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.

scholarly journals Identification of 4-genes model in papillary renal cell tumor microenvironment based on comprehensive analysis

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Liang Luo ◽  
Haiyi Zhou ◽  
Hao Su
Keyword(s):  
Gene Expression ◽  
Regression Analysis ◽  
Tumor Microenvironment ◽  
Renal Cell ◽  
Cox Regression ◽  
Ppi Network ◽  
Hub Genes ◽  
Cox Regression Analysis ◽  
Venn Diagrams ◽  
Kaplan Meier

Abstract Background The tumor microenvironment acts a pivotal part in the occurrence and development of tumor. However, there are few studies on the microenvironment of papillary renal cell carcinoma (PRCC). Our study aims to explore prognostic genes related to tumor microenvironment in PRCC. Methods PRCC expression profiles and clinical data were extracted from The Cancer Gene Atlas (TCGA) and Gene Expression Omnibus (GEO) database. Immune/stromal scores were performed utilizing the ESTIMATE algorithm. Three hundred fifty-seven samples were split into two groups on the basis of median immune/stromal score, and comparison of gene expression was conducted. Intersect genes were obtained by Venn diagrams. Hub genes were selected through protein-protein interaction (PPI) network construction, and relevant functional analysis was conducted by DAVID. We used Kaplan–Meier analysis to identify the correlations between genes and overall survival (OS) and progression-free survival (PFS). Univariate and multivariate cox regression analysis were employed to construct survival model. Cibersort was used to predict the immune cell composition of high and low risk group. Combined nomograms were built to predict PRCC prognosis. Immune properties of PRCC were validated by The Cancer Immunome Atlas (TCIA). Results We found immune/stromal score was correlated with T pathological stages and PRCC subtypes. Nine hundred eighty-nine differentially expressed genes (DEGs) and 1169 DEGs were identified respectively on the basis of immune and stromal score. Venn diagrams indicated that 763 co-upregulated genes and 4 co-downregulated genes were identified. Kaplan-Meier analysis revealed that 120 genes were involved in tumor prognosis. Then PPI network analysis identified 22 hub genes, and four of which were significantly related to OS in patients with PRCC confirmed by cox regression analysis. Finally, we constructed a prognostic nomogram which combined with influence factors. Conclusions Four tumor microenvironment-related genes (CD79A, CXCL13, IL6 and CCL19) were identified as biomarkers for PRCC prognosis.

scholarly journals The relationship between miR-219-5p Gene Polymorphisms and the prognosis of colorectal cancer

2020 ◽  
Author(s):  
Yang Yan ◽  
Xiaohui Du ◽  
Shaoyou Xia ◽  
Songyan Li ◽  
Da Teng ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Regression Analysis ◽  
Prognostic Value ◽  
Cox Regression ◽  
Malignant Tumors ◽  
Survival Rates ◽  
Tnm Staging ◽  
Cox Regression Analysis ◽  
Normal Tissues ◽  
Kaplan Meier

Abstract Background Colorectal cancer (CRC) is one of the most common malignant tumors, its morbidity and mortality are increasing year by year, it is a serious threat to people's health. Some studies have reported that miR-219-5p acts as a tumor suppressor in some malignant tumors. So the purpose of this study was to investigate the prognostic value of miR-219-5p expression in CRC patients. Methods QRT-PCR was used to detect the expression levels of miR-219-5p in CRC tissues and corresponding normal tissues (P < 0.001). The prognostic value of miR-219-5p in CRC was analyzed by Kaplan-Meier and Cox regression analysis. Results The results indicated that the expression of miR-219-5p was significantly lower in CRC tissues, and its expression was closely correlated with tumor differentiation, TNM staging and lymph node metastasis (all P < 0.05). Moreover, Kaplan Meier survival analysis showed that the patients with low expression of miR-219-5p had worse overall survival rates (P < 0.05). Cox regression analysis further demonstrated that miR-219-5p expression was an independent prognostic factor for survival time in CRC patients (P = 0.018, HR = 2.026 and 95%CI: 1.127–3.643). Conclusions All the results suggest that miR-219-5p expression can be used as a potential prognostic biomarker for CRC patients.

