Associations between TAB2 gene polymorphisms and dilated cardiomyopathy in a Chinese population

2020 ◽  
Author(s):  
Can Shen ◽  
Yue Zhong ◽  
Xingming Huang ◽  
Yanyun Wang ◽  
Ying Peng ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Survival Analysis ◽  
Dilated Cardiomyopathy ◽  
Gene Polymorphisms ◽  
Chinese Population ◽  
Cox Regression ◽  
Bonferroni Correction ◽  
Cox Regression Analysis ◽  
Kaplan Meier

Aim: The present study aimed to investigate the role of TAB2 gene polymorphisms in dilated cardiomyopathy (DCM) susceptibility and prognosis in a Chinese population. Materials & methods: A total of 343 DCM patients and 451 controls were enrolled and had their blood genotyped. Survival analysis was evaluated with Kaplan-Meier curves and Cox regression analysis. Results: G carriers (AG/GG) and AG genotype of rs237028 had a higher DCM susceptibility as well as a worse DCM prognosis. Additionally, C carriers (CT/CC) of rs652921 and G carriers (TG/GG) of rs521845 had a higher DCM risk and CC homozygote of rs652921 had a worse DCM prognosis. These associations were still significant after adjustment for the Bonferroni correction. Conclusion: TAB2 gene polymorphisms were associated with DCM susceptibility and prognosis in the Chinese population.

scholarly journals Expression Status and Prognostic Value of m6A RNA Methylation Regulators in Lung Adenocarcinoma

2020 ◽  
Author(s):  
Rui Wang ◽  
Zian Feng ◽  
Jie Hu ◽  
Xiaodong He ◽  
Zuojun Shen
Keyword(s):  
Regression Analysis ◽  
Survival Analysis ◽  
Roc Curve ◽  
Cox Regression ◽  
Risk Group ◽  
Cox Regression Analysis ◽  
Rna Methylation ◽  
Kaplan Meier ◽  
Prediction Efficiency

Abstract Background: N6-methyladenosine (m6A) RNA modification is the most abundant modification method in mRNA, and it plays an important role in the occurrence and development of many cancers. However, data on the role of m6A RNA methylation regulators in lung adenocarcinoma (LUAD) are still lacking. This paper mainly discusses the role of m6A RNA methylation regulators in LUAD, to identify novel prognostic biomarkers.Methods: The gene expression data of 19 m6A methylation regulator in LUAD patients and its relevant clinical parameters were extracted from The Cancer Genome Atlas (TCGA) database. The least absolute shrinkage and selection operator (LASSO) Cox regression algorithm were performed to construct a risk signature and evaluated its prognostic prediction efficiency by using the receiver operating characteristic (ROC) curve. The risk score of each patient was calculated according to the risk signature, and LUAD patients were divided into high-risk group and low-risk group. Kaplan-Meier survival analysis and Cox regression analysis were used to identify the independent prognostic significance of risk signature. Finally, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA) were used to explore the differential signaling pathways and cellular processes between the two groups.Results: The expression of 15 m6A RNA methylation regulators in LUAD tissues was significantly different than that in normal tissues. YTHDF3, YTHDF2, KIAA1429, HNRNPA2B1, RBM15, METTL3, HNRNPC, YTHDF1, IGF2BP2, IGF2BP3, IGF2BP1 were significantly up-regulated in LUAD, and the expressions of FTO, ZC3H13, WTAP, and METL14 were significantly down-regulated. We selected IGF2BP1, HNRNPC, and HNRNPA2B1 to construct the risk signature. ROC curve indicated the area under the curve (AUC) was 0.659, which means the risk signature had a good prediction efficiency. The results of Kaplan-Meier survival analysis and Cox regression analysis showed that the risk score can be used as an independent prognostic factor for LUAD.Conclusions: The m6A RNA methylation regulators IGF2BP1, HNRNPC, and HNRNPA2B1 have a significant correlation with the clinicopathological characteristics of LUAD, which may be a promising prognostic feature and clinical treatment target.

scholarly journals Role of the TGFβ/PDCD4/AP-1 Signaling Pathway in Nasopharyngeal Carcinoma and Its Relationship to Prognosis

2017 ◽  
Vol 43 (4) ◽  
pp. 1392-1401 ◽  
Author(s):  
Jie Ma ◽  
Shu-Hong Xuan ◽  
Yan Li ◽  
Zhi-Ping Zhang ◽  
Xin-Hua Li
Keyword(s):  
Regression Analysis ◽  
Prognostic Factors ◽  
Nasopharyngeal Carcinoma ◽  
Cox Regression ◽  
Advanced Tumor Stage ◽  
Cox Regression Analysis ◽  
Normal Tissues ◽  
Kaplan Meier ◽  
Low Expression

