CKAP2L, as an Independent Risk Factor, Closely Related to the Prognosis of Glioma

Recent studies have found that cytoskeleton-associated protein 2 like (CKAP2L), an important oncogene, is involved in the biological behavior of many malignant tumors, but its function in the malignant course of glioma has not been confirmed. The main purpose of this study was to clarify the relationship between prognostic clinical characteristics of glioma patients and CKAP2L expression using data collected from the GEPIA, HPA, CGGA, TCGA, and GEO databases. CKAP2L expression was significantly increased in glioma. Further, Kaplan-Meier plots revealed that increased expression of CKAP2L was associated with shorter survival time of glioma patients in datasets retrieved from multiple databases. Cox regression analysis indicated that CKAP2L can serve as an independent risk factor but also has relatively reliable diagnostic value for the prognosis of glioma patients. The results of gene set enrichment analysis suggested that CKAP2L may play a regulatory role through the cell cycle, homologous recombination, and N-glycan biosynthesis cell signaling pathways. Several drugs with potential inhibitory effects on CKAP2L were identified in the CMap database that may have therapeutic effects on glioma. Finally, knockdown of CKAP2L inhibited the proliferation and invasion of cells by reducing the expression level of cell cycle-related proteins. This is the first study to demonstrate that high CKAP2L expression leads to poor prognosis in glioma patients, providing a novel target for diagnosis and treatment of glioma.

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Overexpressed XRCC2 as an independent risk factor for poor prognosis in glioma patients

Molecular Medicine ◽

10.1186/s10020-021-00316-0 ◽

2021 ◽

Vol 27 (1) ◽

Author(s):

Zhendong Liu ◽

Wang Zhang ◽

Xingbo Cheng ◽

Hongbo Wang ◽

Lu Bian ◽

...

Keyword(s):

Risk Factor ◽

Expression Pattern ◽

Poor Prognosis ◽

Independent Risk Factor ◽

Cox Regression ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

Cellular Mechanisms ◽

Molecular Features ◽

Meta Analyses

Abstract Background XRCC2, a homologous recombination-related gene, has been reported to be associated with a variety of cancers. However, its role in glioma has not been reported. This study aimed to find out the role of XRCC2 in glioma and reveal in which glioma-specific biological processes is XRCC2 involved based on thousands of glioma samples, thereby, providing a new perspective in the treatment and prognostic evaluation of glioma. Methods The expression characteristics of XRCC2 in thousands of glioma samples from CGGA and TCGA databases were comprehensively analyzed. Wilcox or Kruskal test was used to analyze the expression pattern of XRCC2 in gliomas with different clinical and molecular features. The effect of XRCC2 on the prognosis of glioma patients was explored by Kaplan–Meier and Cox regression. Gene set enrichment analysis (GSEA) revealed the possible cellular mechanisms involved in XRCC2 in glioma. Connectivity map (CMap) was used to screen small molecule drugs targeting XRCC2 and the expression levels of XRCC2 were verified in glioma cells and tissues by RT-qPCR and immunohistochemical staining. Results We found the overexpression of XRCC2 in glioma. Moreover, the overexpressed XRCC2 was associated with a variety of clinical features related to prognosis. Cox and meta-analyses showed that XRCC2 is an independent risk factor for the poor prognosis of glioma. Furthermore, the results of GSEA indicated that overexpressed XRCC2 could promote malignant progression through involved signaling pathways, such as in the cell cycle. Finally, doxazosin, quinostatin, canavanine, and chrysin were identified to exert anti-glioma effects by targeting XRCC2. Conclusions This study analyzed the expression pattern of XRCC2 in gliomas and its relationship with prognosis using multiple datasets. This is the first study to show that XRCC2, a novel oncogene, is significantly overexpressed in glioma and can lead to poor prognosis in glioma patients. XRCC2 could serve as a new biomarker for glioma diagnosis, treatment, and prognosis evaluation, thus bringing new insight into the management of glioma.

