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

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.

Possible pharmacological targets and mechanisms of sivelestat in protecting acute lung injury

Acute lung injury/acute respiratory distress syndrome (ALI/ARDS) is a life-threatening syndrome induced by various diseases, including COVID-19. In the progression of ALI/ARDS, activated neutrophils play a central role by releasing various inflammatory mediators, including elastase. Sivelestat is a selective and competitive inhibitor of neutrophil elastase. Although its protective effects on attenuating ALI/ARDS have been confirmed in several models of lung injury, clinical trials have presented inconsistent results on its therapeutic efficacy. Therefore, in this report, we used a network pharmacology approach coupled with animal experimental validation to unravel the concrete therapeutic targets and biological mechanisms of sivelestat in treating ALI/ARDS. In bioinformatic analyses, we found 118 targets of sivelestat against ALI/ARDS, and identified six hub genes essential for sivelestat treatment of ALI/ARDS, namely ERBB2, GRB2, PTK2, PTPN11, ESR1, and CCND1. We also found that sivelestat targeted several genes expressed in human lung microvascular endothelial cells after lipopolysaccharide (LPS) treatment at 4 h (ICAM-1, PTGS2, RND1, BCL2A1, TNF, CA2, and ADORA2A), 8 h (ICAM-1, PTGS2, RND1, BCL2A1, MMP1, BDKRB1 and SLC40A1), and 24 h (ICAM-1). Further animal experiments showed that sivelestat was able to attenuate LPS-induced ALI by inhibiting the overexpression of ICAM-1, VCAM-1, and PTGS2 and increasing the phosphorylation of PTK2. Taken together, the bioinformatic findings and experimentative data indicate that the therapeutic effects of sivelestat against ALI/ARDS mainly focus on the early stage of ALI/ARDS by pharmacological modulation of inflammatory reaction, vascular endothelial injury, and cell apoptosis-related molecules.

MiR-96-5p Suppresses Progression of Arsenite-Induced Human Keratinocyte Proliferation and Malignant Transformation by Targeting Denticleless E3 Ubiquitin Protein Ligase Homolog

Long-term exposure to arsenic has been linked to a variety of cancers, among which skin cancer is the most prevalent form. However, the mechanism underlying arsenic carcinogenesis is unclear, and there is still limited information on the role of miRNAs in arsenic-induced skin cancer. This study aims to explore the role of miR-96-5p in the arsenite-induced proliferation and malignant transformation of human HaCaT keratinocytes. The GEO database (accession numbers GSE97303, GSE97305, and GSE97306) was used to extract mRNA and miRNA expression profiles of HaCaT cells treated with or without 0.1 μmol/L sodium arsenite for 3 and 7 weeks. In this paper, according to the CCK8 assay result, HaCaT cells exposed to 0.1 μmol/L sodium arsenite for 48 h were finalized. CCK8, MTT, EdU incorporation, and colony formation assays were used to determine the viability and proliferation of HaCaT cells and transformed HaCaT (T-HaCaT) cells. The subcellular localization and relative expression levels of DTL, as well as miR-96-5p in HaCaT cells induced by arsenite, were determined via immunofluorescence, RT-qPCR, and Western blot. Dual-luciferase reporter assay was performed to identify miR-96-5p bound directly to DTL. Transfection of miR-96-5p mimics or DTL siRNA was conducted to verify the arsenite-induced viability of HaCaT cells and T-HaCaT cells. T-HaCaT cells and nude mice were used to construct arsenite-induced malignant transformation and an in vivo xenograft model to demonstrate the over-expressed effect of miR-96-5p. The results showed that DTL was the target gene of miR-96-5p. Meanwhile, we also found that 0.1 μmol/L sodium arsenite upregulated DTL by decreasing the miR-96-5p level, leading to the proliferation and malignant transformation of HaCaT cells. MiR-96-5p agomir treatment slowed the growth of transplanted HaCaT cells transformed by arsenite in a manner associated with DTL downregulation in the nude mice xenograft model. Taken together, we confirmed that miR-96-5p, as a potent regulator of DTL, suppressed arsenite-induced HaCaT cell proliferation and malignant transformation, which might provide a novel therapeutic target for the treatment of arsenic-induced skin cancer.