Background: The objective of the present study was to evaluate the role of the TGFβ/PDCD4/AP-1 pathway in nasopharyngeal carcinoma (NPC) and its relationship to NPC prognosis. Methods: NPC tissues collected from 66 NPC patients were compared to 17 nasopharyngeal mucosa biopsy specimens collected as normal tissues. Immunohistochemical staining was performed to assess expression of transforming growth factor-β receptor I (TGFβRI), programmed cell death 4 (PDCD4) and activator protein-1 (AP-1). The Kaplan-Meier method was applied to evaluate NPC patient overall survival (OS) and progression-free-survival (PFS). Cox regression analysis was used to estimate independent prognostic factors for NPC. The human NPC cell line CNE2 was selected and treated with SB431542, an inhibitor of TGFβRI; expression of TGFβRI and PDCD4 in CNE2 cells was determined by western blotting. NPC tissues showed higher expression of TGFβRI and AP-1 but lower expression of PDCD4 than normal tissues (all P < 0.05). Results: The results of Kaplan-Meier analysis showed that TGFβRI-positive patients and AP-1-positive patients had shorter OS and PFS than TGFβRI-negative patients and AP-1-negative patients; additionally, PDCD4-positive patients had higher OS and PFS than PDCD4-negative patients. Cox regression analysis revealed that advanced tumor stage, overexpression of TGFβRI and AP-1, and low expression of PDCD4 were unfavorable factors influencing OS and PFS in NPC patients. Compared with the control group, expression of TGFβRI decreased and that of PDCD4 increased significantly in CNE2 cells treated with the inhibitor (all P < 0.05). These findings indicate that the TGFβ/PDCD4/AP-1 pathway may be associated with NPC development and progression. Conclusion: High expression of TGFβRI and AP-1 and low expression of PDCD4 may be unfavorable prognostic factors for NPC.

scholarly journals Expression Status and Prognostic Value of m6A RNA Methylation Regulators in Lung Adenocarcinoma

Life ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. 619
Author(s):  
Xiuhong Li ◽  
Zian Feng ◽  
Rui Wang ◽  
Jie Hu ◽  
Xiaodong He ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Survival Analysis ◽  
Lung Adenocarcinoma ◽  
Roc Curve ◽  
Cox Regression ◽  
Cox Regression Analysis ◽  
Rna Methylation ◽  
Kaplan Meier ◽  
M6a Rna Methylation ◽  
Prediction Efficiency

N6-methyladenosine (m6A) RNA modification is the most abundant modification method in mRNA, and it plays an important role in the occurrence and development of many cancers. This paper mainly discusses the role of m6A RNA methylation regulators in lung adenocarcinoma (LUAD) to identify novel prognostic biomarkers. The gene expression data of 19 m6A methylation regulators in LUAD patients and its relevant clinical parameters were extracted from The Cancer Genome Atlas (TCGA) database. We selected three significantly differentially expressed m6A regulators in LUAD to construct the risk signature, and evaluated its prognostic prediction efficiency using the receiver operating characteristic (ROC) curve. Kaplan–Meier survival analysis and Cox regression analysis were used to identify the independent prognostic significance of the risk signature. The ROC curve indicated that the area under the curve (AUC) was 0.659, which means that the risk signature had a good prediction efficiency. The results of the Kaplan–Meier survival analysis and Cox regression analysis showed that the risk score can be used as an independent prognostic factor for LUAD. In addition, we explored the differential signaling pathways and cellular processes related to m6A methylation regulators in LUAD.

scholarly journals Identification of crucial genes of pyrimidine metabolism as biomarkers for gastric cancer prognosis

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Zhengxin Wu ◽  
Jinshui Tan ◽  
Yifan Zhuang ◽  
Mengya Zhong ◽  
Yubo Xiong ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Regression Analysis ◽  
Survival Analysis ◽  
Risk Model ◽  
Cox Regression ◽  
Clinical Samples ◽  
Pyrimidine Metabolism ◽  
Cox Regression Analysis ◽  
Kaplan Meier ◽  
Cox Analysis

