Screening and identification of hub genes in pancreatic cancer by integrated bioinformatics analysis

Pancreatic cancer (Pa) is a malignant tumor of the digestive tract with high degree of malignancy, this study aimed to obtain the hub genes in the tumorigenesis of Pa. Microarray datasets GSE15471, GSE16515, and GSE62452 were downloaded from Gene Expression Omnibus (GEO) database, GEO2R was conducted to screen the differentially expressed genes (DEGs), and functional enrichment analyses were carried out by Database for Annotation, Visualization and Integrated Discovery (DAVID). The protein-protein interaction (PPI) network was constructed with the Search Tool for the Retrieval of Interacting Genes (STRING), and the hub genes were identified by Cytoscape. Totally 205 DEGs were identified, consisting of 51 downregulated genes and 154 upregulated genes enriched in Gene Ontology terms including extracellular matrix (ECM) organization, collagen binding, cell adhesion, and pathways associated with ECM-receptor interaction, focal adhesion, and protein digestion. Two modules in the PPI were chosen and biological process analyses showed that the module genes were mainly enriched in ECM and cell adhesion. Twenty-four hub genes were confirmed, the survival analyses from the cBioPortal online platform revealed that topoisomerase (DNA) II α (TOP2A), periostin (POSTN), plasminogen activator, urokinase (PLAU), and versican (VCAN) may be involved in the carcinogenesis and progression of Pa, and the receiver-operating characteristic curves indicated their diagnostic value for Pa. Among them, TOP2A, POSTN, and PLAU have been previously reported as biomarkers for Pa, and far too little attention has been paid to VCAN. Analysis from R2 online platform showed that Pa patients with high VCAN expression were more sensitive to gemcitabine than those with low level, suggesting that VCAN may be an indicator to guide the use of the chemotherapeutic drug. In vitro experiments also showed that the sensitivity of the VCAN siRNA group to gemcitabine was lower than that of the control group. In conclusion, this study discerned hub genes and pathways related to the development of Pa, and VCAN was identified as a novel biomarker for the diagnose and therapy of Pa.     

Identification of key candidate genes and pathways in multiple myeloma by integrated bioinformatics analysis

Multiple myeloma (MM) is a common hematologic malignancy for which the underlying molecular mechanisms remain largely unclear. This study aimed to elucidate key candidate genes and pathways in MM by integrated bioinformatics analysis. Expression profiles GSE6477 and GSE47552 were obtained from the Gene Expression Omnibus database, and differentially expressed genes (DEGs) with p < .05 and [logFC] > 1 were identified. Functional enrichment, protein–protein interaction network construction and survival analyses were then performed. First, 51 upregulated and 78 downregulated DEGs shared between the two GSE datasets were identified. Second, functional enrichment analysis showed that these DEGs are mainly involved in the B cell receptor signaling pathway, hematopoietic cell lineage, and NF-kappa B pathway. Moreover, interrelation analysis of immune system processes showed enrichment of the downregulated DEGs mainly in B cell differentiation, positive regulation of monocyte chemotaxis and positive regulation of T cell proliferation. Finally, the correlation between DEG expression and survival in MM was evaluated using the PrognoScan database. In conclusion, we identified key candidate genes that affect the outcomes of patients with MM, and these genes might serve as potential therapeutic targets.     

Identification of key genes and pathways of thyroid cancer by integrated bioinformatics analysis

Thyroid cancer is a common endocrine malignancy with a rapidly increasing incidence worldwide. Although its mortality is steady or declining because of earlier diagnoses, its survival rate varies because of different tumour types. Thus, the aim of this study was to identify key biomarkers and novel therapeutic targets in thyroid cancer. The expression profiles of GSE3467, GSE5364, GSE29265 and GSE53157 were downloaded from the Gene Expression Omnibus database, which included a total of 97 thyroid cancer and 48 normal samples. After screening significant differentially expressed genes (DEGs) in each data set, we used the robust rank aggregation method to identify 358 robust DEGs, including 135 upregulated and 224 downregulated genes, in four datasets. Gene Ontology and Kyoto Encyclopaedia of Genes and Genomes pathway enrichment analyses of DEGs were performed by DAVID and the KOBAS online database, respectively. The results showed that these DEGs were significantly enriched in various cancer-related functions and pathways. Then, the STRING database was used to construct the protein–protein interaction network, and modules analysis was performed. Finally, we filtered out five hub genes, including LPAR5, NMU, FN1, NPY1R, and CXCL12, from the whole network. Expression validation and survival analysis of these hub genes based on the The Cancer Genome Atlas database suggested the robustness of the above results. In conclusion, these results provided novel and reliable biomarkers for thyroid cancer, which will be useful for further clinical applications in thyroid cancer diagnosis, prognosis and targeted therapy.     