NUSAP1 Binds ILF2 to Modulate R-Loop Accumulation and DNA Damage in Prostate Cancer

Increased expression of NUSAP1 has been identified as a robust prognostic biomarker in prostate cancer and other malignancies. We have previously shown that NUSAP1 is positively regulated by E2F1 and promotes cancer invasion and metastasis. To further understand the biological function of NUSAP1, we used affinity purification and mass spectrometry proteomic analysis to identify NUSAP1 interactors. We identified 85 unique proteins in the NUSAP1 interactome, including ILF2, DHX9, and other RNA-binding proteins. Using proteomic approaches, we uncovered a function for NUSAP1 in maintaining R-loops and in DNA damage response through its interaction with ILF2. Co-immunoprecipitation and colocalization using confocal microscopy verified the interactions of NUSAP1 with ILF2 and DHX9, and RNA/DNA hybrids. We showed that the microtubule and charged helical domains of NUSAP1 were necessary for the protein-protein interactions. Depletion of ILF2 alone further increased camptothecin-induced R-loop accumulation and DNA damage, and NUSAP1 depletion abolished this effect. In human prostate adenocarcinoma, NUSAP1 and ILF2 mRNA expression levels are positively correlated, elevated, and associated with poor clinical outcomes. Our study identifies a novel role for NUSAP1 in regulating R-loop formation and accumulation in response to DNA damage through its interactions with ILF2 and hence provides a potential therapeutic target.

Systematic investigation of the underlying mechanisms of GLP-1 receptor agonists to prevent myocardial infarction in patients with type 2 diabetes mellitus using network pharmacology

Background: Several clinical trials have demonstrated that glucagon-like peptide-1 (GLP-1) receptor agonists (GLP-1RAs) reduce the incidence of non-fatal myocardial infarction (MI) in patients with type 2 diabetes mellitus (T2DM). However, the underlying mechanism remains unclear. In this study, we applied a network pharmacology method to investigate the mechanisms by which GLP-1RAs reduce MI occurrence in patients with T2DM. Methods: Targets of three GLP-1RAs (liraglutide, semaglutide, and albiglutide), T2DM, and MI were retrieved from online databases. The intersection process and associated targets retrieval were employed to obtain the related targets of GLP-1RAs against T2DM and MI. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genes (KEGG) enrichment analyses were performed. The STRING database was used to obtain the protein-protein interaction (PPI) network, and Cytoscape was used to identify core targets, transcription factors, and modules. Results: A total of 198 targets were retrieved for the three drugs and 511 targets for T2DM with MI. Finally, 51 related targets, including 31 intersection targets and 20 associated targets, were predicted to interfere with the progression of T2DM and MI on using GLP-1RAs. The STRING database was used to establish a PPI network comprising 46 nodes and 175 edges. The PPI network was analyzed using Cytoscape, and seven core targets were screened: AGT, TGFB1, STAT3, TIMP1, MMP9, MMP1, and MMP2. The transcription factor MAFB regulates all seven core targets. The cluster analysis generated three modules. The GO analysis for 51 targets indicated that the terms were mainly enriched in the extracellular matrix, angiotensin, platelets, and endopeptidase. The results of KEGG analysis revealed that the 51 targets primarily participated in the renin-angiotensin system, complement and coagulation cascades, hypertrophic cardiomyopathy, and AGE-RAGE signaling pathway in diabetic complications. Conclusion: GLP-1RAs exert multi-dimensional effects on reducing the occurrence of MI in T2DM patients by interfering with targets, biological processes, and cellular signaling pathways related to atheromatous plaque, myocardial remodeling, and thrombosis.

