Cox Regression
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2021 ◽  
Vol 21 (1) ◽  
Yi Wang ◽  
Ye Tian ◽  
Shouyong Liu ◽  
Zengjun Wang ◽  
Qianwei Xing

Abstract Backgrounds This article aimed to explore the prognostic and immunological roles of AXL gene in clear cell renal cell carcinoma (ccRCC) for overall survival (OS) and to identify the LncRNA/RBP/AXL mRNA networks. Methods AXL-related gene expression matrix and clinical data were obtained from The Cancer Genome Atlas (TCGA) dataset and AXL-related pathways were identified by gene set enrichment analysis (GSEA). We performed univariate/multivariate Cox regression analysis to evaluate independent prognostic factors and the relationships between AXL and immunity were also investigated. Results The outcomes of us indicated that the AXL mRNA expression was up-regulated in ccRCC samples and high expression of AXL was associated with worse OS in TCGA dataset (P < 0.01). Further external verification results from HPA, UALCAN, ICGC dataset, GSE6344, GSE14994, and qRT-PCR remained consistent (all P < 0.05). AXL was also identified as an independent prognostic factor for ccRCC by univariate/multivariate Cox regression analysis (both P < 0.05). A nomogram including AXL expression and clinicopathological factors was established by us and GSEA results found that elevated AXL expression was associated with the JAK-STAT, P53, WNT, VEGF and MAPK signaling pathways. In terms of immunity, AXL was dramatically linked to tumor microenvironment, immune cells, immune infiltration, immune checkpoint molecules and tumor mutational burden (TMB). As for its potential mechanisms, we also identified several LncRNA/RBP/AXL mRNA axes. Conclusions AXL was revealed to play prognostic and immunological roles in ccRCC and LncRNA/RBP/AXL mRNA axes were also identified by us for its potential mechanisms.

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e12554
Liming Zheng ◽  
Xi Gu ◽  
Guojun Zheng ◽  
Xin Li ◽  
Meifang He ◽  

Background Early recurrence of hepatocellular carcinoma (HCC) is a major obstacle to improving the prognosis, and no widely accepted adjuvant therapy guideline for patients post-liver resection is available. Currently, all available methods and biomarkers are insufficient to accurately predict post-operation HCC patients’ risk of early recurrence and their response to adjuvant therapy. Methods In this study, we downloaded four gene expression datasets (GSE14520, GSE54236, GSE87630, and GSE109211) from the Gene Expression Omnibus database and identified 34 common differentially expressed genes associated with HCC dysregulation and response to adjuvant sorafenib. Then, we constructed a novel 11-messenger RNA predictive model by using ROC curves analysis, univariate Cox regression analysis, and LASSO Cox regression analysis. Furthermore, we validated the predictive values of the risk model in GSE14520 and TCGA-LIHC cohorts by using Kaplan–Meier survival analysis, multivariable Cox regression analysis, and decision curve analysis, respectively. Results The risk score model could identify patients with a high risk of HCC recurrence at the early stage and could predict the response of patients to adjuvant sorafenib. Patients with a high risk score had a worse recurrence rate in training cohorts (2-year: p < 0.0001, hazard ratio (HR): 4.658, confidence interval 95% CI [2.895–7.495]; 5-year: p < 0.0001, HR: 3.251, 95% CI [2.155–4.904]) and external validation cohorts (2-year: p < 0.001, HR: 3.65, 95% CI [2.001–6.658]; 5-year: p < 0.001, HR: 3.156, 95% CI [1.78–5.596]). The AUC values of the risk score model for predicting tumor early recurrence were 0.746 and 0.618, and that of the risk score model for predicting the response to adjuvant sorafenib were 0.722 and 0.708 in the different cohort, respectively. Multivariable Cox regression analysis and decision curve analysis also showed that the risk score model was superior to and independent of other clinicopathologic characteristics. Moreover, the risk score model had excellent abilities to predict the overall survival and HCC recurrence of patients with the same tumor stage category. Conclusions Our risk model is a reliable and superior predictive tool. With this model, we could optimize the risk stratification based on early tumor recurrence and could evaluate the response of patients to adjuvant sorafenib after liver resection.