Identification of differentially expressed genes and biological characteristics of colorectal cancer by integrated bioinformatics analysis

Colorectal cancer (CRC) ranks as one of the most common malignant tumors worldwide. Its mortality rate has remained high in recent years. Therefore, the aim of this study was to identify significant differentially expressed genes (DEGs) involved in its pathogenesis, which may be used as novel biomarkers or potential therapeutic targets for CRC. The gene expression profiles of GSE21510, GSE32323, GSE89076, and GSE113513 were downloaded from the Gene Expression Omnibus (GEO) database. After screening DEGs in each GEO data set, we further used the robust rank aggregation method to identify 494 significant DEGs including 212 upregulated and 282 downregulated genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed by DAVID and the KOBAS online database, respectively. These DEGs were shown to be significantly enriched in different cancer-related functions and pathways. Then, the STRING database was used to construct the protein–protein interaction network. The module analysis was performed by the MCODE plug-in of Cytoscape based on the whole network. We finally filtered out seven hub genes by the cytoHubba plug-in, including PPBP, CCL28, CXCL12, INSL5, CXCL3, CXCL10, and CXCL11. The expression validation and survival analysis of these hub genes were analyzed based on The Cancer Genome Atlas database. In conclusion, the robust DEGs associated with the carcinogenesis of CRC were screened through the GEO database, and integrated bioinformatics analysis was conducted. Our study provides reliable molecular biomarkers for screening and diagnosis, prognosis as well as novel therapeutic targets for CRC.     

Identification and analysis of immune-related subtypes of hepatocellular carcinoma

Hepatocellular carcinoma is a malignance that remains difficult to cure. Immunotherapy has shown its potential application in a variety of refractory malignancies. Due to the complexity of immune microenvironment of hepatocellular carcinoma, the efficacy of immunotherapy for hepatocellular carcinoma is not as effective as expected. Expression data of hepatocellular carcinoma from the TCGA and ICGC databases were used for classification and verification of hepatocellular carcinoma subtypes. The immune-related functions and pathways were identified via gene set enrichment analysis, while the sections denoting the subsets of the immune cells were estimated using the CIBERSORT algorithm. Immunity low (Immunity_L), immunity medium (Immunity_M), and immunity high (Immunity_H) were specified as the three immune-related subtypes of hepatocellular carcinoma. The quantity of stromal and immune cells was the most substantial in Immunity_H, compared to the other subtypes. Interestingly, the proportion of M0 macrophages decreased from Immunity_L to Immunity_H, while the proportion of CD8 T cells increased. Furthermore, the HLA genes expression levels, as well as those of six immune checkpoint genes were substantially lower in Immunity_L than in Immunity_H. Functional analysis was performed for 1512 differentially expressed genes between Immunity_L and Immunity_H. Finally, the PPI network was constructed with 118 nodes. The highest connectivity degree nodes were B2M, HLA-DRA, and HLA-DRB1. The above results were verified in ICGC-JP and ICGC-FR databases with a consistent trend. In this study, we divided hepatocellular carcinoma into three subtypes and explored the immune-related characteristics of these subtypes. These results may provide new insights for immunotherapy of hepatocellular carcinoma.     

Identification of core genes and outcomes in hepatocellular carcinoma by bioinformatics analysis