Abstract Background Metabolic reprogramming has been reported in various kinds of cancers and is related to clinical prognosis, but the prognostic role of pyrimidine metabolism in gastric cancer (GC) remains unclear. Methods Here, we employed DEG analysis to detect the differentially expressed genes (DEGs) in pyrimidine metabolic signaling pathway and used univariate Cox analysis, Lasso-penalizes Cox regression analysis, Kaplan–Meier survival analysis, univariate and multivariate Cox regression analysis to explore their prognostic roles in GC. The DEGs were experimentally validated in GC cells and clinical samples by quantitative real-time PCR. Results Through DEG analysis, we found NT5E, DPYS and UPP1 these three genes are highly expressed in GC. This conclusion has also been verified in GC cells and clinical samples. A prognostic risk model was established according to these three DEGs by Univariate Cox analysis and Lasso-penalizes Cox regression analysis. Kaplan–Meier survival analysis suggested that patient cohorts with high risk score undertook a lower overall survival rate than those with low risk score. Stratified survival analysis, Univariate and multivariate Cox regression analysis of this model confirmed that it is a reliable and independent clinical factor. Therefore, we made nomograms to visually depict the survival rate of GC patients according to some important clinical factors including our risk model. Conclusion In a word, our research found that pyrimidine metabolism is dysregulated in GC and established a prognostic model of GC based on genes differentially expressed in pyrimidine metabolism.

scholarly journals Serum Chemerin Predicts the Prognosis of Patients With Dilated Cardiomyopathy

2020 ◽  
Vol 23 (3) ◽  
pp. E276-E280
Author(s):  
Dan Chen ◽  
Juan Wang ◽  
Jianglin Fu
Keyword(s):  
Regression Analysis ◽  
Dilated Cardiomyopathy ◽  
Cox Regression ◽  
Survival Rates ◽  
Prognostic Indicator ◽  
Rank Test ◽  
Cardiac Events ◽  
Cox Regression Analysis ◽  
Kaplan Meier ◽  
Potential Risk Factors

Background: Chemerin is a newly discovered adipokine, which has been reported to be associated with the presence of dilated cardiomyopathy (DCM). The present study aims to evaluate the prognostic value of serum chemerin in patients with DCM. Methods: A total of 214 patients with DCM was recruited and divided into 4 groups, according to quartiles of chemerin levels. Kaplan–Meier analysis was conducted to compare the survival rates among patients with different levels of chemerin, using the log-rank test. Multivariate Cox regression analysis was performed to assess the association of serum chemerin levels and occurrence of major adverse cardiac events (MACEs), including cardiac mortality, stroke and myocardial infarction. Results: The Kaplan-Meier survival analysis indicated that patients with higher concentration of chemerin had shorter event-free survivals for MACEs (P < .01). Cox regression analysis showed that chemerin was a significant predictor of MACEs (Quartile 3 versus Quartile 1: HR=1.79, 95% CI: 1.31-2.79; Quartile 4 versus Quartile 1: HR=2.87, 95% CI: 1.79-4.25) and all-cause death (Quartile 3 versus Quartile 1: HR=1.56, 95% CI: 1.20-2.42; Quartile 4 versus Quartile 1: HR=2.28, 95% CI: 1.52-3.96) after adjusting for potential risk factors. Conclusion: Serum chemerin should be a potential prognostic indicator in patients with DCM.

scholarly journals Identification of Crucial Genes of Pyrimidine Metabolism as Biomarkers for Gastric Cancer Prognosis

2021 ◽  
Author(s):  
Zhengxin Wu ◽  
Jinshui Tan ◽  
Yifan Zhuang ◽  
Mengya Zhong ◽  
Yubo Xiong ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Regression Analysis ◽  
Survival Analysis ◽  
Risk Model ◽  
Cox Regression ◽  
Clinical Samples ◽  
Pyrimidine Metabolism ◽  
Cox Regression Analysis ◽  
Kaplan Meier ◽  
Cox Analysis

Abstract Background Metabolic reprogramming has been reported in various kinds of cancers and is related to clinical prognosis, but the prognostic role of pyrimidine metabolism in gastric cancer (GC) remains unclear. Methods Here, we employed DEG analysis to detect the differentially expressed genes (DEGs) in pyrimidine metabolic signaling pathway and used univariate Cox analysis, Lasso-penalizes Cox regression analysis, Kaplan-Meier survival analysis, univariate and multivariate Cox regression analysis to explore their prognostic roles in GC. The DEGs were experimentally validated in GC cells and clinical samples by quantitative real-time PCR. Results Through DEG analysis, we found NT5E, DPYS and UPP1 these three genes are highly expressed in GC. This conclusion has also been verified in GC cells and clinical samples. A prognostic risk model was established according to these three DEGs by Univariate Cox analysis and Lasso-penalizes Cox regression analysis. Kaplan-Meier survival analysis suggested that patient cohorts with high risk score undertook a lower overall survival rate than those with low risk score. Stratified survival analysis, Univariate and multivariate Cox regression analysis of this model confirmed that it is a reliable and independent clinical factor. Therefore, we made nomograms to visually depict the survival rate of GC patients according to some important clinical factors including our risk model. Conclusion In a word, our research found that pyrimidine metabolism is dysregulated in GC and established a prognostic model of GC based on genes differentially expressed in pyrimidine metabolism.