Female Germ Cell Development in Chickens and Humans: The Chicken Oocyte Enriched Genes Convergent and Divergent with the Human Oocyte

The development of germ cells and other physiological events in the differentiated ovary of humans are highly conserved with several mammalian species, except for the differences in timing. However, comparative knowledge on this topic is very scarce with respect to humans and lower vertebrates, such as chickens. In chickens, female germ cells enter into meiosis around embryonic day (E) 15.5 and are arrested in meiotic prophase I as primary oocytes. The oocytes arrested in meiosis I are accumulated in germ-cell cysts; shortly after hatching, they are enclosed by flattened granulosa cells in order to form primordial follicles. In humans, the process of meiotic recombination in female germ cells begins in the 10–11th week of gestation, and primordial follicles are formed at around week 20. In this review, we comprehensively elucidate both the conservation and the species-specific differences between chickens and humans with respect to germ cell, oocyte, and follicle development. Importantly, we provide functional insights into a set of chicken oocyte enriched genes (from E16 to 1 week post-hatch) that show convergent and divergent expression patterns with respect to the human oocyte (from week 11 to 26).

Identification of G6PC as a potential prognostic biomarker in hepatocellular carcinoma based on bioinformatics analysis

Hepatocellular carcinoma (HCC) has high mortality and incidence rates around the world with limited therapeutic options. There is an urgent need for identification of novel therapeutic targets and biomarkers for early diagnosis and predicting patient survival with HCC. Several studies (GSE102083, GSE29722, GSE101685, and GSE112790) from the GEO database in HCC were screened and analyzed by GEO2R, gene ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis were conducted with the Database for Annotation, Visualization and Integrated Discovery. The protein-protein interaction network was plotted and the module analysis was performed using Search Tool for the Retrieval of Inter-acting Genes/Proteins database and Cytoscape. The expression and survival of key genes were identified using UALCAN, Kaplan-Meier Plotter and ONCOMINE online databases, and the immune infiltration level of key genes was analyzed via the Tumor Immune Estimation Resource (TIMER) database. Through database analysis, eight key genes were finally screened out, and the expressions of cyclin-dependent kinase regulatory subunit 2 and glucose-6-phosphatase catalytic (G6PC), which were closely related to the survival of HCC patients, was detected by using UALCAN. Further analysis on the differential expression of G6PC in multiple cancerous tumors and normal tissues revealed low expression in many solid tumors by Oncomine and TIMER. In addition, Kaplan-Meier plotter and UALCAN database analysis to access diseases prognosis suggested that low expression of G6PC was significantly associated with poor overall survival in HCC patients. Finally, TIMER database analysis showed a significant negative correlation between G6PC and infiltration levels of six kinds of immune cells. The somatic copy number alterations of G6PC were associated with B cells, CD8+ T cells, CD4+ T cells, macrophages, dentritic cells and neutrophils. These bioinformatic data identified G6PC as a potential key gene in the diagnosis and prognosis of HCC.

Identification and clinical validation of NUSAP1 as a novel prognostic biomarker in ovarian cancer

Background

Nucleolar and spindle-associated protein 1 (NUSAP1) was shown to be involved in cell cycle regulation in cancer. However, its prognostic value and underlying mechanism in ovarian cancer remain unclear.

Methods

Oncomine, TCGA, CCLE, and UALCAN databases were used to analyze the expression level of NUSAP1 in ovarian cancer. The Kaplan–Meier plotter database was used to evaluate its prognostic value. The results from these analyses were further validated using immunohistochemical assay. The potential molecular mechanism of NUSAP1 in ovarian cancer was assessed with respect to homologous recombination repair, mismatch repair, and immunology using different databases.

Results

Database analyses and experimental results demonstrated that NUSAP1 was highly expressed in ovarian cancer, its levels being correlated with the FIGO stage. High NUSAP1 expression was an independent risk factor affecting the prognosis of patients with epithelial ovarian cancer. Moreover, NUSAP1 was associated with cell cycle, DNA replication, homologous recombination, and p53 signaling pathway. A positive correlation was identified between the expression of NUSAP1 and BRCA1/2 in ovarian cancer. In addition, NUSAP1 was associated with the expression of DNA mismatch repair genes and immune cell infiltration.

