Identification of aberrantly methylated differentially expressed genes and associated pathways in endometrial cancer using integrated bioinformatic analysis

Disease characteristics and clinical specific survival prediction of spinal ependymoma: a genetic and population-based study

Background

Spinal Ependymoma (SP-EP) is the most commonly occurring tumor affecting the spinal cord. Prompt diagnosis and treatment can significantly enhance prognostic outcomes for patients. In this study, we conducted a comprehensive analysis of RNA sequencing data, along with associated clinical information, from patients diagnosed with SP-EP. The aim was to identify key genes that are characteristic of the disease and develop a survival-related nomogram.

Methods

We first accessed the Gene Expression Integrated Database (GEO) to acquire the microarray dataset pertaining to SP-EP. This dataset was then processed to identify differentially expressed genes (DEGs) between SP-EP samples and normal controls. Furthermore, machine learning techniques and the CIBERSORT algorithm were employed to extract immune characteristic genes specific to SP-EP patients, thereby enhancing the characterization of target genes. Next, we retrieved comprehensive information on patients diagnosed with SP-EP between 2000 and 2020 from the Surveillance, Epidemiology, and End Results Database (SEER). Using this data, we screened for predictive factors that have a significant impact on patient outcomes. A nomogram was constructed to visualize the predicted overall survival (OS) rates of these patients at 3, 5, and 8 years post-diagnosis. Finally, to assess the reliability and clinical utility of our predictive model, we evaluated it using various metrics including the consistency index (C-index), time-dependent receiver operating characteristic (ROC) curves, area under the curve (AUC), calibration curves, and decision curve analysis (DCA).

Results

A total of 5,151 DEGs were identified between the SP-EP sample and the normal sample. Analysis of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways revealed that these DEGs were primarily involved in cellular processes, including cell cycle regulation and cell sensitivity mechanisms. Furthermore, immune infiltration analysis was utilized to identify the core gene CELF4. Regarding the survival rates of patients with SP-EP, the 3-year, 5-year, and 8-year survival rates were 72.5, 57.0, and 40.8%, respectively. Diagnostic age (p < 0.001), gender (p < 0.001), and surgical approach (p < 0.005) were identified as independent prognostic factors for OS. Additionally, a nomogram model was constructed based on these prognostic factors, demonstrating good consistency between predicted and actual results in the study's validation process. Notably, the study also demonstrated that more extensive surgical resection could extend patients' OS.

Conclusion

Through bioinformatics analysis of microarray datasets, we identified CELF4 as a central gene associated with immune infiltration among DEGs. Previous studies have demonstrated that CELF4 may play a pivotal role in the pathogenesis of SP-EP. Furthermore, this study developed and validated a prognostic prediction model in the form of a nomogram utilizing the SEER database, enabling clinicians to accurately assess treatment risks and benefits, thereby enhancing personalized therapeutic strategies and prognosis predictions.

Upregulation of ESPL1 is associated with poor prognostic outcomes in endometrial cancer

BACKGROUND

Extra spindle pole bodies-like 1 (ESPL1) is known to play a crucial role in the segregation of sister chromatids during mitosis. Overexpression of ESPL1 is considered to have oncogenic effects in various human cancers. However, the specific biological function of ESPL1 in endometrial cancer (EC) remains unclear.

METHODS

The TCGA and GEO databases were utilized to assess the expression of ESPL1 in EC. Immunohistochemistry was utilized to detect separase expression in EC samples. Kaplan-Meier survival analysis and Cox regression analysis were performed to evaluate the diagnostic and prognostic significance of ESPL1 in EC. Gene Set Enrichment Analysis (GSEA) was employed to explore the potential signaling pathway of ESPL1 in EC. Cell proliferation and colony formation ability were analyzed using CCK-8 and colony formation assay.

RESULTS

Our analysis revealed that ESPL1 is significantly upregulated in EC, and its overexpression is associated with advanced clinical characteristics and unfavourable prognostic outcomes. Suppression of ESPL1 attenuated proliferation of EC cell line.

CONCLUSION

The upregulation of ESPL1 is associated with advanced disease and poor prognosis in EC patients. These findings suggest that ESPL1 has the potential to serve as a diagnostic and prognostic biomarker in EC, highlighting its significance in the management of EC patients.

Potential bioactive compound and hub gene identification of endometrial carcinoma using systems biology

Endometrial carcinoma is a frequent cancer of the female genital tract. Endometrial carcinoma accounts for 97% of all uterine malignancies and 3 % of sarcomas that develop from the endometrium's glands. Endometrial cancer is frequently found in its early stages since most women quickly report postmenopausal vaginal hemorrhage. The need for more advanced medications to improve survival in such situations is still unfulfilled. As a result, there is growing interest in employing an herbal treatment to treat endometriosis, which seems to be an effective strategy. We have discovered a few unintended targets (ligands) in our investigation that are active components of common therapeutic herbs. The differentially expressed genes (DEG - target protein) for endometrial cancer were found using the NCBI and CIViC databases. In our investigation, the protein used for docking and simulation was PDB ID: 3THW. Using the Cytoscape server, the gene-encoding protein network has been identified. It was discovered that the Protein 3THW's binding energy to the bioactive substance (Asarone) was -7.15 Kcal/mol. It was discovered that the crucial interacting amino acid residues were ILE648, PHE650, ILE651, VAL802, TYR815, VAL817. The properties of the pharmaceutical target are further investigated by employing a molecular simulation study for 100 ns with NAMD software. Low RMSD and SASA (Solvent accessible surface area), high RMSF, High hydrogen bonds, between Asarone and MSH2 demonstrated their potency as endometrial cancer inhibitor compounds. Based on these analyses we infer that the bioactive substances originating from medicinal plants may be an effective treatment for endometrial cancer.Communicated by Ramaswamy H. Sarma.