scholarly journals Determination of a six-gene prognostic model for cervical cancer based on WGCNA combined with LASSO and Cox-PH analysis

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Shiyan Li ◽  
Fengjuan Han ◽  
Na Qi ◽  
Liyang Wen ◽  
Jia Li ◽  
...  
Keyword(s):  
Cervical Cancer ◽  
Regression Analysis ◽  
Risk Model ◽  
Cox Regression ◽  
Hub Genes ◽  
Cox Regression Analysis ◽  
Kaplan Meier ◽  
Risk Curve ◽  
Modular Analysis ◽  
Upregulated Genes

Abstract Aim This study aimed to establish a risk model of hub genes to evaluate the prognosis of patients with cervical cancer. Methods Based on TCGA and GTEx databases, the differentially expressed genes (DEGs) were screened and then analyzed using GO and KEGG analyses. The weighted gene co-expression network (WGCNA) was then used to perform modular analysis of DEGs. Univariate Cox regression analysis combined with LASSO and Cox-pH was used to select the prognostic genes. Then, multivariate Cox regression analysis was used to screen the hub genes. The risk model was established based on hub genes and evaluated by risk curve, survival state, Kaplan-Meier curve, and receiver operating characteristic (ROC) curve. Results We screened 1265 DEGs between cervical cancer and normal samples, of which 620 were downregulated and 645 were upregulated. GO and KEGG analyses revealed that most of the upregulated genes were related to the metastasis of cancer cells, while the downregulated genes mostly acted on the cell cycle. Then, WGCNA mined six modules (red, blue, green, brown, yellow, and gray), and the brown module with the most DEGs and related to multiple cancers was selected for the follow-up study. Eight genes were identified by univariate Cox regression analysis combined with the LASSO Cox-pH model. Then, six hub genes (SLC25A5, ENO1, ANLN, RIBC2, PTTG1, and MCM5) were screened by multivariate Cox regression analysis, and SLC25A5, ANLN, RIBC2, and PTTG1 could be used as independent prognostic factors. Finally, we determined that the risk model established by the six hub genes was effective and stable. Conclusions This study supplies the prognostic value of the risk model and the new promising targets for the cervical cancer treatment, and their biological functions need to be further explored.

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 The Therapeutic Effect of Huo Xue Tong Luo Capsules in Association Research Circulation Osseous (ARCO) Stage II Osteonecrosis of the Femoral Head: A Clinical Study With an Average Follow-up Period of 7.95 Years

2021 ◽  
Vol 12 ◽  
Author(s):  
Xiao-Ming He ◽  
Min-Cong He ◽  
Peng Yang ◽  
Qing-Wen Zhang ◽  
Zhen-Qiu Chen ◽  
...  
Keyword(s):  
Clinical Trial ◽  
Regression Analysis ◽  
Femoral Head ◽  
Treatment Option ◽  
Cox Regression ◽  
Survival Rates ◽  
Stage Ii ◽  
Cox Regression Analysis ◽  
Femoral Head Collapse ◽  
Kaplan Meier