Conclusions

NUSAP1 may be a valuable prognostic marker, as well as a novel biomarker for evaluating the response to immunotherapy of patients with ovarian cancer.

Transcription factor HOXB2 upregulates NUSAP1 to promote the proliferation, invasion and migration of nephroblastoma cells via the PI3K/Akt signaling pathway

The transcription factor homeobox protein Hox-B2 (HOXB2) and its downstream factor nucleolar and spindle-associated protein 1 (NUSAP1) play important regulatory roles in cell proliferation, invasion and migration. However, their effects and specific mechanisms in nephroblastoma have not been previously investigated, to the best of our knowledge. Therefore, in the present study, the mRNA and protein expression levels of HOXB2 and NUSAP1 were determined in nephroblastoma cells using reverse transcription-quantitative PCR and western blot analyses, respectively. Furthermore, cell transfection experiments were carried out to knock down NUSAP1 and overexpress HOXB2 in nephroblastoma cell lines. The proliferative, invasive and migratory abilities of nephroblastoma cells were assessed by MTT, EdU, colony formation, wound healing and Transwell assays. In addition, the JASPAR website was used to predict the association between HOXB2 and NUSAP1, which was further verified by dual-luciferase reporter and chromatin immunoprecipitation assays. Finally, the expression levels of the PI3K/Akt signaling pathway-related proteins were measured by western blot analysis. The results showed that the expression of NUSAP1 was abnormally upregulated in nephroblastoma cell lines. However, NUSAP1 silencing attenuated the proliferation, invasion and migration abilities of nephroblastoma cells. The results also suggested that HOXB2 could transcriptionally activate NUSAP1. Therefore, HOXB2 overexpression abrogated the inhibitory effect of NUSAP1 silencing on the proliferation and metastasis of nephroblastoma cells, possibly via the PI3K/Akt signaling pathway. The aforementioned findings indicated that HOXB2 may upregulate NUSAP1 to promote the proliferation, invasion and migration of nephroblastoma cells via the PI3K/Akt signaling pathway.

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.

Application of Bioinformatics Analysis to Identify Important Pathways and Hub Genes in Ovarian Cancer Affected by WT1

Wilms tumor gene (WT1) is used as a marker for the diagnosis and prognosis of ovarian cancer. However, the molecular mechanisms involving WT1 in ovarian cancer require further study. Herein, we used bioinformatics and other methods to identify important pathways and hub genes in ovarian cancer affected by WT1. The results showed that WT1 is highly expressed in ovarian cancer and is closely related to the overall survival and progression-free survival (PFS) of ovarian cancer. In ovarian cancer cell line SKOV3, WT1 downregulation increased the mRNA expression of 638 genes and decreased the mRNA expression of 512 genes, which were enriched in the FoxO, AMPK, and the Hippo signaling pathways. The STRING online tool and Cytoscape software were used to construct a Protein-protein interaction (PPI) network and for Module analysis, and 18 differentially expressed genes (DEGs) were selected. Kaplan-Meier plotter analysis revealed that 16 of 18 genes were related to prognosis. Analysis of GEPIA datasets indicated that 7 of 16 genes were differentially expressed in ovarian cancer tissues and in normal tissues. The expression of IGFBP1 and FBN1 genes increased significantly after WT1 interference, while the expression of the SERPINA1 gene decreased significantly. The correlation between WT1 expression and that of these three genes was consistent with that of ovarian cancer tissues and normal tissues. According to the GeneMANIA online website analysis, there were complex interactions between WT1, IGFBP1, FBN1, SERPINA1, and 20 other genes. In conclusion, we have identified important signaling pathways involving WT1 that affect ovarian cancer, and distinguished three differentially expressed genes regulated by WT1 associated with the prognosis of ovarian cancer. Our findings provide evidence outlining mechanisms involving WT1 gene expression in ovarian cancer and provides a rational for novel treatment of ovarian cancer.

