Prognostic scoring system for osteosarcoma using network‐regularized high‐dimensional Cox‐regression analysis and potential therapeutic targets

2019 ◽  
Vol 234 (8) ◽  
pp. 13851-13857 ◽  
Author(s):  
Tae Sik Goh ◽  
Jung Sub Lee ◽  
Jeung Il Kim ◽  
Yong Geon Park ◽  
Kyoungjune Pak ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Scoring System ◽  
Cox Regression ◽  
Therapeutic Targets ◽  
High Dimensional ◽  
Cox Regression Analysis

scholarly journals Screening Prognosis-Related lncRNAs Based on WGCNA to Establish a New Risk Score for Predicting Prognosis in Patients with Hepatocellular Carcinoma

2021 ◽  
Vol 2021 ◽  
pp. 1-20
Author(s):  
Xueliang Zhou ◽  
Mengmeng Dou ◽  
Zaoqu Liu ◽  
Dechao Jiao ◽  
Zhaonan Li ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Regression Analysis ◽  
Scoring System ◽  
Normal Tissue ◽  
Cox Regression ◽  
Cox Regression Analysis ◽  
Cerna Network ◽  
Kaplan Meier ◽  
Risk Scoring ◽  
Risk Scoring System

Background. Hepatocellular carcinoma (HCC) remains an important cause of cancer death. The molecular mechanism of hepatocarcinogenesis and prognostic factors of HCC have not been completely uncovered. Methods. In this study, we screened out differentially expressed lncRNAs (DE lncRNAs), miRNAs (DE miRNAs), and mRNAs (DE mRNAs) by comparing the gene expression of HCC and normal tissue in The Cancer Genome Atlas (TCGA) database. DE mRNAs were used to perform Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Then, the miRNA and lncRNA/mRNA modules that were most closely related to the survival time of patients with HCC were screened to construct a competitive endogenous RNA (ceRNA) network by weighted gene coexpression network analysis (WGCNA). Moreover, univariable Cox regression and Kaplan-Meier curve analyses of DE lncRNAs and DE mRNAs were conducted. Finally, the lasso-penalized Cox regression analysis and nomogram model were used to establish a new risk scoring system and predict the prognosis of patients with liver cancer. The expression of survival-related DE lncRNAs was verified by qRT-PCR. Results. A total of 1896 DEmRNAs, 330 DElncRNAs, and 76 DEmiRNAs were identified in HCC and normal tissue samples. Then, the turquoise miRNA and turquoise lncRNA/mRNA modules that were most closely related to the survival time of patients with HCC were screened to construct a ceRNA network by WGCNA. In this ceRNA network, there were 566 lncRNA-miRNA-mRNA regulatory pairs, including 30 upregulated lncRNAs, 16 downregulated miRNAs, and 75 upregulated mRNAs. Moreover, we screened out 19 lncRNAs and 14 hub mRNAs related to prognosis from this ceRNA network by univariable Cox regression and Kaplan-Meier curve analyses. Finally, a new risk scoring system was established by selecting the optimal risk lncRNAs from the 19 prognosis-related lncRNAs through lasso-penalized Cox regression analysis. In addition, we established a nomogram model consisting of independent prognostic factors to predict the survival rate of HCC patients. Finally, the correlation between the risk score and immune cell infiltration and gene set enrichment analysis were determined. Conclusions. In conclusion, the results may provide potential biomarkers or therapeutic targets for HCC and the establishment of the new risk scoring system and nomogram model provides the new perspective for predicting the prognosis of HCC.

scholarly journals Screening prognosis-related lncRNAs based on WGCNA to establish a new risk score for predicting prognosis in patients with hepatocellular carcinoma

2020 ◽  
Author(s):  
Xueliang Zhou ◽  
Mengmeng Dou ◽  
Zaoqu Liu ◽  
Dechao Jiao ◽  
Zhaonan Li ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Regression Analysis ◽  
Scoring System ◽  
Normal Tissue ◽  
Cox Regression ◽  
Cox Regression Analysis ◽  
Cerna Network ◽  
Kaplan Meier ◽  
Risk Scoring ◽  
Risk Scoring System