Hepatocellular carcinoma (HCC) is the most common malignant liver disease in the world. However, the mechanistic relationships among various genes and signaling pathways are still largely unclear. In this study, we aimed to elucidate potential core candidate genes and pathways in HCC. The expression profiles GSE14520, GSE25097, GSE29721, and GSE62232, which cover 606 tumor and 550 nontumour samples, were downloaded from the Gene Expression Omnibus (GEO) database. Furthermore, HCC RNA-seq datasets were also downloaded from the Cancer Genome Atlas (TCGA) database. The differentially expressed genes (DEGs) were filtered using R software, and we performed gene ontology (GO) and Kyoto Encyclopedia of Gene and Genome (KEGG) pathway analysis using the online databases DAVID 6.8 and KOBAS 3.0. Furthermore, the protein-protein interaction (PPI) network complex of these DEGs was constructed by Cytoscape software, the molecular complex detection (MCODE) plug-in and the online database STRING. First, a total of 173 DEGs (41 upregulated and 132 downregulated) were identified that were aberrantly expressed in both the GEO and TCGA datasets. Second, GO analysis revealed that most of the DEGs were significantly enriched in extracellular exosomes, cytosol, extracellular region, and extracellular space. Signaling pathway analysis indicated that the DEGs had common pathways in metabolism-related pathways, cell cycle, and biological oxidations. Third, 146 nodes were identified from the DEG PPI network complex, and two important modules with a high degree were detected using the MCODE plug-in. In addition, 10 core genes were identified, TOP2A, NDC80, FOXM1, HMMR, KNTC1, PTTG1, FEN1, RFC4, SMC4, and PRC1. Finally, Kaplan-Meier analysis of overall survival and correlation analysis were applied to these genes. The abovementioned findings indicate that the identified core genes and pathways in this bioinformatics analysis could significantly enrich our understanding of the development and recurrence of HCC; furthermore, these candidate genes and pathways could be therapeutic targets for HCC treatment.     

The emerging role of MIF in septic shock and infection

The protein mediator described originally as macrophage migration inhibitory factor (MIF) has been re-discovered recently to be both a novel pituitary hormone and a pro-inflammatory, macrophage-derived cytokine. Emerging studies indicate that MIF plays a pivotal role not only in endotoxic shock but also in the host response to a variety of acute and chronic infections.Abbreviations MIF Macrophage migration Inhibitory Factor     

果蝇基因组与功能基因研究进展

黑腹果蝇Drosophila melanogaster是生物科学研究中重要的模式动物之一。2000年,黑腹果蝇全基因组测序完成,随后基因组序列质量不断完善,对其功能基因进行深入研究,为其他高等动物基因组和功能基因的研究提供了巨大帮助。本文综述了近年来基因组功能元件、比较基因组学等方面的最新研究成果,着重介绍了功能基因在Hh信号通路、细胞凋亡方面的研究进展,并对最新的功能基因研究技术进行了简要概述。     

Identification of gene coexpression modules,hub genes,and pathways related to spinal cord injury using integrated bioinformatics methods

Spinal cord injury (SCI) is characterized by dramatic neurons loss and axonal regeneration suppression. The underlying mechanism associated with SCI-induced immune suppression is still unclear. Weighted gene coexpression network analysis (WGCNA) is now widely applied for the identification of the coexpressed modules, hub genes, and pathways associated with clinic traits of diseases. We performed this study to identify hub genes associated with SCI development. Gene Expression Omnibus (GEO) data sets GSE45006 and GSE20907 were downloaded and the significant correlativity and connectivity between them were detected using WGCNA. Three significant consensus modules, including 567 eigengenes, were identified from the master GSE45006 data following the preconditions of approximate scale-free topology for WGCNA. Further bioinformatics analysis showed these eigengenes were involved in inflammatory and immune responses in SCI. Three hub genes Rac2, Itgb2, and Tyrobp and one pathway “natural killer cell-mediated cytotoxicity” were identified following short time-series expression miner, protein-protein interaction network, and functional enrichment analysis. Gradually upregulated expression patterns of Rac2, Itgb2, and Tyrobp genes at 0, 3, 7, and 14 days after SCI were confirmed based on GSE45006 and GSE20907 data set. Finally, we found that Rac2, Itgb2, and Tyrobp genes might take crucial roles in SCI development through the “natural killer cell–mediated cytotoxicity” pathway.     

酸中毒条件下脓毒性休克大鼠胸主动脉对多巴胺反应性的变化

目的:观察不同酸中毒条件下正常大鼠和脓毒性休克大鼠胸主动脉对多巴胺反应性的变化。方法:采用离体血管灌流方法,观察对照组和脓毒性休克组大鼠胸主动脉在不同pH条件下的反应性变化。结果:pH值依次降低,对照组及脓毒性休克组离体胸主动脉对多巴胺反应性均下降,在相同pH值条件下脓毒性休克组比对照组离体血管对多巴胺反应性下降更为明显。结论:①环境pH值的下降会导致正常大鼠和脓毒性休克大鼠离体动脉对多巴胺反应性的下降。②在相同的酸性环境中脓毒性休克大鼠的血管对多巴胺刺激的反应性更差,更易失去活性。     

Changes of microcirculation in healthy volunteers and patients with septic shock in Xining

