetic changes of ARHGAP11A were analyzed by cBioPortal. The protein-protein interaction network and gene functional enrichment analysis were constructed and performed by GeneMANIA and Metascape. Results: We found that the expression levels of ARHGAP11A were elevated in various cancers including gastric cancer when compared with normal tissues. High expression of ARHGAP11A was significantly correlated with a better prognosis in gastric cancer. We revealed that the expression of ARHGAP11A was negatively associated with infiltration levels of CD8+ T cells, CD4+ T cells, macrophages and dendritic cells. In addition, ARHGAP11A expression was significantly correlated with gene markers of these immune cells. Lastly, gene functional enrichment analysis indicated that ARHGAP11A involved in regulating lymphocyte activation, cell division, cell killing, myeloid leukocyte differentiation and leukocyte apoptosis. Conclusion: Our findings demonstrated that ARHGAP11A was a valuable prognostic biomarker in gastric cancer. Further work is needed to validate its role and underlying mechanisms in regulating immune infiltrates.

Knockdown of DLGAP5 suppresses cell proliferation, induces G2/M phase arrest and apoptosis in ovarian cancer

Discs large-associated protein 5 (DLGAP5) is a microtubule-associated protein and is reported to exert oncogenic role in tumorigenesis, including lung cancer and hepatocellular carcinoma. However, the prognostic value and biological function of DLGAP5 in ovarian cancer (OC) still remain unclear. The present study investigated the expression pattern of DLGAP5 by searching the Oncomine microarray database. The correlation between DLGAP5 and survival prognosis of OC patients was analyzed by the online tool KM-plotter. Knockdown of DLGAP5 was achieved by transfection with small interfering RNA targeting DLGAP5 in two OC cell lines (SKOV3 and CAOV3). Cell proliferation was assessed by Cell Counting Kit-8 assay and colony-formation assay. Flow cytometry was utilized to determine the effects of DLGAP5 on cell cycle distribution and apoptosis. The present study data showed that DLGAP5 was significantly upregulated in OC and its higher expression was associated with poor survival prognosis. Knockdown of DLGAP5 significantly suppressed cell proliferation, induced cell cycle G₂/M phase arrest and apoptosis. Western blot analysis further demonstrated that DLGAP5 knockdown downregulated the expression of CDK1, Cyclin B1 and Bcl-2, but upregulated Bax expression. Collectively, these data demonstrate that DLGAP5 might be a promising prognostic therapeutic target for OC treatment.

The Origin of Stroma Influences the Biological Characteristics of Oral Squamous Cell Carcinoma

Simple Summary

Normal stromal cells play a significant role in the progression of cancers but are poorly investigated in oral squamous cell carcinoma (OSCC). In this study, we found that stromal cells derived from the gingival and periodontal ligament tissues could inhibit differentiation and promote the proliferation, invasion, and migration of OSCC both in vitro and in vivo. Furthermore, microarray data suggested that genes, such as CDK1, BUB1B, TOP2A, DLGAP5, BUB1, and CCNB2, probably play a role in influencing the different effects of gingival stromal tissue cells (G-SCs) and periodontal ligament stromal cells (P-SCs) on the progression of OSCC. Therefore, both G-SCs and P-SCs could promote the progression of OSCC, which could be a potential regulatory mechanism in the progression of OSCC.

Abstract

Normal stromal cells surrounding the tumor parenchyma, such as the extracellular matrix (ECM), normal fibroblasts, mesenchymal stromal cells, and osteoblasts, play a significant role in the progression of cancers. However, the role of gingival and periodontal ligament tissue-derived stromal cells in OSCC progression is unclear. In this study, the effect of G-SCs and P-SCs on the differentiation, proliferation, invasion, and migration of OSCC cells in vitro was examined by Giemsa staining, Immunofluorescence (IF), (3-(4,5-dimethylthiazol-2-yl)-5-(3-carboxymethoxyphenyl)-2-(4-sulfophenyl)-2H-tetrazolium) (MTS), invasion, and migration assays. Furthermore, the effect of G-SCs and P-SCs on the differentiation, proliferation, and bone invasion by OSCC cells in vivo was examined by hematoxylin-eosin (HE) staining, immunohistochemistry (IHC), and tartrate-resistant acid phosphatase (TRAP) staining, respectively. Finally, microarray data and bioinformatics analyses identified potential genes that caused the different effects of G-SCs and P-SCs on OSCC progression. The results showed that both G-SCs and P-SCs inhibited the differentiation and promoted the proliferation, invasion, and migration of OSCC in vitro and in vivo. In addition, genes, including CDK1, BUB1B, TOP2A, DLGAP5, BUB1, and CCNB2, are probably involved in causing the different effects of G-SCs and P-SCs on OSCC progression. Therefore, as a potential regulatory mechanism, both G-SCs and P-SCs can promote OSCC progression.

