Development of a Gene Risk Signature for Patients of Pancreatic Cancer

Background. Pancreatic cancer is a highly malignant solid tumor with a high lethality rate, but there is a lack of clinical biomarkers that can assess patient prognosis to optimize treatment. Methods. Gene-expression datasets of pancreatic cancer tissues and normal pancreatic tissues were obtained from the GEO database, and differentially expressed genes analysis and WGCNA analysis were performed after merging and normalizing the datasets. Univariate Cox regression analysis and Lasso Cox regression analysis were used to screen the prognosis-related genes in the modules with the strongest association with pancreatic cancer and construct risk signatures. The performance of the risk signature was subsequently validated by Kaplan–Meier curves, receiver operating characteristic (ROC), and univariate and multivariate Cox analyses. Result. A three-gene risk signature containing CDKN2A, BRCA1, and UBL3 was established. Based on KM curves, ROC curves, and univariate and multivariate Cox regression analyses in the TRAIN cohort and TEST cohort, it was suggested that the three-gene risk signature had better performance in predicting overall survival. Conclusion. This study identifies a three-gene risk signature, constructs a nomogram that can be used to predict pancreatic cancer prognosis, and identifies pathways that may be associated with pancreatic cancer prognosis.

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The Investigation of Associations between TP53 rs1042522, BBC3 rs2032809, CCND1 rs9344, EGFR rs2227983 Polymorphisms and Breast Cancer Phenotype and Prognosis

Diagnostics ◽

10.3390/diagnostics11081419 ◽

2021 ◽

Vol 11 (8) ◽

pp. 1419

Author(s):

Justina Bekampytė ◽

Agnė Bartnykaitė ◽

Aistė Savukaitytė ◽

Rasa Ugenskienė ◽

Erika Korobeinikova ◽

...

Keyword(s):

Breast Cancer ◽

Regression Analysis ◽

Cox Regression ◽

Cancer Prognosis ◽

Nucleotide Polymorphisms ◽

Single Nucleotide ◽

Cox Regression Analysis ◽

Pcr Rflp ◽

Oncological Diseases ◽

Cancer Phenotype

Breast cancer is one of the most common oncological diseases among women worldwide. Cell cycle and apoptosis—related genes TP53, BBC3, CCND1 and EGFR play an important role in the pathogenesis of breast cancer. However, the roles of single nucleotide polymorphisms (SNPs) in these genes have not been fully defined. Therefore, this study aimed to analyze the association between TP53 rs1042522, BBC3 rs2032809, CCND1 rs9344 and EGFR rs2227983 polymorphisms and breast cancer phenotype and prognosis. For the purpose of the analysis, 171 Lithuanian women were enrolled. Genomic DNA was extracted from peripheral blood; PCR-RFLP was used for SNPs analysis. The results showed that BBC3 rs2032809 was associated with age at the time of diagnosis, disease progression, metastasis and death. CCND1 rs9344 was associated with tumor size, however an association resulted in loss of significance after Bonferroni correction. In survival analysis, significant associations were observed between BBC3 rs2032809 and OS, PFS and MFS. EGFR rs2227983 also showed some associations with OS and PFS (univariate Cox regression analysis). However, the results were in loss of significance (multivariate Cox regression analysis). In conclusion, BBC3 rs2032809 polymorphism was associated with breast cancer phenotype and prognosis. Therefore, it could be applied as potential markers for breast cancer prognosis.

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Bioinformatics-Based Identification of Tumor Microenvironment-Related Prognostic Genes in Pancreatic Cancer

Frontiers in Genetics ◽

10.3389/fgene.2021.632803 ◽

2021 ◽

Vol 12 ◽

Author(s):

Shaojie Chen ◽

Feifei Huang ◽

Shangxiang Chen ◽

Yinting Chen ◽

Jiajia Li ◽

...