Background: Huo Xue Tong Luo (HXTL) capsules are an oral preparation that could relieve pain and ameliorate osteonecrosis in patients with asymptomatic osteonecrosis of femoral head (ONFH). We wanted to verify whether it could be a treatment option for ARCO stage II ONFH.Methods: A total of 44 patients (66 hips) with ARCO stage II ONFH were recruited from June 1996 to October 2013 (clinical trial registry number: ChiCTR-RPC-15006,290). HXTL capsules were given under a specific protocol, and the endpoint was set as femoral head collapse. The clinical indicators [including visual analog scale (VAS) and Harris Hip Score (HHS)] and radiological indicators [including Tonnis classification, ARCO stage, Japanese Investigation Committee (JIC) classification, lateral preserved angle (LPA), anterior preserved angle (APA), and combined preserved angle (CPA)] before and after treatment were compared. Kaplan–Meier survival analysis and Cox regression analysis were used to identify the risk factors associated with femoral head collapse.Result: Twenty-six males and 18 females with an average age of 38.3 ± 2.8 were followed for an average of 7.95 years. Forty-six of the 66 (69.7%) hips had no progression in pain or collapse, and patients exhibited a higher HHS (p &lt; 0.05) after therapy. Twenty of the 66 (30.3%) hips progressed in Tonnis classification and ARCO stage, but only one of the 66 (1.5%) hips required total hip arthroplasty (THA). The Kaplan–Meier survivorship curve suggested that the survival rates were 96.97% at 5 years, 69.15% at 10 years, and 40.33% at 15 years. Patients with type A necrotic lesions on anteroposterior (AP) and frog-leg lateral (FLL) radiographs revealed 100% survival rates. Multivariate Cox regression analysis revealed that patients with an LPA ≤ 60.9 exhibited a 3.87 times higher risk of collapse of the femoral head [95% confidence interval (CI), 1.241–5.673] than did those patients with an LPA&gt;60.9.Conclusion: HXTL capsules could be a treatment option for ARCO stage II ONFH, resulting in improved hip function and delayed progression to femoral head collapse, especially when the anterior and lateral portions of the femoral head were not affected. However, an LPA of less than 60.9° may be a risk factor for collapse of the femoral head.Clinical Trial Registration: [http://www.chictr.org.cn/showproj.aspx?projZ10829]

scholarly journals Identification of 4-Genes Model in Papillary Renal Cell Tumor Microenvironment Based on Comprehensive Analysis

2021 ◽  
Author(s):  
Liang Luo ◽  
Haiyi Zhou ◽  
Hao Su
Keyword(s):  
Regression Analysis ◽  
Tumor Microenvironment ◽  
Renal Cell ◽  
Cox Regression ◽  
Expression Profiles ◽  
Ppi Network ◽  
Hub Genes ◽  
Cox Regression Analysis ◽  
Venn Diagrams ◽  
Kaplan Meier

Abstract Background: The tumor microenvironment acts a pivotal part in the occurrence and development of tumor. However, there are few studies on the microenvironment of papillary renal cell carcinoma (PRCC). Our study aims to explore prognostic genes related to tumor microenvironment in PRCC. Methods: PRCC expression profiles and clinical data were extracted from The Cancer Gene Atlas (TCGA) database. Immune/stromal scores were performed utilizing the ESTIMATE algorithm. 323 samples were split into two groups on the basis of median immune/stromal score, and comparison of gene expression were conducted. Cross genes were obtained by Venn diagrams. Hub genes were selected through protein-protein interaction (PPI) network construction, and relevant functional analysis was conducted by DAVID. We used Kaplan–Meier analysis to identify the correlations between genes and overall survival (OS). Finally, univariate and multivariate cox regression analysis were employed to construct survival model and predict prognosis. Results: We found immune/stromal score was correlated with T pathological grade and PRCC subtypes. 989 differentially expressed genes (DEGs) and 1169 DEGs were identified respectively on the basis of immune and stromal score. Venn diagrams indicated that 763 co-upregulated genes and 4 co-downregulated genes were identified. Kaplan-Meier analysis revealed that 120 genes were involved in tumor prognosis. Then PPI network analysis identified 22 hub genes, and four of which were significantly related to OS in patients with PRCC confirmed by cox regression analysis. Conclusions: Four tumor microenvironment-related genes (CD79A, CXCL13, IL6 and CCL19) were identified as biomarkers for PRCC prognosis.

