scholarly journals BCL7A as a novel prognostic biomarker for glioma patients

2021 ◽  
Author(s):  
Junhui Liu ◽  
Lun Gao ◽  
Baowei Ji ◽  
Rongxin Geng ◽  
Jing Chen ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Cox Regression ◽  
Human Cancer ◽  
Adaptive Immune Response ◽  
Suppressor Gene ◽  
Primary Brain Tumor ◽  
Lower Grade ◽  
Potential Contribution ◽  
Cox Regression Analysis ◽  
Prognostic Effect

Abstract Background: Glioma is the most common primary brain tumor and represents one of the most aggressive and lethal types of human cancer. BCL7 family has been found in several cancer types and could be involved in tumor progression. While the role of BCL7 family in human glioma has remained to be elucidated.Methods: Paraffin-embedded tumor samples were obtained to detect BCL7 expression by performing in glioma. Data (including normalized gene expression and corresponding clinical data) were obtained from Gliovis, CGGA, GEO, cBioportal and Oncomine and were used to investigate BCL7 genes expression in glioma. Survival analyses were calculated by Kaplan-Meier methods and Cox regression analysis in TCGA and CGGA. Gene Set Enrichment Analyses (GSEA) and gene ontology (GO) analysis was employed to perform the biological processes enrichment.Results: BCL7A expression in glioma tissues was lower compared to non-tumor brain tissues (NBT), and exhibited a negative correlation with glioma grades. Results from Immunohistochemical (IHC) staining and public dataset validation demonstrated that BCL7B and BCL7C were highly expressed in glioma tissues compared to NBT. Cox regression analysis identified BCL7A as the only gene in the BCL7 family that was independently associated with the prognosis of lower-grade glioma (LGG) and glioblastoma (GBM). GO and GSEA analyses revealed the potential contribution of BCL7A in adaptive immune response and neutrophil activation in the tumor microenvironment. Moreover, we found taht BCL7A had no prognostic effect on the overall survival of GBM patients who received IR only; however, patients who received chemotherapy (TMZ) combined with IR in the high BCL7A group survived longer than patients in the low BCL7A group (HR=0.346, P<0.05).Conclusion: BCL7A is a new tumor suppressor gene and can be adopted as a biomarker for independent prognosis in glioma and to evaluate response to TMZ.

scholarly journals BCL7A as a novel prognostic biomarker for glioma patients

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Junhui Liu ◽  
Lun Gao ◽  
Baowei Ji ◽  
Rongxin Geng ◽  
Jing Chen ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Cox Regression ◽  
Human Cancer ◽  
Adaptive Immune Response ◽  
Suppressor Gene ◽  
Primary Brain Tumor ◽  
Lower Grade ◽  
Potential Contribution ◽  
Cox Regression Analysis ◽  
Prognostic Effect

Abstract Background Glioma is the most common primary brain tumor and represents one of the most aggressive and lethal types of human cancer. BCL7 family has been found in several cancer types and could be involved in tumor progression. While the role of BCL7 family in human glioma has remained to be elucidated. Methods Paraffin-embedded tumor samples were obtained to detect BCL7 expression by performing in glioma. Data (including normalized gene expression and corresponding clinical data) were obtained from Gliovis, CGGA, GEO, cBioportal and Oncomine and were used to investigate BCL7 genes expression in glioma. Survival analyses were calculated by Kaplan–Meier methods and Cox regression analysis in TCGA and CGGA. Gene Set Enrichment Analyses (GSEA) and gene ontology (GO) analysis was employed to perform the biological processes enrichment. Results BCL7A expression in glioma tissues was lower compared to non-tumor brain tissues (NBT), and exhibited a negative correlation with glioma grades. Results from immunohistochemical (IHC) staining and public dataset validation demonstrated that BCL7B and BCL7C were highly expressed in glioma tissues compared to NBT. Cox regression analysis identified BCL7A as the only gene in the BCL7 family that was independently associated with the prognosis of lower-grade glioma (LGG) and glioblastoma (GBM). GO and GSEA analyses revealed the potential contribution of BCL7A in adaptive immune response and neutrophil activation in the tumor microenvironment. Moreover, we found that BCL7A had no prognostic effect on the overall survival of GBM patients who received IR only; however, patients who received chemotherapy (TMZ) combined with IR in the high BCL7A group survived longer than patients in the low BCL7A group (HR = 0.346, p < 0.05). Conclusion BCL7A is a new tumor suppressor gene and can be adopted as a biomarker for independent prognosis in glioma and to evaluate response to TMZ.

