Identification of Potential Biomarkers in Association With Progression and Prognosis in Epithelial Ovarian Cancer by Integrated Bioinformatics Analysis

FoxM1 promotes the proliferation of cervical adenocarcinoma cells through transcriptional activation of FAM83D

Cervical adenocarcinoma exhibits a steadily increasing global incidence with notable demographic shifts toward younger populations. Despite the absence of distinct clinical guidelines differentiating its management from squamous cell carcinoma, treatment strategies remain non-specific, contributing to suboptimal patient outcomes. To address this therapeutic gap, we systematically investigated molecular disparities between adenocarcinoma and squamous cell carcinoma through integrated ChIP-seq and RNA-seq analyses. Our multi-omics approach identified FAM83D as a novel transcriptional target directly regulated by the FoxM1 oncoprotein, demonstrating adenocarcinoma-specific expression in HeLa cells. This regulatory relationship was experimentally validated using quantitative PCR and luciferase reporter assays. Mechanistically, we delineated that FoxM1 governs cell cycle progression and proliferation via FAM83D-dependent pathways. Intriguingly, co-immunoprecipitation studies revealed a physical interaction between FoxM1 and karyopherin α2 (KPNA2), another adenocarcinoma-enriched protein, with their expression levels showing significant positive correlation in clinical specimens. This study not only elucidates the oncogenic axis of FoxM1-FAM83D but also reveals the dual regulatory role of FoxM1 as both a transcriptional activator and protein interaction hub in cervical adenocarcinoma pathogenesis. These findings expand the molecular landscape of this malignancy and identify potential therapeutic entry points for targeted adenocarcinoma interventions.

TRIP13 - a potential drug target in cancer pharmacotherapy

ATPases Associated with Diverse Cellular Activity (AAA+ATPases) are important enzymatic functional proteins in human cells. Thyroid Hormone Receptor Interacting Protein-13 (TRIP13) is a member of this protein superfamily, that partly regulates DNA repair pathways and spindle assembly checkpoints during mitosis. TRIP13 is reported as an oncogene involving multiple pathways in many human malignancies, including multiple myeloma, brain tumors, etc. The structure of TRIP13 reveals the mechanisms for ATP binding and how TRIP13 recognizes the Mitotic Arrest Deficiency-2 (MAD2) protein, with p31comet acting as an adapter protein. DCZ0415, TI17, DCZ5417, and DCZ5418 are the reported small-molecule inhibitors of TRIP13, which have been demonstrated to inhibit TRIP13's biological functions significantly and effective in suppressing various types of malignant cells, indicating that TRIP13 is a significant anticancer drug target. Currently, no systematic reviews are cutting across the functions, structure, and novel inhibitors of TRIP13. This review provides a comprehensive overview of TRIP13's biological functions, its roles in eighteen different cancers, four small molecule inhibitors, different underlying molecular mechanisms, and its functionality as a potential anticancer drug target.

Identification of the biological functions and chemo-therapeutic responses of ITGB superfamily in ovarian cancer

BACKGROUND

Patients with ovarian cancer (OC) tend to face a poor prognosis due to a lack of typical symptoms and a high rate of recurrence and chemo-resistance. Therefore, identifying representative and reliable biomarkers for early diagnosis and prediction of chemo-therapeutic responses is vital for improving the prognosis of OC.

METHODS

Expression levels, IHC staining, and subcellular distribution of eight ITGBs were analyzed using The Cancer Genome Atlas (TCGA)-Ovarian Serous Cystadenocarcinoma (OV) database, GEO DataSets, and the HPA website. PrognoScan and Univariate Cox were used for prognostic analysis. TIDE database, TIMER database, and GSCA database were used to analyze the correlation between immune functions and ITGBs. Consensus clustering analysis was performed to subtype OC patients in the TCGA database. LASSO regression was used to construct the predictive model. The Cytoscape software was used for identifying hub genes. The 'pRRophetic' R package was applied to predict chemo-therapeutic responses of ITGBs.

RESULTS

ITGBs were upregulated in OC tissues except ITGB1 and ITGB3. High expression of ITGBs correlated with an unfavorable prognosis of OC except ITGB2. In OC, there was a strong correlation between immune responses and ITGB2, 6, and 7. In addition, the expression matrix of eight ITGBs divided the TCGA-OV database into two subgroups. Subgroup A showed upregulation of eight ITGBs. The predictive model distinguishes OC patients from favorable prognosis to poor prognosis. Chemo-therapeutic responses showed that ITGBs were able to predict responses of common chemo-therapeutic drugs for patients with OC.

CONCLUSIONS

This article provides evidence for predicting prognosis, immuno-, and chemo-therapeutic responses of ITGBs in OC and reveals related biological functions of ITGBs in OC.

Knockdown of CENPM activates cGAS-STING pathway to inhibit ovarian cancer by promoting pyroptosis

OBJECTIVE

We aimed to screen novel gene signatures for ovarian cancer (OC) and explore the role of biomarkers in OC via regulating pyroptosis using bioinformatics analysis.

