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  • 1
    Online Resource
    Online Resource
    Springer Science and Business Media LLC ; 2019
    In:  Archives of Gynecology and Obstetrics Vol. 299, No. 1 ( 2019-1), p. 35-46
    In: Archives of Gynecology and Obstetrics, Springer Science and Business Media LLC, Vol. 299, No. 1 ( 2019-1), p. 35-46
    Type of Medium: Online Resource
    ISSN: 0932-0067 , 1432-0711
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2019
    detail.hit.zdb_id: 1458450-5
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  • 2
    In: Journal of Cellular Biochemistry, Wiley, Vol. 120, No. 9 ( 2019-09), p. 15378-15388
    Abstract: Breast cancer (BC) remains a serious health threat for women due to its high incidence and the trend of rejuvenation. Accumulating evidence has highlighted that microRNAs (miRNAs) and messenger RNAs (mRNAs) could play important roles in various biological processes involved in the pathogenesis of BC. The present study aimed to identify potential prognostic biomarkers associated with BC. Methods Here, original gene expression profiles of patients with BC was downloaded from The Cancer Genome Atlas (TCGA) database. TargetScan, miRDB, and miRTarBase databases were used to predict the target genes of prognostic‐related differentially expressed miRNAs (DEMs). Subsequently, functional enrichment analysis and topological analysis were performed on the overlaps of target genes and differentially expressed mRNAs (DEGs), and Kaplan‐Meier analysis was used to predict prognosis‐related target genes to identify prognostic biomarkers. Results A total of 218 DEMs and 2222 DEGs were extracted in which eight miRNAs were associated with prognosis, and 278 target DEGs were screened out incorporated into functional enrichment analysis and protein‐protein interaction network visualization studies. Additionally, five hub genes (CXCL12, IGF1, LEF1, MMP1, and RACGAP1) were observed as potential biomarkers for BC prognosis through survival analysis. Conclusion We performed a distinctive correlation analysis of miRNA‐mRNA in BC patients, and identified eight miRNAs and five hub genes may be effective biomarkers for the prognosis of BC patients.
    Type of Medium: Online Resource
    ISSN: 0730-2312 , 1097-4644
    URL: Issue
    Language: English
    Publisher: Wiley
    Publication Date: 2019
    detail.hit.zdb_id: 1479976-5
    SSG: 12
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  • 3
    In: Bioscience Reports, Portland Press Ltd., Vol. 40, No. 1 ( 2020-01-31)
    Abstract: Lung adenocarcinoma (LUAD) is the leading cause of cancer-related death worldwide, and its underlying mechanism remains unclear. Accumulating evidence has highlighted that long non-coding RNA (lncRNA) acts as competitive endogenous RNA (ceRNA) and plays an important role in the occurrence and development of LUAD. Here, we comprehensively analyzed and provided an overview of the lncRNAs, miRNAs, and mRNAs associated with LUAD from The Cancer Genome Atlas (TCGA) database. Then, differentially expressed lncRNAs (DElncRNA), miRNAs (DEmiRNA), and mRNAs (DEmRNA) were used to construct a lncRNA–miRNA–mRNA regulatory network according to interaction information from miRcode, TargetScan, miRTarBase, and miRDB. Finally, the RNAs of the network were analyzed for survival and submitted for Cox regression analysis to construct prognostic indicators. A total of 1123 DElncRNAs, 95 DEmiRNAs, and 2296 DEmRNAs were identified (|log2FoldChange| (FC) & gt; 2 and false discovery rate (FDR) or adjusted P value & lt; 0.01). The ceRNA network was established based on this and included 102 lncRNAs, 19 miRNAs, and 33 mRNAs. The DEmRNAs in the ceRNA network were found to be enriched in various cancer-related biological processes and pathways. We detected 22 lncRNAs, 12 mRNAs, and 1 miRNA in the ceRNA network that were significantly associated with the overall survival of patients with LUAD (P & lt; 0.05). We established three prognostic prediction models and calculated the area under the 1,3,5-year curve (AUC) values of lncRNA, mRNA, and miRNA, respectively. Among them, the prognostic index (PI) of lncRNA showed good predictive ability which was 0.737, 0.702 and 0.671 respectively, and eight lncRNAs can be used as candidate prognostic biomarkers for LUAD. In conclusion, our study provides a new perspective on the prognosis and diagnosis of LUAD on a genome-wide basis, and develops independent prognostic biomarkers for LUAD.
    Type of Medium: Online Resource
    ISSN: 0144-8463 , 1573-4935
    Language: English
    Publisher: Portland Press Ltd.