scholarly journals Immune-Related Gene SERPINE1 Is a Novel Biomarker for Diffuse Lower-Grade Gliomas via Large-Scale Analysis

2021 ◽  
Vol 11 ◽  
Author(s):  
Xiaoming Huang ◽  
Fenglin Zhang ◽  
Dong He ◽  
Xiaoshuai Ji ◽  
Jiajia Gao ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Immune Cell ◽  
Cox Regression ◽  
Expression Patterns ◽  
Critical Role ◽  
Lower Grade ◽  
Hub Genes ◽  
Who Grade ◽  
Primary Tumors ◽  
Cox Regression Analysis

BackgroundGlioma is one of the highly fatal primary tumors in the central nervous system. As a major component of tumor microenvironment (TME), immune cell has been proved to play a critical role in the progression and prognosis of the diffuse lower-grade gliomas (LGGs). This study aims to screen the key immune-related factors of LGGs by investigating the TCGA database.MethodsThe RNA-sequencing data of 508 LGG patients were downloaded in the TCGA database. ESTIMATE algorithm was utilized to calculate the stromal, immune, and ESTIMATE scores, based on which, the differentially expressed genes (DEGs) were analyzed by using “limma” package. Cox regression analysis and the cytoHubba plugin of Cytoscape software were subsequently applied to screen the survival-related genes and hub genes, the intersection of which led to the identification of SERPINE1 that played key roles in the LGGs. The expression patterns, clinical features, and regulatory mechanisms of SERPINE1 in the LGGs were further analyzed by data mining of the TCGA database. What’s more, the above analyses of SERPINE1 were further validated in the LGG cohort from the CGGA database.ResultWe found that stromal and immune cell infiltrations were strongly related to the prognosis and malignancy of the LGGs. A total of 54 survival-related genes and 46 hub genes were screened out in the DEGs, within which SERPINE1 was identified to be significantly overexpressed in the LGG samples compared with the normal tissues. Moreover, the upregulation of SERPINE1 was more pronounced in the gliomas of WHO grade III and IDH wild type, and its expression was correlated with poor prognosis in the LGG patients. The independent prognostic value of SERPINE1 in the LGG patients was also confirmed by Cox regression analysis. In terms of the functions of SERPINE1, the results of enrichment analysis indicated that SERPINE1 was mainly enriched in the immune‐related biological processes and signaling pathways. Furthermore, it was closely associated with infiltrations of immune cells in the LGG microenvironment and acted synergistically with PD1, PD-L1, PD-L2.ConclusionThese findings proved that SERPINE1 could serve as a prognostic biomarker and potential immunotherapy target of LGGs.

Use of serum proteins identified by proteomics to predict prognosis in patients with metastatic renal cell cancer (mRCC) and comparison to the currently used MSKCC survival model

2009 ◽  
Vol 27 (15_suppl) ◽  
pp. 11078-11078
Author(s):  
J. Vermaat ◽  
I. van der Tweel ◽  
N. Mehra ◽  
S. Sleijfer ◽  
J. Y. Engwegen ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Risk Model ◽  
Cox Regression ◽  
Serum Proteins ◽  
Cell Cancer ◽  
Information Criteria ◽  
Survival Model ◽  
Alternative Methods ◽  
Potential Contribution ◽  
Cox Regression Analysis