The High Expression of RRM2 Can Predict the Malignant Transformation of Endometriosis

INTRODUCTION

A large number of epidemiological studies have revealed that women with endometriosis (EMS) have a higher risk of developing endometriosis-associated ovarian cancer (EAOC). At present, there are few studies on predicting the malignant transformation of ovarian endometriosis (OE). The purpose of this study is to identify and verify the molecules that may be able to predict the malignant transformation of OE.

METHODS

The gene expression profiles of ovarian cancer and OE were downloaded from Gene Expression Omnibus (GEO), and a common hub gene ribonucleotide reductase M2 (RRM2) was identified. A total of 44 patients with EAOC and 44 with OE were enrolled in this study. Immunohistochemistry (IHC) and quantitative reverse transcription polymerase chain reaction (RT-qPCR) were used to detect the expression of RRM2, while the relationship between RRM2 and Ki-67 was analyzed by IHC co-localization.

RESULTS

Bioinformatics analysis showed that the expression of RRM2 was low in EMS and high in ovarian cancer. RRM2 was obviously positively expressed in eutopic endometrium (EU), ectopic endometrium (EC), and cancer tissues of EAOC patients. The IHC signal and mRNA levels of RRM2 were higher in the EC of EAOC patients compared with OE patients (P < 0.01). In addition, there was a correlation between the expression of RRM2 and Ki-67 in EC of EAOC patients (P < 0.01).

CONCLUSION

The upregulated expression of RRM2 in the EC of OE patients may indicate malignant transformation. High expression of RRM2 promotes abnormal proliferation of histiocytes. RRM2 can be used as a potential marker of malignant transformation of OE.

High Expression of MYL9 Indicates Poor Clinical Prognosis of Epithelial Ovarian Cancer

BACKGROUND

The prognosis of Epithelial Ovarian Cancer (EOC) is poor, but the prognostic biomarkers are neither sensitive nor specific. Therefore, it is very important to search novel prognostic biomarkers for EOC.

OBJECTIVES

The present study aimed to investigate Myosin Light Chain 9(MYL9) expression in Epithelial Ovarian Cancer (EOC) tissues (including paraffin-embedded and fresh tissue samples) and its relationship with clinicopathological characteristics, as well as its potential prognostic value in patients with EOC.

METHODS

Between March 2009 and December 2018, all of 184 paraffin-embedded cancer tissues from patients with EOC and 41 paratumor tissues, pathologically confirmed at the Memorial Hospital of Sun Yat-sen University and Integrated Hospital of Traditional Chinese Medicine, Southern Medical University, were collected for the present study and were assessed for MYL9 protein expression patterns using Immunohistochemistry (IHC). Furthermore, from August 2013 to November 2019, 16 fresh EOC tissues and their paired paratumor tissues, pathologically confirmed at the Integrated Hospital of Traditional Chinese Medicine, Southern Medical University were analyzed using Reverse-Transcription Quantitative PCR (RT-qPCR) to detect MYL9 mRNA expression levels.

RESULTS

The results showed that MYL9 expression was higher in cancer tissues compared with that in paratumor tissues, and MYL9 overexpression was associated with shorter Recurrence Free Survival (RFS) and Overall Survival (OS) of EOC patients. Furthermore, multivariate Cox model analysis indicated that MYL9 overexpression was an independent poor survival prediction in patients with EOC.

CONCLUSION

MYL9 is upregulated in EOC and may serve as a useful patent of prognostic biomarker in EOC, and it may demonstrate an important value for the clinical treatment and supervision of patients with EOC.

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.

Identification of hub genes and their novel diagnostic and prognostic significance in pancreatic adenocarcinoma

OBJECTIVE

The main reasons for the poor prognoses of pancreatic adenocarcinoma (PA) patients are rapid early-stage progression, advanced stage metastasis, and chemotherapy resistance. Identification of novel diagnostic and prognostic biomarkers of PA is therefore urgently needed.

