A functional genomics screen reveals a strong synergistic effect between docetaxel and the mitotic gene DLGAP5 that is mediated by the androgen receptor

DLGAP5 upregulates E2F1 to promote prostate adenocarcinoma neuroendocrine differentiation

AIMS

DLGAP5 plays a significant role in promoting cancer progression across various cancers. However, the specific role of DLGAP5 in neuroendocrine differentiation (NED) of prostate cancer (PCa) remains elusive. Our objective is to explore the mechanism by which DLGAP5 mediates NED in PCa.

MATERIALS AND METHODS

Utilizing diverse public databases, we conducted bioinformatics analysis to examine DLGAP5 expression in PCa. We confirmed aberrant DLGAP5 expression in various PCa cell lines through Western blotting. Functional assays both in vivo and in vitro have validated the oncogenic role of DLGAP5 in PCa. Furthermore, we sought to identify downstream key genes to elucidate the mechanisms underlying DLGAP5-mediated NED in PCa. We also identified a small molecule drug, AAPK-25, which specifically targets DLGAP5.

KEY FINDINGS

DLGAP5 was highly expressed in NEPC. The suppression of AR signaling promoted DLGAP5 transcription. DLGAP5 endowed PCa cells with a robust ability to proliferate and migrate. E2F1 was an important downstream target of DLGAP5. DLGAP5 mediated the NED of PCa through E2F1. AAPK-25, as an inhibitor of DLGAP5, inhibited PRAD proliferation by repressing the DLGAP5/E2F1 axis both in vitro and in vivo.

SIGNIFICANCE

We identified the AR/DLGAP5/E2F1 signaling pathway as a pivotal mechanism that facilitates the transition of PCa towards a neuroendocrine phenotype. This pathway may represent a promising therapeutic target for NEPC patients.

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.

DLGAP5 Regulates the Proliferation, Migration, Invasion, and Cell Cycle of Breast Cancer Cells via the JAK2/STAT3 Signaling Axis

The aim of this study was to discover new biomarkers to detect breast cancer (BC), which is an aggressive cancer with a high mortality rate. In this study, bioinformatic analyses (differential analysis, weighted gene co-expression network analysis, and machine learning) were performed to identify potential candidate genes for BC to study their molecular mechanisms. Furthermore, Quantitative Real-time PCR and immunohistochemistry assays were used to examine the protein and mRNA expression levels of a particular candidate gene (DLGAP5). And the effects of DLGAP5 on cell proliferation, migration, invasion, and cell cycle were further assessed using the Cell Counting Kit-8 assay, colony formation, Transwell, wound healing, and flow cytometry assays. Moreover, the changes in the JAK2/STAT3 signaling-pathway-related proteins were detected by Western Blot. A total of 44 overlapping genes were obtained by differential analysis and weighted gene co-expression network analysis, of which 25 genes were found in the most tightly connected cluster. Finally, NEK2, CKS2, UHRF1, DLGAP5, and FAM83D were considered as potential biomarkers of BC. Moreover, DLGAP5 was highly expressed in BC. The down-regulation of DLGAP5 may inhibit the proliferation, migration, invasion, and cell cycle of BC cells, and the opposite was true for DLGAP5 overexpression. Correspondingly, silencing or overexpression of the DLGAP5 gene inhibited or activated the JAK2/STAT3 signaling pathway, respectively. DLGAP5, as a potential biomarker of BC, may impact the cell proliferation, migration, invasion, cell cycle, and BC development by modulating the JAK2/STAT3 signaling pathway.

Resistance to prostate cancer treatments

A review of the current treatment options for prostate cancer and the formation of resistance to these regimens has been compiled including primary, acquired, and cross-resistance. The diversification of the pathways involved and the escape routes the tumor is utilizing have been addressed. Whereas early stages of tumor can be cured, there is no treatment available after a point of no return has been reached, leaving palliative treatment as the only option. The major reasons for this outcome are the heterogeneity of tumors, both inter- and intra-individually and the nearly endless number of escape routes, which the tumor can select to overcome the effects of treatment. This means that more focus should be applied to the individualization of both diagnosis and therapy of prostate cancer. In addition to current treatment options, novel drugs and ongoing clinical trials have been addressed in this review.