UBE2C serves as a prognosis biomarker of uterine corpus endometrial carcinoma via promoting tumor migration and invasion

The biological functions of ubiquitin-conjugating enzymes E2 (UBE2) family members in uterine corpus endometrial carcinoma (UCEC) remains unclear. Our study aimed to systematically analyze the expression patterns, prognostic value, biological functions and molecular regulatory mechanisms of UBE2 family in UCEC. Among nine screened UBE2 family members associated with UCEC, UBE2C was the most significantly overexpressed gene with poor prognosis. High expression levels of UBE2C in UCEC was correlated with stages, histological subtypes, patient's menopause status and TP53 mutation. Three molecules (CDC20, PTTG1 and AURKA), were identified as the key co-expression proteins of UBE2C. The generic alterations (mutation, amplification) and DNA hypomethylation might contribute to UBE2C's high expression in UCEC. Furthermore, in vitro experiments showed that the interference of UBE2C inhibited the migration and invasion of endometrial cancer cells, while partially impact cell proliferation and didn't impact the expression of epithelial-mesenchymal transition (EMT) markers. Using comprehensive bioinformatics analysis and in vitro experiments, our study provided a novel insight into the oncogenic role of UBE2 family, specifically UBE2C in UCEC. UBE2C might serve as an effective biomarker to predict poor prognosis and a potential therapeutic target in clinical practice.

Design of a novel multi-epitope vaccine candidate against endometrial cancer using immunoinformatics and bioinformatics approaches

Endometrial cancer (EC) is one of the most common cancers of the female reproductive system. Multi-epitope vaccine may be a promising and effective strategy against EC. In this study, we designed a novel multi-epitope vaccine based on the antigenic proteins PRAME and TMPRSS4 using immunoinformatics and bioinformatics approaches. After a rigorous selection process, 14 cytotoxic T lymphocyte (CTL) epitopes, 6 helper T lymphocyte (HTL) epitopes, and 8 B cell epitopes (BCEs) were finally selected for vaccine construction. To enhance the immunogenicity of the vaccine candidate, the pan HLA DR-binding epitope was included in the vaccine design as an adjuvant. The final vaccine construct had 455 amino acids and a molecular weight of 49.8 kDa, and was predicted to cover 95.03% of the total world population. Docking analysis showed that there were 10 hydrogen bonds and 19 hydrogen bonds in the vaccine-HLA-A*02:01 and vaccine-HLA-DRB1*01:01 complexes, respectively, indicating that the vaccine has a good affinity to MHC molecules. This was further supported by molecular dynamics (MD) simulation. Immune simulation showed that the designed vaccine was able to induce higher levels of immune cell activity, with the secretion of numerous cytokines. The codon adaptation index (CAI) value and GC content of the optimised codon sequences of the vaccine were 0.986 and 54.43%, respectively, indicating that the vaccine has the potential to be highly expressed. The in silico analysis suggested that the designed vaccine may provide a novel therapeutic option for the individualised treatment of EC patients in the future.Communicated by Ramaswamy H. Sarma.

An eleven-gene risk model associated with lymph node metastasis predicts overall survival in lung adenocarcinoma

Lung adenocarcinoma (LUAD) occupies major causes of tumor death. Identifying potential prognostic risk genes is crucial to predict the overall survival of patients with LUAD. In this study, we constructed and proved an 11-gene risk signature. This prognostic signature divided LUAD patients into low- and high-risk groups. The model outperformed in prognostic accuracy at varying follow-up times (AUC for 3 years: 0.699, 5 years: 0.713, and 7 years: 0.716). Two GEO datasets also indicate the great accuracy of the risk signature (AUC = 782 and 771, respectively). Multivariate analysis identified 4 independent risk factors including stage N (HR 1.320, 95% CI 1.102-1.581, P = 0.003), stage T (HR 3.159, 95% CI 1.920-3.959, P < 0.001), tumor status (HR 5.688, 95% CI 3.883-8.334, P < 0.001), and the 11-gene risk model (HR 2.823, 95% CI 1.928-4.133, P < 0.001). The performance of the nomogram was good in the TCGA database (AUC = 0.806, 0.798, and 0.818 for 3-, 5- and 7-year survival). The subgroup analysis in different age, gender, tumor status, clinical stage, and recurrence stratifications indicated that the accuracy was high in different subgroups (all P < 0.05). Briefly, our work established an 11-gene risk model and a nomogram merging the model with clinicopathological characteristics to facilitate individual prediction of LUAD patients for clinicians.