METHODS

Three mRNA microarray datasets were obtained from the Gene Expression Omnibus database to select differentially expressed genes (DEGs). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses for hub genes were performed using DAVID. Correlations between expression levels of hub genes and cancer-infiltrating immune cells were investigated by TIMER. Cox proportional hazard regression analyses were also performed. Serum hub genes were screened using the HPA platform and verified for diagnostic value using ELISAs.

RESULTS

We identified 59 hub genes among 752 DEGs. GO analysis indicated that these 59 hub genes were mainly involved in the defense response to viruses and the type I interferon signaling pathway. We also discovered that RSAD2 and SMC4 were associated with immune cell infiltration in the PA microenvironment. Additionally, DLGAP5 mRNA might be used as an independent risk factor for the prognoses of PA patients. Furthermore, the protein encoded by ISG15, which exists in peripheral blood, was validated as a potential diagnostic biomarker that distinguished PA patients from healthy controls (area under the curve: 0.902, 95% confidence interval: 0.819-0.961).

CONCLUSIONS

Our study suggested that RSAD2 and SMC4 were associated with immune cell infiltration in the PA microenvironment, while DLGAP5 mRNA expression might be an independent risk factor for the survival prognoses of PA patients. Moreover, ELISAs indicated that serum ISG15 could be a potential novel diagnostic biomarker for PA.

Identification of candidate biomarkers correlated with poor prognosis of breast cancer based on bioinformatics analysis

Breast cancer (BC) is a malignancy with high incidence among women in the world. This study aims to screen key genes and potential prognostic biomarkers for BC using bioinformatics analysis. Total 58 normal tissues and 203 cancer tissues were collected from three Gene Expression Omnibus (GEO) gene expression profiles, and then the differential expressed genes (DEGs) were identified. Subsequently, the Gene Ontology (GO) function and Kyoto Encyclopedia of Genes and Genome (KEGG) pathway were analyzed to investigate the biological function of DEGs. Additionally, hub genes were screened by constructing a protein–protein interaction (PPI) network. Then, we explored the prognostic value and molecular mechanism of these hub genes using Kaplan–Meier (KM) curve and Gene Set Enrichment Analysis (GSEA). As a result, 42 up-regulated and 82 down-regulated DEGs were screened out from GEO datasets. The DEGs were mainly related to cell cycles and cell proliferation by GO and KEGG pathway analysis. Furthermore, 12 hub genes (FN1, AURKA, CCNB1, BUB1B, PRC1, TPX2, NUSAP1, TOP2A, KIF20A, KIF2C, RRM2, ASPM) with a high degree were identified initially, among which, 11 hub genes were significantly correlated with the prognosis of BC patients based on the Kaplan–Meier-plotter. GSEA reviewed that these hub genes correlated with KEGG_CELL_CYCLE and HALLMARK_P53_PATHWAY. In conclusion, this study identified 11 key genes as BC potential prognosis biomarkers on the basis of integrated bioinformatics analysis. This finding will improve our knowledge of the BC progress and mechanisms.

Bioinformatics analysis of laryngeal squamous cell carcinoma: seeking key candidate genes and pathways

Background

Laryngeal squamous cell carcinoma (LSCC) is the second most aggressive head and neck squamous cell carcinoma. Although much work has been done to optimize its treatment, patients with LSCC still have poor prognosis. Therefore, figuring out differentially expressed genes (DEGs) contained in the progression of LSCC and employing them as potential therapeutic targets or biomarkers for LSCC is extremely meaningful.

Methods

Overlapping DEGs were screened from two standalone Gene Expression Omnibus datasets, and Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were performed. By applying STRING and Cytoscape, a protein–protein network was built, and module analysis was carried out. The hub genes were selected by maximal clique centrality with the CytoHubba plugin of Cytoscape. UALCAN and GEPIA data were examined to validate the gene expression findings. Moreover, the connection of the hub genes with LSCC patient overall survival was studied employing The Cancer Genome Atlas. Then, western blot, qRT-PCR, CCK-8, wound healing and transwell assays were bring to use for further verify the key genes.