METHODS

Differentially expressed genes (DEGs) of OC were screened from GSE12470 and GSE16709 datasets. Hub genes were determined from protein-protein interaction networks after bioinformatics analysis. The role of Centromeric protein M (CENPM) in OC was assessed by subcutaneous tumor experiment using hematoxylin-eosin and immunohistochemical staining. Tumor metastasis was evaluated by detecting epithelial-mesenchymal transition-related proteins. The proliferation, migration, and invasion were determined using cell counting kit and transwell assay. Enzyme-linked immunosorbent assay was applied to measure inflammatory factors. The mRNA and protein expression were detected using real-time quantitative PCR and western blot.

RESULTS

We determined 9 hub genes (KIFC1, PCLAF, CDCA5, KNTC1, MCM3, OIP5, CENPM, KIF15, and ASF1B) with high prediction value for OC. In SKOV3 and A2780 cells, the expression levels of hub genes were significantly up-regulated, compared with normal ovarian cells. CENPM was selected as a key gene. Knockdown of CENPM suppressed proliferation, migration, and invasion of OC cells. Subcutaneous tumor experiment revealed that CENPM knockdown significantly suppressed tumor growth and metastasis. Additionally, pyroptosis was promoted in OC cells and xenograft tumors after CENPM knockdown. Furthermore, CENPM knockdown activated cGAS-STING pathway and the pathway inhibitor reversed the inhibitory effect of CENPM knockdown on viability, migration, and invasion of OC cells.

CONCLUSION

CENPM was a novel biomarker of OC, and knockdown of CENPM inhibited OC progression by promoting pyroptosis and activating cGAS-STING pathway.

Through the Looking Glass: Updated Insights on Ovarian Cancer Diagnostics

Epithelial ovarian cancer (EOC) is the deadliest gynaecological malignancy and the eighth most prevalent cancer in women, with an abysmal mortality rate of two million worldwide. The existence of multiple overlapping symptoms with other gastrointestinal, genitourinary, and gynaecological maladies often leads to late-stage diagnosis and extensive extra-ovarian metastasis. Due to the absence of any clear early-stage symptoms, current tools only aid in the diagnosis of advanced-stage patients, wherein the 5-year survival plummets further to less than 30%. Therefore, there is a dire need for the identification of novel approaches that not only allow early diagnosis of the disease but also have a greater prognostic value. Toward this, biomarkers provide a gamut of powerful and dynamic tools to allow the identification of a spectrum of different malignancies. Both serum cancer antigen 125 (CA-125) and human epididymis 4 (HE4) are currently being used in clinics not only for EOC but also peritoneal and GI tract cancers. Screening of multiple biomarkers is gradually emerging as a beneficial strategy for early-stage diagnosis, proving instrumental in administration of first-line chemotherapy. These novel biomarkers seem to exhibit an enhanced potential as a diagnostic tool. This review summarizes existing knowledge of the ever-growing field of biomarker identification along with potential future ones, especially for ovarian cancer.

Single-cell and bulk RNA sequencing reveal ligands and receptors associated with worse overall survival in serous ovarian cancer

Background

Serous ovarian carcinoma is the most frequent histological subgroup of ovarian cancer and the leading cause of death among gynecologic tumors. The tumor microenvironment and cancer-associated fibroblasts (CAFs) have a critical role in the origin and progression of cancer. We comprehensively characterized the crosstalk between CAFs and ovarian cancer cells from malignant fluids to identify specific ligands and receptors mediating intercellular communications and disrupted pathways related to prognosis and therapy response.

Methods

Malignant fluids of serous ovarian cancer, including tumor-derived organoids, CAFs-enriched (eCAFs), and malignant effusion cells (no cultured) paired with normal ovarian tissues, were explored by RNA-sequencing. These data were integrated with single-cell RNA-sequencing data of ascites from ovarian cancer patients. The most relevant ligand and receptor interactions were used to identify differentially expressed genes with prognostic values in ovarian cancer.

Results

CAF ligands and epithelial cancer cell receptors were enriched for PI3K-AKT, focal adhesion, and epithelial-mesenchymal transition signaling pathways. Collagens, MIF, MDK, APP, and laminin were detected as the most significant signaling, and the top ligand-receptor interactions THBS2/THBS3 (CAFs)—CD47 (cancer cells), MDK (CAFs)—NCL/SDC2/SDC4 (cancer cells) as potential therapeutic targets. Interestingly, 34 genes encoding receptors and ligands of the PI3K pathway were associated with the outcome, response to treatment, and overall survival in ovarian cancer. Up-regulated genes from this list consistently predicted a worse overall survival (hazard ratio > 1.0 and log-rank P < 0.05) in two independent validation cohorts.

Conclusions

This study describes critical signaling pathways, ligands, and receptors involved in the communication between CAFs and cancer cells that have prognostic and therapeutic significance in ovarian cancer.