Overexpression of SKA Complex Is Associated With Poor Prognosis in Gliomas

The spindle and kinetochore-associated complex is composed of three members: SKA1, SKA2, and SKA3. It is necessary for stabilizing spindle microtubules attaching to kinetochore (KT) in the middle stage of mitosis. The SKA complex is associated with poor prognosis in several human cancers. However, the role of SKA complex in rare malignant diseases, such as gliomas, has not been fully investigated. We investigated several databases, including Oncomine, UALCAN, and cBioPortal to explore the expression profile and prognostic significance of SKA complex in patients with gliomas. Gene ontology and Kyoto Encyclopedia of Genes and Genome pathways were used to analyze the potential enriched pathways. The genes co-expressed with SKA complex were identified and used for developing a protein-protein interaction (PPI) network using the STRING database. We found a significant overexpression of the mRNA levels of SKA1, SKA2, and SKA3 in patients with glioma patients. Higher expression of SKA1 and SKA3, but not SKA2, was significantly correlated with shorter overall survival of patients with glioma. In glioma, SKA complex was found to be involved in nuclear division, chromosome segregation, and DNA replication. The results of PPI network identified 10 hub genes (CCNB2, UBE2C, BUB1B, TPX2, CCNA2, CCNB1, MELK, TOP2A, PBK, and KIF11), all of which were overexpressed and negatively associated with prognosis of patients with glioma. In conclusion, our study sheds new insights into the biological role and prognostic significance of SKA complex in glioma.

Androgen receptor negatively regulates mitotic checkpoint signaling to induce docetaxel resistance in castration-resistant prostate cancer

BACKGROUND

Despite multiple treatment advances for castration-resistant prostate cancer (CRPC), there are currently no curative therapies and patients ultimately to succumb to the disease. Docetaxel (DTX) is the standard first-line chemotherapy for patients with metastatic CRPC; however, drug resistance is inevitable and often develops rapidly, leading to disease progression in nearly all patients. In contrast, when DTX is deployed with androgen deprivation therapy in castration-sensitive disease, more durable responses and improved outcomes are observed, suggesting that aberrant androgen receptor (AR) signaling accelerates DTX resistance in CRPC. In this study, we demonstrate that AR dysregulates the mitotic checkpoint, a critical pathway involved in the anticancer action of DTX.

METHODS

Androgen-dependent and independent cell lines were used to evaluate the role of AR in DTX resistance. Impact of drug treatment on cell viability, survival, and cell-cycle distribution were determined by plate-based viability assay, clonogenic assay, and cell-cycle analysis by flow cytometry, respectively. Mitotic checkpoint kinase signal transduction and apoptosis activation was evaluated by Western blotting. Pathway gene expression analysis was evaluated by RT-PCR. A Bliss independence model was used to calculate synergy scores for drug combination studies.

RESULTS

Activation of AR in hormone-sensitive cells induces a rescue phenotype by increasing cell viability and survival and attenuating G2/M arrest in response to DTX. Analysis of mitotic checkpoint signaling shows that AR negatively regulates spindle checkpoint signaling, resulting in premature mitotic progression and evasion of apoptosis. This phenotype is characteristic of mitotic slippage and is also observed in CRPC cell lines where we demonstrate involvement of AR splice variant AR-v7 in dysregulation of checkpoint signaling. Our findings suggest that DTX resistance is mediated through mechanisms that drive premature mitotic exit. Using pharmacologic inhibitors of anaphase-promoting complex/cyclosome and polo-like kinase 1, we show that blocking mitotic exit induces mitotic arrest, apoptosis, and synergistically inhibits cell survival in combination with DTX.

CONCLUSION

Our results suggest that targeting the mechanisms of dysregulated mitotic checkpoint signaling in AR-reactivated tumors has significant clinical potential to extend treatment benefit with DTX and improve outcomes in patients with lethal prostate cancer.