Results

A total of 235 DEGs were recorded, including 83 upregulated and 152 downregulated genes. A total of nine hub genes that displayed a high degree of connectivity were selected. UALCAN and GEPIA databases verified that these genes were highly expressed in LSCC tissues. High expression of the SPP1, SERPINE1 and Matrix metalloproteinases 1 (MMP1) genes was connected to worse prognosis in patients with LSCC, according to the GEPIA online tool. Western blot and qRT-PCR testify SPP1, SERPINE1 and MMP1 were upregulated in LSCC cells. Inhibition of SPP1, SERPINE1 and MMP1 suppressed cell proliferation, invasion and migration.

Conclusion

The work here identified effective and reliable diagnostic and prognostic molecular biomarkers by unified bioinformatics analysis and experimental verification, indicating novel and necessary therapeutic targets for LSCC.

Identification of Novel Biomarkers Associated With the Prognosis and Potential Pathogenesis of Breast Cancer via Integrated Bioinformatics Analysis

Background:

Breast cancer is the most commonly diagnosed malignancy and a major cause of cancer-related deaths in women globally. Identification of novel prognostic and pathogenesis biomarkers play a pivotal role in the management of the disease.

Methods:

Three data sets from the GEO database were used to identify differentially expressed genes (DEGs) in breast cancer. Gene Ontology (GO) enrichment and Kyoto Encyclopaedia of Genes and Genomes pathway analyses were performed to elucidate the functional roles of the DEGs. Besides, we investigated the translational and protein expression levels and survival data of the DEGs in patients with breast cancer from the Gene Expression Profiling Interactive Analysis (GEPIA), Oncomine, Human Protein Atlas, and Kaplan Meier plotter tool databases. The corresponding change in the expression level of microRNAs in the DEGs was also predicted using miRWalk and TargetScan, and the expression profiles were analyzed using OncomiR. Finally, the expression of novel DEGs were validated in Chinese breast cancer tissues by RT-qPCR.

Results:

A total of 46 DEGs were identified, and GO analysis revealed that these genes were mainly associated with biological processes involved in fatty acid, lipid localization, and regulation of lipid metabolism. Two novel biomarkers, ADH1A and IGSF10, and 4 other genes (APOD, KIT, RBP4, and SFRP1) that were implicated in the prognosis and pathogenesis of breast cancer, exhibited low expression levels in breast cancer tissues. Besides, 14/25 microRNAs targeting 6 genes were first predicted to be associated with breast cancer prognosis. RT-qPCR results of ADH1A and IGSF10 expression in Chinese breast cancer tissues were consistent with the database analysis and showed significant down-regulation.

Conclusion:

ADH1A, IGSF10, and the 14 microRNAs were found to be potential novel biomarkers for the diagnosis, treatment, and prognosis of breast cancer.

Knockdown of KIF15 promotes cell apoptosis by activating crosstalk of multiple pathways in ovarian cancer: bioinformatic and experimental analysis

BACKGROUND

Ovarian cancer (OC) is the most lethal malignancy of women. Unlimited proliferation is a fundamental feature of OC cells. The genes associated with cell proliferation may be histopathologic biomarkers and targets of anti-tumor therapeutic strategies. The present study aimed to identify proliferation-associated biomarkers with prognostic, diagnostic, and therapeutic value and reveal the underlying molecular mechanism of candidate genes involved in OC by a combination of bioinformatic and experimental methods.

RESULTS

KIF15 was upregulated in early-stage OC tissues and could predict poor prognosis of patients of Stage I and II. The knockdown of KIF15 significantly inhibited cell proliferation, tumor formation, and growth as well as promoting apoptosis of OC cells. A combination of experimental and bioinformatic analyses revealed KIF15 knockdown promoted cell apoptosis by activating crosstalk of multiple pathways in OC.