2021 ◽  
Vol 20 (1) ◽  
Jung-Chi Hsu ◽  
Yen-Yun Yang ◽  
Shu-Lin Chuang ◽  
Yi-Wei Chung ◽  
Chih-Hsien Wang ◽  

Abstract Background Atrial fibrillation (AF) is prevalent in patients with type 2 diabetes mellitus (T2DM). Obesity commonly accompanies T2DM, and increases the risk of AF. However, the dose-relationship between body mass index (BMI) and AF risk has seldom been studied in patients with diabetes. Methods This cohort study utilized a database from National Taiwan University Hospital, a tertiary medical center in Taiwan. Between 2014 and 2019, 64,339 adult patients with T2DM were enrolled for analysis. BMI was measured and categorized as underweight (BMI < 18.5), normal (18.5 ≤ BMI < 24), overweight (24 ≤ BMI < 27), obesity class 1 (27 ≤ BMI < 30), obesity class 2 (30 ≤ BMI < 35), or obesity class 3 (BMI ≥ 35). Multivariate Cox regression and spline regression models were employed to estimate the relationship between BMI and the risk of AF in patients with T2DM. Results The incidence of AF was 1.97 per 1000 person-years (median follow-up, 70.7 months). In multivariate Cox regression, using normal BMI as the reference group, underweight (HR 1.52, 95% CI 1.25–1.87, p < 0.001) was associated with a significantly higher risk of AF, while overweight was associated with significantly reduced risk of AF (HR 0.82, 95% CI 0.73–0.89, p < 0.001). Kaplan–Meier analysis showed AF risk was highest in the underweight group, followed by obesity class 3, while the overweight group had the lowest incidence of AF (log-rank test, p < 0.001). The cubic restrictive spline model revealed a “J-shaped” or “L-shaped” relationship between BMI and AF risk. Conclusions Underweight status confers the highest AF risk in Asian patients with T2DM.

Jie Xu ◽  
Mingming Zhao ◽  
Anxin Wang ◽  
Jing Xue ◽  
Si Cheng ◽  

Background Trimethyllysine, a trimethylamine N‐oxide precursor, has been identified as an independent cardiovascular risk factor in acute coronary syndrome. However, limited data are available to examine the role of trimethyllysine in the population with stroke. We aimed to examine the relationship between plasma trimethyllysine levels and stroke outcomes in patients presenting with ischemic stroke or transient ischemic attack. Methods and Results Data of 10 027 patients with ischemic stroke/transient ischemic attack from the CNSR‐III (Third China National Stroke Registry) and 1‐year follow‐up data for stroke outcomes were analyzed. Plasma levels of trimethyllysine were measured with mass spectrometry. The association between trimethyllysine and stroke outcomes was analyzed using Cox regression models. Mediation analysis was performed to examine the mediation effects of risk factors on the associations of trimethyllysine and stroke outcomes. Elevated trimethyllysine levels were associated with increased risk of cardiovascular death (quartile 4 versus quartile 1: adjusted hazard ratio [HR], 1.72; 95% CI, 1.03–2.86) and all‐cause mortality (quartile 4 versus quartile 1: HR, 1.97; 95% CI, 1.40–2.78) in multivariate Cox regression model. However, no associations were found between trimethyllysine and nonfatal stroke recurrence or nonfatal myocardial infarction. Trimethyllysine was associated with cardiovascular death independent of trimethylamine N‐oxide. Both estimated glomerular filtration rate and hs‐CRP (high‐sensitivity C‐reactive protein) had significant mediation effects on the association of trimethyllysine with cardiovascular death, with a mediation effect of 37.8% and 13.4%, respectively. Conclusions Elevated trimethyllysine level is associated with cardiovascular death among patients with ischemic stroke/transient ischemic attack. Mediation analyses propose that trimethyllysine contributes to cardiovascular death through inflammation and renal function, suggesting a possible pathomechanistic link.