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Identification of a five-gene signature in association with overall survival for hepatocellular carcinoma

PeerJ ◽

10.7717/peerj.11273 ◽

2021 ◽

Vol 9 ◽

pp. e11273

Author(s):

Lei Yang ◽

Weilong Yin ◽

Xuechen Liu ◽

Fangcun Li ◽

Li Ma ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Cell Cycle ◽

Overall Survival ◽

Cox Regression ◽

Enrichment Analysis ◽

Gene Signature ◽

Gene Set Enrichment Analysis ◽

Enrichment Score ◽

Hub Genes ◽

Cox Regression Analysis

Background Hepatocellular carcinoma (HCC) is considered to be a malignant tumor with a high incidence and a high mortality. Accurate prognostic models are urgently needed. The present study was aimed at screening the critical genes for prognosis of HCC. Methods The GSE25097, GSE14520, GSE36376 and GSE76427 datasets were obtained from Gene Expression Omnibus (GEO). We used GEO2R to screen differentially expressed genes (DEGs). A protein-protein interaction network of the DEGs was constructed by Cytoscape in order to find hub genes by module analysis. The Metascape was performed to discover biological functions and pathway enrichment of DEGs. MCODE components were calculated to construct a module complex of DEGs. Then, gene set enrichment analysis (GSEA) was used for gene enrichment analysis. ONCOMINE was employed to assess the mRNA expression levels of key genes in HCC, and the survival analysis was conducted using the array from The Cancer Genome Atlas (TCGA) of HCC. Then, the LASSO Cox regression model was performed to establish and identify the prognostic gene signature. We validated the prognostic value of the gene signature in the TCGA cohort. Results We screened out 10 hub genes which were all up-regulated in HCC tissue. They mainly enrich in mitotic cell cycle process. The GSEA results showed that these data sets had good enrichment score and significance in the cell cycle pathway. Each candidate gene may be an indicator of prognostic factors in the development of HCC. However, hub genes expression was weekly associated with overall survival in HCC patients. LASSO Cox regression analysis validated a five-gene signature (including CDC20, CCNB2, NCAPG, ASPM and NUSAP1). These results suggest that five-gene signature model may provide clues for clinical prognostic biomarker of HCC.

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Nomogram With a Novel Microenvironment Signature Is Systematically Constructed and Validated to Predict the Survival Rate of Glioma Patients.

10.20944/preprints202012.0404.v1 ◽

2020 ◽

Author(s):

Tianhua Li ◽

Yiguang Chen ◽

Yongjian Chen ◽

Guangjie Liu ◽

Shisheng Zou ◽

...

Keyword(s):

Cox Regression ◽

Malignant Tumors ◽

Prognostic Index ◽

Enrichment Analysis ◽

Basic Research ◽

Predictive Performance ◽

High Risk Group ◽

Gene Set Enrichment Analysis ◽

Cox Regression Analysis ◽

Kegg Pathways

Glioma accounts for the highest proportion of primary intracranial malignant tumors. Microenvironment enormously influences the process of glioma progression. Our study is to establish an individualized prognostic nomogram for glioma patients with microenvironment signature. Glioma samples of Chinese Glioma Genome Atlas (CGGA) were grouped by the immune and stromal score based on ESTIMATE algorithm. Microenvironment-related genes (MRGs) in glioma were analyzed by R. To determine the best prognostic correlation genes, univariate and multivariate Cox regression analysis were used to analyze MRGs. Use the selected genes (CHI3L1, SOCS3, SLC47A2, COL3A1, SRPX2 and SERPINA3), we established the prognostic risk score model (microenvironment signature) and validated it. Gene Set Enrichment Analysis (GSEA) showed that the high-risk group was mainly enriched in immune and stromal function KEGG pathways. Finally, the nomogram was constructed and evaluated. The receiver operating characteristic (ROC) curve, Calibration plots and decision curve analysis (DCA) of training and validation set indicated the excellent predictive performance of nomogram. In conclusion, the 6-gene microenvironment signature can not only provide directions for the basic research of glioma, but also can be included as an independent prognostic index in nomogram for individual prediction to guide clinical treatment.

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Identification of AC003986.3 as an Independent Risk Factor for Glioma Patient Survival and Functional Analysis

10.21203/rs.3.rs-44898/v1 ◽

2020 ◽

Author(s):

Qinglin Liu ◽

Huijian Ge ◽

Peng Jiang

Keyword(s):