11078 Background: In mRCC the Memorial Sloan-Kettering Cancer Center (MSKCC) risk model (Motzer et al.,JCO2002) is widely used for clinical trial design and patient management. To improve this model, we searched for serum proteins associated with overall survival (OS) using proteomics and determined their potential contribution to the composition of better prognostic models. Methods: Sera from 125 mRCC patients, mostly interferon-treated, collected between 2001–2006 in three Dutch Cancer Centers, were screened by SELDI-TOF mass spectrometry (MS). Identified proteins were analyzed for their association with OS by Cox regression analysis and Kaplan-Meier curves. Three proteins were subsequently validated with conventional ELISAs and immunoturbidimetry. Computed Cox PH regression models were individually compared with the Akaike's Information Criteria (AIC). The final model was statistically bootstrapped to strengthen its validity. Results: SELDI-TOF MS successfully detected eleven prognostic proteins associated with OS. The strongest prognostic proteins, apolipoprotein A-II (ApoA2), serum amyloid alpha (SAA), and transthyretin were validated by alternative methods and confirmed for their association with OS (p=7.4×10-9, p=3.2×10-8 and p=0.0002, respectively). Stepwise multivariable Cox regression analysis provided an optimal combination of prognostic factors; ApoA2, SAA, LDH, performance status and number of metastasis sites. Subsequent categorization of patients into three risk groups generated a novel survival model that robustly predicts patient prognosis (AIC=684 and p=5.8×10-15) with increased accuracy compared to the MSKCC model (AIC=719, p=2.0×10-7). Bootstrapping our model resulted in an optimism correction of 0.04 (R2=0.45). Initiating systemic therapy according to novel proposed model instead of the MSKCC model would result in a change of treatment in 14% of the patients. Conclusions: Using proteomics, serum proteins associated with OS in mRCC patients can be identified. Incorporating some of these factors together with traditional risk factors yields a prognostic model outperforming the MSKCC risk model thereby further improving patients’ management. No significant financial relationships to disclose.

scholarly journals Clinical Significance of SASH1 Expression in Glioma

2015 ◽  
Vol 2015 ◽  
pp. 1-7 ◽  
Author(s):  
Liu Yang ◽  
Haitao Zhang ◽  
Qi Yao ◽  
Yingying Yan ◽  
Ronghua Wu ◽  
...  
Keyword(s):  
Clinical Significance ◽  
Cox Regression ◽  
Tissue Microarrays ◽  
Suppressor Gene ◽  
Clinicopathological Characteristics ◽  
Postoperative Survival ◽  
Low Grade ◽  
Lower Grade ◽  
Cox Regression Analysis ◽  
Kaplan Meier

Objective.SAM and SH3 domain containing 1 (SASH1) is a recently discovered tumor suppressor gene. The role of SASH1 in glioma has not yet been described. We investigated SASH1 expression in glioma cases to determine its clinical significance on glioma pathogenesis and prognosis.Methods.We produced tissue microarrays using 121 patient-derived glioma samples and 30 patient-derived nontumor cerebral samples. Immunohistochemistry and Western blotting were used to evaluate SASH1 expression. We usedFisher’s exact tests to determine relationships between SASH1 expression and clinicopathological characteristics; Cox regression analysis to evaluate the independency of different SASH1 expression; Kaplan-Meier analysis to determine any correlation of SASH1 expression with survival rate.Results.SASH1 expression was closely correlated with the WHO glioma grade. Of the 121 cases, 66.9% with low SASH1 expression were mostly grade III-IV cases, whereas 33.1% with high SASH1 expression were mostly grades I-II. Kaplan-Meier analysis revealed a significant positive correlation between SASH1 expression and postoperative survival.Conclusions.SASH1 was widely expressed in normal and low-grade glioma tissues. SASH1 expression strongly correlated with glioma grades, showing higher expression at a lower grade, which decreased significantly as grade increased. Furthermore, SASH1 expression was positively correlated with better postoperative survival in patients with glioma.