Integration of Chemoinformatics and Multi-Omics Analysis Defines ECT2 as a Potential Target for Cancer Drug Therapy

Epithelial cell transforming 2 (ECT2) is a potential oncogene and a number of recent studies have correlated it with the progression of several human cancers. Despite this elevated attention for ECT2 in oncology-related reports, there is no collective study to combine and integrate the expression and oncogenic behavior of ECT2 in a panel of human cancers. The current study started with a differential expression analysis of ECT2 in cancerous versus normal tissue. Following that, the study asked for the correlation between ECT2 upregulation and tumor stage, grade, and metastasis, along with its effect on patient survival. Moreover, the methylation and phosphorylation status of ECT2 in tumor versus normal tissue was assessed, in addition to the investigation of the ECT2 effect on the immune cell infiltration in the tumor microenvironment. The current study revealed that ECT2 was upregulated as mRNA and protein levels in a list of human tumors, a feature that allowed for the increased filtration of myeloid-derived suppressor cells (MDSC) and decreased the level of natural killer T (NKT) cells, which ultimately led to a poor prognosis survival. Lastly, we screened for several drugs that could inhibit ECT2 and act as antitumor agents. Collectively, this study nominated ECT2 as a prognostic and immunological biomarker, with reported inhibitors that represent potential antitumor drugs.

PPP1R14B is a diagnostic prognostic marker in patients with uterine corpus endometrial carcinoma

Uterine corpus endometrial carcinoma (UCEC) is one of the most common malignancies of the female genital tract. A recently discovered protein-coding gene, PPP1R14B, can inhibit protein phosphatase 1 (PP1) as well as different PP1 holoenzymes, which are important proteins regulating cell growth, the cell cycle, and apoptosis. However, the association between PPP1R14B expression and UCEC remains undefined. The expression profiles of PPP1R14B in multiple cancers were analysed based on TCGA and GTE databases. Then, PPP1R14B expression in UCEC was investigated by gene differential analysis and single gene correlation analysis. In addition, we performed gene ontology term analysis, Kyoto Encyclopedia of Genes and Genomes pathway analysis, gene set enrichment analysis, and Kaplan-Meier survival analysis to predict the potential function of PPP1R14B and its role in the prognosis of UCEC patients. Then, a tool for predicting the prognosis of UCEC, namely, a nomogram model, was constructed. PPP1R14B expression was higher in UCEC tumour tissues than in normal tissues. The results revealed that PPP1R14B expression was indeed closely associated with tumour development. The results of Kaplan-Meier plotter data indicated that patients with high PPP1R14b expression had poorer overall survival, disease-specific survival, and progression-free interval than those with low expression. A nomogram based on the results of multifactor Cox regression was generated. PPP1R14B is a key player in UCEC progression, is associated with a range of adverse outcomes, and can serve as a prognostic marker in the clinic.

Identifying M1-like macrophage related genes for prognosis prediction in lung adenocarcinoma based on a gene co-expression network

Macrophages are one of the most important players in the tumor microenvironment. But the contribution of macrophages to lung adenocarcinoma (LUAD) is still controversial. The current study aimed to display an immune landscape to clarify the function of macrophages and detect prognostic hub genes in LUAD. The transcriptome data were adopted to screen differently expressed genes (DEGs) in The Cancer Genome Atlas database (TCGA). The cell type identification by estimating relative subsets of RNA transcripts (CIBERSORT) algorithm was used to reveal the immune landscape. Weighted gene co-expression network analysis (WGCNA) analysis was performed to identify the hub module associated with macrophages. Function Enrichment analysis was conducted on hub module genes. Moreover, univariate and multivariate Cox regression analyses were performed to identify prognostic hub genes. Kaplan-Meier (KM) and Time-dependent receiver operating characteristic (ROC) curves were plotted to assess the prognostic capacity of the four prognostic hub genes. The GES1196959 dataset from the Gene Expression Omnibus (GEO) database was downloaded to verify the differential expression of the 4 prognostic hub genes.

PRAME Expression in Endometrioid and Serous Endometrial Carcinoma: A Potential Immunotherapeutic Target and Possible Diagnostic Pitfall

Preferentially expressed antigen in melanoma (PRAME) is a cancer testes antigen initially employed as a diagnostic marker for melanoma. Although negative in most normal tissues, its expression has been reported in benign endometrial glands. Additionally, PRAME expression has been identified in a growing list of solid and hematologic malignancies and is of interest as a predictive biomarker, as cancer vaccination strategies and adoptive T-cell transfer targeting this molecule are under clinical investigation; additionally, PRAME may identify candidates for retinoid therapy. However, expression of PRAME has not been well-studied in endometrial cancers. We herein evaluate PRAME expression in endometrial carcinomas to better characterize its limitations as a diagnostic melanoma marker as well as its potential as a predictive biomarker in endometrial carcinomas. PRAME expression was evaluated in 256 endometrioid (n=235) and serous (n=21) endometrial carcinomas via tissue microarray. In all, 89% (227/256) demonstrated some degree of nuclear PRAME expression, including 88% (207/235) of endometrioid carcinomas and 95% (20/21) of serous carcinomas. Diffuse (>50%) expression was observed in 70% (179/256) of all cases, including 69% (163/235) of endometrioid carcinomas and 76% (16/21) of serous carcinomas. There was no association between degree of expression and grade, mismatch repair protein status, or stage. The widespread expression of PRAME in endometrial carcinomas suggests this marker should not be interpreted as specific for melanoma in this context. However PRAME may have utility as a predictive biomarker in endometrial cancer, and expansion of testing of PRAME-based therapies to endometrioid and serous endometrial carcinomas may lead to new therapeutic options for these endometrial cancer subtypes.