Integrative weighted molecular network construction from transcriptomics and genome wide association data to identify shared genetic biomarkers for COPD and lung cancer

Chronic obstructive pulmonary disease (COPD) is a multifactorial progressive airflow obstruction in the lungs, accounting for high morbidity and mortality across the world. This study aims to identify potential COPD blood-based biomarkers by analyzing the dysregulated gene expression patterns in blood and lung tissues with the help of robust computational approaches. The microarray gene expression datasets from blood (136 COPD and 6 controls) and lung tissues (16 COPD and 19 controls) were analyzed to detect shared differentially expressed genes (DEGs). Then these DEGs were used to construct COPD protein network-clusters and functionally enrich them against gene ontology annotation terms. The hub genes in the COPD network clusters were then queried in GWAS catalog and in several cancer expression databases to explore their pathogenic roles in lung cancers. The comparison of blood and lung tissue datasets revealed 63 shared DEGs. Of these DEGs, 12 COPD hub gene-network clusters (SREK1, TMEM67, IRAK2, MECOM, ASB4, C1QTNF2, CDC42BPA, DPF3, DET1, CCDC74B, KHK, and DDX3Y) connected to dysregulations of protein degradation, inflammatory cytokine production, airway remodeling, and immune cell activity were prioritized with the help of protein interactome and functional enrichment analysis. Interestingly, IRAK2 and MECOM hub genes from these COPD network clusters are known for their involvement in different pulmonary diseases. Additional COPD hub genes like SREK1, TMEM67, CDC42BPA, DPF3, and ASB4 were identified as prognostic markers in lung cancer, which is reported in 1% of COPD patients. This study identified 12 gene network- clusters as potential blood based genetic biomarkers for COPD diagnosis and prognosis.

Effect of CDCA5 on Proliferation and Metastasis of Triple Negative Breast Cancer Cells under shRNA Interference Technology

Objective

It was to explore the effect of cell division cycle associated 5 (CDCA5) under shRNA interference on proliferation and metastasis of triple negative breast cancer (TNBC) cells.

Methods

MDA-ME-231 and BT549 cells were selected as the research objects. According to the different interference methods and CDCA5 interference sequences, they were divided into the interference group 1_MDA-ME-231, the interference group 2_MDA-ME-231, the interference group 1_BT549, the interference group 2_BT549 (using shRNA technology), the control group _MDA-ME-231, and the control group _BT549 (breast cancer cells under normal culture conditions). MCF10A cells were routinely cultured as the negative control group to analyze the effect of CDCA5 expression on the proliferation and migration of cancer cells.

Results

The expression of CDCA5 protein in _MDA-ME-231 and _BT549 cells in control group was significantly higher than that in negative control group (P < 0.05). Compared with the control group, the inhibition rates of CDCA5 expression in 1_MDA-ME-231, 2_MDA-ME-231, 1_BT549, and 2_BT549 cells in the interference group were 39.01%, 42.98%, 49.57%, and 60.98%, respectively (P < 0.05). From 12 h, the proliferation level of TNBC cells at different culture time was lower than that of the control group (P < 0.05). Compared with the number of staining cells in the control group, the positive staining cells in 1_MDA-ME-231 (61.42%), 2_MDA-ME-231 (72.06%), 1_BT549 (52.53%), and 2_BT549 (59.65%) in the interference group were significantly decreased (P < 0.05).

Conclusion

The results show that the expression of CDCA5 in TNBC is increased, which plays an important role in the proliferation and migration of cancer cells. shRNA interference technology can knock down the expression of CDCA5 and inhibit its “promoting cancer” effect.

Bayesian hierarchical lasso Cox model: A 9-gene prognostic signature for overall survival in gastric cancer in an Asian population

Objective

Gastric cancer (GC) is one of the most common tumour diseases worldwide and has poor survival, especially in the Asian population. Exploration based on biomarkers would be efficient for better diagnosis, prediction, and targeted therapy.

Methods

Expression profiles were downloaded from the Gene Expression Omnibus (GEO) database. Survival-related genes were identified by gene set enrichment analysis (GSEA) and univariate Cox. Then, we applied a Bayesian hierarchical lasso Cox model for prognostic signature screening. Protein-protein interaction and Spearman analysis were performed. Kaplan–Meier and receiver operating characteristic (ROC) curve analysis were applied to evaluate the prediction performance. Multivariate Cox regression was used to identify prognostic factors, and a prognostic nomogram was constructed for clinical application.

Results

With the Bayesian lasso Cox model, a 9-gene signature included TNFRSF11A, NMNAT1, EIF5A, NOTCH3, TOR2A, E2F8, PSMA5, TPMT, and KIF11 was established to predict overall survival in GC. Protein-protein interaction analysis indicated that E2F8 was likely related to KIF11. Kaplan-Meier analysis showed a significant difference between the high-risk and low-risk groups (P<0.001). Multivariate analysis demonstrated that the 9-gene signature was an independent predictor (HR = 2.609, 95% CI 2.017–3.370), and the C-index of the integrative model reached 0.75. Function enrichment analysis for different risk groups revealed the most significant enrichment pathway/term, including pyrimidine metabolism and respiratory electron transport chain.

Conclusion

Our findings suggested that a novel prognostic model based on a 9-gene signature was developed to predict GC patients in high-risk and improve prediction performance. We hope our model could provide a reference for risk classification and clinical decision-making.

Integrative Pan-Cancer Analysis of KIF15 Reveals Its Diagnosis and Prognosis Value in Nasopharyngeal Carcinoma

Background

KIF15 plays a vital role in many biological processes and has been reported to influence the occurrence and development of certain human cancers. However, there are few systematic evaluations on the role of KIF15 in human cancers, and the role of KIF15 in the diagnosis and prognosis of nasopharyngeal carcinoma (NPC) also remains unexplored. Therefore, this study aimed to conduct a pan-cancer analysis of KIF15 and evaluate its diagnostic and prognostic potential in NPC.