Predictive Value of Atrial Electromechanical Delay on Long-Term Cardiovascular Outcomes in Hemodialysis Patients

2015 ◽  
Vol 42 (3) ◽  
pp. 239-249 ◽  
Author(s):  
Kultigin Turkmen ◽  
Levent Demirtas ◽  
Ergun Topal ◽  
Abduzhappar Gaipov ◽  
Ismail Kocyigit ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Total Cholesterol ◽  
Cox Regression ◽  
Healthy Individuals ◽  
Electromechanical Delay ◽  
Cox Regression Analysis ◽  
Atrial Electromechanical Delay ◽  
Kaplan Meier ◽  
All Cause Mortality ◽  
Spearman Test

Background: Atrial electromechanical delay (AEMD) times were considered independent predictors of cardiovascular morbidity among the general population. We aimed at evaluating AEMD times and other risk factors associated with 2-year combined cardiovascular (CV) events in HD patients. Material and Methods: Sixty hemodialysis (HD) and 44 healthy individuals were enrolled in this prospective study. Echocardiography was performed before the mid-week dialysis session for HD patients. Data were expressed as mean ± SD. Spearman test was used to assess linear associations. Survival was examined with the Kaplan-Meier method. Multivariate Cox regression analysis was used to determine the predictors of combined CV events in this cohort. Results: At the beginning of the study, left intra-atrial-AEMD times were significantly longer in HD patients compared to the left intra-atrial-AEMD times in healthy individuals. After 24 months, 41 patients were still on HD treatment and 19 (31.6%) had died. Serum triglyceride, total cholesterol and albumin were found to be higher and C-reactive protein (CRP) levels, left intra-atrial EMD time (LIAT) and interatrial EMD times were found to be lower in survived HD patients. With the cut-off median values of 3.5 g/dl for albumin, 0.87 mg/dl for CRP, 157 mg/dl for total cholesterol and 151 mg/dl for triglyceride, the Kaplan-Meier curves demonstrated significant differences in terms of all-cause mortality. We also demonstrated the Kaplan-Meier survival curves of HD patients according to tertile values of LIAT. Cox regression analysis revealed that increased CRP and higher LIAT were found to be independent predictors of combined CV events. Conclusions: Increased LIAT and inflammation were found to be closely associated with 2 years combined CV events and all-cause mortality in HD patients.

scholarly journals Association of masseter area and radiodensity with three-month survival after proximal anterior circulation occlusion

2020 ◽  
Vol 13 (1) ◽  
pp. 25-29 ◽  
Author(s):  
Iisa Lindström ◽  
Sara Protto ◽  
Niina Khan ◽  
Jussi Hernesniemi ◽  
Niko Sillanpää ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Ischemic Stroke ◽  
Acute Ischemic Stroke ◽  
Cox Regression ◽  
Multivariable Logistic Regression Analysis ◽  
Anterior Circulation ◽  
Term Survival ◽  
Cox Regression Analysis ◽  
Kaplan Meier

BackgroundMasseter area (MA), a surrogate for sarcopenia, appears to be useful when estimating postoperative survival, but there is lack of consensus regarding the potential predictive value of sarcopenia in acute ischemic stroke (AIS) patients. We hypothesized that MA and density (MD) evaluated from pre-interventional CT angiography scans predict postinterventional survival in patients undergoing mechanical thrombectomy (MT).Materials and methods312 patients treated with MT for acute occlusions of the internal carotid artery (ICA) or the M1 segment of the middle cerebral artery (M1-MCA) between 2013 and 2018. Median follow-up was 27.4 months (range 0–70.4). Binary logistic (alive at 3 months, OR <1) and Cox regression analyses were used to study the effect of MA and MD averages (MAavg and MDavg) on survival.ResultsIn Kaplan–Meier analysis, there was a significant inverse relationship with both MDavg and MAavg and mortality (MDavg P<0.001, MAavg P=0.002). Long-term mortality was 19.6% (n=61) and 3-month mortality 12.2% (n=38). In multivariable logistic regression analysis at 3 months, per 1-SD increase MDavg (OR 0.61, 95% CI 0.41 to 0.92, P=0.018:) and MAavg (OR 0.57, 95% CI 0.35 to 0.91, P=0.019) were the independent predictors associated with lower mortality. In Cox regression analysis, MDavg and MAavg were not associated with long-term survival.ConclusionsIn acute ischemic stroke patients, MDavg and MAavg are independent predictors of 3-month survival after MT of the ICA or M1-MCA. A 1-SD increase in MDavg and MAavg was associated with a 39%–43% decrease in the probability of death during the first 3 months after MT.