Identification of potential differentially methylated gene-related biomarkers in endometriosis

Aim: To identify epigenetic alterations of differentially expressed genes and screen out targeted therapeutic drugs in endometriosis. Methods: Based on the Gene Expression Omnibus database and a series of biological information analysis tools, supplemented by validation of clinical samples, aberrant DNA methylation-driven genes and their functions were explored, as well as possible targeted drugs. Results: This study screened out a range of DNA methylation-driven genes that were associated with powerful properties and corresponding pathways. Among them, BDNF and CCL2 were key genes in the development of endometriosis. Four chemical agents have been flagged as potential treatments for endometriosis. Conclusion: These candidate genes and small-molecule agents may be further explored as potential targets and drugs for endometriosis diagnosis and therapy, respectively.

Construction and validation of a prognostic model based on 11 lymph node metastasis-related genes for overall survival in endometrial cancer

BACKGROUND

Endometrial cancer (EC) is one of the most common malignant tumors in female reproductive system. The incidence of lymph node metastasis (LNM) is only about 10% in clinically suspected early-stage EC patients. Discovering prognostic models and effective biomarkers for early diagnosis is important to reduce the mortality rate.

METHODS

A least absolute shrinkage and selection operator (LASSO) regression was conducted to identify the characteristic dimension decrease and distinguish porgnostic LNM related genes signature. Subsequently, a novel prognosis-related nomogram was constructed to predict overall survival (OS). Survival analysis was carried out to explore the individual prognostic significance of the risk model and key gene was validated in vitro.

RESULTS

In total, 89 lymph node related genes (LRGs) were identified. Based on the LASSO Cox regression, 11 genes were selected for the development of a risk evaluation model. The Kaplan-Meier curve indicated that patients in the low-risk group had considerably better OS (p = 3.583e-08). The area under the ROC curve (AUC) of this model was 0.718 at 5 years of OS. Then, we developed an OS-associated nomogram that included the risk score and clinicopathological features. The concordance index of the nomogram was 0.769. The survival verification performed in three subgroups from the nomogram demonstrated the validity of the model. The AUC of the nomogram was 0.787 at 5 years OS. Proliferation and metastasis of HMGB3 were explored in EC cell line. External validation with 30 patients in our hospital showed that patients with low-risk scores had a longer OS (p-value = 0.03). Finally, we revealed that the most frequently mutated genes in the low-risk and high-risk groups are PTEN and TP53, respectively.

CONCLUSIONS

Our results suggest that LNM plays an important role in the prognosis, and HMGB3 was potential as a biomarker for EC patients.

The DNA methylation landscape of five pediatric-tumor types

Fewer DNA mutations have been identified in pediatric tumors than in adult tumors, suggesting that alternative tumorigenic mechanisms, including aberrant DNA methylation, may play a prominent role. In one epigenetic process of regulating gene expression, methyl groups are attached at the 5-carbon of the cytosine ring, leading to 5-methylcytosine (5mC). In somatic cells, 5mC occurs mostly in CpG islands, which are often within promoter regions. In Wilms tumors and acute myeloid leukemias, increased levels of epigenetic silencing have been associated with worse patient outcomes. However, to date, researchers have studied methylation primarily in adult tumors and for specific genes-but not on a pan-pediatric cancer scale. We addressed these gaps first by aggregating methylation data from 309 noncancerous samples, establishing baseline expectations for each probe and gene. Even though these samples represent diverse, noncancerous tissue types and population ancestral groups, methylation levels were consistent for most genes. Second, we compared tumor methylation levels against the baseline values for 489 pediatric tumors representing five cancer types: Wilms tumors, clear cell sarcomas of the kidney, rhabdoid tumors, neuroblastomas, and osteosarcomas. Tumor hypomethylation was more common than hypermethylation, and as many as 41.7% of genes were hypomethylated in a given tumor, compared to a maximum of 34.2% for hypermethylated genes. However, in known oncogenes, hypermethylation was more than twice as common as in other genes. We identified 139 probes (31 genes) that were differentially methylated between at least one tumor type and baseline levels, and 32 genes that were differentially methylated across the pediatric tumor types. We evaluated whether genomic events and aberrant methylation were mutually exclusive but did not find evidence of this phenomenon.