Prognostic role of aberrant mTOR activation in patients with stage II and III colorectal cancer

2020 ◽  
Vol 14 (12) ◽  
pp. 1127-1137
Author(s):  
Tong-Tong Zhang ◽  
Yi-Qing Zhu ◽  
Hong-Qing Cai ◽  
Jun-Wen Zheng ◽  
Jia-Jie Hao ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Cox Regression ◽  
Disease Free Survival ◽  
Stage Ii ◽  
Poor Prognostic Factor ◽  
Cox Regression Analysis ◽  
Kaplan Meier ◽  
Potential Biomarker ◽  
Risk Predictor

Aim: This study aimed to develop an effective risk predictor for patients with stage II and III colorectal cancer (CRC). Materials & methods: The prognostic value of p-mTOR (Ser2448) levels was analyzed using Kaplan–Meier survival analysis and Cox regression analysis. Results: The levels of p-mTOR were increased in CRC specimens and significantly correlated with poor prognosis in patients with stage II and III CRC. Notably, the p-mTOR level was an independent poor prognostic factor for disease-free survival and overall survival in stage II CRC. Conclusion: Aberrant mTOR activation was significantly associated with the risk of recurrence or death in patients with stage II and III CRC, thus this activated proteins that may serve as a potential biomarker for high-risk CRC.

The Role of Surgery in IDH-Wild-Type Lower-Grade Gliomas: Threshold at a High Extent of Resection Should be Pursued

Neurosurgery ◽  
2021 ◽  
Author(s):  
Peng Wang ◽  
Chen Luo ◽  
Peng-jie Hong ◽  
Wen-ting Rui ◽  
Shuai Wu
Keyword(s):  
Cox Regression ◽  
Progression Free Survival ◽  
Extent Of Resection ◽  
Lower Grade ◽  
Wild Type ◽  
Cox Regression Analysis ◽  
Kaplan Meier ◽  
Lower Grade Glioma ◽  
Clinical Benefits

Abstract BACKGROUND While maximizing extent of resection (EOR) is associated with longer survival in lower-grade glioma (LGG) patients, the number of cases remains insufficient in determining a EOR threshold to elucidate the clinical benefits, especially in IDH-wild-type LGG patients. OBJECTIVE To identify the effects of EOR on the survival outcomes of IDH-wild-type LGG patients. METHODS IDH-wild-type LGG patients were retrospectively reviewed. The effect of EOR and other predictor variables on overall survival (OS) and progression-free survival (PFS) was analyzed using Cox regression models and the Kaplan-Meier method. RESULTS A total of 94 patients (median OS: 48.9 mo; median follow-up: 30.6 mo) were included in this study. In the multivariable Cox regression analysis, postoperative residual volume was associated with prolonged OS (HR = 2.238; 95% confidence interval [CI], 1.130-4.435; P = .021) and PFS (HR = 2.075; 95% CI, 1.113-3.869; P = .022). Thresholds at a minimum EOR of 97.0% or a maximum residue of 3.0 cm3 were necessary to impact OS positively. For the telomerase reverse transcriptase (TERT)p-wild-type group, such an association was absent. Significant differences in survival existed between the TERTp-wild-type and mutant patients who underwent relatively incomplete resections (residual ≥2.0 cm3 + TERTp wild type: median OS of 62.6 mo [95% CI: 39.7-85.5 mo]; residual ≥2.0 cm3 + TERTp mutant: median OS of 20.0 mo [95% CI:14.6-25.4 mo]). CONCLUSION Our results support the core role of maximal safe resection in the treatment of IDH-wild-type LGGs, especially for IDH-wild-type + TERTp-mutant LGGs. Importantly, the survival benefits of surgery could only be elucidated at a high EOR cut-off point.

scholarly journals Identification of Immune-Related Prognostic mRNA and lncRNA in Patients with Hepatocellular Carcinoma