Prognostic value of D-dimer/fibrinogen ratio in the adverse outcomes of patients hospitalized for heart failure

2020 ◽  
Vol 14 (18) ◽  
pp. 1733-1745
Author(s):  
Tian-Jun Zhao ◽  
Qian-Kun Yang ◽  
Chun-Yu Tan ◽  
Li-Dan Bi ◽  
Jie Li ◽  
...  
Keyword(s):  
Heart Failure ◽  
Regression Analysis ◽  
Cox Regression ◽  
Prognostic Indicator ◽  
Adverse Outcomes ◽  
Rank Test ◽  
Clinical Value ◽  
Cox Regression Analysis ◽  
Kaplan Meier ◽  
D Dimer

Aim: To evaluate the clinical value of plasma D-dimer/fibrinogen ratio (DFR) in patients hospitalized for heart failure (HF). Methods: Clinical data of 235 patients were retrospectively analyzed. Kaplan–Meier method and Cox regression analysis were used to identify significant prognosticators. Results: The Kaplan–Meier analysis showed that a higher DFR level was significantly associated with an increase in the end point outcomes, including HF readmission, thrombotic events and death (log-rank test: p < 0.001). The multivariate Cox regression analysis showed that the high tertile of DFR was significantly associated with the study end points (HR: 2.18; 95% CI: 1.31–3.62; p = 0.003), compared with the low tertile. Conclusion: DFR is a reliable prognostic indicator for patients hospitalized for HF.

Comparison of 24-hour and Office Pulse Wave Velocity for Prediction of Mortality in Hemodialysis Patients

2019 ◽  
Vol 49 (4) ◽  
pp. 317-327 ◽  
Author(s):  
Julia Matschkal ◽  
Christopher C. Mayer ◽  
Pantelis A. Sarafidis ◽  
Georg Lorenz ◽  
Matthias C. Braunisch ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Pulse Wave Velocity ◽  
Wave Velocity ◽  
Cardiovascular Mortality ◽  
Pulse Wave ◽  
Cox Regression ◽  
Hemodialysis Patients ◽  
Cox Regression Analysis ◽  
Kaplan Meier ◽  
All Cause Mortality

Background: Mortality in hemodialysis patients still remains unacceptably high. Enhanced arterial stiffness is a known cardiovascular risk factor, and pulse wave velocity (PWV) has proven to be a valid parameter to quantify risk. Recent studies showed controversial results regarding the prognostic significance of PWV for mortality in hemodialysis patients, which may be due to methodological issues, such as assessment of PWV in the office setting (Office-PWV). Method: This study cohort contains patients from the “Risk stratification in end-stage renal disease – the ISAR study,” a multicenter prospective longitudinal observatory cohort study. We examined and compared the predictive value of ambulatory 24-hour PWV (24 h-PWV) and Office-PWV on mortality in a total of 344 hemodialysis patients. The endpoints of the study were all-cause and cardiovascular mortality. Survival analysis included Kaplan-Meier estimates and Cox regression analysis. Results: During a follow-up of 36 months, a total of 89 patients died, 35 patients due to cardiovascular cause. Kaplan-Meier estimates for tertiles of 24 h-PWV and Office-PWV were similarly associated with mortality. In univariate Cox regression analysis, 24 h-PWV and Office-PWV were equivalent predictors for all-cause and cardiovascular mortality. After adjustment for common risk factors, only 24 h-PWV remained solely predictive for all-cause mortality (hazard ratio 2.51 [95% CI 1.31–4.81]; p = 0.004). Conclusions: Comparing both measurements, 24 h-PWV is an independent predictor for all-cause-mortality in hemodialysis patients beyond Office-PWV.

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