2021 ◽  
Vol 21 (1) ◽  
Rong Wei ◽  
Guoye Qi ◽  
Zixin Zeng ◽  
Ningning Shen ◽  
Ziyue Wang ◽  

Abstract Background Pancreatic cancer has been a threateningly lethal malignant tumor worldwide. Despite the promising survival improvement in other cancer types attributing to the fast development of molecular precise medicine, the current treatment situation of pancreatic cancer is still woefully challenging since its limited response to neither traditional radiotherapy and chemotherapy nor emerging immunotherapy. The study is to explore potential responsible genes during the development of pancreatic cancer, thus identifying promising gene indicators and probable drug targets. Methods Different bioinformatic analysis were used to interpret the genetic events in pancreatic cancer development. Firstly, based on multiple cDNA microarray profiles from Gene Expression Omnibus (GEO) database, the genes with differently mRNA expression in cancer comparing to normal pancreatic tissues were identified, followed by being grouped based on the difference level. Then, GO and KEGG were performed to separately interpret the multiple groups of genes, and further Kaplan–Meier survival and Cox Regression analysis assisted us to scale down the candidate genes and select the potential key genes. Further, the basic physicochemical properties, the association with immune cells infiltration, mutation or other types variations besides expression gap in pancreatic cancer comparing to normal tissues of the selected key genes were analyzed. Moreover, the aberrant changed expression of key genes was validated by immunohistochemistry (IHC) experiment using local hospital tissue microarray samples and the clinical significance was explored based on TCGA clinical data. Results Firstly, a total of 22,491 genes were identified to express differently in cancer comparing to normal pancreatic tissues based on 5 cDNA expression profiles, and the difference of 487/22491 genes was over eightfold, and 55/487 genes were shared in multi profiles. Moreover, after genes interpretation which showed the > eightfold genes were mainly related to extracellular matrix structural constituent regulation, Kaplan–Meier survival and Cox-regression analysis were performed continually, and the result indicated that of the 55 extracellular locating genes, GPRC5A and IMUP were the only two independent prognostic indicators of pancreatic cancer. Further, detailed information of IMUP and GPRC5A were analyzed including their physicochemical properties, their expression and variation ratio and their association with immune cells infiltration in cancer, as well as the probable signaling pathways of genes regulation on pancreatic cancer development. Lastly, local IHC experiment performed on PAAD tissue array which was produced with 62 local hospital patients samples confirmed that GPRC5A and IMUP were abnormally up-regulated in pancreatic cancer, which directly associated with worse patients both overall (OS) and recurrence free survival (RFS). Conclusions Using multiple bioinformatic analysis as well as local hospital samples validation, we revealed that GPRC5A and IMUP expression were abnormally up-regulated in pancreatic cancer which associated statistical significantly with patients survival, and the genes’ biological features and clinical significance were also explored. However, more detailed experiments and clinical trials are obligatory to support their further potential drug-target role in clinical medical treatment.

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Xiaotao Li ◽  
Shi Fu ◽  
Yinglong Huang ◽  
Ting Luan ◽  
Haifeng Wang ◽  

Abstract Background Bladder cancer (BC) is one of the most common malignancies and has a relatively poor outcome worldwide. In this study, we attempted to construct a novel metabolism-related gene (MRG) signature for predicting the survival probability of BC patients. Methods First, differentially expressed MRGs between BC and normal samples were identified and used to construct a protein-protein interaction (PPI) network and perform mutation analysis. Next, univariate Cox regression analysis was utilized to select prognostic genes, and multivariate Cox regression analysis was applied to establish an MRG signature for predicting the survival probability of BC patients. Moreover, Kaplan-Meier (KM) survival analysis and receiver operating characteristic (ROC) analysis were performed to evaluate the predictive capability of the MRG signature. Finally, a nomogram based on the MRG signature was established to better predict the survival of BC. Results In the present study, 27 differentially expressed MRGs were identified, most of which presented mutations in BC patients, and LRP1 showed the highest mutation rate. Next, an MRG signature, including MAOB, FASN and LRP1, was established by using univariate and multivariate Cox regression analysis. Furthermore, survival analysis indicated that BC patients in the high-risk group had a dramatically lower survival probability than those in the low-risk group. Finally, Cox regression analysis showed that the risk score was an independent prognostic factor, and a nomogram integrating age, pathological tumor stage and risk score was established and presented good predictive ability. Conclusion We successfully constructed a novel MRG signature to predict the prognosis of BC patients, which might contribute to the clinical treatment of BC.