The Unique Biology behind the Early Onset of Breast Cancer

Breast cancer commonly affects women of older age; however, in developing countries, up to 20% of breast cancer cases present in young women (younger than 40 years as defined by oncology literature). Breast cancer in young women is often defined to be aggressive in nature, usually of high histological grade at the time of diagnosis and negative for endocrine receptors with poor overall survival rate. Several researchers have attributed this aggressive nature to a hidden unique biology. However, findings in this aspect remain controversial. Thus, in this article, we aimed to review published work addressing somatic mutations, chromosome copy number variants, single nucleotide polymorphisms, differential gene expression, microRNAs and gene methylation profile of early-onset breast cancer, as well as its altered pathways resulting from those aberrations. Distinct biology behind early-onset of breast cancer was clear among estrogen receptor-positive and sporadic cases. However, further research is needed to determine and validate specific novel markers, which may help in customizing therapy for this group of patients.

Identification of Potential Diagnostic and Prognostic Biomarkers for Colorectal Cancer Based on GEO and TCGA Databases

Colorectal cancer (CRC) is one of the most common neoplastic diseases worldwide. With a high recurrence rate among all cancers, treatment of CRC only improved a little over the last two decades. The mortality and morbidity rates can be significantly lessened by earlier diagnosis and prompt treatment. Available biomarkers are not sensitive enough for the diagnosis of CRC, whereas the standard diagnostic method, endoscopy, is an invasive test and expensive. Hence, seeking the diagnostic and prognostic biomarkers of CRC is urgent and challenging. With that order, we screened the overlapped differentially expressed genes (DEGs) of GEO (GSE110223, GSE110224, GSE113513) and TCGA datasets. Subsequent protein-protein interaction network analysis recognized the hub genes among these DEGs. Further functional analyses including Gene Ontology and KEGG pathway analysis and gene set enrichment analysis were processed to investigate the role of these genes and potential underlying mechanisms in CRC. Kaplan-Meier analysis and Cox hazard ratio analysis were carried out to clarify the diagnostic and prognostic role of these genes. In conclusion, our present study demonstrated that CCNA2, MAD2L1, DLGAP5, AURKA, and RRM2 are all potential diagnostic biomarkers for CRC and may also be potential treatment targets for clinical implication in the future.

Bioinformatic Identification of Hub Genes and Analysis of Prognostic Values in Colorectal Cancer

The purpose of this study is to discover novel hub genes which are helpful for diagnosis, prognosis, and targeted therapy in colorectal cancer (CRC) by using bioinformatics analysis. GSE74602, GSE110225, and GSE113513 were extracted from the gene expression omnibus (GEO). Differentially expressed genes (DEGs) in expression profiles were identified by GEO2R. Gene ontology and Kyoto Encyclopedia of Genes and Genomes analyses of the DEGs were carried out in the Database for Annotation, Visualization, and Integrated Discovery (DAVID). String database and cytoscape were used for building protein-protein interaction (PPI) network and module analysis. The UALCAN was used for in-depth analysis of data of CRC patients from The Cancer Genome Atlas (TCGA) to identify expression levels and overall survival rates of hub genes. The DEGs included 107 up-regulation genes and 232 down-regulation genes. Twenty-nine (29) hub genes and two significant modules were screened from PPI network. The expression levels of hub genes in TCGA were verified. Survival analysis curve indicated high expression of CCNA2, CCNB1, DLGAP5, were related to high survival rates, and low expression of TIMP1 were associated with high survival rates. These results suggest that DEGs may be the hub genes of CRC, and CCNA2, CCNB1, DLGAP5, TIMP1 may be the potential prognostic markers of CRC.

Identification of a five-gene signature for predicting the progression and prognosis of stage I endometrial carcinoma

Uterine corpus endometrial carcinoma (UCEC) is often diagnosed at an early clinical stage based on abnormal vaginal bleeding. However, the prognosis of UCEC is poor. The present study was conducted to identify novel tumor grade-related genes with the potential to predict the prognosis and progression of UCEC. A total of three gene expression microarray datasets were downloaded from the Gene Expression Omnibus database, and one RNA-sequencing dataset with corresponding clinical information of patients with UCEC was obtained from The Cancer Genome Atlas database. In summary, 1,447 differentially expressed genes (DEGs) were identified between endometrial cancerous tissues and normal endometrial tissues. Weighted gene co-expression network analysis was performed to assess the associations between DEGs and clinical traits. In total, five genes were found to be highly associated with the tumorigenesis and prognosis of UCEC. Among them, BUB1 mitotic checkpoint serine/threonine kinase B, cyclin B1, cell-division cycle protein 20 and non-SMC condensing I complex subunit G were involved in cell cycle regulation pathways, and DLG-associated protein 5 was involved in the Notch receptor 3 signaling pathway based on functional enrichment analyses. Of the five genes, four were highly expressed in endometrial cancerous tissues compared with normal endometrial tissues at the protein level. In addition, the higher expression of these genes predicted a higher tumor grade and worse overall survival. In conclusion, the present study revealed a 5-gene signature that can be used to predict the progression of UCEC.

