Genetics research最新文献

{"title":"Clinical Significance of NKD Inhibitor of WNT Signaling Pathway 1 (NKD1) in Glioblastoma.","authors":"Lijun Li,&nbsp;Ruiying Gao,&nbsp;Weizhong Huangfu,&nbsp;Fang Zhang,&nbsp;Ruixia Wang","doi":"10.1155/2023/1184101","DOIUrl":"https://doi.org/10.1155/2023/1184101","url":null,"abstract":"<p><strong>Introduction: </strong>As the most malignant type of gliomas, glioblastoma is characterized with disappointing prognosis. Here, we aimed to investigate expression and function of NKD inhibitor of Wnt signaling pathway 1 (NKD1), an antagonist of Wnt-beta-catenin signaling pathways, in glioblastoma.</p><p><strong>Methods: </strong>The mRNA level of NKD1 was firstly retrieved from TCGA glioma dataset to evaluate its correlation with clinical characteristics and its value in prognosis prediction. Then, its protein expression level in glioblastoma was tested by immunohistochemistry staining in a retrospectively cohort collected from our medical center (<i>n</i> = 66). Univariate and multivariate survival analyses were conducted to assess its effect on glioma prognosis. Two glioblastoma cell lines, U87 and U251, were used to further investigate the tumor-related role of NKD1 through overexpression strategy in combination with cell proliferation assays. Immune cell enrichment in glioblastoma and its correlation with NKD1 level was finally assessed using bioinformatics analyses.</p><p><strong>Results: </strong>NKD1 shows a lower expression level in glioblastoma compared to that in the normal brain or other glioma subtypes, which is independently correlated to a worse prognosis in both the TCGA cohort and our retrospective cohort. Overexpressing NKD1 in glioblastoma cell lines can significantly attenuate cell proliferation. In addition, expression of NKD1 in glioblastoma is negatively correlated to the T cell infiltration, indicating it may have crosstalk with the tumor immune microenvironment.</p><p><strong>Conclusions: </strong>NKD1 inhibits glioblastoma progression and its downregulated expression indicates a poor prognosis.</p>","PeriodicalId":12778,"journal":{"name":"Genetics research","volume":"2023 ","pages":"1184101"},"PeriodicalIF":1.5,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10038739/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9561100","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integrated Bioinformatics Analysis to Screen Hub Gene Signatures for Fetal Growth Restriction.","authors":"Jingjin Yang,&nbsp;Yuxin Liu,&nbsp;Minyue Dong","doi":"10.1155/2023/3367406","DOIUrl":"https://doi.org/10.1155/2023/3367406","url":null,"abstract":"<p><strong>Background: </strong>Fetal growth restriction (FGR) is the impairment of the biological growth potential of the fetus and often leads to adverse pregnancy outcomes. The molecular mechanisms for the development of FGR, however, are still unclear. The purpose of this study is to identify critical genes associated with FGR through an integrated bioinformatics approach and explore the potential pathogenesis of FGR.</p><p><strong>Methods: </strong>We downloaded FGR-related gene microarray data, used weighted gene co-expression network analysis (WGCNA), differentially expressed genes (DEGs), and protein-protein interaction (PPI) networks to screen hub genes. The GSE24129 gene set was used for validation of critical gene expression levels and diagnostic capabilities.</p><p><strong>Results: </strong>A weighted gene co-expression network was constructed, and 5000 genes were divided into 12 modules. Of these modules, the blue module showed the closest relationship with FGR. Taking the intersection of the DEGs and genes in the blue module as pivotal genes, 277 genes were identified, and 20 crucial genes were screened from the PPI network. The GSE24129 gene set verified the expression of 20 genes, and CXCL9, CXCR3, and ITGAX genes were identified as actual pivotal genes. The expression levels of CXCL9, CXCR3, and ITGAX were increased in both the training and validation sets, and ROC curve validation revealed that these three pivotal genes had a significant diagnostic ability for FGR. Single-gene GSEA results showed that all three core genes activated \"hematopoietic cell lineage\" and \"cell adhesion molecules\" and inhibited the \"cGMP-PKG signaling pathway\" in the development of FGR. CXCL9, CXCR3, and ITGAX may therefore be closely associated with the development of FGR and may serve as potential biomarkers for the diagnosis and treatment of FGR.