Methods

The expression pattern, prognostic value, molecular function, tumor mutation burden, microsatellite instability, and immune cell infiltration of KIF15 were examined based on public databases. Next, the diagnostic value of KIF15 in NPC was analyzed using the Gene Expression Omnibus (GEO) database and immunohistochemistry (IHC). Kaplan–Meier curves, Cox regression analyses, and nomograms were used to evaluate the effects of KIF15 expression on NPC prognosis. Finally, the effect of KIF15 on NPC was explored by in vitro experiments.

Results

The expression of KIF15 was significantly upregulated in 20 out of 33 cancer types compared to adjacent normal tissue. Kyoto Encyclopedia of Genes and Genomes enrichment (KEGG) analysis showed that KIF15 could participate in several cancer-related pathways. The increased expression level of KIF15 was correlated with worse clinical outcomes in many types of human cancers. Additionally, KIF15 expression was related to cancer infiltration of immune cells, tumor mutation burden, and microsatellite instability. In the analysis of NPC, KIF15 was significantly upregulated based on the GEO database and immunohistochemistry. A high expression of KIF15 was negatively associated with the prognosis of patients with NPC. A nomogram model integrating clinical characteristics and KIF15 expression was established, and it showed good predictive ability with an area under the curve value of 0.73. KIF15 knockdown significantly inhibited NPC cell proliferation and migration.

Conclusions

Our findings revealed the important and functional role of KIF15 as an oncogene in pan-cancer. Moreover, high expression of KIF15 was found in NPC tissues, and was correlated with poor prognosis in NPC. KIF15 may serve as a potential therapeutic target in NPC treatment.

Prognostic Value and Therapeutic Potential of CBX Family Members in Ovarian Cancer

Background: Ovarian cancer (OV) is one of the common malignant tumors and has a poor prognosis. Chromobox (CBX) family proteins are critical components of epigenetic regulation complexes that repress target genes transcriptionally via chromatin modification. Some studies have investigated the function specifications among several CBXs members in multiple cancer types, however, little is known about the functions and prognostic roles of distinct CBXs family proteins in ovarian cancer. Methods: In this study, several bioinformatics databases and in vitro experiments were used to analyze the expression profiles, prognostic values, and therapeutic potential of the CBXs family (CBX1-8) in ovarian cancer. Results: It was found that higher expression of CBX3/8 and lower expression of CBX1/6/7 were detected in OV tissues. CBX2/4/5/8 were significantly correlated with individual cancer stages of OV. The expression of CBX1/2/3 were all significantly associated with worse overall survival (OS) and progression-free survival (PFS) for OV patients, whereas the expression of other five CBXs members showed either irrelevant (CBX5 and CBX8) or inconsistent (CBX4, CBX6, and CBX7) results for both OS and PFS in OV. These results showed that only CBX3 had consistent results in expression and prognosis. Further cell experiments also showed that CBX3 promoted the proliferation of ovarian cancer cells. CBX3 was highly expressed in chemoresistant OV tissues. These results indicated that CBX3 was the most likely prognostic indicator and new therapeutic target in OV. Furthermore, gene enrichment analysis suggests that the CBXs family was primarily involved in mast cell activation and mast cell mediated immunity. Individual CBXs members were associated with varying degrees of the infiltration of immune cells, especially B cells. Finally, a high genetic alteration rate of CBXs family (39%) was observed in OV. The low methylation status of CBX3/8 in OV may be associated with their high expression levels. Conclusions: Taken together, these findings exhibited the pivotal value of CBXs family members (especially CBX3) in the prognosis and chemoresistance of ovarian cancer. Our results may provide new insight to explore new prognostic biomarkers and therapeutic targets for ovarian cancer.

Comprehensive study of a novel immune-related lncRNA for prognosis and drug treatment of cervical squamous cell carcinoma

A comprehensive study focusing on immune-related long non-coding RNAs (lncRNAs) in cervical cancer (CC) was performed. Through the integration of TCGA data, a total of 266 immune-related lncRNAs were obtained. We defined all samples as an entire set, and randomly divided them into train set and test set at a ratio of 1:1. Univariate, LASSO and multivariate Cox regression analyses were carried out based on train set for key lncRNAs (UBL7-AS1, AC083809.1, LIPE-AS1, PCED1B-AS1, ELFN1-AS1 and NCK1-DT) to construct a prognostic model, while the others were used for validation. The overall survival (OS) suggested that we may have longer survival expectations for patients classified into the low-risk group. The P values of risk score in univariate analysis and multivariate analysis were all less than 0.05, indicating the ability of risk score to independently assess the prognosis of patients. For clinical application, a nomogram with a high degree of agreement between the predicted curve and the actual curve was constructed. Subsequently, immune status and chemotherapy response were investigated in two prognostic subtypes. The associations between risk score and immune cell were estimated, in which CD8+ T cells showed the highest positive correlation and activated mast cell showed the highest negative correlation. In addition, checkpoint proteins (CTLA4, LAG3, PD-1, and TIGIT) showing negative correlation with risk score were found to be upregulated in low-risk group. A total of 3 chemotherapy drugs including paclitaxel, vinorelbine and methotrexate were considered effective in patients of high-risk group. Using 6 key immune-related lncRNAs, we identified two prognostic subtypes and provided new insights for CC immunotherapy.