Risk Factor ◽

Clinical Features ◽

Independent Risk Factor ◽

Cox Regression ◽

Patient Survival ◽

Cell Metabolism ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

Pathological Grade ◽

Gene Sets

Abstract Background: To validate the potential of AC003986.3 in predicting glioma patient survival and analyze its underlying mechanism.Methods: Gene expression and clinical features of the patients with gliomas were obtained from The Cancer Genome Atlatls. Correlation between AC003986.3 expression profile and patient clinical features and survival were analyzed. Multivariate Cox regression was employed to determine the risk factors for patient survival and construct the prediction model for survival. Validation of the multivariate Cox regression model was performed by comparing the survival curves between the model-predicted high and low death risk subgroups and calculating the accuracy of predicting 1, 2, 3, and 5 years survival by the model. Target genes were predicted with Ensemble Browser. Gene set enrichment analysis was performed to explore AC003986.3 related gene sets enrichment in Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathways.Results: 655 samples with gene expression and complete clinical features were obtained from The Cancer Genome Atlas. Clinical features enrolled in this study were follow up time, survival status, race, gender, race and pathological grade. AC003986.3 expression was positively related to patient age and pathological grade. Patients with High AC003986.3 expression suffered a poorer survival than those with low expression. Multivariate Cox regression revealed that AC003986.3 expression was an independent risk factor for patient survival irrespective of age and pathological grade. Predicted by Ensemble Browser, TWIST1 was identified as the target of AC003986.3. Gene set enrichment analysis revealed that AC003986.3 related gene sets were mainly enriched in cell metabolism.Conclusions: AC003986.3 expression was closely related to age and pathological grade in glioma patients, and was an independent risk factor for patient survival irrespective of age and pathological grade. AC003986.3 was mainly involved in regulating tumor cell metabolism, and this effect is probably mediated by TWIST1.

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Molecular Classification Based on Prognostic and Cell Cycle-Associated Genes in Patients With Colon Cancer

Frontiers in Oncology ◽

10.3389/fonc.2021.636591 ◽

2021 ◽

Vol 11 ◽

Author(s):

Zhiyuan Zhang ◽

Meiling Ji ◽

Jie Li ◽

Qi Wu ◽

Yuanjian Huang ◽

...

Keyword(s):

Cell Cycle ◽

Colon Cancer ◽

Cox Regression ◽

Enrichment Analysis ◽

Molecular Classification ◽

Original Data ◽

Gene Set Enrichment Analysis ◽

Data Sets ◽

Data Set ◽

Cox Regression Analysis

The molecular classification of patients with colon cancer is inconclusive. The gene set enrichment analysis (GSEA) of dysregulated genes among normal and tumor tissues indicated that the cell cycle played a crucial role in colon cancer. We performed univariate Cox regression analysis to find out the prognostic-related genes, and these genes were then intersected with cell cycle-associated genes and were further recognized as prognostic and cell cycle-associated genes. Unsupervised non-negative matrix factorization (NMF) clustering was performed based on cell cycle-associated genes. Two subgroups were identified with different overall survival, clinical features, cell cycle enrichment profile, and mutation profile. Through nearest template prediction (NTP), the molecular classification could be effectively repeated in the original data set and validated in several independent data sets indicating that the classification is highly repeatable. Furthermore, we constructed two prognostic signatures in two subgroups, respectively. Our molecular classification based on cell cycle may provide novel insight into the treatment and the prognosis of colon cancer.

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Abnormal TACC3 Expression is an Independent Prognostic Biomarker in Lung Carcinoma

10.21203/rs.3.rs-121095/v1 ◽

2020 ◽

Author(s):

Dongwei He ◽

Xiaoyan Fan ◽

Yulong Zhang ◽

You Li

Keyword(s):

Risk Factor ◽

Lung Carcinoma ◽

Independent Risk Factor ◽

Cox Regression ◽

Coiled Coil ◽

Enrichment Analysis ◽

Diagnostic Value ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Roc Curve Analysis

Abstract Background: Abnormal expression of transforming acidic coiled-coil protein 3 (TACC3) correlates with tumorigenesis of many human malignancies. However, the expression pattern of TACC3 and its clinical significance have not been well characterized in lung carcinoma (LUAD) so far. Objective: To investigate the association of TACC3 expression level with the clinicopathological characteristics and prognosis of LUAD patients.Methods: In the study, based on Oncomine, Gene Expression Profiling Interactive Analysis (GEPIA), UALCAN, and The Cancer Genome Atlas (TCGA) databases, the expression of TACC3 was determined in LUAD patients. Further, the expression of TACC3 was established using qRT-PCR in LUAD patients. Results: Our results showed that TACC3 was significantly overexpressed in LUAD tumors compared with non-tumors in the above public databases (all p<0.01). A receiver operating characteristic (ROC) curve analysis suggested that TACC3 may have diagnostic value in LUAD patients (normal vs tumor: AUC = 0.940). Kaplan-Meier analysis further demonstrated that high TACC3 expression in tumors was significantly associated with worse overall survival (OS) in LUAD patients (all p<0.01). In addition, Univariate and multivariate Cox regression analyses showed that TACC3 was an independent risk factor for OS among LUAD patients (HR = 1.02, 95% CI: 1.01-1.04, p = 0.00823; HR=1.43, 95% CI: 1.17-1.70, p <0.001). Finally, using gene set enrichment analysis (GSEA 3.0), we found that a series of potential pathways related to TACC3 were highly enriched with the high TACC3 expression phenotype (p = 0.024, p = 0.003, respectively). Conclusions: The present study provides evidence that TACC3 expression is upregulated in tumors and may be an independent risk factor for prognosis in LUAD patients.