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.

Development and Validation of Novel Biomarkers Related to M2 Macrophages Infiltration by Weighted Gene Co-Expression Network Analysis in Prostate Cancer

M2-tumor-associated macrophages (TAMs) work as a promoter in the processes of bone metastases, chemotherapy resistance, and castration resistance in prostate cancer (PCa), but how M2-TAMs affect PCa has not been fully understood. In this study, we analyzed the proportion of tumor-infiltrating immune cells using the CIBERSORT algorithm, based on samples from the Cancer Genome Atlas database. Then we performed weighted gene co-expression network analysis to examine the modules concerning infiltrated M2-TAMs. Gene Ontology analysis and pathway enrichment analysis were performed for functional annotation and a protein–protein interaction network was constructed. The International Cancer Genomics Consortium cohort was used as a validation cohort. The red module showed the most correlation with M2-TAMs in PCa. Biological processes and pathways were mainly associated with the immune-related processes, as revealed by functional annotation. Four hub genes were screened: ACSL1, DLGAP5, KIF23 and NCAPG. Further validation showed that the four hub genes had a higher expression level in tumor tissues than that in normal tissues, and they were good prognosis biomarkers for PCa. In conclusion, these findings contribute to understanding the underlying molecular mechanisms of how M2-TAMs affect PCa, and looking for the potential biomarkers and therapeutic targets for PCa patients.

Establishment of Novel DNA Methylation-Based Prostate Cancer Subtypes and a Risk-Predicting Eight-Gene Signature

Prostate cancer (PCa) is the most common malignant tumor affecting males worldwide. The substantial heterogeneity in PCa presents a major challenge with respect to molecular analyses, patient stratification, and treatment. Least absolute shrinkage and selection operator was used to select eight risk-CpG sites. Using an unsupervised clustering analysis, called consensus clustering, we found that patients with PCa could be divided into two subtypes (Methylation_H and Methylation_L) based on the DNA methylation status at these CpG sites. Differences in the epigenome, genome, transcriptome, disease status, immune cell composition, and function between the identified subtypes were explored using The Cancer Genome Atlas database. This analysis clearly revealed the risk characteristics of the Methylation_H subtype. Using a weighted correlation network analysis to select risk-related genes and least absolute shrinkage and selection operator, we constructed a prediction signature for prognosis based on the subtype classification. We further validated its effectiveness using four public datasets. The two novel PCa subtypes and risk predictive signature developed in this study may be effective indicators of prognosis.

Global Gene Expression of Cultured Human Dermal Fibroblasts: Focus on Cell Cycle and Proliferation Status in Improving the Condition of Face Skin

Chronological skin ageing is an inevitable physiological process that results in thin and sagging skin, fine wrinkles, and gradual dermal atrophy. The main therapeutic approaches to soft tissue augmentation involve using dermal fillers, where natural fillers, such as autologous fibroblasts, are involved in generating dermal matrix proteins. The aim of this study was to determine the global transcriptome profile of three passages of dermal autologous fibroblasts from a male volunteer, focusing on the processes of the cell cycle and cell proliferation status to estimate the optimal passage of the tested cells with respect to their reimplantation. We performed K-means clustering and validation of the expression of the selected mRNA by qRT-PCR. Ten genes were selected (ANLN, BUB1, CDC20, CCNA2, DLGAP5, MKI67, PLK1, PRC1, SPAG5, and TPX2) from the top five processes annotated to cluster 5. Detailed microarray analysis of the fibroblast genes indicated that the cell population of the third passage exhibited the highest number of upregulated genes involved in the cell cycle and cell proliferation. In all cases, the results of qRT-PCR confirmed the differences in expression of the selected mRNAs between fibroblasts from the primary culture (C0) and from the first (C1), second (C2), and third (C3) cell passage. Our results thus suggest that these cells might be useful for increasing fibroblast numbers after reimplantation into a recipient's skin, and the method used in this study seems to be an excellent tool for autologous transplantation allowing the rejuvenation of aging skin.