Hypermethylated CDO1 and ZNF454 in Cytological Specimens as Screening Biomarkers for Endometrial Cancer

We aimed to estimate the diagnostic value of DNA methylation levels in cytological samples of endometrial cancer (EC) and atypical hyperplasia (AH). Two hypermethylated genes, namely, cysteine dioxygenase type 1 (CDO1) and zinc finger protein 454 (ZNF454), in patients with EC were identified from The Cancer Genome Atlas database. In 103 endometrial histological specimens (the training set), the methylation levels of candidate genes were verified by quantitative methylation-specific polymerase chain reaction (qMSP). The methylation levels of another 120 cytological specimens (the testing set) were evaluated. Sensitivity (Se), specificity (Sp), accuracy, and area under the curve (AUC) were determined, with diagnosis verified by histopathological results. CDO1 and ZNF454 verified hypermethylation in histological specimens of patients with EC and AH compared with those with benign and normal endometrium (P < 0.001). In cytological specimens, hypermethylated CDO1 showed 86.36% Se and 90.79% Sp with the cutoff value of 6.0 to distinguish between malignant and benign groups; ZNF454 showed 79.55% Se and 93.42% Sp with the cutoff value of 7.1. When the two genes were combined, Se increased to 90.91% and Sp was 86.84%. AUC reached 0.931 (95% CI: 0.885–0.976). The diagnostic accuracy with cytology had no significant difference with endometrial tissue (P = 0.847 for CDO1, P = 0.108 for ZNF454, and P = 0.665 for their combination). Hypermethylated CDO1 and ZNF454 in endometrial cytology showed high Se, Sp, and AUC to detect EC and AH. Methylation analysis of endometrial cytology is promising biomarker for the screening of EC and AH.

Necdin, one of the important pathway proteins in the regulation of osteosarcoma progression by microRNA-200c

MicroRNA-200c (miR-200c) generally acts as a tumor suppressor in multiple cancer types and a promising therapeutic target in tumorigenesis. However, only a few studies have explained the role of miR-200c in the development of osteosarcoma (OS). In this study, we investigated the role of miR-200c in OS progression and identified the regulatory pathway protein NDN involved in inhibiting the occurrence and development of OS. Firstly, we found that miR-200c is downregulated in OS cells and tissues. As well, in vitro and in vivo experiments showed that upregulating miR-200c inhibits the proliferation, invasion, metastasis of Saos-2 cells, promotes the apoptosis of Saos-2 cells and suppresses tumor growth in mice, indicating miR-200c plays a major role in regulating the OS progression. Furthermore, bioinformatics analysis showed that an anti-tumor protein, necdin (NDN), might be a potential target by miR-200c. To verify this hypothesis, we measured the expression level of NDN in OS cells and tissues and found NDN is downregulated, suggesting NDN is functional in OS progression. Moreover, we found that the expression levels of NDN and miR-200c in in vivo and in vitro experiments were positively correlated. However, the results of dual-luciferase reporter gene experiment showed miR-200c does not directly act on the 3ʹ untranslated region (UTR) of NDN gene, indicating that NDN might be an important pathway protein which regulates OS progression in the presence of miR-200c. Therefore, miR-200c/NDN could be potential targets for developing effective treatment against OS.

ESPL1 Is a Novel Prognostic Biomarker Associated With the Malignant Features of Glioma

Research has confirmed that extra spindle pole bodies-like 1 (ESPL1), an etiological factor, promotes the malignant progression of cancers. However, the relationship between ESPL1 and glioma has not yet been demonstrated. The purpose of this study was to reveal the potential mechanisms of ESPL1-mediated malignant glioma progression. Gene expression data and detailed clinical information of glioma cases were obtained from multiple public databases. Subsequently, a series of bioinformatics analyses were used to elucidate the effects of ESPL1 on glioma. The results demonstrated that the mRNA and protein levels of ESPL1 in glioma were higher than those in normal brain tissues. In addition, ESPL1 expression was considerably associated with the clinical and pathological features of gliomas, such as World Health Organization grade, histology, and 1p19q co-deletion status. Importantly, ESPL1 reduced the overall survival (OS) of glioma patients and had prognostic value for gliomas. Gene set enrichment analysis (GSEA) indirectly revealed that ESPL1 regulates the activation of cancer-related pathways, such as the cell cycle and base excision repair pathways. In addition, we used the Connectivity Map (CMap) database to screen three molecular drugs that inhibit ESPL1: thioguanosine, antimycin A, and zidovudine. Finally, reverse transcription-quantitative polymerase chain reaction (RT-qPCR) was used to detect the expression levels of ESPL1 in glioma cell lines. This study plays an important role in revealing the etiology of glioma by revealing the function of ESPL1, providing a potential molecular marker for the diagnosis and treatment of glioma, especially low-grade glioma.