Objective: The purpose of this study is to investigate the characteristic of microcirculation in healthy volunteers and patients with septic shock in both Xining(2 260 m) and Nanjing(10 m). Methods: A total of 62 cases, 33 healthy volunteers, 22 cases in Xining,(2 260 m above sea level) and 11 cases in Nanjing(10 m above sea level); and 29 septic shock, 13 cases in Xining and 16 cases in Nanjing were collected. The total vessel density(TVD), perfused vessel density(PVD), proportion of perfused vessel(PPV) and microcirculation flow index(MFI) of both healthy volunteers and septic shock had been investigated by using sidestream dark field(SDF). Analyzed and managed the image data by using AVA3.0 software. Results: In the healthy volunteers in Xining area(22 cases),the volume of TVD(15.59 ± 2.58 mm/mm~2), PVD(15.58 ± 2.58 mm/mm~2) and PPV(96.60% ± 4.63%) were significant higher than the volume of TVD(10.0 ± 2.10 mm/mm~2), PVD(10.81 ± 2.38 mm/mm~2) and PPV(84.24% ± 8.00%) of the volunteers(11 cases) in Nanjing(11 cases). But the MFI(2.17 ± 0.31) of the healthy volunteers in the Xining was significant lower(P0.05) than the MFI(3.21 ± 0.34) in the healthy volunteers of Nanjing. In the septic shock group(13 cases) in the Xining, the volume of TVD(5.44 ± 1.94 mm/mm~2), PVD(4.18 ± 1.61 mm/mm~2), PPV(42.14%± 5.38%) and MFI(1.05 ± 0.32) compared with the volume of the healthy volunteers in Xining, the TVD(15.59 ± 2.58 mm/mm~2), PVD(5.58 ± 2.58 mm/mm~2), PPV(96.60% ± 4.63%) and MFI(2.17 ± 0.30) were significant lower(P0.05). In the healthy volunteers compare with septic shock group in Nanjing area, the TVD(6.80±1.72 vs 10.00±2.10, P0.05), PVD(5.86±1.58 vs10.81±2.38,P0.05), PPV(45.42±4.86 vs 84.24±4.86, P0.05), MFI(1.28±0.28 vs 3.21±0.34 P0.05), there was significant decreased. In the septic shock group in the Xining compared with the septic shock in Nanjing, there was no significant difference. 10 of 13 patients with septic shock were survived in Xining. 13 of 16 patients with septic shock were survived in Nanjing. Conclusion: The changes of physiological and pathophysiological characteristic in microcirculation induced by hypoxia would be useful for clinical treatment of septic shock at high altitude.     

Analysis of peripheral blood lymphocyte subsets and prognosis in patients with septic shock

The purpose of the study is to study the relationship between peripheral blood lymphocyte subset proportion and prognosis in patients with septic shock. Fifty‐two patients with septic shock, admitted to the intensive care unit between March 2007 and December 2010, were enrolled in this study. Peripheral blood lymphocyte subset proportions were measured using flow cytometry. The percentage of CD3⁺CD4⁺ T lymphocytes and CD19⁺ lymphocytes, CD4⁺/CD8⁺ T cell ratio were substantially lower in patients with septic shock compared to the control group (P < 0.01). The percentage of CD3⁺CD8⁺ T lymphocytes did not differ significantly between the two groups (P > 0.05). The percentage of CD16⁺CD56⁺ lymphocytes was higher in patients with septic shock than in the control group (P < 0.01). Compared with the survivor group, the percentage of CD3⁺CD4⁺ T lymphocytes and CD19⁺ lymphocytes, CD4⁺/CD8⁺ T cell ratio were clearly lower in the non‐survivor group (P < 0.01). There was no difference in the percentage of CD3⁺CD8⁺ T lymphocytes between the non‐survivor and survivor groups (P > 0.05). The percentage of CD16⁺CD56⁺ lymphocytes was higher in the non‐survivor group than in the survivor group (P < 0.05). The total maximum SOFA score and the delta SOFA score were much higher in the non‐survivor group than in the survivor group (P < 0.01). Immune imbalance occurs in patients with septic shock. Peripheral blood lymphocyte subset proportion and SOFA scores can be used to assess the treatment and prognosis of septic shock.     