Elevated mRNA expression levels of DLGAP5 are associated with poor prognosis in breast cancer

Breast cancer is the most commonly diagnosed type of cancer and one of the leading causes of cancer-associated mortality in women. In addition, the underlying molecular mechanisms of the occurrence and development of breast cancer requires further investigation. In the present study, bioinformatics analysis was performed to identify differentially expressed genes (DEGs) between breast cancer and normal breast tissues to investigate the underlying molecular mechanisms. In addition, reverse transcription-quantitative PCR and immunohistochemistry (IHC) were performed to investigate the protein and mRNA expression levels of a specific DEG, discs large-associated protein 5 (DLGAP5). A Cell Counting Kit-8 assay and flow cytometry analysis were used to assess the effects of DLGAP5 on cell proliferation. In total, 85 DEGs were identified in the three Gene Expression Omnibus datasets, including 40 upregulated and 45 downregulated genes. In addition, 30 hub genes were identified following the construction of a protein-protein interaction network, and 28 of the 30 hub genes were established to be indicators of breast cancer prognosis. DLGAP5 was highly expressed in breast cancer specimens, and its expression levels were correlated with clinical stage and lymph node status. In addition, downregulation of DLGAP5 repressed the proliferation of breast cancer MDA-MB-231 cells and induced cell cycle arrest. Additionally, DLGAP5 was identified to be localized in the mitochondria, and the presence of a conserved microtubule-associated proteins 1A/1B light chain 3B-interacting region motif suggested that DLGAP5 may serve a role in mitophagy. The present results demonstrated an association between DLGAP5 expression levels and the clinicopathological characteristics of patients with breast cancer using IHC. In conclusion, DLGAP5 may be a promising target in the diagnosis and treatment of breast cancer.

Identification of key biomarkers associated with development and prognosis in patients with ovarian carcinoma: evidence from bioinformatic analysis

BACKGROUND

Ovarian cancer (OC) is the deadliest cause in the gynecological malignancies. Most OC patients are diagnosed in advanced stages with less than 40% of women cured. However, the possible mechanism underlying tumorigenesis and candidate biomarkers remain to be further elucidated.

RESULTS

Gene expression profiles of GSE18520, GSE54388, and GSE27651 were available from Gene Expression Omnibus (GEO) database with a total of 91 OC samples and 22 normal ovarian (OV) tissues. Three hundred forty-nine differentially expressed genes (DEGs) were screened between OC tissues and OV tissues via GEO2R and online Venn software, followed by KEGG pathway and gene ontology (GO) enrichment analysis. The enriched functions and pathways of these DEGs contain male gonad development, cellular response to transforming growth factor beta stimulus, positive regulation of transcription from RNA polymerase II promoter, calcium independent cell-cell adhesion via plasma membrane cell adhesion molecules, extracellular matrix organization, pathways in cancer, cell cycle, cell adhesion molecules, PI3K-AKT signaling pathway, and progesterone mediated oocyte maturation. The protein-protein network (PPI) was established and module analysis was carried out using STRING and Cytoscape. Next, with PPI network analyzed by four topological methods in Cytohubba plugin of Cytoscape, 6 overlapping genes (DTL, DLGAP5, KIF15, NUSAP1, RRM2, and TOP2A) were eventually selected. GEPIA and Oncomine were implemented for validating the gene expression and all the six hub genes were highly expressed in OC specimens compared to normal OV tissues. Furthermore, 5 of 6 genes except for DTL were associated with worse prognosis using Kaplan Meier-plotter online tool and 3 of 6 genes were significantly related to clinical stages, including RRM2, DTL, and KIF15. Additionally, cBioPortal showed that TOP2A and RRM2 were the targets of cancer drugs in patients with OC, indicating the other four genes may also be potential drug targets.

CONCLUSION

Six hub genes (DTL, DLGAP5, KIF15, NUSAP1, RRM2, and TOP2A) present promising predictive value for the development and prognosis of OC and may be used as candidate targets for diagnosis and treatment of OC.