</p>","PeriodicalId":12778,"journal":{"name":"Genetics research","volume":"2023 ","pages":"3367406"},"PeriodicalIF":1.5,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10079385/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9637393","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identification of DUSP7 as an RNA Marker for Prognostic Stratification in Acute Myeloid Leukemia: Evidence from Large Population Cohorts.","authors":"Xin Gao","doi":"10.1155/2023/4348290","DOIUrl":"https://doi.org/10.1155/2023/4348290","url":null,"abstract":"<p><strong>Background: </strong>The problem of prognostic stratification in acute myeloid leukemia (AML) patients still has limitations.</p><p><strong>Methods: </strong>The expression profile data and clinical features of AML patients were obtained from multiple publicly available sources, including GSE71014, TCGA-LAML, and TARGET-AML. Single-cell analysis was performed using the TISCH project. All the analysis was conducted in the <i>R</i> software.</p><p><strong>Results: </strong>In our study, three public AML cohorts, GSE71014, TARGET-AML, and TCGA-AML, were selected. Then, we identified the prognosis-related molecules through bioinformatic analysis. Finally, the DUSP7 was noticed as a risk factor for AML patients, which has not been reported previously. Biological enrichment analysis and immune-related analysis were performed to illustrate the role of DUSP7 in AML. Single-cell analysis indicated that the DUSP7 was widely distributed in various cells, especially in monocyte/macrophages and malignant. Following this, a prognosis model based on DUSP7-derived genes was constructed, which showed a good prognosis prediction ability in all cohorts.</p><p><strong>Conclusions: </strong>Our results preliminarily reveal the role and potential mechanism of DUSP7 in AML, providing direction for future research.</p>","PeriodicalId":12778,"journal":{"name":"Genetics research","volume":"2023 ","pages":"4348290"},"PeriodicalIF":1.5,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10396553/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10307400","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identification of Potential Biomarkers of Septic Shock Based on Pathway and Transcriptome Analyses of Immune-Related Genes.","authors":"Jie Wang,&nbsp;Jie Cai,&nbsp;Linlin Yue,&nbsp;Xixi Zhou,&nbsp;Chunlin Hu,&nbsp;Hongquan Zhu","doi":"10.1155/2023/9991613","DOIUrl":"https://doi.org/10.1155/2023/9991613","url":null,"abstract":"<p><p>Immunoregulation is crucial to septic shock (SS) but has not been clearly explained. Our aim was to explore potential biomarkers for SS by pathway and transcriptional analyses of immune-related genes to improve early detection. GSE57065 and GSE95233 microarray data were used to screen differentially expressed genes (DEGs) in SS. Gene Ontology and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway enrichment analyses of DEGs were performed, and correlations between immune cell and pathway enrichment scores were analyzed. The predictive value of candidate genes was evaluated by receiver operating characteristic (ROC) curves. GSE66099, GSE4607, and GSE13904 datasets were used for external validation. Blood samples from six patients and six controls were collected for validation by qRT-PCR and western blotting. In total, 550 DEGs in SS were identified; these genes were involved in the immune response, inflammation, and infection. Immune-related pathways and levels of infiltration of CD4 + TCM, CD8 + T cells, and preadipocytes differed between SS cases and controls. Seventeen genes were identified as potential biomarkers of SS (areas under ROC curves >0.9). The downregulation of <i>CD8A</i>, <i>CD247</i>, <i>CD3G</i>, <i>LCK</i>, and <i>HLA-DRA</i> in SS was experimentally confirmed. We identified several immune-related biomarkers in SS that may improve early identification of disease risk.</p>","PeriodicalId":12778,"journal":{"name":"Genetics research","volume":"2023 ","pages":"9991613"},"PeriodicalIF":1.5,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10423089/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10012119","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Systematically Prognostic Analyses of Gastric Cancer Patients with Ovarian Metastasis.","authors":"Peng Peng,&nbsp;Xiuyuan Liu,&nbsp;Lin Yang,&nbsp;Zhenguang Gu,&nbsp;Lin Cai","doi":"10.1155/2023/9923428","DOIUrl":"https://doi.org/10.1155/2023/9923428","url":null,"abstract":"<p><p>Ovarian metastasis of gastric cancer indicates that the disease has reached the late stage and the opportunity for radical surgery is