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Expression and prognosis of CDC45 in cervical cancer based on the GEO database

PeerJ ◽

10.7717/peerj.12114 ◽

2021 ◽

Vol 9 ◽

pp. e12114 ◽

Cited By ~ 1

Author(s):

Zikang He ◽

Xiaojin Wang ◽

Zhiming Yang ◽

Ying Jiang ◽

Luhui Li ◽

...

Keyword(s):

Cell Cycle ◽

Cervical Cancer ◽

Cox Regression ◽

Differential Expression Analysis ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

Cox Regression Analysis ◽

Potential Biomarker ◽

Geo Database ◽

Differential Genes

Cervical cancer is one of the most common malignant tumors in women, and its morbidity and mortality are increasing year by year worldwide. Therefore, an urgent and challenging task is to identify potential biomarkers for cervical cancer. This study aims to identify the hub genes based on the GEO database and then validate their prognostic values in cervical cancer by multiple databases. By analysis, we obtained 83 co-expressed differential genes from the GEO database (GSE63514, GSE67522 and GSE39001). GO and KEGG enrichment analysis showed that these 83 co-expressed it mainly involved differential genes in DNA replication, cell division, cell cycle, etc.. The PPI network was constructed and top 10 genes with protein-protein interaction were selected. Then, we validated ten genes using some databases such as TCGA, GTEx and oncomine. Survival analysis demonstrated significant differences in CDC45, RFC4, TOP2A. Differential expression analysis showed that these genes were highly expressed in cervical cancer tissues. Furthermore, univariate and multivariate cox regression analysis indicated that CDC45 and clinical stage IV were independent prognostic factors for cervical cancer. In addition, the HPA database validated the protein expression level of CDC45 in cervical cancer. Further studies investigated the relationship between CDC45 and tumor-infiltrating immune cells via CIBERSORT. Finally, gene set enrichment analysis (GSEA) showed CDC45 related genes were mainly enriched in cell cycle, chromosome, catalytic activity acting on DNA, etc. These results suggested CDC45 may be a potential biomarker associated with the prognosis of cervical cancer.

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Identification of AC003986.3 as an independent risk factor for glioma patient survival and functional analysis

10.21203/rs.3.rs-17695/v1 ◽

2020 ◽

Author(s):

Qinglin Liu ◽

Huijian Ge ◽

Peng Liu ◽

Youxiang Li ◽

Peng Jiang

Keyword(s):

Risk Factor ◽

Clinical Features ◽

Independent Risk Factor ◽

Cox Regression ◽

Patient Survival ◽

Cell Metabolism ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

Pathological Grade ◽

Gene Sets

Abstract Background To validate the potential of AC003986.3 in predicting glioma patient survival and analyze its underlying function and mechanism. Methods Gene expression and clinical features of the patients were obtained from The Cancer Genome Atlatls. Correlation between AC003986.3 expression profile and patient clinical features and survival were analyzed. Multivariate Cox regression was employed to determine the risk factors for patient survival and construct the prediction model for survival. Validation of the multivariate Cox regression model was tested by comparing the survival curves between the model-predicted high and low death risk subgroups and calculating the accuracy of predicting 1, 2, 3, and 5 years survival by the model. Target genes were predicted with Ensemble Browser. Gene set enrichment analysis was performed to explore AC003986.3 related gene sets enrichment in Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathways. Results 655 samples with gene expression and complete clinical features were obtained from The Cancer Genome Atlas. Clinical features enrolled in this study were follow up time, survival status, race, gender, race and pathological grade. AC003986.3 expression was positively related to patient age and pathological grade. High AC003986.3 expression glioma patients suffered a poorer survival than those with low expression. Multivariate Cox regression revealed that AC003986.3 expression was an independent risk factor for patient survival irrespective of age and pathological grade. Predicted by Ensemble Browser, TWIST1 was the target of AC003986.3. Gene set enrichment analysis revealed that AC003986.3 related gene sets were mainly enriched in cell metabolism. Conclusions AC003986.3 expression is closely related to age and pathological grade in glioma patients, and is an independent risk factor for patient survival irrespective of age and pathological grade. AC003986.3 is mainly involved in regulating tumor cell metabolism, and this effect is probably mediated by TWIST1.