scholarly journals Prognostic Value of an Autophagy-Related Five-Gene Signature for Lower-Grade Glioma Patients

2021 ◽  
Vol 11 ◽  
Author(s):  
Jin-Cheng Guo ◽  
Qing-Shuang Wei ◽  
Lei Dong ◽  
Shuang-Sang Fang ◽  
Feng Li ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Cox Regression ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
The Cancer Genome Atlas ◽  
Molecular Characteristics ◽  
Lower Grade ◽  
Cox Regression Analysis ◽  
Tcga Dataset ◽  
Genome Atlas

Background: Molecular characteristics can be good indicators of tumor prognosis and have been introduced into the classification of gliomas. The prognosis of patients with newly classified lower-grade gliomas (LGGs, including grade 2 and grade 3 gliomas) is highly heterogeneous, and new molecular markers are urgently needed.Methods: Autophagy related genes (ATGs) were obtained from Human Autophagy Database (HADb). From the Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA), gene expression profiles including ATG expression information and patient clinical data were downloaded. Cox regression analysis, receiver operating characteristic (ROC) analysis, Kaplan–Meier analysis, random survival forest algorithm (RSFVH) and stratification analysis were performed.Results: Through univariate Cox regression analysis, we found a total of 127 ATGs associated with the prognosis of LGG patients from TCGA dataset and a total of 131 survival-related ATGs from CGGA dataset. Using TCGA dataset as the training group (n = 524), we constructed a five-ATG signature (including BAG1, BID, MAP1LC3C, NRG3, PTK6), which could divide LGG patients into two risk groups with significantly different overall survival (Log Rank P &lt; 0.001). Then we confirmed in the independent CGGA dataset that the five-ATG signature had the ability to predict prognosis (n = 431, Log Rank P &lt; 0.001). We further discovered that the predictive ability of the five-ATG signature was better than the existing clinical indicators and IDH mutation status. In addition, the five-ATG signature could further classify patients after receiving radiotherapy or chemotherapy into groups with different prognosis.Conclusions: We identified a five-ATG signature that could be a reliable prognostic marker and might be therapeutic targets for autophagy therapy for LGG patients.

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 Effects of marital status on overall and cancer-specific survival in laryngeal cancer patients: a population-based study

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Zhao Ding ◽  
Deshun Yu ◽  
Hefeng Li ◽  
Yueming Ding
Keyword(s):  
Marital Status ◽  
Cancer Patients ◽  
Laryngeal Cancer ◽  
Cox Regression ◽  
Group Analysis ◽  
Population Based ◽  
Cancer Specific Survival ◽  
Cox Regression Analysis ◽  
Prognostic Effect ◽  
The Difference

AbstractMarital status has long been recognized as an important prognostic factor for many cancers, however its’ prognostic effect for patients with laryngeal cancer has not been fully examined. We retrospectively analyzed 8834 laryngeal cancer patients in the Surveillance Epidemiology and End Results database from 2004 to 2010. Patients were divided into four groups: married, widowed, single, and divorced/separated. The difference in overall survival (OS) and cancer-specific survival (CSS) of the various marital subgroups were calculated using the Kaplan–Meier curve. Multivariate Cox regression analysis screened for independent prognostic factors. Propensity score matching (PSM) was also conducted to minimize selection bias. We included 8834 eligible patients (4817 married, 894 widowed, 1732 single and 1391 divorced/separated) with laryngeal cancer. The 5-year OS and CSS of married, widowed, single, and separated/divorced patients were examined. Univariate and multivariate analyses found marital status to be an independent predictor of survival. Subgroup survival analysis showed that the OS and CSS rates in widowed patients were always the lowest in the various American Joint Committee on Cancer stages, irrespective of sex. Widowed patients demonstrated worse OS and CSS in the 1:1 matched group analysis. Among patients with laryngeal cancer, widowed patients represented the highest-risk group, with the lowest OS and CSS.

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.

Sign in / Sign up

Export Citation Format

Share Document