Identification and prognostic value of DLGAP5 in endometrial cancer

Background

Endometrial cancer poses a serious threat to women’s health worldwide, and its pathogenesis, although actively explored, is not fully understood. DLGAP5 is a recently identified cell cycle-regulation gene not reported in endometrial cancer. This study was aiming to analyze the role of DLGAP5 in tumorigenesis and development and to investigate its prognostic significance of patients with endometrial cancer.

Methodology

Microarray datasets (GSE17025, GSE39099 and GSE63678) from the GEO database were used for comparative analysis, and their intersection was obtained by applying the Venn diagram, and DLGAP5 was selected as the target gene. Next, transcriptome data (n = 578) was downloaded from TCGA-UCEC to analyze the mRNA expression profile of DLGAP5. Then, immunohistochemical data provided by HPA were used to identify the different protein expression levels of DLGAP5 in tumor tissues and normal tissues. Subsequently, the prognostic meaning of DLGAP5 in patients with endometrial cancer was explored based on survival data from TCGA-UCEC (n = 541). Finally, the reliability of DLGAP5 expression was verified by RT-qPCR.

Results

Transcriptome data from TCGA-UCEC, immunohistochemical data from HPA, and RT-qPCR results from clinical samples were used for triple validation to confirm that the expression of DLGAP5 in endometrial cancer tissues was significantly higher than that in normal endometrial tissues. Kaplan–Meier survival analysis announced that the expression level of DLGAP5 was negatively correlated with the overall survival of patients with endometrial cancer.

Conclusions

DLGAP5 is a potential oncogene with cell cycle regulation, and its overexpression can predict the poor prognosis of patients with endometrial cancer. As a candidate target for the diagnosis and treatment of endometrial cancer, it is worthwhile to make further study to reveal the carcinogenicity of DLGAP5 and the mechanism of its resistance of organisms.

Bioinformatics analysis combined with experiments to explore potential prognostic factors for pancreatic cancer

Background

Pancreatic cancer is a common malignant tumor of the digestive tract. It has a high degree of malignancy and poor prognosis. Finding effective molecular markers has great significance for pancreatic cancer diagnosis and treatment. This study aimed to investigate DLGAP5 expression in pancreatic cancer and explore the possible mechanisms and clinical value of DLGAP5 in tumorigenesis and tumor development.

Methods

Differentially expressed genes were screened using the Gene Expression Omnibus (GEO) data set GSE16515. Gene Ontology (GO)-based functional analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways enrichment analysis were performed on the corresponding proteins of the above genes using the Database for Annotation, Visualization, and Integrated Discovery (DAVID). The Kaplan–Meier Plotter database was used to analyze the relationship between differentially expressed genes and pancreatic cancer prognosis. The most prognostic gene, DLGAP5, was screened out, and the Oncomine and gene expression profiling interactive analysis (GEPIA) databases were used to analyze its expression in pancreatic cancer and other cancer tissues. The Cancer Genome Atlas (TCGA) database was used to analyze the overall survival of DLGAP5. Gene set enrichment analysis (GSEA) was performed to explore its possible molecular mechanisms in pancreatic cancer. Furthermore, the biological behavior of DLGAP5 in pancreatic cancer was verified by cell function experiments.

Results

A total of 201 significant upregulated differentially expressed genes and 79 downregulated genes were selected. The biological processes with significant enrichment of differential genes included cell adhesion, apoptosis, wound healing, leukocyte migration, angiogenesis. Pathways were mainly enriched in tumor-related signaling pathways such as cancer pathways, the extracellular matrix-receptor interaction pathway, and the p53 signaling pathway. DLGAP5 was significantly expressed in pancreatic cancer, and its expression level had a significant effect on patients’ survival time and progression-free survival. GSEA results indicated that DLGAP5 had significantly enriched into signaling pathways such as the cell cycle, the p53 signaling pathway, and oocyte meiosis. The experimental results showed that when we knocked down the expression of DLGAP5 in pancreatic cancer cells, their proliferation ability was significantly inhibited, and their invasion and migration ability significantly decreased.