Screening of key biomarkers and immune infiltration in Pulmonary Arterial Hypertension via integrated bioinformatics analysis

This study aimed to screen key biomarkers and investigate immune infiltration in pulmonary arterial hypertension (PAH) based on integrated bioinformatics analysis. The Gene Expression Omnibus (GEO) database was used to download three mRNA expression profiles comprising 91 PAH lung specimens and 49 normal lung specimens. Three mRNA expression datasets were combined, and differentially expressed genes (DEGs) were obtained. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses and the protein-protein interaction (PPI) network of DEGs were performed using the STRING and DAVID databases, respectively. The diagnostic value of hub gene expression in PAH was also analyzed. Finally, the infiltration of immune cells in PAH was analyzed using the CIBERSORT algorithm. Total 182 DEGs (117 upregulated and 65 downregulated) were identified, and 15 hub genes were screened. These 15 hub genes were significantly associated with immune system functions such as myeloid leukocyte migration, neutrophil migration, cell chemotaxis, Toll-like receptor signaling pathway, and NF-κB signaling pathway. A 7-gene-based model was constructed and had a better diagnostic value in identifying PAH tissues compared with normal controls. The immune infiltration profiles of the PAH and normal control samples were significantly different. High proportions of resting NK cells, activated mast cells, monocytes, and neutrophils were found in PAH samples, while high proportions of resting T cells CD4 memory and Macrophages M1 cell were found in normal control samples. Functional enrichment of DEGs and immune infiltration analysis between PAH and normal control samples might help to understand the pathogenesis of PAH.

Pivotal factors associated with the immunosuppressive tumor microenvironment and melanoma metastasis

BACKGROUND

Considering melanoma is the deadliest malignancy among dermatoma and presently lacks effective therapies, there is an urgent need to investigate the potential mechanisms underlying melanoma metastasis and determine prospective therapeutic targets for precise treatment of melanoma.

METHOD

Hub genes in melanoma metastasis were identified by analyzing RNA-seq data (mRNA, miRNA, and lncRNA) obtained from TCGA database. Then the identified hub genes were validated in human tissues with qRT-PCR, followed by survival analysis. Competing endogenous RNAs of the hub genes were defined to clarify potential molecular mechanism of melanoma progression. Then central gene-related signaling pathways were analyzed, followed by immune cell abundance analysis in tumor microenvironment with CYTERSORTx.

RESULT

A tetrad of IL2RA, IL2RG, IFNG, and IL7R genes were determined as hub genes and verified by qRT-PCR, which were significantly associated with unfavorable prognosis in melanoma. LINC02446, LINC01857, and LINC02384 may act as competing endogenous lncRNAs of IL2RA and IL7R through absorbing their shared miR.891a.5p and miR.203b.3p. JAK-STAT signaling pathway identified as the most relevant pathway in melanoma metastasis, as well as a wealthy of genes including TNFRSF 13B, TNFRSF17, TNFRSF9, TNFRSF8, TNFRSF13C, TNFRSF11B, LAG3, NRP1, ENTPD1, NT5E, CCL21, and CCR7, may induce tumor autoimmune suppression through enhancing regulatory T-cell abundance and performance in the tumor microenvironment. And regulatory T-cell proportion was indeed critically elevated in metastatic melanoma relative to primary melanoma, as well as in highly expressed IL2RA, IL2RG, IL7R, and IFNG group than their respective counterparts.

CONCLUSION

Elevated IL2RA, IL2RG, IL7R, and IFNG expression may play a central role in promoting melanoma metastasis through up regulation of intratumoral regulatory T-cell proportion mainly by activation of JAK-STAT signaling pathway. LINC02446, LINC01857, and LINC02384 may stimulate melanoma progression by reducing tumor-protecting miR.891a.5p and miR.203b.3p. A number of identified molecules including TNFRSF13B, LAG3, NRP1, ENTPD1, NT5E, CCL21, and CCR7 can serve as future therapeutic targets in melanoma treatment.

A ten-gene methylation signature as a novel biomarker for improving prediction of prognosis and indicating gene targets in endometrial cancer

Endometrial cancer (EC) is a common female reproductive tumor worldwide. Nonetheless, the pathogenesis of EC still remains ambiguous and associated epigenetic mechanism still to be explored. The goal of this study is to investigate whether gene methylation signature is associated with overall survival (OS) for EC patients. In this study, a 10-gene methylation risk model was built and the OS in high- and low-risk groups was significant different. The area under the ROC curve (AUC) of this model was 0.856 at 5 years survival. The nomogram could accurately predict the OS in EC patients, with concordance index and AUC at 5 year survival reached 0.796 and 0.792, respectively. Furthermore, we verified the nomogram with 24 patients in our center and the Kaplan-Meier survival curve also proved to be significantly different (p < 0.01). WGCNA revealed a key gene group for the model and further bioinformatics analysis indicated 6 genes as the hub genes in the module. Knockdown of MMP12 inhibited the proliferation, invasion and metastasis of EC cells. After all, a methylation signature and a nomogram based on this signature were constructed, and they could both predict survival in patients with EC. Moreover, WGCNA model identified MMP12 as a potential target for the treatment of EC.

Screening of Hub Genes Associated with Pulmonary Arterial Hypertension by Integrated Bioinformatic Analysis

Background

Pulmonary arterial hypertension (PAH) is a disease or pathophysiological syndrome which has a low survival rate with abnormally elevated pulmonary artery pressure caused by known or unknown reasons. In addition, the pathogenesis of PAH is not fully understood. Therefore, it has become an urgent matter to search for clinical molecular markers of PAH, study the pathogenesis of PAH, and contribute to the development of new science-based PAH diagnosis and targeted treatment methods.