2022 ◽  
Vol 2022 ◽  
pp. 1-16
Author(s):  
Dan Chen ◽  
Xiaoting Li ◽  
Hui Li ◽  
Kai Wang ◽  
Xianghua Tian
Keyword(s):  
Hepatocellular Carcinoma ◽  
Flow Cytometry ◽  
T Cells ◽  
Regression Analysis ◽  
Survival Analysis ◽  
Immune Cells ◽  
Cox Regression ◽  
Differentially Expressed ◽  
Cox Regression Analysis ◽  
Immune Related Genes

Background. As the most common hepatic malignancy, hepatocellular carcinoma (HCC) has a high incidence; therefore, in this paper, the immune-related genes were sought as biomarkers in liver cancer. Methods. In this study, a differential expression analysis of lncRNA and mRNA in The Cancer Genome Atlas (TCGA) dataset between the HCC group and the normal control group was performed. Enrichment analysis was used to screen immune-related differentially expressed genes. Cox regression analysis and survival analysis were used to determine prognostic genes of HCC, whose expression was detected by molecular experiments. Finally, important immune cells were identified by immune cell infiltration and detected by flow cytometry. Results. Compared with the normal group, 1613 differentially expressed mRNAs (DEmRs) and 1237 differentially expressed lncRNAs (DElncRs) were found in HCC. Among them, 143 immune-related DEmRs and 39 immune-related DElncRs were screened out. These genes were mainly related to MAPK cascade, PI3K-AKT signaling pathway, and TGF-beta. Through Cox regression analysis and survival analysis, MMP9, SPP1, HAGLR, LINC02202, and RP11-598F7.3 were finally determined as the potential diagnostic biomarkers for HCC. The gene expression was verified by RT-qPCR and western blot. In addition, CD4 + memory resting T cells and CD8 + T cells were identified as protective factors for overall survival of HCC, and they were found highly expressed in HCC through flow cytometry. Conclusion. The study explored the dysregulation mechanism and potential biomarkers of immune-related genes and further identified the influence of immune cells on the prognosis of HCC, providing a theoretical basis for the prognosis prediction and immunotherapy in HCC patients.

scholarly journals Identification and Analysis of Three Hub Prognostic Genes Related to Osteosarcoma Metastasis

2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Jianye Tan ◽  
Haofeng Liang ◽  
Bingsheng Yang ◽  
Shuang Zhu ◽  
Guofeng Wu ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Cox Regression ◽  
Survival Rates ◽  
Prognostic Biomarkers ◽  
Messenger Rnas ◽  
Hub Genes ◽  
Cox Regression Analysis ◽  
Expression Levels ◽  
Kaplan Meier ◽  
Before And After

Osteosarcoma (OS) often occurs in children and often undergoes metastasis, resulting in lower survival rates. Information on the complexity and pathogenic mechanism of OS is limited, and thus, the development of treatments involving alternative molecular and genetic targets is hampered. We categorized transcriptome data into metastasis and nonmetastasis groups, and 400 differential RNAs (230 messenger RNAs (mRNAs) and 170 long noncoding RNAs (lncRNAs)) were obtained by the edgeR package. Prognostic genes were identified by performing univariate Cox regression analysis and the Kaplan–Meier (KM) survival analysis. We then examined the correlation between the expression level of prognostic lncRNAs and mRNAs. Furthermore, microRNAs (miRNAs) corresponding to the coexpression of lncRNA-mRNA was predicted, which was used to construct a competitive endogenous RNA (ceRNA) regulatory network. Finally, multivariate Cox proportional risk regression analysis was used to identify hub prognostic genes. Three hub prognostic genes (ABCG8, LOXL4, and PDE1B) were identified as potential prognostic biomarkers and therapeutic targets for OS. Furthermore, transcriptions factors (TFs) (DBP, ESX1, FOS, FOXI1, MEF2C, NFE2, and OTX2) and lncRNAs (RP11-357H14.16, RP11-284N8.3, and RP11-629G13.1) that were able to affect the expression levels of genes before and after transcription were found to regulate the prognostic hub genes. In addition, we identified drugs related to the prognostic hub genes, which may have potential clinical applications. Immunohistochemistry (IHC) and quantitative real-time polymerase chain reaction (qRT-PCR) confirmed that the expression levels of ABCG8, LOXL4, and PDE1B coincided with the results of bioinformatics analysis. Moreover, the relationship between the hub prognostic gene expression and patient prognosis was also validated. Our study elucidated the roles of three novel prognostic biomarkers in the pathogenesis of OS as well as presenting a potential clinical treatment for OS.

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