    Publication Date: 2020
    detail.hit.zdb_id: 2014993-1
    SSG: 12
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  • 4
    Online Resource
    Online Resource
    Frontiers Media SA ; 2022
    In:  Frontiers in Immunology Vol. 13 ( 2022-4-26)
    In: Frontiers in Immunology, Frontiers Media SA, Vol. 13 ( 2022-4-26)
    Abstract: To construct an immune-related gene prognostic index (IRGPI) for breast cancer (BC) and investigate its prognostic specificity and the molecular and immune characteristics. Methods BC hub genes were identified from The Cancer Genome Atlas and immune-related databases using weighted gene co-expression network analysis (WGCNA). IRGPI was constructed using univariate, LASSO, and multivariate regression analyses, and was validated with GSE58812 and GSE97342 in the Gene Expression Omnibus database (GEO). At the same time, we evaluated the predictive ability of IRGPI for different BC subtypes. Subsequently, the molecular and immune characteristics, clinical relevance, and benefits of immune checkpoint inhibitor treatment were analyzed for different IRGPI subgroups. Results IRGPI consisted of six genes: SOCS3, TCF7L2, TSLP NPR3, ANO6, and HMGB3. The IRGPI 1-, 5-, and 10-years area under curve (AUC) values were 0.635, 0.752, and 0.753, respectively, indicating that IRGPI has good potential in predicting the long-term survival of BC patients, consistent with the results in the GEO cohort. IRGPI showed good predictive power in four different breast cancer subtypes: ER positive, PR positive, HER2 positive and triple-negative ( P & lt;0.01). Compared with the low-IRGPI group, the high-IRGPI group had a worse prognosis and a lower degree of immune infiltrating cells ( p & lt; 0.05). IRGPI showed specificity in distinguishing age, TNM stage, ER, and HER2 statuses, and our study found that the high-IRGPI group had low tumor immune dysfunction and exclusion (TIDE), microsatellite instability (MSI), and T cell dysfunction scores ( p & lt; 0.05). In addition, compared with the TIDE and TIS models, showed that the AUCs of IRGPI were better during the 5-year follow-up. Conclusion IRGPI can be used as an independent prognostic indicator of breast cancer, providing a method for monitoring the long-term treatment of BC.
    Type of Medium: Online Resource
    ISSN: 1664-3224
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2022
    detail.hit.zdb_id: 2606827-8
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  • 5
    Online Resource
    Online Resource
    Informa UK Limited ; 2021
    In:  Pharmacogenomics and Personalized Medicine Vol. Volume 14 ( 2021-01), p. 15-26
    In: Pharmacogenomics and Personalized Medicine, Informa UK Limited, Vol. Volume 14 ( 2021-01), p. 15-26
    Type of Medium: Online Resource
    ISSN: 1178-7066
    Language: English
    Publisher: Informa UK Limited
    Publication Date: 2021
    detail.hit.zdb_id: 2508173-1
    SSG: 15,3
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  • 6
    In: Disease Markers, Hindawi Limited, Vol. 2019 ( 2019-12-04), p. 1-14
    Abstract: Background . Lung squamous cell carcinoma (LUSC) is a subtype of highly malignant lung cancer with poor prognosis, for which smoking is the main risk factor. However, the underlying genetic and molecular mechanisms of smoking-related LUSC remain largely unknown. Methods . We mined existing LUSC-related mRNA, miRNA, and lncRNA transcriptome data and corresponding clinical data from The Cancer Genome Atlas (TCGA) database and divided them into smoking and nonsmoking groups, followed by differential expression analysis. Functional enrichment analysis of the unique differentially expressed mRNAs of the two groups was performed using the DAVID database. Subsequently, the lncRNA-miRNA-mRNA competing endogenous RNA (ceRNA) network of LUSC in smoking and nonsmoking groups was constructed. Finally, survival analyses were performed to determine the effects of differentially expressed lncRNAs/mRNAs/miRNAs that were involved in the ceRNA network on overall survival and to discover the hub genes. Results . A total of 1696 lncRNAs, 125 miRNAs, and 3246 mRNAs and 1784 lncRNAs, 96 miRNAs, and 3229 mRNAs with differentially expressed profiles were identified in the smoking and nonsmoking groups, respectively. The ceRNA network and survival analysis revealed four lncRNAs (LINC00466, DLX6-AS1, LINC00261, and AGBL1), one miRNA (hsa-mir-210), and two mRNAs (CITED2 and ENPP4), with the potential as biomarkers for smoking-related LUSC diagnosis and prognosis. Conclusion . Taken together, our research has identified the differences in the ceRNA regulatory networks between smoking and nonsmoking LUSC, which could lay the foundation for future clinical research.