Abstract Background: Hepatocellular carcinoma (HCC) remains an important cause of cancer death. The molecular mechanism of hepatocarcinogenesis and prognostic factors of HCC have not been completely uncovered. Methods: In this study, we screened out differentially expressed lncRNAs (DE lncRNAs), miRNAs (DE miRNAs), and mRNAs (DE mRNAs) by comparing the gene expression of HCC and normal tissue in the The Cancer Genome Atlas (TCGA) database. DE mRNAs were used to perform gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Then, the miRNA and lncRNA/mRNA modules that were most closely related to the survival time of patients with HCC were screened to construct a competitive endogenous RNA (ceRNA) network by weighted gene coexpression network analysis (WGCNA). Moreover, univariable Cox regression and Kaplan-Meier curve analyses of DE lncRNAs and DE mRNAs were conducted. Finally, the lasso‐penalized Cox regression analysis and nomogram model were used to establish new risk scoring system and predict the prognosis of patients with liver cancer. Results: A total of 1896 DEmRNAs, 330 DElncRNAs, and 76 DEmiRNAs were identified in HCC and normal tissue samples. Then, the turquoise miRNA and turquoise lncRNA/mRNA modules that were most closely related to the survival time of patients with HCC were screened to construct a ceRNA network by WGCNA. In this ceRNA network, there were 566 lncRNA-miRNA-mRNA regulatory pairs, including 30 upregulated lncRNAs, 16 downregulated miRNAs and 75 upregulated mRNAs. Moreover, we screened out 19 lncRNAs and 14 hub mRNAs related to prognosis from this ceRNA network by univariable Cox regression and Kaplan-Meier curve analyses. Finally, a new risk scoring system was established by selecting the optimal risk lncRNAs from the 19 prognosis-related lncRNAs through lasso‐penalized Cox regression analysis. In addition, we established a nomogram model consisting of independent prognostic factors to predict the survival rate of HCC patients. Conclusions: In conclusion, the results may provide potential biomarkers or therapeutic targets for HCC, and the establishment of new risk scoring system and nomogram model provide the new perspective for predicting the prognosis of HCC.

Red Blood Cell Indices in Relation to Post-stroke Psychiatric Disorders: A Longitudinal Study in a Follow-up Stroke Clinic

2020 ◽  
Vol 17 (3) ◽  
pp. 218-223
Author(s):  
Haichao Wang ◽  
Li Gong ◽  
Xiaomei Xia ◽  
Qiong Dong ◽  
Aiping Jin ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Ischemic Stroke ◽  
Blood Cell ◽  
Cox Regression ◽  
Depression And Anxiety ◽  
Cox Regression Analysis ◽  
Post Stroke ◽  
Rbc Indices ◽  
Post Stroke Depression

Background: Depression and anxiety after stroke are common conditions that are likely to be neglected. Abnormal red blood cell (RBC) indices may be associated with neuropsychiatric disorders. However, the association of RBC indices with post-stroke depression (PSD) and poststroke anxiety (PSA) has not been sufficiently investigated. Methods: We aimed to investigate the trajectory of post-stroke depression and anxiety in our follow- up stroke clinic at 1, 3, and 6 months, and the association of RBC indices with these. One hundred and sixty-two patients with a new diagnosis of ischemic stroke were followed up at 1, 3, and 6 months, and underwent Patient Health Questionnaire-9 (PHQ-9) and the general anxiety disorder 7-item (GAD-7) questionnaire for evaluation of depression and anxiety, respectively. First, we used Kaplan-Meier analysis to investigate the accumulated incidences of post-stroke depression and post-stroke anxiety. Next, to explore the association of RBC indices with psychiatric disorders after an ischemic stroke attack, we adjusted for demographic and vascular risk factors using multivariate Cox regression analysis. Results: Of the 162 patients with new-onset of ischemic stroke, we found the accumulated incidence rates of PSD (1.2%, 17.9%, and 35.8%) and PSA (1.2%, 13.6%, and 15.4%) at 1, 3, and 6 months, respectively. The incident PSD and PSA increased 3 months after a stroke attack. Multivariate Cox regression analysis indicated independent positive associations between PSD risk and higher mean corpuscular volume (MCV) (OR=1.42, 95% CI=1.16-1.76), older age (OR=2.63, 95% CI=1.16-5.93), and a negative relationship between male sex (OR=0.95, 95% CI=0.91-0.99) and PSA. Conclusion: The risks of PSD and PSA increased substantially 3 months beyond stroke onset. Of the RBC indices, higher MCV, showed an independent positive association with PSD.

scholarly journals Identification and development of an independent immune-related genes prognostic model for breast cancer

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Lin Chen ◽  
Yuxiang Dong ◽  
Yitong Pan ◽  
Yuhan Zhang ◽  
Ping Liu ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Regression Analysis ◽  
Cox Regression ◽  
Gene Set Enrichment Analysis ◽  
Risk Scores ◽  
Validation Dataset ◽  
Immune Gene ◽  
Cox Regression Analysis ◽  
Immune Genes ◽  
Immune Related Genes