2021 ◽  
Zhaoming Zhou ◽  
Mingyao Lai ◽  
Jiayin Yu ◽  
Jiangfen Zhou ◽  
Qingjun Hu ◽  

Abstract Background: Glioblastoma (GBM) is a common primary brain tumor with a high incidence in adults with malignant and fast-growing biological characteristics. In this study, we explore the immune-related prognosis markers of GBM at the mRNA level.Methods: The sequencing data and clinical information of GBM patients were downloaded from The Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA). The differentially expressed genes (DEGs) were calculated between normal tissues from the Genotype-Tissue Expression (GTEx) database and tumor tissues from TCGA and CGGA. We obtained immune genes from the ImmProt database. The intersection of DEGs and immune genes were defined as the immune-related differential genes (IR-DEGs), based on which, survival associated IR-DEGs were determined by multivariate Cox regression analysis. The survival risk score (SRS) was determined for each sample with the top 6 prognostic associated IR-DEGs. One-year, two-year, and three-year potential survival were predicted by the prognosis prediction model established by multivariate and univariate Cox regression. In addition, we performed CIBERSORT in GBM patients with samples from TCGA cohort; association analysis was performed with prognostic IR-DEGs and immune cells. Furthermore, the influence of prognostic IR-DEGs on the brain tumor microenvironment (TME) was validated in single-cell sequencing analysis.Results: We found 301 IR-DRGs in GBM primary tumor compared with normal tissue, and 19 of them could predict the overall survival (OS) more accurately in GBM patients. Six IR-DEGs (PLAUR, TNFSF14, CTSB, SOCS3, PTX3, and FCGR2B) were selected to construct the SRS, with which, GBM patients were divided into two different groups which combined with high and low risk. The SRS was found to be an independent prognostic factor for GBM and could predict GBM patients’ possible survival with an acceptable efficiency. Moreover, the expression of 6 IR-DEGs and their co-expressed IR-DEGs could influence TME and were associated with GBM prognosis.Conclusions: This study identified a potential immune prognostic signature of glioblastoma, which could enhance the prognosis prediction ability for GBM patients. The immune-related-genes in the TME could potentially benefit the immunotherapy development for GBM patients.

2021 ◽  
Yinan Hu ◽  
Jingyi Liu ◽  
Jiahao Yu ◽  
Fangfang Yang ◽  
Miao Zhang ◽  

Abstract Background: Hepatocellular carcinoma (HCC) is one of the most common malignancies worldwide. Costimulatory molecules have been proven to be the foundation of immunotherapy. However, the potential roles of costimulatory molecule genes (CMGs) in HCC remain unclear. Our study is aimed to develop a costimulatory molecule-related gene signature that could evaluate the prognosis of HCC patients.Methods: Based on The Cancer Gene Atlas (TCGA) database, univariate Cox regression analysis was applied in CMGs to identify prognosis-related CMGs. Consensus clustering analysis was performed to stratify HCC patients into different subtypes and compared them in OS. Subsequently, the LASSO Cox regression analysis was performed to construct the CMGs-related prognostic signature and Kaplan–Meier survival curves as well as ROC curve were used to validate the predictive capability. Then we explored the correlations of the risk signature with tumor-infiltrating immune cells, tumor mutation burden (TMB) and response to immunotherapy. The expression levels of prognosis-related CMGs were validated in HCC using qRT-PCR method.Results: All HCC patients were classified into two clusters based on 11 CMGs with prognosis values and cluster 2 correlated with a poorer prognosis. Next, a prognostic signature of six CMGs was constructed, which was an independent risk factor for HCC patients. Patients with low-risk score were associated with better prognosis. The correlation analysis showed that the risk signature could predict the infiltration of immune cells and immune status of the immune microenvironment in HCC. The qRT-PCR indicated six CMGs with significantly differential expression in HCC tissues and normal tissues.Conclusion: In conclusion, our CMGs-related risk signature could be used as a prediction tool in survival assessment and immunotherapy for HCC patients.