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.

Development and validation of an intra-tumor heterogeneity-related signature to predict prognosis of bladder cancer: a study based on single-cell RNA-seq

Intra-tumor heterogeneity (ITH) was a potential mechanism of progression and drug resistance in bladder cancer (BCa). However, the understanding of ITH in BCa remains insufficient. Single-cell RNA sequencing (scRNA-seq) profiles of 2075 cells were analyzed, and 2940 cell markers were screened. The ITH of 396 cases was evaluated, and 96 ITH-related genes were identified. Based on the gene-pair strategy, 96 genes were cyclically paired, and an 8-gene-pair model was successfully established to evaluate the overall survival of BCa through Lasso and multivariate Cox regressions. The risk model showed high predictive value in the training dataset (n = 396, p = 0) and external validation datasets (n = 165, p = 2.497e-02; n = 224, p = 3.423e-02). The model was also valuable for the prediction of clinical treatment outcomes. Totally, a prognostic model based on scRNA-seq and ITH was successfully constructed and validated in large cohorts, providing novel clues for ITH study of BCa.

Meta-analysis identifying epithelial-derived transcriptomes predicts poor clinical outcome and immune infiltrations in ovarian cancer

BACKGROUND

Previous studies revealed that the epithelial component is associated with the modulation of the ovarian tumor microenvironment (TME). However, the identification of key transcriptional signatures of laser capture microdissected human ovarian cancer epithelia remains lacking.

METHODS

We identified the differentially expressed transcriptional signatures of human ovarian cancer epithelia by meta-analysis of GSE14407, GSE2765, GSE38666, GSE40595, and GSE54388. Then we investigated the enrichment of KEGG pathways that are associated with epithelia-derived transcriptomes. Finally, we investigated the correlation of key epithelia-hub genes with the survival prognosis and immune infiltrations. Finally, we investigated the genetic alterations of key prognostic hub genes and their diagnostic efficacy in ovarian cancer epithelia.

RESULTS

We identified 1339 differentially expressed genes (DEGs) in ovarian cancer epithelia including 541upregulated and 798 downregulated genes. We identified 21 (such as E2F4, FOXM1, TFDP1, E2F1, and SIN3A) and 11 (such as JUN, DDX4, FOSL1, NOC2L, and HMGA1) master transcriptional regulators (MTRs) that are interacted with upregulated and the downregulated genes in ovarian tumor epithelium, respectively. The STRING-based analysis identified hub genes (such as CDK1, CCNB1, AURKA, CDC20, and CCNA2) in ovarian cancer epithelia. The significant clusters of identified hub genes are associated with the enrichment of KEGG pathways including cell cycle, DNA replication, cytokine-cytokine receptor interaction, pathways in cancer, and focal adhesion. The upregulation of SCNN1A and CDCA3 and the downregulation of SOX6 are correlated with a shorter survival prognosis in ovarian cancer (OV). The expression level of SOX6 is negatively correlated with immune score and positively correlated with tumor purity in OV. Moreover, SOX6 is negatively correlated with the infiltration of TILs, CD8+ T cells, CD4+ Regulatory T cells, cytolytic activity, T cell activation, pDC, neutrophils, and macrophages in OV. Also, SOX6 is negatively correlated with various immune markers including CD8A, PRF1, GZMA, GZMB, NKG7, CCL3, and CCL4, indicating the immune regulatory efficiency of SOX6 in the TME of OV. Furthermore, SCNN1A, CDCA3, and SOX6 genes are genetically altered in OV and the expression levels of SCNN1A and SOX6 genes showed diagnostic efficacy in ovarian cancer epithelia.

CONCLUSIONS

The identified ovarian cancer epithelial-derived key transcriptional signatures are significantly correlated with survival prognosis and immune infiltrations, and may provide new insight into the diagnosis and treatment of epithelial ovarian cancer.

FOXM1: A Multifunctional Oncoprotein and Emerging Therapeutic Target in Ovarian Cancer

Forkhead box M1 (FOXM1) is a member of the conserved forkhead box (FOX) transcription factor family. Over the last two decades, FOXM1 has emerged as a multifunctional oncoprotein and a robust biomarker of poor prognosis in many human malignancies. In this review article, we address the current knowledge regarding the mechanisms of regulation and oncogenic functions of FOXM1, particularly in the context of ovarian cancer. FOXM1 and its associated oncogenic transcriptional signature are enriched in >85% of ovarian cancer cases and FOXM1 expression and activity can be enhanced by a plethora of genomic, transcriptional, post-transcriptional, and post-translational mechanisms. As a master transcriptional regulator, FOXM1 promotes critical oncogenic phenotypes in ovarian cancer, including: (1) cell proliferation, (2) invasion and metastasis, (3) chemotherapy resistance, (4) cancer stem cell (CSC) properties, (5) genomic instability, and (6) altered cellular metabolism. We additionally discuss the evidence for FOXM1 as a cancer biomarker, describe the rationale for FOXM1 as a cancer therapeutic target, and provide an overview of therapeutic strategies used to target FOXM1 for cancer treatment.