    Type of Medium: Online Resource
    ISSN: 0278-0240 , 1875-8630
    Language: English
    Publisher: Hindawi Limited
    Publication Date: 2019
    detail.hit.zdb_id: 2033253-1
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  • 7
    Online Resource
    Online Resource
    PeerJ ; 2019
    In:  PeerJ Vol. 7 ( 2019-09-17), p. e7727-
    In: PeerJ, PeerJ, Vol. 7 ( 2019-09-17), p. e7727-
    Abstract: Long noncoding RNAs (lncRNAs) play a role in the formation, development, and prognosis of various cancers. Our study aimed to identify prognostic-related lncRNAs in lung squamous cell carcinoma (LUSC), which may provide new perspectives for individualized treatment of patients. Materials and Methods The RNA sequencing (lncRNA, microRNA (miRNA), mRNA) data and clinical information related to LUSC were obtained from The Cancer Genome Atlas (TCGA) database. Differentially expressed RNA sequences were used to construct the competitive endogenous RNA (ceRNA) network. In present study, we mainly used two prognostic verification methods, Cox analysis and survival analysis, to identify the prognostic relevance of specific lncRNAs and construct prognostic model of lncRNA. Results Datasets on 551 samples of lncRNA and mRNA and 523 miRNA samples were retrieved from the TCGA database. Analysis of the normal and LUSC samples identified 170 DElncRNAs, 331 DEmiRNAs, and 417 DEmRNAs differentially expressed RNAs. The ceRNA network contained 27 lncRNAs, 43 miRNAs, and 11 mRNAs. Furthermore, we identified seven specific lncRNAs (ERVH48-1, HCG9, SEC62-AS1, AC022148.1, LINC00460, C5orf17, LINC00261) as potential prognostic factors after correlation analysis, and five of the seven lncRNAs (AC022148.1, HCG9, LINC00460, C5orf17, LINC00261) constructed a prognostic model of LUSC. Conclusion In present study, we identified seven lncRNAs in the ceRNA network that are associated with potential prognosis in LUSC patients, and constructed a prognostic model of LUSC which can be used to assess the prognosis risk of clinical patients. Further biological experiments are needed to elucidate the specific molecular mechanisms underlying them.
    Type of Medium: Online Resource
    ISSN: 2167-8359
    Language: English
    Publisher: PeerJ
    Publication Date: 2019
    detail.hit.zdb_id: 2703241-3
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  • 8
    Online Resource
    Online Resource
    Wiley ; 2019
    In:  Journal of Cellular and Molecular Medicine Vol. 23, No. 12 ( 2019-12), p. 8410-8419
    In: Journal of Cellular and Molecular Medicine, Wiley, Vol. 23, No. 12 ( 2019-12), p. 8410-8419
    Abstract: Long non‐coding RNAs (lncRNAs), which competitively bind miRNAs to regulate target mRNA expression in the competing endogenous RNAs (ceRNAs) network, have attracted increasing attention in breast cancer research. We aim to find more effective therapeutic targets and prognostic markers for breast cancer. LncRNA, mRNA and miRNA expression profiles of breast cancer were downloaded from TCGA database. We screened the top 5000 lncRNAs, top 5000 mRNAs and all miRNAs to perform weighted gene co‐expression network analysis. The correlation between modules and clinical information of breast cancer was identified by Pearson's correlation coefficient. Based on the most relevant modules, we constructed a ceRNA network of breast cancer. Additionally, the standard Kaplan‐Meier univariate curve analysis was adopted to identify the prognosis of lncRNAs. Ultimately, a total of 23 and 5 modules were generated in the lncRNAs/mRNAs and miRNAs co‐expression network, respectively. According to the Green module of lncRNAs/mRNAs and Blue module of miRNAs, our constructed ceRNA network consisted of 52 lncRNAs, 17miRNAs and 79 mRNAs. Through survival analysis, 5 lncRNAs (AL117190.1, COL4A2‐AS1, LINC00184, MEG3 and MIR22HG) were identified as crucial prognostic factors for patients with breast cancer. Taken together, we have identified five novel lncRNAs related to prognosis of breast cancer. Our study has contributed to the deeper understanding of the molecular mechanism of breast cancer and provided novel insights into the use of breast cancer drugs and prognosis.