restricted. However, the clinical characteristics and prognosis of patients with gastric cancer ovarian metastasis (GCOM) remain to be illustrated. Here, we retrieved the information of 780 GCOM cases from the Surveillance, Epidemiology, and End Results (SEERs) database and analyzed their clinicopathological characteristics as well as their survival. According to our data, most GCOM patients showed poor pathological differentiation, advanced T and N stages. The prognostic factors include patients' age, tumor size, surgical resection, and chemotherapy treatment. Of note, the marriage status was also identified as an independent prognostic factor. Besides the identification of prognostic factors, we established nomograms to help predict the overall survival and cancer-specific survival of GCOM, respectively.</p>","PeriodicalId":12778,"journal":{"name":"Genetics research","volume":"2023 ","pages":"9923428"},"PeriodicalIF":1.5,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10164873/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9479238","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identification of PANoptosis-Based Prognostic Signature for Predicting Efficacy of Immunotherapy and Chemotherapy in Hepatocellular Carcinoma.","authors":"Xiaofeng Xiong,&nbsp;Qianben Song,&nbsp;Mengjia Jing,&nbsp;Wei Yan","doi":"10.1155/2023/6879022","DOIUrl":"https://doi.org/10.1155/2023/6879022","url":null,"abstract":"<p><strong>Background: </strong>PANoptosis has been a research hotspot, but the role of PANoptosis in hepatocellular carcinoma (HCC) remains widely unknown. Drug resistance and low response rate are the main limitations of chemotherapy and immunotherapy in HCC. Thus, construction of a prognostic signature to predict prognosis and recognize ideal patients for corresponding chemotherapy and immunotherapy is necessary.</p><p><strong>Method: </strong>The mRNA expression data of HCC patients was collected from TCGA database. Through LASSO and Cox regression, we developed a prognostic signature based on PANoptosis-related genes. KM analysis and ROC curve were implemented to evaluate the prognostic efficacy of this signature, and ICGC and GEO database were used as external validation cohorts. The immune cell infiltration, immune status, and IC50 of chemotherapeutic drugs were compared among different risk subgroups. The relationships between the signature and the efficacy of ICI therapy, sorafenib treatment, and transcatheter arterial chemoembolization (TACE) therapy were investigated.</p><p><strong>Result: </strong>A 3-gene prognostic signature was constructed which divided the patients into low- and high-risk subgroups. Low-risk patients had better prognosis, and the risk score was proved to be an independent predictor of overall survival (OS), which had a well predictive effect. Patients in high-risk population had more immunosuppressive cells (Tregs, M0 macrophages, and MDSCs), higher TIDE score and TP53 mutation rate, and elevated activity of base excision repair (BER) pathways. Patients with low risk benefited more from ICI, TACE, and sorafenib therapy. The predictive value of the risk score was comparable with TIDE and MSI for OS under ICI therapy. The risk score could be a biomarker to predict the response to ICI, TACE, and sorafenib therapy.</p><p><strong>Conclusion: </strong>The novel signature based on PANoptosis is a promising biomarker to distinguish the prognosis predict the benefit of ICI, TACE, and sorafenib therapy, and forecast the response to them.</p>","PeriodicalId":12778,"journal":{"name":"Genetics research","volume":"2023 ","pages":"6879022"},"PeriodicalIF":1.5,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10260314/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9659847","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Bioinformatics-Based Identification of CircRNA-MicroRNA-mRNA Network for Calcific Aortic Valve Disease.","authors":"Linghong Song,&nbsp;Yubing Wang,&nbsp;Yufei Feng,&nbsp;Hao Peng,&nbsp;Chengyan Wang,&nbsp;Juncang Duan,&nbsp;Kejian Liu,&nbsp;Xihua Shen,&nbsp;Wenyi Gu,&nbsp;Yan Qi,&nbsp;Shan Jin,&nbsp;Lijuan Pang","doi":"10.1155/2023/8194338","DOIUrl":"https://doi.org/10.1155/2023/8194338","url":null,"abstract":"<p><strong>Background: </strong>Calcific aortic valve disease (CAVD) is the most common native valve disease. Valvular interstitial cell (VIC) osteogenic differentiation and valvular endothelial cell (VEC) dysfunction are key steps in CAVD progression. Circular RNA (circRNAs) is involved in regulating osteogenic differentiation with mesenchymal cells and is associated with multiple disease progression, but the function of circRNAs in CAVD remains unknown. Here, we aimed to investigate the effect and potential significance of circRNA-miRNA-mRNA networks in CAVD.