CONCLUSION

KIF15, an early-stage prognostic gene, was identified as a candidate histopathologic biomarker and therapeutic target of OC.

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.

PTEN/AKT/mTOR signaling mediates anticancer effects of epigallocatechin‑3‑gallate in ovarian cancer

Epigallocatechin‑3‑gallate (EGCG), a polyphenol present in green tea, exhibits anticancer effects in various types of cancer. A number of studies have focused on the effects of EGCG on lung cancer, but not ovarian cancer. Previous reports have implicated that EGCG suppressed ovarian cancer cell proliferation and induced apoptosis, but its potential anticancer mechanisms and signaling pathways remain unclear. Thus, it is necessary to determine the anti‑ovarian cancer effects of EGCG and explore the underlying mechanisms. In the present study, EGCG exerted stronger proliferation inhibition on SKOV3 cells compared with A549 cells and induced apoptosis in SKOV3 cells, as well as upregulated PTEN expression and downregulated the expression of phosphoinositide‑dependent kinase‑1 (PDK1), phosphor (p)‑AKT and p‑mTOR. These effects were reversed by the PTEN inhibitor VO‑Ohpic trihydrate. The results of the mouse xenograft experiment demonstrated that 50 mg/kg EGCG exhibited increased tumor growth inhibition compared with 5 mg/kg paclitaxel. In addition, PTEN expression was upregulated, whereas the expression levels of PDK1, p‑AKT and p‑mTOR were downregulated in the EGCG treatment group compared with those in untreated mice in vivo. In conclusion, the results of the present study provided a new underlying mechanism of the effect of EGCG on ovarian cancer and may lead to the development of EGCG as a candidate drug for ovarian cancer therapy.

A Notch4 missense mutation is associated with susceptibility to tuberculosis in Chinese population

BACKGROUND

The infection process of tuberculosis is related to the interactions between Mycobacterium tuberculosis (MTB) and the host immune system. Polymorphisms in genes involved in the host immune system are related to susceptibility to tuberculosis. The Notch signalling pathway regulates innate and adaptive immunity. Notch4 is a member of the Notch receptor family and may be a negative regulator of Mtb-induced inflammation. However, little is known about the association between Notch4 genetic polymorphisms and susceptibility to tuberculosis; therefore, we explored the association between Notch4 variants and susceptibility to tuberculosis in China.

MATERIALS AND METHODS

A total of 900 tuberculosis patients and 1534 healthy people serving as controls were enrolled consecutively at West China Hospital between January 2014 and February 2016 Twelve selected SNPs (rs2071277, rs2071285, rs206016, rs438475, rs2256594, rs429853, rs422951, rs415929, rs915895, rs443198, rs3830041 and rs375244) were genotyped by a custom-by-design 2 48-plex SNP scan TM kit. The frequencies of the alleles, genotypes and genetic models of the variants were compared between the two groups, while the SNP-SNP interactions were analysed by Multifactor Dimensionality Reduction (MDR) software. The odds ratio (OR) with a corresponding 95% confidence interval (CI) was calculated.

RESULTS

The G allele rs2071277 of Notch4 was associated with a decreased risk for tuberculosis (OR 0.844; 95% CI 0.748-0.954, p = .006). The G allele rs422951 of Notch4 was associated with a decreased risk for tuberculosis (OR 0.818; 95% CI 0.703-0.950, p = .008). These findings were consistent with the results from both the dominant model and additive model. The allele, genotype and genetic model frequencies for the other SNPs were similar in the two groups (all P > .05). One haplotype (GTG) consisting of rs2071277, rs2071285 and rs206016 was associated with tuberculosis risk (p = .011).

CONCLUSION

Ours is the first study implies that the G allele variants of rs2071277 and rs422951 in Notch4 influence susceptibility to tuberculosis in a Chinese population, suggesting that Notch signalling is involved in the pathogenesis of tuberculosis. More studies with functional verification will refine our understanding of the role of Notch signalling and provide novel avenues for therapeutic intervention.