Conclusions

DLGAP5 can be used as a prognostic indicator for pancreatic cancer and affect the occurrence and development of pancreatic cancer.

Identification of potential crucial genes associated with the pathogenesis and prognosis of pancreatic adenocarcinoma

Pancreatic adenocarcinoma (PAAD) is a type of malignant tumor with the highest mortality rate among all neoplasms worldwide, and its exact pathogenesis is still poorly understood. Timely diagnosis and treatment are of great importance in order to decrease the mortality rate of PAAD. Therefore, identifying new biomarkers for diagnosis and prognosis is essential to enable early detection of PAAD and to improve the overall survival (OS) rate. In order to screen and integrate differentially expressed genes (DEGs) between PAAD and normal tissues, a total of seven datasets were downloaded from the Gene Expression Omnibus database and the ‘limma’ and ‘robustrankggreg’ packages in R software were used. The Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analysis of the DEGs was performed using the Database for Annotation, Visualization and Integrated Discovery website, and the protein-protein interaction network analysis was performed using the Search Tool for the Retrieval of Interacting Genes/Proteins database. A gene prognostic signature was constructed using the Cox regression model. A total of 10 genes (CDK1, CCNB1, CDC20, ASPM, UBE2C, TPX2, TOP2A, NUSAP1, KIF20A and DLGAP5) that may be associated with pancreatic adenocarcinoma were identified. According to the differentially expressed genes in The Cancer Genome Atlas, the present study set up four prognostic signatures (matrix metalloproteinase 12, sodium voltage-gated channel α subunit 11, tetraspanin 1 and SH3 domain and tetratricopeptide repeats-containing 2), which effectively predicted OS. The hub genes that were highly associated with the occurrence, development and prognosis of PAAD were identified, which may be helpful to further understand the molecular basis of pancreatic cancer and guide the synthesis of drugs for PPAD.

Identification of key genes for esophageal squamous cell carcinoma via integrated bioinformatics analysis and experimental confirmation

Background

Esophageal squamous cell carcinoma (ESCC) as the main subtype of esophageal cancer (EC) is a leading cause of cancer-related death worldwide. Despite advances in early diagnosis and clinical management, the long-term survival of ESCC patients remains disappointing, due to a lack of full understanding of the molecular mechanisms.

Methods

In order to identify the differentially expressed genes (DEGs) in ESCC, the microarray datasets GSE20347 and GSE26886 from Gene Expression Omnibus (GEO) database were analyzed. The enrichment analyses of gene ontology (GO) terms, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and Gene Set Enrichment Analysis (GSEA) were performed for the DEGs. The protein-protein interaction (PPI) network of these DEGs was constructed using the Cytoscape software based on the STRING database to select as hub genes for weighted co-expression network analysis (WGCNA) with ESCC samples from TCGA database.

Results

A total of 746 DEGs were commonly shared in the two datasets including 286 upregulated genes and 460 downregulated genes in ESCC. The DEGs were enriched in biological processes such as extracellular matrix organization, proliferation and keratinocyte differentiation, and were enriched in biological pathways such as ECM-receptor interaction and cell cycle. GSEA analysis also indicated the enrichment of upregulated DEGs in cell cycle. The 40 DEGs were selected as hub genes. The MEblack module was found to be enriched in the cell cycle, Spliceosome, DNA replication and Oocyte meiosis. Among the hub genes correlated with MEblack module, GSEA analysis indicated that DEGs of TCGA samples with DLGAP5 upregulation was enriched in cell cycle. Moreover, the highly endogenous expression of DLGAP5 was confirmed in ESCC cells. DLGAP5 knockdown significantly inhibited the proliferation of ESCC cells.

Conclusions

DEGs and hub genes such as DLGAP5 from independent datasets in the current study will provide clues to elucidate the molecular mechanisms involved in development and progression of ESCC.

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.