</p><p><strong>Methods: </strong>Two mRNA datasets, one miRNA dataset, and one circRNA dataset of CAVD downloaded from GEO were used to identify DE-circRNAs, DE-miRNAs, and DE-mRNAs. Based on the online website prediction function, the common mRNAs (FmRNAs) for constructing circRNA-miRNA-mRNA networks were identified. GO and KEGG enrichment analyses were performed on FmRNAs. In addition, hub genes were identified by PPI networks. Based on the expression of each data set, the circRNA-miRNA-hub gene network was constructed by Cytoscape (version 3.6.1).</p><p><strong>Results: </strong>32 DE-circRNAs, 206 DE-miRNAs, and 2170 DE-mRNAs were identified. Fifty-nine FmRNAs were obtained by intersection. The KEGG pathway analysis of FmRNAs was enriched in pathways in cancer, JAK-STAT signaling pathway, cell cycle, and MAPK signaling pathway. Meanwhile, transcription, nucleolus, and protein homodimerization activity were significantly enriched in GO analysis. Eight hub genes were identified based on the PPI network. Three possible regulatory networks in CAVD disease were obtained based on the biological functions of circRNAs including: hsa_circ_0026817-hsa-miR-211-5p-CACNA1C, hsa_circ_0007215-hsa-miR-1252-5p-MECP2, and hsa_circ_0007215-hsa-miR-1343-3p- RBL1.</p><p><strong>Conclusion: </strong>The present bionformatics analysis suggests the functional effect for the circRNA-miRNA-mRNA network in CAVD pathogenesis and provides new targets for therapeutics.</p>","PeriodicalId":12778,"journal":{"name":"Genetics research","volume":"2023 ","pages":"8194338"},"PeriodicalIF":1.5,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10208756/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9667115","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Bioinformatics Analysis Identifies TNFRSF1A as a Biomarker of Liver Injury in Sepsis TNFRSF1A is a Biomarker for Septic Liver Injury.","authors":"Shangxun Zhou,&nbsp;Wei Zhao,&nbsp;Junjie Li,&nbsp;Yang Huang,&nbsp;Jing Yang,&nbsp;Qianmei Wang,&nbsp;Yunyun Xu,&nbsp;Chujun Duan,&nbsp;Yutong Wang,&nbsp;Wen Yin","doi":"10.1155/2022/1493744","DOIUrl":"https://doi.org/10.1155/2022/1493744","url":null,"abstract":"<p><p>Sepsis is a severe disease with high mortality, and liver injury is an independent risk factor for sepsis morbidity and mortality. We analyzed co-differentially expressed genes (co-DEGs) to explore potential biomarkers and therapeutic targets for sepsis-related liver injury. Three gene expression datasets (GSE60088, GSE23767, and GSE71530) were downloaded from the Gene Expression Omnibus (GEO). DEGs were screened between sepsis and control samples using GEO2R. The association of these DEGs with infection and liver disease was analyzed by using the CTD database. GO functional analysis, KEGG pathway enrichment analysis, and protein-protein interaction (PPI) network analysis were performed to elucidate the potential molecular mechanism of DEGs. DEGs of different tissues in GSE60088 were analyzed again to obtain specific markers of septic liver injury. Mouse model of sepsis was also established by cecal ligation and puncture (CLP), and the expression of specific markers in liver, lung, and kidney tissues was analyzed using Western blot. Here, we identified 21 DEGs in three datasets with 8 hub genes, all of which showed higher inference scores in liver diseases than bacterial infections. Among them, only TNFRSF1A had a liver-specific differential expression. TNFRSF1A was also confirmed to be specifically reduced in septic liver tissues in mice. Therefore, TNFRSF1A may serve as a potential biomarker for septic liver injury.</p>","PeriodicalId":12778,"journal":{"name":"Genetics research","volume":" ","pages":"1493744"},"PeriodicalIF":1.5,"publicationDate":"2022-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9587912/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40427538","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An Integrative Multi-Omics Analysis Based on Nomogram for Predicting Prostate Cancer Bone Metastasis Incidence.","authors":"Jun Zhao,&nbsp;Rui Wang,&nbsp;Xiaoxin Sun,&nbsp;Kai Huang,&nbsp;Jiacheng Jin,&nbsp;Lan Lan,&nbsp;Yuli Jian,&nbsp;Zhongyang Xu,&nbsp;Haotian Wu,&nbsp;Shujing Wang,&nbsp;Jianbo Wang","doi":"10.1155/2022/8213723","DOIUrl":"https://doi.org/10.1155/2022/8213723","url":null,"abstract":"<p><strong>Background: </strong>The most common site of prostate cancer metastasis is bone tissue with many recent studies having conducted genomic and clinical research regarding bone metastatic prostate cancer. However, further work is needed to better define those patients that are at an elevated risk of such metastasis.