Systemic Analysis of the DNA Replication Regulator MCM Complex in Ovarian Cancer and Its Prognostic Value

Microliposome maintenance (MCM) 2, MCM3, MCM4, MCM5, MCM6, and MCM7 are DNA replication regulators and are involved in the progression of multiple cancer types, but their role in ovarian cancer is still unclear. The purpose of this study is to clarify the biological function and prognostic value of the MCM complex in ovarian cancer (OS) progression. We analyzed DNA alterations, mRNA and protein levels, protein structure, PPI network, functional enrichment, and prognostic value in OC based on the Oncomine, cBioPortal, TCGA, CPTAC, PDB, GeneMANIA, DAVID, KEGG, and GSCALite databases. The results indicated that the protein levels of these DNA replication regulators were increased significantly. Moreover, survival analysis showed a prognostic signature based on the MCM complex, which performed moderately well in terms of OS prognostic prediction. Additionally, protein structure, functional enrichment, and PPI network analyses indicated that the MCM complex synergistically promoted OC progression by accelerating DNA replication and the cell cycle. In conclusion, our study suggested that the MCM complex might be a potential target and prognostic marker for OC patients.

Ubiquitin Proteasome Pathway Transcriptome in Epithelial Ovarian Cancer

In this article, we reviewed the transcription of genes coding for components of the ubiquitin proteasome pathway in publicly available datasets of epithelial ovarian cancer (EOC). KEGG analysis was used to identify the major pathways distinguishing EOC of low malignant potential (LMP) from invasive high-grade serous ovarian carcinomas (HGSOC), and to identify the components of the ubiquitin proteasome system that contributed to these pathways. We identified elevated transcription of several genes encoding ubiquitin conjugases associated with HGSOC. Fifty-eight genes coding for ubiquitin ligases and more than 100 genes encoding ubiquitin ligase adaptors that were differentially expressed between LMP and HGSOC were also identified. Many differentially expressed genes encoding E3 ligase adaptors were Cullin Ring Ligase (CRL) adaptors, and 64 of them belonged to the Cullin 4 DCX/DWD family of CRLs. The data suggest that CRLs play a role in HGSOC and that some of these proteins may be novel therapeutic targets. Differential expression of genes encoding deubiquitinases and proteasome subunits was also noted.

Intestinal mucosa-derived DNA methylation signatures in the penetrating intestinal mucosal lesions of Crohn's disease

The purpose of this study was to evaluate genome-wide DNA methylation changes in intestinal mucosa tissue of adult patients with Crohn's disease comprehensively. DNA methylation chip was used to analyze abnormal methylation sites among penetrating and non-penetrating intestinal mucosa tissue of Crohn's disease and normal intestinal mucosa tissue of healthy controls. Methylation abnormalities of different locus were verified by pyrosequencing and quantitative polymerase chain reaction. Differential DNA methylation sites were participated in the positive regulation of apoptosis and the positive regulation of IL-8 production and were enriched in signaling pathways related to inflammatory bowel disease and extracellular matrix receptor interaction signaling pathways. Correlation analysis showed that the methylation abnormalities of HLA-DRB1 (r = - 0.62, P < 0.001), MUC1 (r = - 0.45, P = 0.01), YPEL5 (r = - 0.55, P = 0.001) and CBLB (r = - 0.62, P < 0.001) were significantly negatively correlated with their relative expression levels. The degree of methylation abnormality of MUC1 was negatively correlated with the disease activity score of Crohn's disease (r = - 0.50, P = 0.01). Apoptosis, interleukin-8 production and abnormal extracellular matrix might be involved in the mechanism of penetrating intestinal mucosal lesions in Crohn's disease. The degree of abnormal methylation of MUC1 was negatively correlated with the disease activity of Crohn's disease.

Identification of potential markers for differentiating epithelial ovarian cancer from ovarian low malignant potential tumors through integrated bioinformatics analysis

Background

Epithelial ovarian cancer (EOC), as a lethal malignancy in women, is often diagnosed as advanced stages. In contrast, intermediating between benign and malignant tumors, ovarian low malignant potential (LMP) tumors show a good prognosis. However, the differential diagnosis of the two diseases is not ideal, resulting in delays or unnecessary therapies. Therefore, unveiling the molecular differences between LMP and EOC may contribute to differential diagnosis and novel therapeutic and preventive policies development for EOC.

Methods

In this study, three microarray data (GSE9899, GSE57477 and GSE27651) were used to explore the differentially expressed genes (DEGs) between LMP and EOC samples. Then, 5 genes were screened by protein–protein interaction (PPI) network, receiver operating characteristic (ROC), survival and Pearson correlation analysis. Meanwhile, chemical-core gene network construction was performed to identify the potential drugs or risk factors for EOC based on 5 core genes. Finally, we also identified the potential function of the 5 genes for EOC through pathway analysis.

Results

Two hundred thirty-four DEGs were successfully screened, including 81 up-regulated genes and 153 down-regulated genes. Then, 5 core genes (CCNB1, KIF20A, ASPM, AURKA, and KIF23) were identified through PPI network analysis, ROC analysis, survival and Pearson correlation analysis, which show better diagnostic efficiency and higher prognostic value for EOC. Furthermore, NetworkAnalyst was used to identify top 15 chemicals that link with the 5 core genes. Among them, 11 chemicals were potential drugs and 4 chemicals were risk factors for EOC. Finally, we found that all 5 core genes mainly regulate EOC development via the cell cycle pathway by the bioinformatic analysis.