2021 ◽  
Siyu YAN ◽  
Wei-Xian Yang ◽  
Pei-Pei Lu ◽  
Xuan-Tong Guo ◽  
Cai-Xia Guo ◽  

Abstract Background Integrative Chinese and Western Medicine (ICWM) is widely used in coronary artery disease (CAD) patients after percutaneous coronary intervention (PCI) in China. However, the evidence-based on the long-term prognosis and large sample on this topic are weak. The purpose of this study is to evaluate the correlation between the therapeutic effect of ICWM and the prognosis of patients after PCI.Methods This study is a prospective observational real-world cohort study that was conducted from September 2016 to August 2019 in Fuwai Hospital. The study was reviewed and approved by the Ethics Review Committee of Fuwai Hospital, Chinese Academy of Medical Sciences. We consecutively screened 6000 patients after PCI and they were followed up for 2 years. ICWM were related to prognostic outcomes using unadjusted (Kaplan-Meier curves) and risk-adjusted (multivariable Cox regression) analyses. The primary endpoint was a composite of all-cause death, revascularization, and myocardial infarction.Results A total of 5942 patients after PCI were enrolled in this study, 5453 patients were included in the final analysis (4189[76.8%] were male; mean [SD] age, 61.91[9.91] years). There were 2932 patients (53.8%) in western medicine group (WMG) and 2521 patients (46.2%) in integrated medicine group (IMG). Cox regression analysis showed that IMG had a 27% lower cumulative risk of the major adverse cardiovascular event (MACE) than WMG (hazard ratio [HR], 0.73; 95% CI, 0.63-0.85; P<0.0001), especially in all-cause mortality and revascularization.Conclusions Among patients after PCI, ICWM compared with conventional western medicine was correlated with a lower risk of 2-year MACE. Further research is needed to provide higher levels of evidence.

2021 ◽  
Fangchao Zhao ◽  
Ren Niu ◽  
Yishuai Li ◽  
Zefang Dong ◽  
Xuebo Qin ◽  

Abstract Background: As the major type of esophageal cancer (ESCA), esophageal squamous cell carcinoma (ESCC) is also related to the highest malignant level and low survival rates across the world. Increasing people recognize long non-coding RNAs (lncRNAs) as significant mediators in regulating ferroptosis and iron-metabolism. Determining the prognostic value of ferroptosis and iron-metabolism related lncRNAs (FIRLs) in ESCC is thus critical. Methods: Pearson’s correlation analysis was carried out between ferroptosis and iron-metabolism-related genes (FIRGs) and all lncRNAs to derive the FIRLs. Based on weighted gene co-expression network exploration (WCGNA), least absolute shrinkage and selection operator (LASSO) regression and Cox regression analysis, a risk stratification system was established. According to Kaplan-Meier analysis, receiver operating characteristic (ROC) curve analysis, and univariate and multivariate Cox regression analyses, the predictive ability and clinical relevance of the risk stratification system were evaluated. The validity of the established prognostic signature was further examined in TCGA (training set) and GEO (validation set) cohorts. A nomogram with enhanced precision for forecasting OS was set up on basis of the independent prognostic elements. Gene Ontology (GO) term enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were applied for the identification of pathways in which FIRLs significantly enriched. we used cell culture, transfection, CCK-8, and qRT-PCR as in vitro assays. Results: An 3-FIRLs risk stratification system was developed by multivariate Cox regression analysis to divide patients into two risk groups. Patients in the high-risk group had worse prognosis than patients in the low-risk group. Multivariate Cox regression analysis showed the risk stratification system was an independent prognostic indicator. Receiver operating characteristic curve (ROC) analysis proved the predictive accuracy of the signature. The area under time-dependent ROC curve (AUC) reached 0.853 at 1 year, 0.802 at 2 years, 0.740 at 5 years in the training cohort and 0.712 at 1 year, 0.822 at 2 years, 0.883 at 5 years in the validation cohort. Functional enrichment analysis predicted potential associations of 49 possible upstream regulated FIRGs with ferroptosis and iron-metabolism processes and oncological signatures. Analysis of the immune cell infiltration landscape showed that ESCC in the high-risk group tended be immunologically “cold”. In vitro experiments suggested that LINC01068 promoted ESCC cell proliferation. Conclusion: The risk stratification system based on FIRLs could serve as a reliable tool for forecasting the survival of patients with ESCC.

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