灰葡萄孢犬尿氨酸途径关键酶基因的鉴定

【背景】灰葡萄孢是一种重要的植物病原真菌,实验室前期明确了灰葡萄孢犬尿氨酸单加氧酶(kynurenine3-monooxygenase,KMO)基因BcKMO参与调控病菌的生长发育和致病力。犬尿氨酸单加氧酶(KMO)是犬尿氨酸途径的关键酶,但灰葡萄孢是否存在犬尿氨酸途径及其在病菌生长、发育和致病过程中的功能尚未见相关报道。【目的】鉴定灰葡萄孢犬尿氨酸途径中的关键酶基因,确定灰葡萄孢犬尿氨酸途径的存在,为阐明灰葡萄孢生长发育和致病力的分子机理奠定基础。【方法】利用生物信息学方法,对灰葡萄孢犬尿氨酸途径中犬尿氨酸酶(kynureninase,KYN)、吲哚-2,3-双加氧酶(indoleamine-2,3-dioxygenase,IDO)、犬尿氨酸氨基转移酶(kynurenine amino transferase,KAT)的编码基因进行分析;利用Real-time PCR技术,检测灰葡萄孢野生型BC22、BcKMO基因T-DNA插入突变体BCG183、恢复菌株BCG183/BcKMO中犬尿氨酸途径关键酶基因的表达水平;利用真菌犬尿氨酸酶KYN检测试剂盒,测定BcKMO突变体中犬尿氨酸酶(KYN)的含量。【结果】灰葡萄孢中含有2个犬尿氨酸氨基转移酶(KAT)的编码基因、3个吲哚-2,3-双加氧酶(IDO)的编码基因、10个犬尿氨酸氨基转移酶(KAT)的编码基因。灰葡萄孢KYN编码基因、IDO编码基因、KAT编码基因在突变体BCG183中的表达水平显著高于或低于在野生型和恢复菌株。突变体BCG183中犬尿氨酸酶(KYN)的含量显著低于野生型BC22和恢复菌株。【结论】灰葡萄孢中存在犬尿氨酸途径,灰葡萄孢BcKMO基因突变影响KYN、IDO和KAT编码基因的表达以及犬尿氨酸酶(KYN)的含量。     

内源性一氧化碳对内毒素休克肺组织和肾组织保护作用的实验研究

目的：研究内毒素休克时内源性一氧化碳（CO）对肺组织和肾组织的保护作用及其机制;方法：采用盲肠结扎穿孔（CLP）的方法建立大鼠内毒素休克模型,通过免疫组化、光镜下组织形态学观察及超氧化物岐化酶活性、丙二醛含量的测定进行研究;结果：治疗组肺组织和肾组织病变明显减轻,炎症反应及脂质过氧化程度减轻;结论：内毒素休克时内源性CO对肺组织和肾组织具有保护作用,且此保护作用与其抑制炎症反应和抗氧化作用有重要关系。     

葡萄SAUR基因家族鉴定与生物信息学分析

为了研究葡萄早期应答生长素基因SAUR(Small auxin-up RNA)家族,本研究利用全基因组信息鉴定了葡萄64个SAUR家族成员,并对SAUR家族成员的基因结构、氨基酸特性、染色体定位、基因进化、基因功能以及组织表达进行分析。结果表明,葡萄全基因组上64个SAUR家族成员在19条染色体中的8条染色体上呈现簇状分布,主要分布在3、4号染色体上,其中3号染色体上数量最多为37个;葡萄SAUR家族基因长度较短,有59个基因是无内含子基因;蛋白理化特征分析显示,多数SAUR蛋白呈碱性,结构稳定性较差,蛋白脂溶指数高,呈亲水性;基因功能预测结果表明,葡萄SAUR基因主要担当生长因子、结构蛋白、转录、转录调控以及响应胁迫应答和免疫应答6种功能,其中更多参与生长调节功能;根据系统进化分析将其分为10个分支,另外不同组织表达谱的分析结果表明SAUR基因家族成员具有不同的组织表达模式,对于非生物胁迫具有一定的调节作用。这些信息为葡萄SAUR基因家族功能分析奠定了一定的工作基础。     

Identifying breast cancer subtypes associated modules and biomarkers by integrated bioinformatics analysis