    Type of Medium: Online Resource
    ISSN: 1582-1838 , 1582-4934
    URL: Issue
    Language: English
    Publisher: Wiley
    Publication Date: 2019
    detail.hit.zdb_id: 2076114-4
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  • 9
    Online Resource
    Online Resource
    Ovid Technologies (Wolters Kluwer Health) ; 2018
    In:  Medicine Vol. 97, No. 47 ( 2018-11), p. e13264-
    In: Medicine, Ovid Technologies (Wolters Kluwer Health), Vol. 97, No. 47 ( 2018-11), p. e13264-
    Abstract: Previous studies on the association between statin use and survival outcomes in gynecologic cancers have presented conflicting results. No independent studies to elucidate the association between statin use and survival outcomes of endometrial cancer (EC) have been conducted. Methods: To gather updated evidence, we carried out an extensive literature search on Medline (PubMed and OvidSP), Embase, Cochrane Library, China National Knowledge Infrastructure (CNKI), wanfang data, and Vip network to identify all potential studies on the effect of statins on the prognosis of endometrial carcinoma. The design and quality of all studies were evaluated, and a fixed-effects model was used to calculate pooled hazard ratios (HRs) for overall survival (OS) and disease-specific survival (DSS). Results: Of the 219 articles screened, 9 articles were eligible, including 8 articles and 1 abstract. A total of 5923 patients with endometrial cancer who used statins were identified. Statin use was related to increased overall survival (HR, 0.80; 95% confidence interval [CI], 0.66–0.95, without significant heterogeneity, I 2  = 52%, P  = .080). Statin users also had increased disease-specific survival (HR, 0.69; 95% CI, 0.61–0.79, I 2  = 0.0%). Conclusion: Statins are beneficial to the survival outcome of patients with endometrial cancer. The selection of statins as a 1st-line agent seems justified for endometrial carcinoma.
    Type of Medium: Online Resource
    ISSN: 0025-7974 , 1536-5964
    Language: English
    Publisher: Ovid Technologies (Wolters Kluwer Health)
    Publication Date: 2018
    detail.hit.zdb_id: 2049818-4
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  • 10
    In: Journal of Cellular Biochemistry, Wiley, Vol. 120, No. 5 ( 2019-05), p. 7056-7067
    Abstract: Recent studies have shown that long noncoding RNAs (lncRNA) HOX transcript antisense intergenic RNA (HOTAIR) polymorphisms are associated with cancer susceptibility. The greatest threat to women’s health among a variety of cancers is breast cancer (BC), cervical cancer (CC), and ovarian cancer (OC), and the incidence of it is increasing. We performed a meta‐analysis to clarify the relationship between lncRNA HOTAIR expression and BC, CC, and OC susceptibility. We thoroughly searched PubMed, Embase, and the Cochrane Library to obtain the relevant literature. We extracted data from case groups and control groups for each single‐nucleotide polymorphism (SNP) (rs4759314, rs920778, rs189663, rs12826786, rs7958904, and rs874945) and compared the relationship between alleles, codominance models, dominant and invisible models and BC, CC, and OC susceptibility. Our study included 11 studies with a total of 5322 patients. There was a significant association between the rs4759314 polymorphism of HOTAIR and susceptibility to BC, CC, and OC (codominant model: AG/AA odds ratio [OR] = 1.13 [95% confidence intervals [CI] , 1.00‐1.29], GG/AA OR = 1.54 [95% CI, 1.06‐2.23] ; dominant model: GG + AG/AA OR = 1.16 [95% CI, 1.02‐1.32]; and recessive model: GG/AA + AG OR = 1.51 [95% CI, 1.05‐2.19] ). The association between the expression of rs920778 and BC, CC, and OC susceptibility was not clear (alleles T/C: OR = 1.28 [95% CI, 0.87‐1.89]; in codominant model: CT/CC OR = 1.10, [95% CI, 0.71‐1.71] , TT/CC OR = 1.29 [95% CI, 0.59‐2.80]; dominant model: TC + TT/CC OR = 1.16, [95% CI, 0.73‐1.86] ; and recessive model: TT/TC + CC OR = 1.43, [95% CI, 0.83‐2.47]). HOTAIR polymorphism rs1899663 was associated with BC, CC, and OC susceptibility to a certain extent, (alleles T/G OR = 0.90 [95% CI, 0.69‐1.16] ; in the codominant model: GT/GG OR = 0.81 [95% CI, 0.50‐1.30], TT/GG OR = 1.04 [95% CI, 0.63‐1.72] ; dominant model: GT + TT/GG OR = 0.82 [95% CI, 0.52‐1.29]; and recessive model: TT/GT + GG OR = 1.21 [95% CI, 0.76‐1.94] ). The rs12826786, rs7958904, and rs874945 polymorphisms were associated with a certain degree of BC, CC, and OC susceptibility, but they were not statistically significant. HOTAIR rs4759314 increased susceptibility to BC, CC, and OC in some patients; rs029778 and rs1899663 also increased susceptibility to some extent. SNPs rs12826786, rs7958904, and rs874945 did not correlate with an effect on patient susceptibility to BC, CC, and OC.
    Type of Medium: Online Resource
    ISSN: 0730-2312 , 1097-4644
    URL: Issue
    Language: English
    Publisher: Wiley
    Publication Date: 2019
    detail.hit.zdb_id: 1479976-5
    SSG: 12
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