Keyword(s):

Pancreatic Cancer ◽

Overall Survival ◽

Regression Analysis ◽

Tumor Microenvironment ◽

Operating Characteristic ◽

Cox Regression ◽

Time Dependent ◽

Concordance Index ◽

Cox Regression Analysis ◽

Score Model

ObjectiveGrowing evidence has highlighted that the immune and stromal cells that infiltrate in pancreatic cancer microenvironment significantly influence tumor progression. However, reliable microenvironment-related prognostic gene signatures are yet to be established. The present study aimed to elucidate tumor microenvironment-related prognostic genes in pancreatic cancer.MethodsWe applied the ESTIMATE algorithm to categorize patients with pancreatic cancer from TCGA dataset into high and low immune/stromal score groups and determined their differentially expressed genes. Then, univariate and LASSO Cox regression was performed to identify overall survival-related differentially expressed genes (DEGs). And multivariate Cox regression analysis was used to screen independent prognostic genes and construct a risk score model. Finally, the performance of the risk score model was evaluated by Kaplan-Meier curve, time-dependent receiver operating characteristic and Harrell’s concordance index.ResultsThe overall survival analysis demonstrated that high immune/stromal score groups were closely associated with poor prognosis. The multivariate Cox regression analysis indicated that the signatures of four genes, including TRPC7, CXCL10, CUX2, and COL2A1, were independent prognostic factors. Subsequently, the risk prediction model constructed by those genes was superior to AJCC staging as evaluated by time-dependent receiver operating characteristic and Harrell’s concordance index, and both KRAS and TP53 mutations were closely associated with high risk scores. In addition, CXCL10 was predominantly expressed by tumor associated macrophages and its receptor CXCR3 was highly expressed in T cells at the single-cell level.ConclusionsThis study comprehensively investigated the tumor microenvironment and verified immune/stromal-related biomarkers for pancreatic cancer.

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

Journal of Oncology ◽

10.1155/2021/6646459 ◽

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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Identification of Epithelial–Mesenchymal Transition-Related Prognostic lncRNAs Biomarkers Associated With Melanoma Microenvironment

Frontiers in Cell and Developmental Biology ◽

10.3389/fcell.2021.679133 ◽

2021 ◽

Vol 9 ◽

Author(s):

Bo Xiao ◽

Liyan Liu ◽

Zhuoyuan Chen ◽

Aoyu Li ◽

Pingxiao Wang ◽

...

Keyword(s):

Cox Regression ◽

Epithelial Mesenchymal Transition ◽

Enrichment Analysis ◽

Roc Curves ◽

Risk Groups ◽

Gene Set Enrichment Analysis ◽

Gene Set Enrichment ◽

Mesenchymal Transition ◽

Cox Regression Analysis ◽

Kaplan Meier

Melanoma is the most common cancer of the skin, associated with a worse prognosis and distant metastasis. Epithelial–mesenchymal transition (EMT) is a reversible cellular biological process that plays significant roles in diverse tumor functions, and it is modulated by specific genes and transcription factors. The relevance of EMT-related lncRNAs in melanoma has not been determined. Therefore, RNA expression data and clinical features were collected from the TCGA database (N = 447). Melanoma samples were randomly assigned into the training (315) and testing sets (132). An EMT-related lncRNA signature was constructed via comprehensive analyses of lncRNA expression level and corresponding clinical data. The Kaplan-Meier analysis showed significant differences in overall survival in patients with melanoma in the low and high-risk groups in two sets. Receiver operating characteristic (ROC) curves were used to measure the performance of the model. Cox regression analysis indicated that the risk score was an independent prognostic factor in two sets. Besides, a nomogram was constructed based on the independent variables. Gene Set Enrichment Analysis (GSEA) was applied to evaluate the potential biological functions in the two risk groups. Furthermore, the melanoma microenvironment was evaluated using ESTIMATE and CIBERSORT algorithms in the risk groups. This study indicates that EMT-related lncRNAs can function as potential independent prognostic biomarkers for melanoma survival.

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Identification of a Novel Gene Model-Based Homologous Recombination Deficiency Score to Improve Survival Prediction of TNBC.

10.21203/rs.3.rs-472194/v1 ◽

2021 ◽

Author(s):

Wenxiang Zhang ◽

Bolun Ai ◽

Xiangyi Kong ◽

Xiangyu Wang ◽

Jie Zhai ◽

...

Keyword(s):