</p><p><strong>Methods: </strong>SEER and TCGA databases were searched to develop a nomogram for predicting prostate cancer bone metastasis.</p><p><strong>Results: </strong>Herein, we leveraged the Surveillance, Epidemiology, and End Results (SEER) database to construct a predictive nomogram capable of readily and accurately predicted the odds of bone metastasis in prostate cancer patients. This nomogram was utilized to assign patients with prostate cancer included in The Cancer Genome Atlas (TCGA) to cohorts at a high or low risk of bone metastasis (HRBM and LRBM, respectively). Comparisons of these LRBM and HRBM cohorts revealed marked differences in mutational landscapes between these patient cohorts, with increased frequencies of gene fusions, somatic copy number variations (CNVs), and single nucleotide variations (SNVs), particularly in the P53 gene, being evident in the HRBM cohort. We additionally identified lncRNAs, miRNAs, and mRNAs that were differentially expressed between these two patient cohorts and used them to construct a competing endogenous RNA (ceRNA) network. Moreover, three weighted gene co-expression network analysis (WGCNA) modules were constructed from the results of these analyses, with KIF14, MYH7, and COL10A1 being identified as hub genes within these modules. We further found immune response activity levels in the HRBM cohort to be elevated relative to that in the LRBM cohort, with single sample gene enrichment analysis (ssGSEA) scores for the immune checkpoint signature being increased in HRBM patient samples relative to those from LRBM patients.</p><p><strong>Conclusion: </strong>We successfully developed a nomogram capable of readily detecting patients with prostate cancer at an elevated risk of bone metastasis.</p>","PeriodicalId":12778,"journal":{"name":"Genetics research","volume":" ","pages":"8213723"},"PeriodicalIF":1.5,"publicationDate":"2022-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9537037/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"33513368","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"ASPM, CDC20, DLGAP5, BUB1B, CDCA8, and NCAPG May Serve as Diagnostic and Prognostic Biomarkers in Endometrial Carcinoma.","authors":"Qiaoling Zhang,&nbsp;Yingmei Wang,&nbsp;Fengxia Xue","doi":"10.1155/2022/3217248","DOIUrl":"https://doi.org/10.1155/2022/3217248","url":null,"abstract":"<p><p>Uterine Corpus Endometrial Carcinoma (UCEC), the most common gynecologic malignancy in developed countries, remains to be a major public health problem. Further studies are surely needed to elucidate the tumorigenesis of UCEC. Herein, intersecting 203 differentially expressed genes (DEGs) were identified with the GSE17025, GSE63678, and The Cancer Genome Atlas-UCEC datasets. The Gene Ontology/Kyoto Encyclopedia of Genes and Genomes functional enrichment analysis and protein-protein interaction (PPI) network were performed on those 203 DEGs. Intriguingly, 6 of the top 10 nodes in the PPI network were related to unfavorable prognosis, that is, ASPM, CDC20, DLGAP5, BUB1B, CDCA8, and NCAPG. The mRNA and protein expression levels of the 6 hub genes were elevated in UCEC tissues compared to normal tissues. Higher expression of the 6 hub genes was associated with poor prognostic clinicopathological characteristics. The receiver operating characteristic curve suggested the significant diagnostic ability of the 6 hub genes for UCEC. Then, underlying pathogeneses of UCEC including promoter methylation level, TP53 mutation status, genomic genetic variation, and immune cells infiltration were analyzed. The mRNA expression level of the 6 hub genes was also higher in cervical squamous cell carcinoma and endocervical adenocarcinoma, uterine carcinosarcoma, and ovarian serous cystadenocarcinoma tissues than in corresponding normal tissues. In conclusion, ASPM, CDC20, DLGAP5, BUB1B, CDCA8, and NCAPG may be considered diagnostic and prognostic biomarkers in UCEC.</p>","PeriodicalId":12778,"journal":{"name":"Genetics research","volume":" ","pages":"3217248"},"PeriodicalIF":1.5,"publicationDate":"2022-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9509287/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40390273","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}