Conclusion

Based on an integrated bioinformatic analysis, we identified potential biomarkers, risk factors and drugs for EOC, which may help to provide new ideas for EOC diagnosis, condition appraisal, prevention and treatment in future.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13048-021-00794-0.

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

Background

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

Methods

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

Results

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

Conclusion

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

Identification of Potential Hub Genes Related to Diagnosis and Prognosis of Hepatitis B Virus-Related Hepatocellular Carcinoma via Integrated Bioinformatics Analysis

Hepatocellular carcinoma (HCC) is a common malignant cancer with poor survival outcomes, and hepatitis B virus (HBV) infection is most likely to contribute to HCC. But the molecular mechanism remains obscure. Our study intended to identify the candidate potential hub genes associated with the carcinogenesis of HBV-related HCC (HBV-HCC), which may be helpful in developing novel tumor biomarkers for potential targeted therapies. Four transcriptome datasets (GSE84402, GSE25097, GSE94660, and GSE121248) were used to screen the 309 overlapping differentially expressed genes (DEGs), including 100 upregulated genes and 209 downregulated genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment were used to explore the biological function of DEGs. A PPI network based on the STRING database was constructed and visualized by the Cytoscape software, consisting of 209 nodes and 1676 edges. Then, we recognized 17 hub genes by CytoHubba plugin, which were further validated on additional three datasets (GSE14520, TCGA-LIHC, and ICGC-LIRI-JP). The diagnostic effectiveness of hub genes was assessed with receiver operating characteristic (ROC) analysis, and all hub genes displayed good performance in discriminating TNM stage I patient samples and normal tissue ones. For prognostic analysis, two prognostic key genes (TOP2A and KIF11) out of the 17 hub genes were screened and used to develop a prognostic signature, which showed good potential for overall survival (OS) stratification of HBV-HCC patients. Gene Set Enrichment Analysis (GSEA) was performed in order to better understand the function of this prognostic gene signature. Finally, the miRNA-mRNA regulatory relationships of all hub genes in human liver were predicted using miRNet. In conclusion, the current study gives further insight on the pathogenesis and carcinogenesis of HBV-HCC, and the identified DEGs provide a promising direction for improving the diagnostic, prognostic, and therapeutic outcomes of HBV-HCC.

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.

Investigating Patterns of Immune Interaction in Ovarian Cancer: Probing the O-glycoproteome by the Macrophage Galactose-Like C-type Lectin (MGL)

Glycosylation, the posttranslational linking of sugar molecules to proteins, is notoriously altered during tumor transformation. More specifically in carcinomas, GalNAc-type O-glycosylation, is characterized by biosynthetically immature truncated glycans present on the cancer cell surface, which profoundly impact anti-tumor immune recognition. The tumor-associated glycan pattern may thus be regarded as a biomarker of immune modulation. In epithelial ovarian cancer (EOC) there is a particular lack of specific biomarkers and molecular targets to aid early diagnosis and develop novel therapeutic interventions. The aim of this study was to investigate the ovarian cancer O-glycoproteome and identify tumor-associated glycoproteins relevant in tumor-dendritic cell (DC) interactions, mediated by macrophage galactose-like C type lectin (MGL), which recognizes the tumor-associated Tn O-glycan. Lectin weak affinity chromatography (LWAC) was employed to probe the O-glycopeptidome by MGL and Vicia villosa agglutinin (VVA) lectin using glycoengineered ovarian cancer cell lines and ovarian cancer tissues as input material. Biochemical and bioinformatics analysis gave information on the glycan arrangement recognized by MGL in tumor cells. The potential MGL binders identified were located, as expected, at the cell membrane, but also within the intracellular compartment and the matrisome, suggesting that MGL in vivo may play a complex role in sensing microenvironmental cues. The tumor glycoproteins binders for MGL may become relevant to characterize the interaction between the immune system and tumor progression and contribute to the design of glycan targeting-based strategies for EOC immunotherapeutic interventions.

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.

Bioinformatics analysis of FOLR1 expression, functional enrichment, related signaling pathways and relationship with prognosis in ovarian cancer

Objective To investigate folate-receptor 1 (FOLR1) expression in ovarian cancer and its association with patient prognosis.

Methods TCGA and Oncomine databases were used to collect data about FOLR1 mRNA expression in multiple carcinomas. FOLR1 mRNA expression levels in ovarian cancer samples and corresponding adjacent normal ovary tissue were compared. A protein-protein interaction (PPI) network was constructed using the STRING database of FOLR1 and relevant genes. The overall survival (OS) and progression free survival (PFS) rates of ovarian cancer patients in high- and low- FOLR1 expression groups were compared by log-rank test. Sixty-six ovarian epithelial carcinoma samples were included in the study, and tumor specimens of the 66 cases were tested for FOLR1 protein expression by an immunohistochemistry assay.

Results FOLR1 mRNA was significantly elevated in ovarian cancer compared to other carcinomas. FOLR1 mRNA expression levels were significantly higher in tumor tissues than in the corresponding normal tissues (P<0.05) of ovarian cancer patients. The PPI network indicated that the local clustering coefficient was 0.898, indicating that the PPI network was enriched significantly (P<0.05). The median PFS values were 22.39 and 19.00 months for lowand high-FOLR1 expression groups, respectively, with significant statistical difference between the two (HR=1.26, 95%CI:1.09-1.45, P<0.05). FOLR1 protein expression was correlated with tumor differentiation (P<0.05) in ovarian cancer patients. However, its levels were not correlated with patient age, tumor diameter, lymph node metastasis or FIGO stage (P>0.05).