Breast cancer is the most common form of cancer afflicting women worldwide. Patients with breast cancer of different molecular classifications need varied treatments. Since it is known that the development of breast cancer involves multiple genes and functions, identification of functional gene modules (clusters of the functionally related genes) is indispensable as opposed to isolated genes, in order to investigate their relationship derived from the gene co-expression analysis. In total, 6315 differentially expressed genes (DEGs) were recognized and subjected to the co-expression analysis. Seven modules were screened out. The blue and turquoise modules have been selected from the module trait association analysis since the genes in these two modules are significantly correlated with the breast cancer subtypes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment show that the blue module genes engaged in cell cycle, DNA replication, p53 signaling pathway, and pathway in cancer. According to the connectivity analysis and survival analysis, 8 out of 96 hub genes were filtered and have shown the highest expression in basal-like breast cancer. Furthermore, the hub genes were validated by the external datasets and quantitative real-time PCR (qRT-PCR). In summary, hub genes of Cyclin E1 (CCNE1), Centromere Protein N (CENPN), Checkpoint kinase 1 (CHEK1), Polo-like kinase 1 (PLK1), DNA replication and sister chromatid cohesion 1 (DSCC1), Family with sequence similarity 64, member A (FAM64A), Ubiquitin Conjugating Enzyme E2 C (UBE2C) and Ubiquitin Conjugating Enzyme E2 T (UBE2T) may serve as the prognostic markers for different subtypes of breast cancer.     

Identification of key microRNAs and hub genes in non-small-cell lung cancer using integrative bioinformatics and functional analyses

Non-small-cell lung cancer (NSCLC) is an extremely debilitating respiratory malignancy. However, the pathogenesis of NSCLC has not been fully clarified. The main objective of our study was to identify potential microRNAs (miRNAs) and their regulatory mechanism in NSCLC. Using a systematic review, two NSCLC-associated miRNA data sets (GSE102286 and GSE56036) were obtained from Gene Expression Omnibus, and the differentially expressed miRNAs (DE-miRNAs) were accessed by GEO2R. Survival analysis of candidate DE-miRNAs was conducted using the Kaplan-Meier plotter database. To further illustrate the roles of DE-miRNAs in NSCLC, their potential target genes were predicted by miRNet and were annotated by the Database for Annotation, Visualization and Integrated Discovery (DAVID) program. Moreover, the protein-protein interaction (PPI) and miRNA-hub gene regulatory network were established using the STRING database and Cytoscape software. The function of DE-miRNAs in NSCLC cells was evaluated by transwell assay. Compared with normal tissues, a total of eight DE-miRNAs was commonly changed in two data sets. The survival analysis showed that six miRNAs (miR-21-5p, miR-31-5p, miR-708-5p, miR-30a-5p, miR-451a, and miR-126-3p) were significantly correlated with overall survival. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis indicated that target genes of upregulated miRNAs were enriched in pathways in cancer, microRNAs in cancer and proteoglycans in cancer, while the target genes of downregulated miRNAs were mainly associated with pathways in cancer, the PI3K-Akt signaling pathway and HTLV-I infection. Based on the miRNA-hub gene network and expression analysis, PTEN, EGFR, STAT3, RHOA, VEGFA, TP53, CTNNB1, and KRAS were identified as potential target genes. Furthermore, all six miRNAs exhibited significant effects on NSCLC cell invasion. These findings indicate that six DE-miRNAs and their target genes may play important roles in the pathogenesis of NSCLC, which will provide novel information for NSCLC treatments.     

Identification of key genes and pathways associated with sex difference in osteoarthritis based on bioinformatics analysis

Objectives:The present study aimed to identify different key genes and pathways between postmenopausal females and males by studying differentially expressed genes (DEGs).Methods:{"type":"entrez-geo","attrs":{"text":"GSE32317","term_id":"32317"}}GSE32317 and {"type":"entrez-geo","attrs":{"text":"GSE55457","term_id":"55457"}}GSE55457 gene expression data were downloaded from the GEO database, and DEGs were discovered using R software to obtain overlapping DEGs. The interaction between overlapping DEGs was further analyzed by establishing the protein-protein interaction (PPI) network. Finally, GO and KEGG were used for enrichment analysis.Results:924 overlapping DEGs between postmenopausal women and men with osteoarthritis (OA) were identified, including 674 up-regulated genes and 249 down-regulated ones. And 10 hub genes were identified in the PPI network, including BMP4, KDM6A, JMJD1C, NFATC1, PRKX, SRF, ZFX, LAMTOR5, UFD1L and AMBN. The findings of the functional enrichment analysis suggested that these genes were predominantly expressed in MAPK signaling pathway as well as the Thyroid hormone signaling pathway, indicating that those two pathways may be involved in onset and disease progression of OA in postmenopausal patients.Conclusion:BMP4, KDM6A, JMJD1C, PRKX, ZFX and LAMTOR5 are expected to play crucial roles in disease development in postmenopausal patients and may be ideal targets or prognostic markers for the treatment of OA.