Methods

In this study, the Gene Expression Omnibus (GEO) database was used to downloaded a microarray dataset about PAH, and the differentially expressed genes (DEGs) between PAH and normal control were screened out. Moreover, we performed the functional enrichment analyses and protein-protein interaction (PPI) network analyses of the DEGs. In addition, the prediction of miRNA and transcriptional factor (TF) of hub genes and construction miRNA-TF-hub gene network were performed. Besides, the ROC curve was used to evaluate the diagnostic value of hub genes. Finally, the potential drug targets for the 5 identified hub genes were screened out.

Results

69 DEGs were identified between PAH samples and normal samples. GO and KEGG pathway analyses revealed that these DEGs were mostly enriched in the inflammatory response and cytokine-cytokine receptor interaction, respectively. The miRNA-hub genes network was conducted subsequently with 131 miRNAs, 7 TFs, and 5 hub genes (CCL5, CXCL12, VCAM1, CXCR1, and SPP1) which screened out via constructing the PPI network. 17 drugs interacted with 5 hub genes were identified.

Conclusions

Through bioinformatic analysis of microarray data sets, 5 hub genes (CCL5, CXCL12, VCAM1, CXCR1, and SPP1) were identified from DEGs between control samples and PAH samples. Studies showed that the five hub genes might play an important role in the development of PAH. These 5 hub genes might be potential biomarkers for diagnosis or targets for the treatment of PAH. In addition, our work also indicated that paying more attention on studies based on these 5 hub genes might help to understand the molecular mechanism of the development of PAH.

Establishment and validation of a prognostic nomogram based on a novel five-DNA methylation signature for survival in endometrial cancer patients

Background

This study aimed to explore the prognostic role of DNA methylation pattern in endometrial cancer (EC) patients.

Methods

Differentially methylated genes (DMGs) of EC patients with distinct survival from The Cancer Genome Atlas (TCGA) database were analyzed to identify methylated genes as biomarkers for EC prognosis. The Least Absolute Shrinkage and Selection Operator (LASSO) analysis was used to construct a risk score model. A nomogram was built based on analysis combining the risk score model with clinicopathological signatures together, and then verified in the validation cohort and patients in our own center.

Results

In total, 157 DMGs were identified between different prognostic groups. Based on the LASSO analysis, five genes (GBP4, OR8K3, GABRA2, RIPPLY2, and TRBV5‐7) were screened for the establishment of risk score model. The model outperformed in prognostic accuracy at varying follow‐up times (AUC for 3 years: 0.824, 5 years: 0.926, and 7 years: 0.853). Multivariate analysis identified four independent risk factors including menopausal status (HR = 3.006, 95%CI: 1.062–8.511, p = 0.038), recurrence (HR = 2.116, 95%CI: 1.061–4.379, p = 0.046), lymph node metastasis (LNM, HR = 3.465, 95%CI: 1.225–9.807, p = 0.019), and five‐DNA methylation risk model (HR = 3.654, 95%CI: 1.458–9.161, p = 0.006) in training cohort. The performance of the nomogram was good in the training (AUC = 0.828), validation (AUC = 0.866) and the whole cohorts (AUC = 0.843). Furthermore, we verified the nomogram with 24 patients in our center and the Kaplan–Meier survival curve also proved to be significantly different (p < 0.01). The subgroup analysis in different stratifications indicated that the accuracy was high in different subgroups for age, histological type, tumor grade, and clinical stage (all p < 0.01).

Conclusions

Briefly, our work established and verified a five‐DNA methylation risk model, and a nomogram merging the model with clinicopathological characteristics to facilitate individual prediction of EC patients for clinicians.

FKBP4 Accelerates Malignant Progression of Non-Small-Cell Lung Cancer by Activating the Akt/mTOR Signaling Pathway

Objective

To study the expression, biological function, and mechanism of FKBP4 in non-small-cell lung cancer (NSCLC).

Methods

First of all, the expression of FKBP4 in NSCLC tissues and cell lines was detected by qRT-PCR; then, the effects of FKBP4 on proliferation, apoptosis, migration, and invasion of NSCLC were studied by CCK-8 assays, flow cytometry assays, wound-healing assays, and Transwell assays. After that, tumor xenografts were used to explore the effect of FKBP4 on NSCLC tumor growth in vivo, and the phosphorylation of Akt and mTOR was measured by western blot.

Results

FKBP4 was highly expressed in NSCLC tissues and cells, and its expression was closely related to NSCLC tumor size, lymph node metastasis, and patient prognosis. In vitro, FKBP4 can promote NSCLC cell proliferation, migration, and invasion and inhibit NSCLC cell apoptosis. In vivo, FKBP4 can promote NSCLC tumor growth. Furthermore, FKBP4 can promote Akt and mTOR phosphorylation and activate the Akt/mTOR signaling pathway and an mTOR inhibitor can neutralize the functions of FKBP4 in NSCLC cells.

Conclusion

FKBP4 serves as an oncogene to promote malignant processes in NSCLC, and it has the potential to be used as a biological marker and therapeutic target for NSCLC.