Conclusion FOLR1 is upregulated in epithelial ovarian cancer, and its expression is correlated with patients’ progression free survival, making it a valuable biomarker for prognosis.

Claudin 10 acts as a novel biomarker for the prognosis of patients with ovarian cancer

Ovarian cancer (OC) is one of the most fatal gynecological malignancies in the world and confers a poor 5-year survival rate. The present study was designed to discover novel prognostic markers for patients with OC in order to estimate disease metastasis or recurrence. Based on the large cohorts of transcriptome data from multicenter sources, a comprehensive analysis was performed to explore potential prognostic markers. A total of 269 differentially expressed genes were identified, of which 32 were upregulated and 237 downregulated in OC tissues compared with the corresponding expression in normal tissues. Kaplan-Meier analysis, log-rank test and nomogram analysis were employed to demonstrate that low expression levels of claudin 10 (CLDN10) were associated with a less favorable disease prognosis. The most promising prognostic marker for OC was subsequently selected. Additionally, the prognostic nomogram was constructed in order to assess the 5-year survival rate using CLDN10 expression as a prognostic marker for OC. Furthermore, gene set enrichment analysis and analysis of the tumor-associated competing endogenous RNA network were performed to elucidate the potential biological processes associated with CLDN10 expression. The current results indicated that CLDN10 may influence OC progression via transforming growth factor-β (TGF-β)- or WNT/β-catenin-induced epithelial-to-mesenchymal transition (EMT). The associations among CLDN10, microRNA-486-5p, TGF-β, WNT/β-catenin and EMT should be further investigated in future studies.

The role of the CDCA gene family in ovarian cancer

Background

Ovarian cancer is a frequently-occurring reproductive system malignancy in females, which leads to an annual of over 100 thousand deaths worldwide.

Methods

The electronic databases, including GEPIA, ONCOMINE, Metascape, and Kaplan-Meier Plotter, were used to examine both survival and transcriptional data regarding the cell division cycle associated (CDCA) gene family among ovarian cancer patients.

Results

All CDCA genes expression levels were up-regulated in ovarian cancer tissues relative to those in non-carcinoma ovarian counterparts. Besides, CDCA5/7 expression levels were related to the late tumor stage. In addition, the Kaplan-Meier Plotter database was employed to carry out survival analysis, which suggested that ovarian cancer patients with increased CDCA2/3/5/7 expression levels had poor overall survival (OS) (P<0.05). Moreover, ovarian cancer patients that had up-regulated mRNA expression levels of CDCA2/5/8 had markedly reduced progression-free survival (PFS) (P<0.05); and up-regulated CDCA4 expression showed remarkable association with reduced post-progression survival (PPS) (P<0.05). Additionally, the following processes were affected by CDCA genes alterations, including R-HAS-2500257: resolution of sister chromatid cohesion; GO:0051301: cell division; CORUM: 1118: Chromosomal passenger complex (CPC, including CDCA8, INCENP, AURKB and BIRC5); CORUM: 127: NDC80 kinetochore complex; M129: PID PLK1 pathway; and GO: 0007080: mitotic metaphase plate congression, all of which were subjected to marked regulation since the alterations affected CDCA genes.

Conclusions

Up-regulated CDCA gene expression in ovarian cancer tissues probably played a crucial part in the occurrence of ovarian cancer. The up-regulated CDCA2/3/5/7 expression levels were used as the potential prognostic markers to improve the poor ovarian cancer survival and prognostic accuracy. Moreover, CDCA genes probably exerted their functions in tumorigenesis through the PLK1 pathway.

Depletion of UBE2C reduces ovarian cancer malignancy and reverses cisplatin resistance via downregulating CDK1

Ovarian cancer is the most lethal gynecological malignancy, but the mechanisms of ovarian cancer progression and cisplatin resistance remain unclear. Emerging evidence suggested that ubiquitin-conjugating enzyme E2C (UBE2C) was highly expressed in a variety of tumors and acted as an oncogene. In our study, we demonstrated that UBE2C was overexpressed in ovarian cancer by immunohistochemistry (IHC) and The Cancer Genome Atlas (TCGA) database analysis. It was also found that high levels of UBE2C expression predicted worse clinical outcomes in ovarian cancer. After knocking down UBE2C, SKOV3 and A2780 cells showed inhibitory cell proliferation, increased apoptosis by blocking G2/M transition in vitro and in vivo. Besides, the downregulation of UBE2C reversed the cisplatin resistance states of SKOV3/DDP and A2780/DDP cells. Interestingly, CDK1 expression was also downregulated in UBE2C depleted ovarian cancer cells. Furthermore, we found that UBE2C expression was highly correlated with CDK1 expression in ovarian cancer tissues and cell lines, indicating that UBE2C might cooperate with CDK1 in ovarian tumorigenesis. Collectively, our findings strongly supported UBE2C as a candidate oncogene and a potential target for the treatment of ovarian cancer.