Breast Cancer ◽

Gene Expression ◽

Homologous Recombination ◽

Risk Score ◽

Cox Regression ◽

Roc Curves ◽

Cox Regression Analysis ◽

Homologous Recombination Deficiency ◽

Ajcc Stage ◽

Kaplan Meier

Abstract Background Triple-negative breast cancer (TNBC) is a specific histological type of breast cancer with a poor prognosis, early recurrence, which lacks durable chemotherapy responses and effective targeted therapies. We aimed to construct an accurate prognostic risk model based on homologous recombination deficiency (HRD) - gene expression profiles for improving prognosis prediction of TNBC. Methods Triple-negative breast cancer RNA sequencing data and sample clinical information were downloaded from the breast invasive carcinoma (BRCA) cohort in the Cancer Genome Atlas (TCGA) database. Combined with the HRD database, tumor samples were divided into two sets. We screened differentially expressed genes (DEGs) and then identified HRD-related prognostic genes using weighted gene co-expression network analysis (WGCNA) and Cox regression analysis. The least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analysis were used to identifying key prognostic genes. Risk scores were calculated and compared with HRD score, Kaplan–Meier (KM) survival analysis were used to assess its prognostic power. GSE103091 dataset from GEO (Gene Expression Omnibus) database was used to validate the signature. Univariate and multivariate Cox regression were performed to independently verify the prognosis of the risk score. A nomogram was constructed and revealed by time-dependent ROC curves to guide clinical practice. Results We found that HRD tumor samples (HRD score > = 42) in TNBC patients were associated with poor overall survival (p = 0.027). We identified a total of 147 differential genes including 203 up-regulated and 213 down-regulated genes, among which 29 were prognosis-related genes. Through the LASSO method, 6 key prognostic genes ((MUCL1, IVL, FAM46C, CHI3L1, PRR15L, and CLEC3A) were selected and a 6-gene risk score was constructed. We found risk score was negatively associated with homologous recombination deficiency (HRD) scores (r = -0.22, p = 0.019). Compared with the low-risk group, Kaplan-Meier survival analysis shows that the high-risk group has an obvious poorer prognosis (P < 0.0001). Finally, we integrated the risk score model and clinical factors of TNBC (AJCC-stage, HRD score, T stage, and N stage) to construct a compound nomogram. Time-dependent ROC curves showed the risk score performed better in 1-, 3- and 5-year survival predictions compared with AJCC-stage. Conclusions Based on HRD gene expression data, our six HRD-related gene signature and nomogram could be practical and reliable tools for predicting OS in patients with TNBC.

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

American Journal of Nephrology ◽

10.1159/000441099 ◽

2015 ◽

Vol 42 (3) ◽

pp. 239-249 ◽

Cited By ~ 2

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.

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Favorable 90-Day Mortality in Obese Caucasian Patients with Septic Shock According to the Sepsis-3 Definition

Journal of Clinical Medicine ◽

10.3390/jcm9010046 ◽

2019 ◽

Vol 9 (1) ◽

pp. 46 ◽

Cited By ~ 1

Author(s):

Caspar Mewes ◽

Carolin Böhnke ◽

Tessa Alexander ◽

Benedikt Büttner ◽

José Hinz ◽

...

Keyword(s):

Septic Shock ◽

Protective Effect ◽

Cox Regression ◽

Obese Patients ◽

Cox Regression Analysis ◽

Kaplan Meier ◽

Threatening Condition ◽

Life Threatening ◽

Caucasian Patients ◽

Patient Prognosis

Septic shock is a frequent life-threatening condition and a leading cause of mortality in intensive care units (ICUs). Previous investigations have reported a potentially protective effect of obesity in septic shock patients. However, prior results have been inconsistent, focused on short-term in-hospital mortality and inadequately adjusted for confounders, and they have rarely applied the currently valid Sepsis-3 definition criteria for septic shock. This investigation examined the effect of obesity on 90-day mortality in patients with septic shock selected from a prospectively enrolled cohort of septic patients. A total of 352 patients who met the Sepsis-3 criteria for septic shock were enrolled in this study. Body-mass index (BMI) was used to divide the cohort into 24% obese (BMI ≥ 30 kg/m2) and 76% non-obese (BMI < 30 kg/m2) patients. Kaplan-Meier survival analysis revealed a significantly lower 90-day mortality (31% vs. 43%; p = 0.0436) in obese patients compared to non-obese patients. Additional analyses of baseline characteristics, disease severity, and microbiological findings outlined further statistically significant differences among the groups. Multivariate Cox regression analysis estimated a significant protective effect of obesity on 90-day mortality after adjustment for confounders. An understanding of the underlying physiologic mechanisms may improve therapeutic strategies and patient prognosis.

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

Journal of NeuroInterventional Surgery ◽

10.1136/neurintsurg-2020-015837 ◽

2020 ◽

Vol 13 (1) ◽

pp. 25-29 ◽

Cited By ~ 1

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.

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

Biomarkers in Medicine ◽

10.2217/bmm-2020-0553 ◽

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.

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

American Journal of Nephrology ◽

10.1159/000499532 ◽

2019 ◽

Vol 49 (4) ◽

pp. 317-327 ◽

Cited By ~ 10

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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