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Cigarette smoking may accelerate the progression of IgA nephropathy

BMC Nephrology ◽

10.1186/s12882-021-02453-4 ◽

2021 ◽

Vol 22 (1) ◽

Author(s):

Siqing Wang ◽

Aiya Qin ◽

Gaiqin Pei ◽

Zheng Jiang ◽

Lingqiu Dong ◽

...

Keyword(s):

Risk Factor ◽

Propensity Score ◽

Cigarette Smoking ◽

Independent Risk Factor ◽

Cox Regression ◽

Cohort Analysis ◽

Cox Proportional Hazards ◽

Study Endpoint ◽

Cox Regression Analysis ◽

Ckd Stage

Abstract Background Whether cigarette smoking is associated with the progression of immunoglobulin A nephropathy (IgAN) remains uncertain; therefore, we aimed to evaluate the effect of cigarette smoking on the prognosis of IgAN. Methods We divided 1239 IgAN patients from West China Hospital of Sichuan University who met the inclusion criteria into smoker (current or former) and non-smoker groups. The endpoint was end-stage renal disease (ESRD: eGFR < 15 mL/min/1.73 m2 or undergoing renal replacement treatment) and/or eGFR decreased by > 50%. Kaplan–Meier, correlation, logistic regression and Cox proportional hazards analyses were performed. The association between cigarette smoking and IgAN was further verified by propensity-score-matched cohort analysis. Results During the mean follow-up period of 61 months, 19% (40/209) of the smoker group and 11% (110/1030) of the non-smoker group reached the study endpoint (p < 0.001). Multivariate Cox regression analysis revealed that cigarette smoking (hazard ratio (HR) = 1.58; p = 0.043) was an independent risk factor predicting poor renal progression in IgAN, and that IgAN patients with chronic kidney disease (CKD) stage 3–4 were more susceptible to cigarette smoking (p < 0.001). After propensity score matching (PSM), a significant correlation between cigarette smoking and renal outcomes in IgAN patients was seen. Furthermore, Spearman’s correlation test revealed that smoking dose was negatively correlated with eGFR (r = 0.141; p < 0.001) and positively related with proteinuria (r = 0.096; p = 0.001). Conclusions Cigarette smoking is an independent risk factor for IgAN progression, especially for advanced patients.

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Tertiary Gleason Pattern 5 is An Independent Risk Factor for Prostate Cancer with GS 7: A Retrospective Study from China.

10.21203/rs.3.rs-173878/v1 ◽

2021 ◽

Author(s):

Desheng Cai ◽

Zixin Wang ◽

Yu Fan ◽

Lin Cai ◽

Kan Gong

Keyword(s):

Prostate Cancer ◽

Risk Factor ◽

Independent Risk Factor ◽

Cox Regression ◽

Prostate Volume ◽

Surgical Margin ◽

Rank Test ◽

Positive Surgical Margin ◽

Cox Regression Analysis ◽

Gleason Pattern

Abstract Background: Tertiary Gleason pattern 5 (TGP5) was found to be prognostic in prostate cancer (PCa) after radical prostatectomy (RP), but related data from China was rare. Our study was aimed at finding out the effect of TGP5 on PCa with Gleason score (GS) 7 and supplementing data from China in this field.Methods: A total of 229 cases met with inclusion criteria during Jan. 2014 to Dec. 2018 were reviewed. Cases were divided into GS 7 without TGP5 and GS 7 with TGP5. We compared age at diagnosis, preoperative PSA level, prostate volume, PSA density (PSAD), GS variation, clinical T staging, pathological T staging, T staging variation, extra-prostatic extension (EPE), positive surgical margin (PSM) and seminal vesicle invasion (SVI) between the groups. Effects of TGP5 on prognosis of PCa with GS 7 were evaluated using biochemical recurrence (BCR) as the primary end point.Results: TGP5 was related to higher PSM rate (P=0.001) and BCR rate (P=0.009) but not related to higher preoperative PSA level, larger prostate volume, higher PSAD, GS upgrade, poorer clinical/pathological T staging, T upstaging, EPE and SVI (all P>0.05). The median follow-up time was 24 months (interquartile range 17.5-45.5). TGP5 was an independent risk factor to PCa with GS 7 after RP using Kaplan-Meier log-rank test (P=0.018). Both univariable and multivariable cox-regression analysis pointed out that TGP5 increased the incidence of BCR in PCa with GS 7 (P<0.05). Stratified analyses were also done.Conclusion: TGP5 is an independent risk factor predicting of BCR after RP in PCa with GS 7 from China. TGP5 is related to higher PSM rate and BCR incidence. It is time to renew the contemporary Grading Group system with the consideration of TGP.

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