The New Paradigm of Network Medicine to Analyze Breast Cancer Phenotypes

Breast cancer (BC) is a heterogeneous and complex disease as witnessed by the existence of different subtypes and clinical characteristics that poses significant challenges in disease management. The complexity of this tumor may rely on the highly interconnected nature of the various biological processes as stated by the new paradigm of Network Medicine. We explored The Cancer Genome Atlas (TCGA)-BRCA data set, by applying the network-based algorithm named SWItch Miner, and mapping the findings on the human interactome to capture the molecular interconnections associated with the disease modules. To characterize BC phenotypes, we constructed protein-protein interaction modules based on "hub genes", called switch genes, both common and specific to the four tumor subtypes. Transcriptomic profiles of patients were stratified according to both clinical (immunohistochemistry) and genetic (PAM50) classifications. 266 and 372 switch genes were identified from immunohistochemistry and PAM50 classifications, respectively. Moreover, the identified switch genes were functionally characterized to select an interconnected pathway of disease genes. By intersecting the common switch genes of the two classifications, we selected a unique signature of 28 disease genes that were BC subtype-independent and classification subtype-independent. Data were validated both in vitro (10 BC cell lines) and ex vivo (66 BC tissues) experiments. Results showed that four of these hub proteins (AURKA, CDC45, ESPL1, and RAD54L) were over-expressed in all tumor subtypes. Moreover, the inhibition of one of the identified switch genes (AURKA) similarly affected all BC subtypes. In conclusion, using a network-based approach, we identified a common BC disease module which might reflect its pathological signature, suggesting a new vision to face with the disease heterogeneity.

Development and Validation of a Five-immune Gene Pair Signature in Endometrial Carcinoma

BACKGROUND

Endometrial cancer (EC) is a common gynecological malignancy worldwide. Immunity is closely related to the occurrence and prognosis of EC. At the same time, immune-related genes have great potential as prognostic markers in many types of cancer.

OBJECTIVE

Therefore, we attempt to develop immune-related gene markers to enhance prognosis prediction of EC.

METHODS

542 samples of EC gene expression data and clinical follow-up information were downloaded from The Cancer Genome Atlas (TCGA). The samples were randomly divided into two groups, one group as a training set (N=271), and one set as a validation set. (N=271). In the training set, the gene pairs were established based on the relative expression levels of 271 immune genes, and the prognosis-related gene pairs were screened. The lasso was used to select the features, and finally, the robust biomarkers were screened. Finally, the prognostic model of the immune gene pair was established and verified by the validation data set.

RESULTS

10030 immune gene pair (IRGPs) were obtained, and univariate survival analysis was used to identify 1809 prognostic-related IRGPs (p<0.05). 5-IRGPs were obtained by lasso regression feature selection, and multivariate regression was used to establish 5-IRGPs signature, 5-IRGPs signature is an independent prognostic factor for EC patients, and could be risk stratified in patients with TCGA datasets, age, ethnicity, stage, and histological classification (p<0.05). The mean AUC of survival in both the training set and the validation set was greater than 0.7, indicating that 5-IRGPs signature has superior classification performance in patients with EC. In addition, 5-IRGPs have the highest average C index (0.795) compared to the prognostic characteristics of the three endometrial cancers reported in the past and Stage and Age.

CONCLUSION

This study constructed a 5-IRGPs signature as a novel prognostic marker for predicting survival in patients with EC.

Identification of aberrantly methylated differentially expressed genes and associated pathways in endometrial cancer using integrated bioinformatic analysis

Endometrial cancer (EC) is a fatal female reproductive tumor. Bioinformatic tools are increasingly developed to screen out molecular targets related to EC. In this study, http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE17025 and http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE40032 were obtained from Gene Expression Omnibus (GEO). “limma” package and Venn diagram tool were used to identify hub genes. FunRich was used for functional analysis. Retrieval of Interacting Genes Database (STRING) was used to analyze protein‐protein interaction (PPI) complex. Cancer Genome Atlas (TCGA), GEPIA, immunohistochemistry staining, and ROC curve analysis were carried out for validation. Univariate and multivariate regression analyses were performed to predict the risk score. Compound muscle action potential (CMap) was used to find potential drugs. GSEA was also done. We retrieved seven oncogenes which were upregulated and hypomethylated and 12 tumor suppressor genes (TSGs) which were downregulated and hypermethylated. The upregulated and hypomethylated genes were strikingly enriched in term “immune response” while the downregulated and hypermethylated genes were mainly focused on term “aromatic compound catabolic process.” TCGA and GEPIA were used to screen out EDNRB, CDO1, NDN, PLCD1, ROR2, ESPL1, PRAME, and PTTG1. Among them, ESPL1 and ROR2 were identified by Cox regression analysis and were used to construct prognostic risk model. The result showed that ESPL1 was a negative independent prognostic factor. Cmap identified aminoglutethimide, luteolin, sulfadimethoxine, and maprotiline had correlation with EC. GSEA results showed that “hedgehog signaling pathway” was enriched. This research inferred potential aberrantly methylated DEGs and dysregulated pathways may participate in EC development and firstly reported eight hub genes, including EDNRB, CDO1, NDN, PLCD1, ROR2, ESPL1, PRAME, and PTTG1 that could be used to predict EC prognosis. Aminoglutethimide and luteolin may be used to fight against EC.