Abstract Background Breast cancer is one of the main malignant tumors that threaten the lives of women, which has received more and more clinical attention worldwide. There are increasing evidences showing that the immune micro-environment of breast cancer (BC) seriously affects the clinical outcome. This study aims to explore the role of tumor immune genes in the prognosis of BC patients and construct an immune-related genes prognostic index. Methods The list of 2498 immune genes was obtained from ImmPort database. In addition, gene expression data and clinical characteristics data of BC patients were also obtained from the TCGA database. The prognostic correlation of the differential genes was analyzed through Survival package. Cox regression analysis was performed to analyze the prognostic effect of immune genes. According to the regression coefficients of prognostic immune genes in regression analysis, an immune risk scores model was established. Gene set enrichment analysis (GSEA) was performed to probe the biological correlation of immune gene scores. P < 0.05 was considered to be statistically significant. Results In total, 556 immune genes were differentially expressed between normal tissues and BC tissues (p < 0. 05). According to the univariate cox regression analysis, a total of 66 immune genes were statistically significant for survival risk, of which 30 were associated with overall survival (P < 0.05). Finally, a 15 immune genes risk scores model was established. All patients were divided into high- and low-groups. KM survival analysis revealed that high immune risk scores represented worse survival (p < 0.001). ROC curve indicated that the immune genes risk scores model had a good reliability in predicting prognosis (5-year OS, AUC = 0.752). The established risk model showed splendid AUC value in the validation dataset (3-year over survival (OS) AUC = 0.685, 5-year OS AUC = 0.717, P = 0.00048). Moreover, the immune risk signature was proved to be an independent prognostic factor for BC patients. Finally, it was found that 15 immune genes and risk scores had significant clinical correlations, and were involved in a variety of carcinogenic pathways. Conclusion In conclusion, our study provides a new perspective for the expression of immune genes in BC. The constructed model has potential value for the prognostic prediction of BC patients and may provide some references for the clinical precision immunotherapy of patients.

scholarly journals The Role of Hydraulic Silicate Cements on Long-Term Properties and Biocompatibility of Partial Pulpotomy in Permanent Teeth

Materials ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 305
Author(s):  
Chung-Min Kang ◽  
Saemi Seong ◽  
Je Seon Song ◽  
Yooseok Shin
Keyword(s):  
Regression Analysis ◽  
Cox Regression ◽  
Antimicrobial Properties ◽  
Permanent Teeth ◽  
Success Rates ◽  
Pulp Tissue ◽  
Cox Regression Analysis ◽  
Clinical Variables

The use of hydraulic silicate cements (HSCs) for vital pulp therapy has been found to release calcium and hydroxyl ions promoting pulp tissue healing and mineralized tissue formation. The present study investigated whether HSCs such as mineral trioxide aggregate (MTA) affect their biological and antimicrobial properties when used as long-term pulp protection materials. The effect of variables on treatment outcomes of three HSCs (ProRoot MTA, OrthoMTA, and RetroMTA) was evaluated clinically and radiographically over a 48–78 month follow-up period. Survival analysis was performed using Kaplan–Meier survival curves. Fisher’s exact test and Cox regression analysis were used to determine hazard ratios of clinical variables. The overall success rate of MTA partial pulpotomy was 89.3%; Cumulative success rates of the three HSCs were not statistically different when analyzed by Cox proportional hazard regression analysis. None of the investigated clinical variables affected success rates significantly. These HSCs showed favorable biocompatibility and antimicrobial properties in partial pulpotomy of permanent teeth in long-term follow-up, with no statistical differences between clinical factors.

scholarly journals The prognostic and diagnostic significance of the neutrophil-to-lymphocyte ratio in hepatocellular carcinoma: a prospective controlled study

2021 ◽  
Author(s):  
Philip J. Johnson ◽  
Sofi Dhanaraj ◽  
Sarah Berhane ◽  
Laura Bonnett ◽  
Yuk Ting Ma
Keyword(s):  
Hepatocellular Carcinoma ◽  
Regression Analysis ◽  
Prognostic Factor ◽  
Cox Regression ◽  
Prognostic Models ◽  
Controlled Study ◽  
Cox Regression Analysis ◽  
Neutrophil Lymphocyte Ratio ◽  
Lymphocyte Ratio ◽  
Significant Difference

Abstract Background The neutrophil–lymphocyte ratio (NLR), a presumed measure of the balance between neutrophil-associated pro-tumour inflammation and lymphocyte-dependent antitumour immune function, has been suggested as a prognostic factor for several cancers, including hepatocellular carcinoma (HCC). Methods In this study, a prospectively accrued cohort of 781 patients (493 HCC and 288 chronic liver disease (CLD) without HCC) were followed-up for more than 6 years. NLR levels between HCC and CLD patients were compared, and the effect of baseline NLR on overall survival amongst HCC patients was assessed via multivariable Cox regression analysis. Results On entry into the study (‘baseline’), there was no clinically significant difference in the NLR values between CLD and HCC patients. Amongst HCC patients, NLR levels closest to last visit/death were significantly higher compared to baseline. Multivariable Cox regression analysis showed that NLR was an independent prognostic factor, even after adjustment for the HCC stage. Conclusion NLR is a significant independent factor influencing survival in HCC patients, hence offering an additional dimension in prognostic models.

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

Diagnostics ◽  
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.

Sign in / Sign up

Export Citation Format

Share Document